Prediction of Reservoir Properties from Processes and Architecture in Deep-Water Clastic Systems

Prediction of reservoir properties from processes and architecture in deep-water clastic systems

A thesis submitted to The University of Manchester for the degree of Doctor of Philosophy in the Faculty of Science and Engineering

2019

Daniel Bell

School of Natural Sciences

Department of Earth and Environmental Sciences

TABLE OF CONTENTS

TABLE OF CONTENTS ...... 2 LIST OF FIGURES ...... 8 LIST OF TABLES ...... 13 ABSTRACT...... 14 DECLARATION ...... 15 COPYRIGHT STATEMENT ...... 18 ACKNOWLEDGEMENTS ...... 19

CHAPTER 1: ...... RATIONALE 21

1.1 CHAPTER 3: HOW DOES DEPOSITIONAL RESERVOIR QUALITY VARY SPATIALLY IN SUBMARINE LOBES AND CHANNEL-FILLS? ...... 22 1.2 CHAPTER 4: HOW DO BED-SCALE BARRIERS AFFECT SANDSTONE CONNECTIVITY? ... 22 1.3 CHAPTER 5: WHICH HETEROGENEITIES MATTER TO FLOW IN SUBMARINE LOBES, AND HOW ARE THEY DISTRIBUTED? ...... 24

1.4 CHAPTER 6: HOW ARE FACIES AND ARCHITECTURE ORGANISED IN THREE DIMENSIONS IN SUBMARINE CHANNEL-FILLS, AND HOW MIGHT THIS AFFECT RESERVOIR PREDICTION? ...... 25 1.5 CHAPTER 7: DO CONTEMPORANEOUS LOBE DEPOSITS IN A BASIN EXHIBIT THE SAME ARCHITECTURES AND STACKING PATTERNS? ...... 26

CHAPTER 2: ...... DEEP-WATER DEPOSITIONAL SYSTEMS: PROCESSES, PRODUCTS, AND IMPLICATIONS ...... 28

2.1 INTRODUCTION ...... 28 2.2 FLOW PROCESSES ...... 29 Turbulent flows ...... 29 Debris flows ...... 32 Transitional flows ...... 33 2.3 PROCESS CONTROLS ON RESERVOIR QUALITY ...... 35 Introduction ...... 35 High-density turbidites (HDTs) ...... 37 Low-density turbidites (LDTs) ...... 38 Hybrid beds ...... 38 Mudstones ...... 39 Detrital clays: Hero, and villain? ...... 40 2

2.4 COMPONENTS OF DEEP-WATER DEPOSITIONAL SYSTEMS ...... 43 Submarine channels ...... 43 Channel-lobe transition zones ...... 49 Submarine lobes ...... 50 2.5 BED-SCALE CONTROLS ON RESERVOIR QUALITY DISTRIBUTION ...... 56 Introduction ...... 56 Modelling architectural elements ...... 57 Bed-scale barriers ...... 58

CHAPTER 3: ...... SPATIAL VARIABILITY IN DEPOSITIONAL RESERVOIR QUALITY OF DEEP-WATER CHANNEL-FILL AND LOBE DEPOSITS ...... 61

3.1 ABSTRACT ...... 61 3.2 INTRODUCTION ...... 62 3.3 GEOLOGICAL SETTING ...... 64 3.4 METHODS ...... 65 3.5 FACIES ...... 67 3.6 ARCHITECTURAL ELEMENT INTERPRETATIONS ...... 73 Figure 3.5: Architectural panels of Lobe 1 of the Upper Broto system ...... 74 Gerbe architectural element ...... 75 Broto architectural element ...... 75 3.7 RESULTS ...... 76 Composition ...... 76 Gerbe channel-fill element ...... 83 Lobe 1 ...... 85 3.8 DISCUSSION ...... 89 Spatial variation in depositional reservoir quality ...... 89 Implications of detrital matrix distribution ...... 95 3.9 CONCLUSIONS ...... 96

CHAPTER 4: ...... THE EFFECT OF BED-SCALE HETEROGENEITIES ON VERTICAL PERMEABILITY IN CLASTIC SANDSTONES ...... 98

4.1 ABSTRACT ...... 98 4.2 INTRODUCTION ...... 98

4.3 METHODS ...... 100 4.4 RESULTS ...... 101 Siltstone-drape test ...... 101

Mudstone-clast test ...... 104

4.5 DISCUSSION ...... 105 Effect of siltstone barriers on bed-scale connectivity...... 105 Effect of mudstone-clasts on bed-scale connectivity ...... 106 Implications for modelling ...... 108 4.6 CONCLUSIONS ...... 110

CHAPTER 5: .. BED-SCALE MODELLING OF DEEP-WATER LOBES: WHICH HETEROGENEITIES MATTER TO FLOW? ...... 111

5.1 ABSTRACT ...... 111 5.2 INTRODUCTION ...... 112 5.3 METHODS ...... 114 5.4 FACIES AND MODEL INPUT ...... 114 5.5 GEOLOGICAL SETTING ...... 120 The Tanqua depocentre ...... 120 Lobe 6 ...... 121 5.6 RESULTS ...... 122 Net-to-gross ...... 122 Vertical permeability ...... 124 Spatial variability of reservoir quality in Lobe 6 ...... 126 5.7 DISCUSSION ...... 128 Controls on the distribution of Kv values...... 128 Implications of lobe-fingers ...... 131 5.8 CONCLUSIONS ...... 133

CHAPTER 6: ..... STRATIGRAPHIC HIERARCHY AND 3-D EVOLUTION OF A SUBMARINE SLOPE CHANNEL SYSTEM ...... 134

6.1 ABSTRACT ...... 134 6.2 INTRODUCTION ...... 134 6.3 GEOLOGICAL SETTING ...... 136 6.4 METHODS AND DATA SET ...... 137 6.5 FACIES AND CHANNEL HIERARCHY ...... 142 Facies ...... 142 Channel hierarchy ...... 143 6.6 RESULTS ...... 144 Architectural element descriptions ...... 144

Palaeocurrents ...... 155 Channel architecture interpretations ...... 156 Channel complex architecture ...... 157 Distribution of channel-base-deposits ...... 159 6.7 DISCUSSION ...... 160 Stratigraphic evolution ...... 160 3D channel architecture ...... 163 Controls on channel element geometry ...... 163 Subsurface implications ...... 165

6.8 CONCLUSIONS ...... 167

CHAPTER 7: ...... TOPOGRAPHIC CONTROLS ON THE DEVELOPMENT OF CONTEMPORANEOUS BUT CONTRASTING BASIN-FLOOR DEPOSITIONAL ARCHITECTURES ...... 168

7.1 ABSTRACT ...... 168 7.2 INTRODUCTION ...... 169 7.3 GEOLOGICAL SETTING ...... 171 7.4 DATASET AND METHODS ...... 172 7.5 FACIES ASSOCIATIONS ...... 173 Thick-bedded sandstones ...... 179 Medium-bedded sandstones...... 180 Thin-bedded sandstones ...... 181 Hybrid beds ...... 181 Deflected-flow facies ...... 182 Draped scour surfaces and coarse-grained lag deposits ...... 186 Debrites ...... 186 Megabeds...... 187 7.6 PALEOCURRENTS ...... 189 7.7 FACIES VARIABILITY AND GEOMETRY...... 192 Proximal localities ...... 192 Medial localities ...... 194 Distal localities ...... 197

7.8 DISCUSSION ...... 198 Process transformations and products of flow deflection ...... 198 Contemporaneous systems with different stacking patterns ...... 202 7.9 CONCLUSIONS ...... 206 5

CHAPTER 8: ...... SYNTHESIS 208

8.1 HOW DOES DEPOSITIONAL RESERVOIR QUALITY VARY SPATIALLY IN SUBMARINE LOBES AND CHANNEL-FILLS? ...... 208 How do sediment gravity flow processes control the distribution of depositional reservoir quality? ... 209 8.2 HOW DO BED-SCALE BARRIERS AFFECT SANDSTONE CONNECTIVITY? ...... 210 How does siltstone thickness affect vertical permeability?...... 210 How does mudstone-clast density affect vertical permeability? ...... 211 8.3 WHICH HETEROGENEITIES MATTER TO FLOW IN SUBMARINE LOBES, AND HOW ARE THEY DISTRIBUTED?...... 212 Which bed-scale heterogeneities matter to flow? ...... 213 How does vertical permeability (Kv) vary spatially within submarine lobes? ...... 213 8.4 HOW ARE FACIES AND ARCHITECTURE ORGANISED IN THREE DIMENSIONS IN SUBMARINE CHANNEL-FILLS, AND HOW MIGHT THIS AFFECT RESERVOIR PREDICTION? 214 How do the facies and spatial distribution of channel-base-deposits vary? ...... 215 8.5 DO CONTEMPORANEOUS LOBE DEPOSITS IN A BASIN EXHIBIT THE SAME ARCHITECTURES AND STACKING PATTERNS? ...... 216 8.6 FUTURE RESEARCH DIRECTIONS ...... 217 Depositional reservoir quality of unconfined submarine fans ...... 217 Depositional reservoir quality of modern systems ...... 218 Quantitative analysis of mudstone-clast distribution ...... 218 Multiscale modelling of deep-water depositional systems ...... 218 Quantitative analysis of channel-base-deposits ...... 219 Discerning the transition from sheet-like to compensational stacking of lobes ...... 219

CHAPTER 9: ...... CONCLUSIONS 221

CHAPTER 10: ...... REFERENCES 223

CHAPTER 11: ...... APPENDIX A: JACA BASIN LOGGED SECTIONS 263

CHAPTER 12: ...... APPENDIX B: KLEIN HANGKLIP LOGGED SECTIONS 280

CHAPTER 13: ...... APPENDIX C: SBED 298 6

13.1 GEOMETRY MODELLING ...... 298

13.2 PROPERTY MODELLING ...... 298

Total words (including references): 73,690

LIST OF FIGURES

FIGURE 1.1: LATE QUATERNARY CONGO FAN COMPRISING: MAIN FEEDER CANYON; SUBMARINE CHANNEL-LEVEE SYSTEM; AND TERMINAL LOBES (PICOT ET AL., 2016). .. 29 FIGURE 1.2:SCHEMATIC COMPARISON OF SEDIMENT SUPPORT MECHANISM AND DEPOSITIONAL PROCESSES IN LOW- AND HIGH-DENSITY TURBIDITY CURRENTS (TALLING ET AL., 2012)...... 30 FIGURE 1.3: PROCESSES AND PRODUCTS OF FLOWS TRANSITIONAL BETWEEN FULLY TURBULENT, AND LAMINAR (HAUGHTON ET AL., 2009)...... 31 FIGURE 1.4: DOWN-CURRENT FLOW TRANSFORMATION OF A TURBULENT FLOW TO A TRANSITIONAL-LAMINAR FLOW...... 33 FIGURE 1.5: THE EFFECT OF GRAIN-SIZE ON PERMEABILITY AND POROSITY...... 36 FIGURE 1.6: THE EFFECT OF MUD-CONTENT OF POROSITY AND PERMEABILITY...... 37 FIGURE 1.7: POROSITY AND PERMEABILITY OF DISCRETE BED-TYPES, TIGUENTOURINE FIELD, ILLIZI BASIN, ALGERIA...... 38 FIGURE 1.8: SCHEMATIC MODEL OF THE RELATIONSHIP BETWEEN FLOW-TYPE STRUCTURE, THEIR RESULTANT DEPOSIT TEXTURE, AND ASSOCIATED RESERVOIR PROPERTIES...... 39 FIGURE 1.9: CONCEPTUAL MODEL DOCUMENTING CHANGES IN POROSITY, PERMEABILITY, AND QUARTZ CEMENT DEVELOPMENT DURING BURIAL IN DISCRETE BED-TYPES...... 40 FIGURE 1.10: CLAY, AND CLAY-TYPE DISTRIBUTION IN THE RAVENGLASS ESTUARY, U.K (GRIFFITHS ET AL., 2019)...... 42 FIGURE 1.11: IMPACT OF CLAY MINERALS ON POROSITY AND PERMEABILITY IN THE ROTLIEGENDES SANDSTONES (WORTHINGTON, 2003; AFTER WILSON, 1992)...... 43 FIGURE 1.12: SCHEMATIC DEPICTION OF HETEROGENEITIES WHICH MAY BE ENCOUNTERED IN CHANNEL-FILL DEPOSITS...... 44 FIGURE 1.13: CHANNEL-FILL HIERARCHY OF THE TRES PASOS FORMATION, CHILE...... 45 FIGURE 1.14: ARCHITECTURE AND FACIES DISTRIBUTION OF THE GABRIOLA CHANNEL ELEMENT, TRES PASOS FORMATION, CHILE (HUBBARD ET AL., 2014)...... 46 FIGURE 1.15: TYPES OF CHANNEL-BASE-DEPOSIT COMMONLY IDENTIFIED IN CHANNEL- FILLS (ALPAK ET AL., 2013) ...... 48 FIGURE 1.16: SURFACE AND STRATIGRAPHIC EXPRESSIONS OF A CHANNEL-LOBE TRANSITION-ZONE, FORT BROWN FORMATION, SOUTH AFRICA (BROOKS ET AL., 2018)...... 49 FIGURE 1.17: GEOMETRY AND FACIES INTERPRETATION OF SUBMARINE LOBES DEPOSITS OF THE SEA LION FAN, NORTH FALKLAND BASIN, FALKLAND ISLANDS (DODD ET AL., 2019)...... 51 8

FIGURE 1.18: SCHEMATIC ILLUSTRATION OF FLOW INTERACTION AND TRANSFORMATION

WHEN INTERACTING WITH COUNTER-SLOPES...... 53 FIGURE 1.19: HIERARCHICAL SCHEME OF TURBIDITE DEPOSITS FROM THE TANQUA DEPOCENTRE...... 54 FIGURE 1.20: FACIES AND FLOW-TYPE DISTRIBUTION IN SUBMARINE LOBES...... 55 FIGURE 1.21: IMPACT OF MUD-FRACTION ON THE PERMEABILITY OF SEDIMENTARY STRUCTURES...... 58 FIGURE 1.22: THE EFFECT OF SILTSTONE FRACTION (X-AXIS) ON PERMEABILITY...... 59 FIGURE 1.23: MUDSTONE-CLAST-RICH FACIES IN A CHANNEL AXIS. TRES PASOS

FORMATION, CHILE...... 60 FIGURE 3.1: LOCALITY MAPS ...... 63 FIGURE 3.2: STRATIGRAPHY AND GEOLOGICAL SETTING OF THE AÍNSA-JACA BASIN FILL 65 FIGURE 3.3: THE WORKFLOW FOR A REPEATABLE STRATIGRAPHIC SAMPLING METHOD .... 67 FIGURE 3.4: ARCHITECTURAL PANEL OF THE GERBE CHANNEL-FILL ELEMENT ...... 73 FIGURE 3.5: ARCHITECTURAL PANELS OF LOBE 1 OF THE UPPER BROTO SYSTEM ...... 74 FIGURE 3.6: FACIES ASSOCIATION PHOTOS ...... 77 FIGURE 3.7: QFL (QUARTZ, FELDSPAR, LITHIC FRAGMENTS) PLOTS ...... 79

FIGURE 3.8: SPATIAL VARIATION IN TEXTURAL AND ARCHITECTURAL PROPERTIES WITHIN LOBE 1 AND THE GERBE CHANNEL-FILL ELEMENT...... 82 FIGURE 3.9: EXAMPLE GRAIN-SCALE TEXTURES OF LITHOFACIES ...... 83 FIGURE 3.10: SCHEMATIC ILLUSTRATION OF THE SPATIAL VARIATION IN ARCHITECTURAL AND TEXTURAL PROPERTIES WITHIN DEEP-WATER CHANNEL-FILL ELEMENTS AND LOBES ...... 85 FIGURE 3.11: VERTICAL VARIATION IN TEXTURAL PROPERTIES AT EACH GERBE LOGGED SECTION ...... 87 FIGURE 3.12: VARIATION OF TEXTURAL PROPERTIES WITHIN CHANNEL AND LOBE SUB- ENVIRONMENTS ...... 89 FIGURE 3.13: FLOW PROCESS CONTROLS ON CHANNEL-FILL RESERVOIR POTENTIAL ...... 91 FIGURE 3.14: ILLUSTRATION OF FLOW-PROCESS CONTROLS ON RESERVOIR POTENTIAL WITHIN LOBES ...... 94 FIGURE 4.1: EXAMPLES OF SBEDTM MODELS REALISED IN THE EXPERIMENT...... 102 FIGURE 4.2: GRAPHS ILLUSTRATING THE EFFECTS OF SILTSTONE THICKNESS AND MUDSTONE-CLAST DENSITY ON KV...... 103 FIGURE 4.3: A) THE EFFECT OF SILTSTONE AS A PROPORTION OF SANDSTONE THICKNESS ON KV...... 104 FIGURE 4.4: THE EFFECT OF INCREASING MUDSTONE-CLAST DENSITY ON KV...... 107 9

FIGURE 4.5: SCHEMATIC 2D ILLUSTRATION OF HOW AMALGAMATION AFFECTS PATHWAYS

BETWEEN TWO SANDSTONES...... 108 FIGURE 4.6: SCHEMATIC ILLUSTRATION OF TWO AMALGAMATED SANDSTONES WITH MUDSTONE-CLASTS AT THE AMALGAMATION SURFACE IN CROSS-SECTION AND PLAN VIEW...... 109 FIGURE 5.1: WORKFLOW FOR DEVELOPING MODELS OF SEDIMENTARY LOGS USING SBEDTM...... 113 FIGURE 5.2: OUTCROP, AND SUBSURFACE ANALOGUE, BED-TYPE SCHEME USED IN THE STUDY...... 118

FIGURE 5.3: LOCALITY MAPS...... 119 FIGURE 5.4: LOBE SUB-ENVIRONMENT TERMINOLOGY USED IN THE STUDY...... 121 FIGURE 5.5: STRATIGRAPHIC CROSS-SECTIONS OF LOBE 6 IN THE GEMSBOK VALLEY (A), AND SKOORSTEENBERG (B), AREAS...... 123 FIGURE 5.6: THE NET-TO-GROSS AND UPSCALED VERTICAL PERMEABILITY OF EACH REALISATION IN THE GEMSBOK VALLEY (A) AND SKOORSTEENBERG (B) TRANSECTS...... 125 FIGURE 5.7: SPATIAL VARIABILITY IN KV IN LOBE 6...... 128

FIGURE 5.8: SCHEMATIC ILLUSTRATION OF KV DISTRIBUTION IN A DEEP-WATER LOBE DEPOSIT...... 130 FIGURE 5.9: SCHEMATIC MODEL ILLUSTRATING IMPLICATIONS THE STUDY MAY HAVE FOR HYDROCARBON MIGRATION AND PREDICTION OF STRATIGRAPHIC TRAPS...... 132 FIGURE 6.1: LOCALITY MAPS AND STRATIGRAPHIC CONTEXT OF THE STUDY AREA ...... 138 FIGURE 6.2: REPRESENTATIVE PHOTOGRAPHS OF LITHOFACIES IN THE STUDY AREA ...... 142 FIGURE 6.3: PHOTOPANEL INTERPRETATION OF AN ACROSS-DEPOSITIONAL-STRIKE ORIENTED CLIFF-FACE ...... 143 FIGURE 6.4: SCHEMATIC SUMMARY OF THE HIERARCHICAL ARRANGEMENT APPLIED TO THE KLEIN HANGKLIP CHANNEL-FILL ...... 144 FIGURE 6.5: SEDIMENTARY LOGS AND CORRELATION PANELS FROM THE STUDY AREA. REFER TO FIG. 1C FOR REFERENCING...... 146 FIGURE 6.6: DEPOSITIONAL STRIKE ORIENTED CORRELATION PANELS ...... 147 FIGURE 6.7: EROSION SURFACES AND CHANNEL-BASE-DEPOSITS ...... 149 FIGURE 6.8: DEPOSITIONAL DIP ORIENTED PANELS FROM PROXIMAL (LEFT) TO DISTAL (RIGHT)...... 151 FIGURE 6.9: ANNOTATED PHOTOMOSAIC OF AN E-W ORIENTED CLIFF FACE ON THE SOUTHERN SIDE OF KLEIN HANGKLIP...... 153

FIGURE 6.10: LATERAL VARIABILITY IN FACIES OF THE KHKD CHANNEL-BASE-DEPOSIT...... 154 FIGURE 6.11: PALAEOCURRENT DATA COLLECTED IN THE FIELD...... 155 FIGURE 6.12: STRATIGRAPHIC EVOLUTION OF THE KHK CHANNEL SYSTEM...... 158 FIGURE 6.13: SCHEMATIC ILLUSTRATION OF CHANNEL EVOLUTION AND FLOW BEHAVIOUR IN THE CHANNEL AXIS OF RESPECTIVE CHANNEL COMPLEXES...... 162 FIGURE 6.14: COMPARISON OF SCALES OF OBSERVATION...... 166 FIGURE 7.1: LOCATION AND GEOLOGICAL CONTEXT OF THE STUDY AREA...... 171 FIGURE 7.2: STRATIGRAPHIC COLUMN OF THE PYRENEAN FORELAND BASIN FILL ...... 173

FIGURE 7.3: SATELLITE IMAGERY OF THE FIELD AREA...... 174 FIGURE 7.4: BED-SCALE FACIES DEPOSITED FROM TURBIDITY CURRENTS ...... 179 FIGURE 7.5: SELECTED HYBRID-BED FACIES DEMONSTRATING THE RANGE OF BED TYPES OBSERVED ...... 183 FIGURE 7.6: DEFLECTED FLOW DEPOSITS OBSERVED IN THE FIELD AREA ...... 184 FIGURE 7.7: CONTACT OF DB-1 WITH SUBSTRATE NEAR THE YÉSERO LOCALITY ...... 187 FIGURE 7.8: THE EL CHATE CLIFF SECTION ...... 188 FIGURE 7.9: PALEOCURRENTS AND EVIDENCE FOR FLOW DEFLECTION ...... 190

FIGURE 7.10: DOWN-DEPOSITIONAL-DIP-ORIENTED CORRELATION PANEL ...... 191 FIGURE 7.11: STRATIGRAPHIC INTERPRETATIONS OF PROXIMAL LOBES AND GEOMETRY OF LOBE 6 ...... 193 FIGURE 7.12: GRAPHS ILLUSTRATING THE SPATIAL VARIABILITY OF HYBRID-BED ABUNDANCE AND PROPORTIONAL THICKNESS ...... 195 FIGURE 7.13: ACROSS-STRIKE ARCHITECTURAL PANELS AT THE DISTAL LOCATIONS OF ANSÓ AND HECHO ...... 196 FIGURE 7.14: MODEL TO EXPLAIN THE FACIES, STRUCTURES, AND PALEOCURRENTS OBSERVED ...... 200 FIGURE 7.15: SCHEMATIC INTERPRETATION OF THE JACA BASIN PALEOGEOGRAPHY DURING DEPOSITION OF THE UPPER BROTO TURBIDITE SYSTEM ...... 204 FIGURE 7.16: SCHEMATIC ILLUSTRATION OF HOW DEFLECTED COHESIVE FLOWS CAN INFLUENCE DEPOSITIONAL TOPOGRAPHY ...... 206 FIGURE 10.1: A LECINA LOGGED SECTION ...... 263 FIGURE 10.2: ACÍN LOGGED SECTION ...... 264 FIGURE 10.3: ANSO NORTH LOGGED SECTION ...... 265 FIGURE 10.4: ANSO SOUTH LOGGED SECTION ...... 266 FIGURE 10.5: ARAGUES DEL PUERTO LOGGED SECTION...... 267 FIGURE 10.6: BARRANCO EL CHATE LOGGED SECTION ...... 268 11

FIGURE 10.7: BUESA LOGGED SECTION ...... 269

FIGURE 10.8: EL BANO LOGGED SECTION ...... 270 FIGURE 10.9: FANLO 1 LOGGED SECTION ...... 271 FIGURE 10.10: FANLO 2 LOGGED SECTION...... 272 FIGURE 10.11: FANLO TRACK LOGGED SECTION...... 273 FIGURE 10.12: HECHO NORTH LOGGED SECTION...... 274 FIGURE 10.13: HECHO SOUTH LOGGED SECTION...... 275 FIGURE 10.14: LINAS DE BROTO LOGGED SECTION...... 276 FIGURE 10.15: URDUES LOGGED SECTION...... 277

FIGURE 10.16: YESERO LOGGED SECTION...... 278 FIGURE 10.17: YESERO 2 LOGGED SECTION...... 279 FIGURE 11.1: KHK LOG 1...... 280 FIGURE 11.2: KHK LOG 2...... 281 FIGURE 11.3: KHK LOG 3...... 282 FIGURE 11.4: KHK LOG 4...... 283 FIGURE 11.5: KHK LOG 5...... 284 FIGURE 11.6: KHK LOG 6...... 284

FIGURE 11.7: KHK LOG 7...... 285 FIGURE 11.8: KHK LOG 8...... 286 FIGURE 11.9: KHK LOG 9...... 286 FIGURE 11.10: KHK LOG 10...... 287 FIGURE 11.11: KHK LOG 11...... 287 FIGURE 11.12: KHK LOG 12...... 288 FIGURE 11.13: KHK LOG 13...... 289 FIGURE 11.14: KHK LOG 14...... 290 FIGURE 11.15: KHK LOG 15...... 291 FIGURE 11.16: KHK LOG 16...... 292 FIGURE 11.17: KHK LOG 17...... 293 FIGURE 11.18: KHK LOG 18...... 294 FIGURE 11.19: KHK LOG 19...... 295 FIGURE 11.20: KHK LOG 20...... 296 FIGURE 11.21: KHK LOG 21...... 297

LIST OF TABLES

TABLE 3:1: LITHOFACIES OBSERVED IN THE STUDY AREA ...... 68 TABLE 3:2: FACIES ASSOCIATIONS OBSERVED IN THE STUDY AREA ...... 71 TABLE 3:3: ARCHITECTURAL AND TEXTURAL PROPERTIES AT EACH LOGGED SECTION ...... 81 TABLE 3:4: ARCHITECTURAL AND TEXTURAL PROPERTIES OF FACIES ASSOCIATIONS ...... 81 TABLE 4:1: INPUT PARAMETERS USED IN MODEL REALISATIONS...... 101 TABLE 6:1: LITHOFACIES OBSERVED IN THE FIELD AREA ...... 139 TABLE 7:1: SUMMARY OF LITHOFACIES OBSERVED IN THE STUDY AREA...... 175

ABSTRACT

Deep-water depositional systems are sculpted, and built from the deposits of, discrete flow-types and depositional processes. Different flow processes govern the interactions with substrate, and control whether flows are depositional or erosional, the architecture of the geobodies, and the grain-scale texture of any deposit. The interplay of these variables results in a wide-range of heterogeneities at different scales in deep-water systems. These heterogeneities, from grain-scale, to bed-scale, to architectural-element- scale, each exert strong controls on reservoir quality distribution and performance. Therefore, understanding where these heterogeneities develop, how they develop, and how they impact fluid flow important for reservoir quality prediction in the subsurface.

Here, multiple methods including: 1) petrographic thin section analysis; 2) sedimentary logging; 3) architectural panel analysis; and 4) reservoir modelling, are used to document the distribution and effects of each scale of heterogeneity. Datasets utilised include: outcrop studies of the Tanqua Depocentre, South Africa, and the Jaca Basin, Spain; and core-plug and bed-type data from the X Formation, North Sea.

Key outcomes of the study include: 1) the spatial variability of grain-scale texture, and its associated effects on reservoir quality, is quantified for the first time in lobe and channel-fill deposits. Axial positions are shown to have better reservoir potential than marginal or fringe positions due to an abundance of coarser-grained, cleaner, high-density turbidites; 2) bed-scale heterogeneities, and bed-types with discrete grain-scale textures, are demonstrated to exert strong controls on connectivity and permeability in reservoir models. These heterogeneities strongly impact permeability in models of discrete sub- environments of a submarine lobe deposit. Axial positions exhibit the highest permeabilities due to an abundance of structureless sandstone, whereas fringe and off-axis positions are characterised by structured sandstones, and exhibit low permeabilities. Realisations of a distal lobe finger reveal high permeabilities, and challenge the notion that the distal lobe fringe is all poor-reservoir quality; 3) architecture and facies distribution of a submarine channel-fill are characterised in three dimensions, and reveal consistent lateral axial to margin trends, whereas longitudinal changes in facies are less-predictable. Characterisation of channel-base-deposits and their distribution demonstrate challenges in their identification, and implications for reservoir compartmentalisation; 4) variable flow confinement and flow deflection are suggested to influence lobe stacking patterns and depositional processes, increasing heterogeneity at multiple scales adjacent basin margins, and therefore reservoir quality distribution. 14

DECLARATION

University of Manchester PhD by published work Candidate Declaration

Candidate Name: Daniel Bell

Faculty: Science and Engineering

Thesis Title: Prediction of reservoir properties from processes and architecture in deep-water clastic systems

I declare that the thesis has been composed by myself and that the work, other than that identified below, has not be submitted for any other degree or professional qualification. I confirm that the work submitted is my own, except where work which has formed part of jointly-authored publications has been included. My contribution and those of the other authors to this work have been explicitly indicated below. I confirm that appropriate credit has been given within this thesis where reference has been made to the work of others.

1. Author contributions

Chapter 3: Bell, D., Kane, I. A., Pontén, A. S. M., Flint, S. S., Hodgson, D. M., and Barrett, B. J., Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits

Status:

Published in Marine and Petroleum Geology, Volume 98, 2018: Pages 97 – 115.

Author contributions:

1. Bell, D.: Main author. Responsible for data collection, processing, and analysis. Wrote manuscript. 2. Kane, I. A.: In depth discussion, discussion of techniques, fieldwork assistance. Detailed manuscript reviews. 3. Pontén, A. S. M.: In depth discussion, detailed manuscript review. 4. Flint, S. S.: In depth discussion, manuscript review. 5. Hodgson, D. M.: In depth discussion, discussion of techniques, fieldwork assistance. Manuscript review. 6. Barrett, B. J.: Fieldwork assistance, discussion of techniques. Manuscript review.

Chapter 4: Bell, D., Pontén, A. S. M., Kane I. A., Obradors Latre, A., and Nair, K. The effect of bed-scale heterogeneities on vertical permeability in clastic sandstones.

Status:

Submitted to Petroleum Geoscience, June 2019.

Author contributions:

Chapter 5: Bell, D., Pontén, A. S. M., Kane I. A., Obradors Latre, A., Nair, K., Thrana, C., Hodgson, D. M., Flint S. S., Bed-scale modelling of deep-water lobes: which heterogeneities matter to flow?

Status:

In preparation for submission.

Author contributions:

1. Bell, D.: Main author. Data collation, processing, and analysis. Wrote manuscript. 2. Pontén, A. S. M.: In depth discussion, detailed manuscript review. 3. Kane, I. A.: In depth discussion. Detailed manuscript review. 4. Obradors Latre, A.: In depth discussion. Data collation. Manuscript review. 5. Nair, K.: Discussion of data. Introduction to software. Manuscript review. 6. Thrana, C.: Discussion of data. Data collation. Manuscript review. 7. Hodgson D. M.: Discussion of data. Manuscript review. 8. Flint, S. S.: Manuscript discussion and review.

Chapter 6: Bell, D., Kane I. A., Hodgson D. M., Pontén, A. S. M., Hansen, L. A. S., and Flint, S. S., Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system

Status:

Accepted in Sedimentology September 2019.

Author contributions:

1. Bell, D.: Main author. Data collection, collation, processing, and analysis. Wrote manuscript. 16

2. Kane, I. A.: In depth discussion. Fieldwork assistance. Detailed manuscript review. 3. Hodgson D. M.: In depth discussion. Fieldwork assistance. Detailed manuscript review. 4. Pontén, A. S. M.: In depth discussion. Detailed manuscript review. 5. Hansen, L. A. S.: Field assistance. Discussion of data. Manuscript review. 6. Flint, S. S.: Manuscript discussion and review.

Chapter 7: Bell, D., Stevenson C. J., Kane, I. A., Hodgson, D. M., Poyatos-Moré, M., Topographic controls on the development of contemporaneous but contrasting basin-floor depositional architectures

Status:

Published in Journal of Sedimentary Research, Volume 88, 2018: Pages 1166 – 1189.

Author contributions:

1. Bell, D.: Main author. Data collection, collation, processing, and analysis. Wrote manuscript. 2. Stevenson, C. J.: Field assistance. In depth discussion. Detailed manuscript review. 3. Kane, I. A.: In depth discussion. Fieldwork assistance. Detailed manuscript review. 4. Hodgson, D. M.: In depth discussion. Fieldwork assistance. Detailed manuscript review. 5. Poyatos-Moré, M.: In depth discussion. Fieldwork assistance. Detailed manuscript review. 2. Proportion of work submitted whilst candidate was at the University of Manchester.

All work, except that declared below, has been completed whilst at the University of Manchester.

3. Work submitted in support of another degree.

The following data was presented in support of “Controls on processes and depositional architecture in a confined deep-water basin, the Jaca Basin, Spain”, Daniel Bell, MSc by Research, University of 2016, University of Leeds:

1. Sedimentary logs: A Lecina, Barranco El Chate, Buesa, El Bano, Fanlo 1, Fanlo 2, Fanlo Track, Linás de Broto, and Yésero. 2. Iterations of Figures 7.7, 7.8, and 7.11.

I. The author of this thesis (including any appendices and/or schedules to this thesis) owns certain copyright or related rights in it (the “Copyright”) and s/he has given The University of Manchester certain rights to use such Copyright, including for administrative purposes. II. Copies of this thesis, either in full or in extracts and whether in hard or electronic copy, may be made only in accordance with the Copyright, Designs and Patents Act 1988 (as amended) and regulations issued under it or, where appropriate, in accordance with licensing agreements which the University has from time to time. This page must form part of any such copies made. III. The ownership of certain Copyright, patents, designs, trademarks and other intellectual property (the “Intellectual Property”) and any reproductions of copyright works in the thesis, for example graphs and tables (“Reproductions”), which may be described in this thesis, may not be owned by the author and may be owned by third parties. Such Intellectual Property and Reproductions cannot and must not be made available for use without the prior written permission of the owner(s) of the relevant Intellectual Property and/or Reproductions. IV. Further information on the conditions under which disclosure, publication and commercialisation of this thesis, the Copyright and any Intellectual Property and/or Reproductions described in it may take place is available in the University IP Policy (see http://documents.manchester.ac.uk/DocuInfo.aspx?DocID=2442 0), in any relevant Thesis restriction declarations deposited in the University Library, The University Library’s regulations (see http://www.library.manchester.ac.uk/about/regulations/) and in The University’s policy on Presentation of Theses.

ACKNOWLEDGEMENTS

Throughout the last 4 years countless people have contributed to my academic achievements during, and personal enjoyment of, my time in Manchester. While there are too many to name here, I endeavour to express my gratitude to many of those as possible.

Firstly I thank Ian Kane for giving me the opportunity to take on this project, and for allowing me the freedom to pursue my own academic interests during the last 4 years. Ian is also acknowledged for his supervision during the project that has opened up opportunities I could only have dreamed of five years ago. I have immensely enjoyed my time working closely with Ian, and our friendship devoid of any visible emotions.

I am also indebted to my other supervisors for all their work during the project, from fieldwork to meetings and manuscript feedback: Dave Hodgson, who it has been a privilege to work with and learn from over the last 5 years (but mostly for delivering a milkshake from Laingsburg to Sadawa for me); Anna Pontén, for being the nicest of the team, and for making me feel home in the Equinor sedimentology team which was a fantastic experience; and Steve Flint for welcoming me into the Manchester Stratgroup fold, and for valuable insights into the capabilities of the human liver on fieldwork.

It has been a pleasure to meet and become friends with so many people in Manchester during my stay here. All of the PhD students from the Basins group, the Late Lunchers, and members Monday/Tuesday/Wednesday night football have all made my time here memorable.

I am honoured to have had so many wonderful officemates during my PhD: Eoin Dunlevy, Luz Gomis-Cartesio, Kévin Boulesteix, Zoe Cumberpatch, Ander Martinez- Donate, Ashley Ayckbourne, Sarah Newport, and Ammar Balila. It is also worth acknowledging Arka (W.B.M), for his daily 4.30 visits for a chat. Special thanks must go to Eoin for being an absolute rock, great fun, and for endless gossip; to Kévin for the daily abuse of each other, and weekly reinterpretation of his entire dataset; and to Luz for always brightening up the office, and for having an absolute tardis of a snack drawer.

I give thanks to all the members of the research groups I have been part of. SedResQ: Euan, Ross, Arne, Jefferson, Zoe, Ashley, and Ander. StratGroup: Miquel, Yvonne, Menno, Hannah, Janet, Andrea, Bonita, Grace, Dave, and Charley. All of whom have been a pleasure to work with, and have made hugely entertaining team trips and nights out. I also thank all of the staff members who have always been up for a chat,

whether science or gossip, and always up for a pint: Rhodri Jerrett, Rufus Brunt, and Chris Stevenson.

I am hugely grateful to my field assistants who were enormous help during my field seasons in the Pyrenees and Karoo: Bonita, Larissa Hansen, Charley Allen, Hannah Brooks, and Dave Lee. I am particularly thankful to Bonster, Dave Hodgson, and Ian Kane for ensuring the 2016 Pyrenean field season was one of the most memorable I have had: wine materialising from thin air, Clitheroe, fording rivers in an A3, the hotel owner giving his mum our washing to do, and the suitcase incident.

I also must thank my housemates during the final year: Gina Kuippers, Steve Long, Eoin, and Arne, for making Brundretts Road such a wonderful experience. And of course for ensuring we outdid Theresa May by securing a successful Brundrexit.

I would also like to thank all of the staff in the Williamson Building for their help during the last three years, whether it be booking trips, ordering equipment, sorting car hire, taking away our recycling, or handling deliveries. In particular I’d like to thank Dave Norwood, Annette Barker, and Andy Thomas who have never been able to do enough to help.

Lastly, and most certainly not least, I have to express my dearest thanks to my family for the support. Not just over the last 4 years, but the last 27 in helping me achieve what I have today. More thanks than I can possibly give go to my mum for her effort in encouraging all my interests at an early age, especially reading factual books, and for always being proud of me. I’m also indebted to my dad for sitting and watching documentaries with me and telling me countless factoids when I was younger (roles have reversed now). Finally I would like to thank my grandparents: Margaret and Donald, and Jean and Fred; who I am sure would have been incredibly proud.

Chapter 1:Rationale CHAPTER 1: Rationale Successions of sedimentary rock are host to large volumes of valuable resources such as hydrocarbons, groundwater, and minerals (Boggs et al., 1992; Bryant and Flint, 1992; Pettingill, 1998; Ruffell et al., 1998; Bersezio et al., 1999; Garland et al., 1999; Mayall et al., 2006; McKie et al., 2015); and are important reservoir for the storage of carbon dioxide in carbon capture and storage projects (Gibson-Poole et al., 2004; Gunter et al., 2004; Melick et al., 2009). The majority of these resources are hosted in subsurface reservoirs, often buried below several kilometres of overburden. Traditional methods of imaging these reservoirs rely on seismic surveys, which are large-scale but have poor vertical resolution; and well-log and core data, which have excellent vertical resolution but are essentially one dimensional and challenging to extrapolate away from the data point. In order to fill in these gaps in scale and knowledge, reservoir modelling became a crucial tool in the hydrocarbon industry (e.g. Begg and King, 1985; Bryant and Flint, 1992; Garland et al., 1999; Keogh et al., 2007; Pyrcz et al., 2015). Reservoir modelling coalesces around the central theme of increasing our knowledge of the subsurface in a quantitative manner in order to evaluate and engineer a reservoir (Ringrose and Bentley, 2015). Reservoir modelling takes place during all phases of the development cycle, and covers a range of practices, including: geological modelling of structure, facies, and depositional architecture; and property modelling of porosity and permeability, and how they are distributed in the reservoir (Ringrose and Bentley, 2015).

As exploration and development projects began to target more challenging prospects, the traditional methods of trend mapping and interpolation became unsuitable for the heterogeneities encountered in the subsurface (Bryant and Flint, 1992; Keogh et al., 2007). Outcrop analogues, and the quantitative data extracted from them, are now used to make more informed rock models of the subsurface (Desbarats, 1987; Hodgetts et al., 2004; Falivene et al., 2006). Data on heterogeneities such as facies proportions, and the distribution of baffles and barriers, are stochastically modelled to produce a range of values to reduce uncertainty in the subsurface (Deutsch, 1989; Jackson and Muggeridge, 2000; Stephen et al., 2001; Pyrcz et al., 2005; Ringrose et al., 2005). As such, documentation of heterogeneities from outcrop studies, and how they might influence reservoir quality, provide input into models of the subsurface otherwise lacking data (Martinius et al., 2017).

In this study heterogeneities common to deep-water depositional systems, and their effects on reservoir quality, are documented and discussed at several scale from grain-scale, to bed-scale, to architectural element scale. The study is academic in scope, with a focus on sedimentology and the control depositional processes exert on reservoir quality 21

Chapter 1:Rationale distribution. As such, much of the literature referenced is drawn from academic studies of sedimentology and modelling comparative to the extensive body of subsurface case-studies.

1.1 Chapter 3: How does depositional reservoir quality vary spatially in submarine lobes and channel-fills? “Depositional reservoir quality” is the reservoir potential of a deposit prior to post- depositional modification (Porten et al., 2016). The flow-type has a strong influence on the texture of a deposit (Hirst et al., 2002; Lien et al., 2006; Njoku and Pirmez, 2011; Kilhams et al., 2012; Porten et al., 2016; Kane et al., 2017). The primary texture of a deposit: grain- size, sorting, and detrital clay content, all influence primary porosity and permeability (Fraser, 1935; Beard and Weyl, 1973; Revil and Cathles III, 1999), which can be maintained post-burial (e.g. Ehrenberg, 1993; Hirst et al., 2002; Njoku and Pirmez, 2011; Marchand et al., 2015; Porten et al., 2016; Haile et al., 2017).

Individual bed-types and lithofacies have variable grain-scale textures (e.g. Hirst et al., 2002; Lien et al., 2006; Porten et al., 2016; Southern et al., 2017), therefore the spatial arrangement of these depositional facies determines depositional reservoir quality distribution in architectural elements. The stacking pattern of architectural elements, and their inherited grain-scale texture, means the depositional reservoir quality of sands have implications at larger scales and hierarchical levels. Therefore, understanding facies distribution and grain-scale character in architectural elements is critical to improved prediction of reservoir distribution. Previous publications that integrate architectural- and grain-scale observations typically consider broad proximal-to-distal trends, or facies variability with limited spatial control (Hirst et al., 2002; Lien et al., 2006; Njoku and Pirmez, 2011; Kilhams et al., 2012; Marchand et al., 2015; Porten et al., 2016). Despite this, no published work has quantified spatial changes in texture, and therefore depositional reservoir quality, in a single architectural element.

To investigate this the following research questions will be addressed: 1) how can an architectural element be characterised at grain-scale? 2) How does reservoir potential vary spatially within an individual architectural element? 3) How do sediment gravity flow processes influence depositional reservoir quality and its distribution?

1.2 Chapter 4: How do bed-scale barriers affect sandstone connectivity? The bed-scale bridges the gap between the architectural element- and grain-scales and incorporates heterogeneities from the two. For example, the distribution of pore-scale

Chapter 1:Rationale permeability in different lithofacies within a bed (e.g. Ringrose et al. 2005; Nordahl et al. 2006; Southern et al. 2017), and the degree of amalgamation or dispersed clasts between beds (e.g. Bachu and Cuthiell, 1990). It is demonstrated that these relatively small-scale barriers and heterogeneities can exert strong controls on permeability (e.g. Bachu and Cuthiell, 1990; Jackson et al., 2005; Ringrose et al., 2005; Kashikara et al., 2010; Nordahl et al., 2014; Martinius et al., 2017), modelling of which can improve prediction of recovery and water-cut, and therefore what infrastructure is required for a well (Elfenbein et al., 2005). Despite this, bed-scale modelling is often a “missing-link” in both the development of prospects, and publications.

Most studies utilising bed-scale modelling focus on upscaling lithofacies permeability to architectural element scales (e.g. Ringrose et al., 2005; Nordahl et al., 2006; Ruvo et al., 2008; Nordahl et al., 2014). Comparatively little work addresses the fundamental controls of simple barriers on vertical permeability (Kv) at the intra- and inter- bed-scale (though see: Bachu and Cuthiell, 1990; Cuthiell et al., 1991; Kashikara et al., 2010). Continuous, or discontinuous layers of clay-rich, fine-grained sediment frequently referred to as siltstone-, mudstone-, or shale-layers are effective barriers to the flow of fluids (e.g. Begg and King, 1985). Many studies have considered how the continuity, distribution, or areal or volumetric fraction of these siltstones affect connectivity (e.g. Haldorsen and Lake, 1984; Begg and King, 1985; Desbarats, 1987; Jackson and Muggeridge, 2000; Stephen et al., 2001; Janssen and Bossie-Codreanu, 2005), and typically model multiple siltstone layers in a given model. However, no published studies address the fundamental question of how the thickness of individual siltstone layers affect connectivity.

Similarly, in many studies mudstone-clasts are grouped into structureless sandstone facies within beds. However, it is recognised that mudstone clasts can affect permeability (Bachu and Cuthiell, 1990; Cuthiell et al., 1991; Kashikara et al., 2010), and strongly influence the effectiveness of improved oil recovery techniques (Kashikara et al., 2010). A further problem is mudstone-clasts create heterogeneity that is not captured by core-plugs or permeameters. Despite this, only Kashikara et al., (2010) utilise numerous stochastic models to analyse the effect of mudstone-clasts on permeability in three dimensions. This study addresses the following research questions: 1) how can the effects of bed-scale barriers to fluid flow be modelled? 2) How does siltstone-drape thickness affect Kv? 3) How does mudstone-clast density affect Kv? And 4) do the different types of barrier have contrasting effects on Kv?

Chapter 1:Rationale 1.3 Chapter 5: Which heterogeneities matter to flow in submarine lobes, and how are they distributed? Lobe deposits contain heterogeneity at a range of scales which can strongly impact their porosity and permeability. Many studies consider heterogeneities in bed types, architectural elements, and stacking patterns of lobes (Mutti, 1977; Haughton et al., 2003; Prélat et al., 2009; Kane and Pontén, 2012; Grundvåg et al., 2014; Marini et al., 2015; Spychala et al., 2017b; Pierce et al., 2018), but most of these are qualitative, and few model or discuss how discrete heterogeneities affect fluid flow. Despite this wealth of information there are very few published studies which model lobes (Garland et al., 1999; Pyrcz et al., 2005; Ruvo et al., 2008; Pyrcz et al., 2015; Hofstra et al., 2017; Jo and Pyrcz, 2019), or indeed deep-water architectural elements in general (Falivene et al., 2006; Larue and Hovadik, 2006; McHargue et al., 2011; Alpak et al., 2013; Pyrcz et al., 2015; Hofstra et al., 2017; Jackson et al., 2019). Many of these studies focus on large-scale controls, or stacking patterns of elements, and few seek to isolate the effects of bed-types or bed-scale heterogeneities. Bed-scale heterogeneities such as the spatial organisation of grain-scale textures and lamina-types associated with discrete depositional processes, and distribution of barriers within and between beds can strongly affect permeability (Cuthiell et al., 1991; Ruvo et al., 2008; Kashikara et al., 2010; Southern et al., 2017), and are commonly above the resolution of traditional sampling techniques (e.g. core plug). Consequently there is lack of integration of where and how these different types of heterogeneity affect effective permeability in lobe deposits.

Lobe deposits show spatial variability in bed-types and lithofacies, and therefore reservoir quality. This spatial heterogeneity is often packaged into facies associations, and ascribed to depositional sub-environments. The lobe axis is typically characterised by thick- bedded, amalgamated, HDTs (e.g. Prélat et al., 2009; Grundvåg et al., 2014; Marini et al., 2015; Spychala et al., 2017b), with good reservoir properties. Lobe off-axis positions, comprise a mixture of HDTs and LDTs (Prélat et al., 2009; Grundvåg et al., 2014; Marini et al., 2015; Spychala et al., 2017b), which could lead to good or poor reservoir properties depending on the quality and abundance of LDTs (Hirst et al., 2002; Lien et al., 2006). Lobe fringes are the outermost deposits of a (sandstone part of a) lobe. Because of this, there is increasing interest in their character due to their potential to form stratigraphic traps. Contrasting facies have been recognised between the lateral fringe, characterised by LDTs (Prélat et al., 2009; Spychala et al., 2017b); and the frontal fringe, which comprises both LDTs and hybrid beds (Hodgson, 2009; Grundvåg et al., 2014; Kane et al., 2017; Spychala et al., 2017b; Fonnesu et al., 2018), though HDTs may reach distal parts of lobes

Chapter 1:Rationale in “lobe fingers” (Groenenberg et al., 2010; Dodd et al., 2019; Hansen et al., 2019). The abundance of hybrid beds commonly leads to the assertion that the frontal fringe is poor reservoir quality. However, a lack of modelling of lobe sub-environments means that this claim has not been investigated.

An extensive outcrop dataset from Fan 3 of the Tanqua Depocentre, Karoo Basin, South Africa, is combined with a subsurface dataset from the X Formation, North Sea, to model the spatial distribution of vertical permeability in lobe deposits. The following research questions are addressed: 1) how can we model architectural elements at bed-scale? 2) Which bed-scale heterogeneities matter to flow? 3) How does vertical permeability (Kv) vary spatially within submarine lobes?

1.4 Chapter 6: How are facies and architecture organised in three dimensions in submarine channel-fills, and how might this affect reservoir prediction? Submarine slope channels often exhibit complicated and abrupt facies heterogeneity and depositional geometries, making them challenging to interpret in subsurface data. Outcrop analogues are often used to develop gross depositional environment, and reservoir models of subsurface data (e.g., Bryant and Flint, 1992; Clark and Pickering, 1996; Campion et al., 2000; Sullivan et al., 2000; McCaffrey and Kneller, 2001; Hodgetts et al., 2004; Bakke et al., 2008; Bakke et al., 2013; Hofstra et al., 2017). A shortcoming of most outcrop analogues is that they are limited to 2D cliff-faces or outcrop belts (e.g. Walker, 1966, 1975; Campion et al., 2000; Sullivan et al., 2000; Kane et al., 2009; Moody et al., 2012; Macauley and Hubbard, 2013; Bain and Hubbard, 2016; Li et al., 2016); which provide useful information on facies proportions and architecture, and therefore likely reservoir quality, in depositional-dip or –strike, but little information of how this changes in 3D. Limited studies are able to constrain architecture and facies distribution of submarine channel-fills in 3D; this was attempted by Pyles et al. (2010; 2012), who extrapolated LiDAR surfaces from limited outcrop. A consequence of this is that many assumptions of facies and architectural continuity are made based on limited data. Many outcrop analogues are from relatively small, coarse-grained, foreland basins, which may be poor analogues for comparatively large, fine-grained systems that are common offshore passive margins with continental drainage basins (e.g. Reading and Richards, 1994; Bouma, 2000; Stelting et al., 2000; Hubbard et al., 2005; Pickering and Corregidor, 2005; Prélat et al., 2010; Kane and Pontén, 2012).

Many channel studies are biased towards the sandstone part of the fill, its sedimentary facies, and architecture. It is now known that channel-fills are commonly time

Chapter 1:Rationale transgressive (e.g. McHargue et al., 2011; Sylvester et al., 2011; Hubbard et al., 2014; Hodgson et al., 2016), and their excavation and fill may be caused by innumerous flows over long periods of time. The manifestations of flows which excavated and maintained the channel-surface, and bypassed sediment further down-dip, are erosion surfaces and their associated channel-base-deposits. The nature of these channel-base-deposits can be used to infer the characteristics of their parent flows, and may be used to predict the presence or absence of sandstone down-dip (Walker, 1975b; Mutti and Normark, 1987; Barton et al., 2010; Hubbard et al., 2014; Stevenson et al., 2015; Li et al., 2016). As channel-base-deposits are often fine-grained and poorly-sorted, they can act as baffles to fluid flow. The spatial organisation of these deposits, and the stacking patterns of the channel-fills they are part of, can therefore affect reservoir quality, and time of water breakthrough (e.g. Hofstra et al., 2017). Despite this, there is little published work on the distribution and character of these deposits, and those that do are based on predominantly 2D data, which provide limited information on changes in and out of the plane of interest. Consequently, little is known of how the character of channel-base-deposits varies laterally and longitudinally, and at different hierarchical levels.

To resolve these gaps in knowledge the following research questions are investigated: 1) how does the channel-fill evolve stratigraphically? 2) What is the nature of down-dip and across-strike architectural and facies variability within the channel-complex- set? 3) How do the facies and spatial distribution of channel-base-deposits vary? And 4) what are the implications for reservoir connectivity and interpretation of subsurface data?

1.5 Chapter 7: Do contemporaneous lobe deposits in a basin exhibit the same architectures and stacking patterns? The terminal deposits of turbulent (including transitional) flows on the basin floor are commonly thought to form one of two end-member stacking patterns: relatively unconfined lobes which stack compensationally; or individual laterally extensive tabular beds, commonly termed “sheets”. Basin-floor lobes form discrete composite sand bodies with subtle convex-upward topography and display predictable changes in bed thickness and facies (e.g., Prélat et al., 2009; Grundvåg et al., 2014; Marini et al., 2015; Spychala et al., 2017a). Compensational stacking of lobes occurs where depositional relief causes subsequent flows to be routed to, and deposited in, adjacent topographic lows (e.g. Mutti and Sonnino, 1981; Deptuck et al., 2008; Prélat et al., 2009; Picot et al., 2016; Jo and Pyrcz, 2019). Tabular stacking is described in basin settings where flows were laterally confined, preventing them from dissipating laterally (e.g., Hesse, 1964; Ricci-Lucchi and Valmori, 1980; Ricci-Lucchi, 1984; Remacha and Fernández, 2003; Tinterri et al., 2003; Amy et al., 26

Chapter 1:Rationale 2007; Marini et al., 2015). These beds can be traced over tens to hundreds of kilometers, may be basin-wide, and show gradual facies changes compared to compensationally stacked deposits (e.g., Hirayama and Nakajima, 1977; Ricci-Lucchi and Valmori, 1980; Talling et al., 2007; Stevenson et al., 2014a). Understanding the controls and distribution of these contrasting stacking patterns is important for palaeogeographic reconstructions, and prediction of reservoir architecture in the subsurface. Recent work has recognized that basin-fills can comprise both compensational and tabular stacking patterns through time (Marini et al., 2015; Fonnesu et al., 2018; Liu et al., 2018). However, it is not known whether both stacking patterns can exist concomitantly, as many basins lack unequivocal marker horizons. The occurrence of contrasting stacking patterns is commonly ascribed to flow magnitude (e.g. Fonnesu et al., 2018). However, in confined basins there may be a range of controls which influence the stacking of gravity flow deposits.

Hybrid beds have been recognised in a range of depositional environments, and multiple processes have been invoked to explain their formation. Hybrid beds are typically of relatively poor reservoir quality compared to HDTs (Porten et al., 2016; Southern et al., 2017). Therefore, understanding their distribution and formative processes can aid reservoir quality prediction and performance. Hybrid beds are typically interpreted to develop in lobe fringe positions of relatively unconfined lobes (e.g., Haughton et al., 2003; Talling et al., 2004; Haughton et al., 2009; Hodgson, 2009; Kane and Pontén, 2012; Grundvåg et al., 2014; Kane et al., 2017; Spychala et al., 2017a; Spychala et al., 2017b; Fonnesu et al., 2018). However, hybrid beds have also been recognised to develop adjacent to confining slopes (e.g., McCaffrey and Kneller, 2001; Muzzi Magalhaes and Tinterri, 2010; Patacci and Haughton, 2014; Fonnesu et al., 2015; Southern et al., 2015; Tinterri and Tagliaferri, 2015). The primary process interpreted to cause this flow transformation is deceleration of the flow against the slope (Patacci and Haughton, 2014; Southern et al., 2015). However, as basin-floor substrate is compositionally similar to that of the flow the source of the clay causing transformation is challenging to constrain. Alternatively, deflected flows have been suggested to shear the aggrading deposit, developing a poorly sorted liquefied texture (Remacha and Fernández, 2003; Tinterri et al., 2016).

To elucidate these problems the following research questions are investigated: 1) how are turbidites and other gravity-flow deposits distributed spatially in a basin that variably confined the parent flows spatially? 2) What is the spatial distribution of stacking patterns? 3) Where are hybrid beds developed, and how do they affect the facies distributions and stacking of basin-floor deposits? 4) What controlled the development of hybrid beds?

Chapter 2:Deep-water depositional systems: Processes, products, and implications CHAPTER 2: Deep-water depositional systems: Processes, products, and implications

2.1 Introduction Submarine fans are amongst the largest depositional bodies on the planet, and are often the ultimate sink of sediment transported to the ocean. From proximal to distal, submarine fan systems generally comprise: a large feeder canyon or channel, which may significantly cut back into the continental slope (Fig. 2.1; e.g. Burke, 1972; Normark, 1978; Walker, 1992; Millington and Clark, 1995; Kolla et al., 2001; Prather, 2003; Wynn et al., 2007; Jegou et al., 2008; Di Celma et al., 2014); a slope channel-levee system, which may also prograde far from the continental slope (Fig. 2.1; e.g. Normark, 1978; Reading and Richards, 1994; Bouma, 2001; Posamentier, 2003; Mayall et al., 2006; Kane et al., 2007; Jegou et al., 2008; Janocko et al., 2013; Morris et al., 2014; Peakall and Sumner, 2015; Hodgson et al., 2016); and lobes at the end of the system (Fig. 2.1; Walker, 1966b; Mutti and Ricci-Lucchi, 1972; Mutti, 1977; Walker, 1978; Reading and Richards, 1994; Johnson et al., 2001; Gervais et al., 2006; Deptuck et al., 2008; Prélat et al., 2009; Grundvåg et al., 2014; Picot et al., 2016; Dodd et al., 2019). Submarine gravity flows feed these depositional systems, and are amongst the largest sediment transport agents on Earth; with individual flows transporting up to an order of magnitude more sediment than the annual global sediment flux of all rivers (Milliman and Syvitski, 1992; Talling et al., 2007b). However, due to their occurrence on the seafloor they are difficult to observe directly, thus knowledge is limited compared to terrestrial or shallow-marine depositional processes. Understanding the flow processes in deep-water systems, and their associated deposits, is important for: the assessment of seafloor geohazards, the prediction of reservoir quality distribution in the subsurface, and prediction of sediment and pollutant dispersal into the deep-oceans (e.g. Pettingill, 1998; Heinrich and Piatanesi, 2000; McSaveney et al., 2000; Ward, 2001; Bondevik et al., 2003; Lien et al., 2006; Saller et al., 2008; Kilhams et al., 2012; Hunt et al., 2014; Talling et al., 2014; Woodall et al., 2014; Gwiazda et al., 2015; Marchand et al., 2015; McKie et al., 2015; Dodd et al., 2019; Kane and Clare, 2019).

Chapter 2:Deep-water depositional systems: Processes, products, and implications

Figure 2.1: Late Quaternary Congo Fan comprising: main feeder canyon; submarine channel-levee system; and terminal lobes (Picot et al., 2016).

2.2 Flow processes Submarine gravity flows can be classified into three main sediment transport mechanisms: 1) Turbulent flows (Kuenen and Migliorini, 1950; Middleton, 1967; Lowe, 1982; McCaffrey and Kneller, 2001; Baas et al., 2009); 2) laminar flows (Hampton, 1972; Nardin et al., 1979; Ilstad et al., 2004; Pickering and Corregidor, 2005; Baas et al., 2009), and; 3) hybrid, or transitional, flows (Haughton et al., 2003; Sylvester and Lowe, 2004; Talling et al., 2007a; Baas et al., 2009; Haughton et al., 2009; Kane and Pontén, 2012; Kane et al., 2017).

Turbulent flows

Turbidity currents are submarine gravity flows in which fluid turbulence plays a major role in sustaining the sediment load. Turbidity currents can be classified into: 1) High-density turbidity currents; and 2) low-density turbidity currents (Figs 2.2 and 2.3).

Chapter 2:Deep-water depositional systems: Processes, products, and implications

Figure 2.2:Schematic comparison of sediment support mechanism and depositional processes in low- and high-density turbidity currents (Talling et al., 2012).

Low-density turbidity currents (LDTCs)

In LDTCs fluid turbulence acts as the grain support mechanism through the entire vertical profile of a turbidity current (Fig 2.2). Turbulence is generated at the upper boundary of the flow as well as the base of the head due to shear stresses between the flow and ambient fluid, and lower boundary as a result of shear stresses between the flow and substrate (Middleton and Hampton, 1973; Lowe, 1982; Buckee et al., 2001; Gardner et al., 2003; Talling et al., 2012). LDTCs are defined by Lowe (1982) as a turbidity current which forms tractional divisions only (ripple cross-lamination and planar laminations; Fig. 2.2). Planar laminations are interpreted to be formed due to the migration of low-amplitude bed- waves (Southard, 1991). Ripple cross-lamination (RXL) structures record deposition and reworking by dilute, fully turbulent flows with relatively low rates of sediment fallout (Walker, 1967; Allen, 1982; Southard, 1991; Jobe et al., 2012). RXL formation is suppressed at high sedimentation rates and only develops in turbulent flows, indicating that presence of RXL is a good indicator of fully turbulent, dilute flows (Sumner et al., 2008; Baas et al., 2011).

Chapter 2:Deep-water depositional systems: Processes, products, and implications

Figure 2.3: Processes and products of flows transitional between fully turbulent, and laminar (Haughton et al., 2009). A) Comparison of flow contrasting flow-types, their structure, and resultant deposits. Note that “composite/co-genetic flows” are synonymous with “transitional flows”. B) Schematic illustration of two types of flow transformation: 1) down-current dilution of a debris flow into a turbidity current; 2) down- current transformation of a turbidity current.

Chapter 2:Deep-water depositional systems: Processes, products, and implications High-density turbidity currents (HDTCs)

HDTCs differ from LDTCs in that they have two-phase flow behaviour: an upper, low-density Newtonian turbulent flow moving above a non-Newtonian plastic flow phase (Fig. 2.2; Kuenen and Migliorini, 1950; Middleton, 1967). The lower, non-Newtonian phase is typically of a higher sediment concentration than the upper-phase (Fig. 2.2; Azpiroz- Zabala et al., 2017; Paull et al., 2018; Stevenson et al., 2018); and it is suggested that processes other than fluid turbulence may act to support particles in the lower boundary layer (e.g. grain-grain interactions, reduced density differences between particles and fluid, increased fluid velocity, and development of excess pore pressure; Kuenen, 1951; Lowe, 1982; Talling et al., 2012). Due to their two-phase structure, HDTCs exhibit a stepped vertical concentration profile (Middleton, 1993); a higher-concentration lower-phase with a constant, or weakly decreasing concentration; and an upper, lower-concentration phase with exponentially decreasing concentration. Increased sediment concentrations are generally interpreted to damp near-bed turbulence, restricting the development of bedforms (Lowe, 1988; Talling et al., 2012).

HDTCs may deposit in a layer-by-layer fashion rather than en-masse (Kneller and Branney, 1995), but at higher bed aggradation rates compared to LDTCs (Talling et al., 2012). Clean, massive sandstones form where sediment fallout is so rapid that there is insufficient time for the overriding flow to rework the deposit (Kuenen, 1966; Middleton and Hampton, 1973; Lowe, 1982). Deposits from near-bed highly concentrated layers termed ‘traction carpets’ (Fig. 2.2; Dzulynski and Sanders, 1962; Hiscott and Middleton, 1980; Lowe, 1982; Sohn, 1997) can be sheared laterally by the overriding flow, developing a form of planar lamination (Sumner et al., 2008; Talling et al., 2012). As forms of planar laminations are interpreted to be developed by both HDTCs and LDTCs, it has been suggested that the transition between high- and low-density turbidity currents lies within the planar laminated division of turbidites (Fig. 2.2; Talling et al., 2012).

Debris flows

Debris flows are poorly-sorted, gravity-driven, non-Newtonian mixtures of sediment and water. Subaqueous debris flows, here grouped to include plastic and elastic mechanical behaviour of submarine gravity flows, are supported by their yield strength, as opposed to fluid turbulence or dispersive pressure, which enables them to transport large clasts (Nardin et al., 1979; Hampton et al., 1996; Iverson, 1997; Sohn, 2000; Kane et al., 2009). The behaviour of a debris flow and its deposit is controlled by the internal mixture

Chapter 2:Deep-water depositional systems: Processes, products, and implications of solids and fluids, and their interaction with each other (Sohn, 2000). Therefore, debris flow processes are dependent on the properties of the grains and clasts (size, density, and volume fraction), and of the interstitial fluids (density, viscosity, and volume fraction) (Sohn, 2000), all of which are dependent on the matrix mud-content (Iverson et al., 2010). Debris flows are capable of transporting material over long distances (e.g. Masson et al., 1997), and tend to deposit en masse abruptly due to ‘freezing’ (Nardin et al., 1979; Talling et al., 2012); though Major (1997) recognised that this ‘freezing’ is diachronous both temporally and spatially.

Transitional flows

Figure 2.4: Down-current flow transformation of a turbulent flow to a transitional-laminar flow. This is interpreted to form due to flow deceleration and entrainment of substrate. A) Demonstrates the spatial distribution of hybrid beds within a submarine lobe (Kane et al., 2017).

Individual sediment gravity flows can transform longitudinally from turbulent to laminar, or vice-versa. Flows which exhibit characteristics of both flow states are termed transitional flows (Figs. 2.3, 2.4; Baas et al., 2009; Hodgson, 2009; Baas et al., 2011; Kane and Pontén, 2012; Kane et al., 2017; Southern et al., 2017), which deposit hybrid beds (Fig. 2.3; Haughton et al., 2003; Talling et al., 2004; Haughton et al., 2009; Hodgson, 2009; Spychala et al., 2017a). Hybrid beds can show marked spatial heterogeneity (e.g. Fonnesu et al., 2015); however, an idealised hybrid bed typically exhibits: a basal sandstone deposited by a HDTC; a linked co-genetic debritic division deposited by a laminar flow and an

Chapter 2:Deep-water depositional systems: Processes, products, and implications overlying low-density turbidite (Wood and Smith, 1958; Talling et al., 2004; Haughton et al., 2009; Baas et al., 2011).

Transitional flows develop due to rheological changes within a single flow, which can be simplified into two types of flow transformation: 1) Transformation of a turbidity current into a transitional flow; and 2) transformation of a debris flow into a transitional flow (Fig. 5B):

Turbidity currents can transform into a transitional flow in two primary ways: 1) an initial turbidity current can entrain substrate into the flow (Figs. 2.3B, 2.4). Bulking of the flow increases both sediment and clay concentration, which dampens turbulence and increases flow cohesion (Fig. 2.4; Piper and Aksu, 1987; Mulder et al., 1997; Kane et al., 2017). The increase in flow cohesion and suppression of turbulence promotes the development of laminar flow conditions forming a plug flow (Figs. 2.3, 2.4; Baas and Best, 2002; Baas et al., 2009; Sumner et al., 2009; Baas et al., 2011). Relatively low shear stresses are required to entrain cohesive mud (Mitchener and Torfs, 1996; Mohrig et al., 1998), and small amounts of erosion are capable of dramatically altering flow properties to cause local flow transformation (Talling et al., 2004; Fonnesu et al., 2015; Fonnesu et al., 2018). Updip erosion of substrate, and its subsequent breakup, suggests the deposit of such a flow will show turbidite characteristics proximally, and hybrid bed characteristics distally, a pattern commonly observed in submarine lobes (Fig. 2.4; Talling et al., 2004; Hodgson, 2009; Kane and Pontén, 2012; Grundvåg et al., 2014; Kane et al., 2017; Spychala et al., 2017b; Fonnesu et al., 2018); 2) a decelerating turbidity current can transition into a transitional flow. Experimental work has shown that turbulence is replaced by laminar plug flows as the method of sediment suspension as flows decelerate and increase in clay-concentration (Fig. 2.4; Baas and Best, 2002; Baas et al., 2009). As turbulence decreases coarser grains fall from suspension, and the flow collapses, effectively increasing clay-concentration in a positive feedback relationship, promoting transitional flow conditions (Fig. 2.4). Such a relationship is interpreted to develop in distal parts of systems (Hodgson, 2009; Kane and Pontén, 2012; Kane et al., 2017), and adjacent to topography, where flows interact with, and are forced to decelerate against a counter-slope (Muzzi Magalhaes and Tinterri, 2010; Patacci and Haughton, 2014; Southern et al., 2015; Tinterri et al., 2016).

The generation of a turbidity current from a debris flow (e.g. Hampton, 1972) is facilitated by the entrainment of ambient fluid into the debris flow (Fig. 2.3B). This sufficiently dilutes the flow to the point where fluid turbulence becomes the dominant transport mechanism (Fig. 2.3B; Mohrig et al., 1998; Piper et al., 1999; Marr et al., 2001;

Chapter 2:Deep-water depositional systems: Processes, products, and implications Baas and Best, 2002). This co-genetic turbidity current outruns, and is deposited before the debris flow, which deposits on top of it (Fig.2.3B; Mohrig et al., 1998; Marr et al., 2001; Talling et al., 2004; Haughton et al., 2009). This model assumes the generated turbidity current is able to accelerate away from the debris flow, and that the debris flow bypasses the proximal parts of a fan before depositing in the fan fringes on top of the turbidite (Talling et al., 2004; Haughton et al., 2009).

Of the two primary processes for developing transitional flows, transformation of a turbidity current through erosion or deceleration, or both, is most likely to be responsible for the generation of the vast majority of transitional flow deposits (Talling et al., 2004; Haughton et al., 2009; Kane et al., 2017; Fonnesu et al., 2018). This is supported by observed proximal-to-distal facies changes in both hybrid beds and submarine lobes. Hybrid beds are common in distal parts of lobes, with the corresponding proximal deposits lacking a debritic division, supporting the longitudinal flow transformation from turbulent to transitional or laminar flow conditions (Hodgson, 2009; Kane and Pontén, 2012; Grundvåg et al., 2014; Kane et al., 2017; Spychala et al., 2017b; Fonnesu et al., 2018).

2.3 Process controls on reservoir quality

Introduction

The quality of a hydrocarbon reservoir is predominantly controlled by porosity and permeability, whether it be the reservoir itself, the seal, or migration pathways (e.g. Marzano, 1988; Ramm and Bjørlykke, 1994; Bloch et al., 2002; Ehrenberg et al., 2008). Many studies recognise the importance of compaction and cementation (e.g. Bloch et al., 2002; Marchand et al., 2002; Dutton et al., 2003; Mansurbeg et al., 2008; Ajdukiewicz et al., 2010). However, the porosity and permeability of unconsolidated sand is controlled by the primary texture of the deposit (Fraser, 1935; Beard and Weyl, 1973), which is not as well- studied with respect to petroleum geoscience. The grain-size of a deposit controls the size of pore throats, and therefore permeability; though is independent of porosity in well- sorted sands (Fig. 2.5; Fraser, 1935; Head and Rogers, 1961; Beard and Weyl, 1973). The sorting of a deposit can influence both permeability and porosity. In well-sorted deposits grains are able to stack with large intergranular spaces, positively impacting porosity and permeability (Fraser, 1935; Head and Rogers, 1961; Beard and Weyl, 1973). Conversely, in poorly sorted deposits, grains pack more irregularly, and fine-grains are able to fill intergranular space, reducing porosity and permeability (Fraser, 1935; Head and Rogers, 1961; Beard and Weyl, 1973), and porosity decrease is greater with finer grain-size of a

Chapter 2:Deep-water depositional systems: Processes, products, and implications given sorting (Head and Rogers, 1961). Detrital clay negatively affects the porosity and permeability of unconsolidated sand by blocking intergranular space and pore throats (Fig. 2.6; Revil and Cathles III, 1999), and can swell when wet to further reduce permeability (e.g. Aksu et al., 2015).

Figure 2.5: The effect of grain-size on permeability and porosity. A) Permeability is shown to increase with increasing grain-size in proximal hybrid beds and HDTs, whereas the trend is poorly distinguished in distal hybrid beds. B) There is weak correlation between grain-size and porosity (Porten et al., 2016).

The term ‘depositional sand quality’ is used to describe the primary deposits influenced by these parameters (Ehrenberg, 1997). These primary controls on sand deposition have been demonstrated to influence porosity and permeability in both terrestrial and shallow-marine environments (Pryor, 1973; Haile et al., 2018), and deep- water sandstones (Marzano, 1988; Hirst et al., 2002; Lien et al., 2006; Ehrenberg et al., 2008; Njoku and Pirmez, 2011; Kilhams et al., 2012; Marchand et al., 2015; Porten et al., 2016; Southern et al., 2017). Despite the large potential of deep-water hydrocarbon plays (e.g. Pettingill, 1998), there is little published work which relates deep-water depositional facies and architecture to reservoir quality (Lien et al., 2006; Njoku and Pirmez, 2011; Kilhams et al., 2012; Marchand et al., 2015; Porten et al., 2016; Southern et al., 2017), or ‘depositional reservoir quality’ as defined by Porten et al. (2016). Whilst individual facies associations are different in each case study, there are general similarities between the resulting deposits and formative processes. Therefore characterisation of the reservoir properties associated with the range of flow processes can be used to build geological models applicable to a range of basin settings.

Chapter 2:Deep-water depositional systems: Processes, products, and implications

Figure 2.6: The effect of mud-content on porosity and permeability. A) Increasing fractions of mud reduce permeability within sandstone. B) Porosity decreases with increasing mud content which fills intergranular space. However, above 50% mud volume porosity increases as loosely-packed clays can preserve large intergranular spaces (Revil and Cathles III, 1999).

High-density turbidites (HDTs)

Relatively thick-bedded sandstones, lacking tractional structures, are usually considered to be products of high-density turbidity currents typical of proximal and axial regions of deep-water systems (Lowe, 1982; Mutti, 1992; Baas et al., 2004; Prélat et al., 2009; Grundvåg et al., 2014; Marini et al., 2015; Spychala et al., 2017b). HDTs are typically relatively coarse-grained and low in detrital clay, and despite being more poorly-sorted than low-density turbidites usually exhibit the highest primary porosities (average 24.1%, Kilhams et al., 2012) and permeabilities (Figs. 2.7, 2.8; average 370mD vertical, Kilhams et al., 2012; see also: Hirst et al., 2002; Lien et al., 2006; Kilhams et al., 2012; Zhang et al., 2015; Porten et al., 2016). Thick-bedded sandstones containing dewatering structures can have higher permeability values due to the removal of fluidised clay from the bed, locally decreasing the clay content (Lien et al., 2006; Porten et al., 2016).

Chapter 2:Deep-water depositional systems: Processes, products, and implications Low-density turbidites (LDTs)

Sandstones containing tractional structures are considered to be the products of low-density turbidity currents (e.g. Lowe, 1982; Mutti, 1992; Hirst et al., 2002; Lien et al., 2006; Jobe et al., 2012; Talling et al., 2012; Spychala et al., 2015; Porten et al., 2016). LDTs are typically finer-grained, more well-sorted, and have higher detrital clay contents than genetically related HDTs (Lowe, 1982; Mutti, 1992; Lien et al., 2006; Kilhams et al., 2012; Zhang et al., 2015; Porten et al., 2016). This results in lower depositional porosity and permeabilities (Figs. 2.7, 2.8). Average porosities (17.5%, Kilhams et al., 2012) and permeabilities (average vertical permeability 21.24mD, Kilhams et al., 2012) are lower than those of high-density turbidites of a given system (Fig. 2.7; Hirst et al., 2002; Lien et al., 2006; Njoku and Pirmez, 2011; Kilhams et al., 2012).

Figure 2.7: Porosity and permeability of discrete bed-types, Tiguentourine field, Illizi Basin, Algeria. The best reservoir qualities in “traditional” deep-water facies are HDTs. Conversely LDTs and hybrid beds (muddy HDTs and sandy debrites) have lower permeabilities (Hirst et al., 2002).

Hybrid beds

Hybrid beds typically consist of a lower sandstone rich division and an upper, matrix-rich division. Due to the elevated matrix contents, particularly in the upper divisions, hybrid beds have lower, typically up to an order of magnitude, permeabilities than HDTs (Fig. 2.8; Porten et al., 2016). Hybrid beds can broadly be classified as proximal or distal based on their facies and reservoir properties (Porten et al., 2016; Kane et al., 2017). Proximal hybrid beds typically have a clean basal sandstone graded into argillaceous sandstone which is commonly dewatered with occasional mudstone clasts (Kane and 38

Chapter 2:Deep-water depositional systems: Processes, products, and implications Pontén, 2012; Porten et al., 2016). Distal hybrid beds typically consist of a thinner, finer- grained, lower sandstone overlain by a mudstone-rich debritic division (Kane and Pontén, 2012; Porten et al., 2016). Proximal hybrid beds are typically coarser-grained, have lower detrital clay contents, and have porosities between 20 – 30% and permeabilities spanning 3 – 500mD (Porten et al., 2016). Distal hybrid beds are typically finer-grained and have higher detrital clay content, resulting in lower porosity and permeability (13 - 28%, and 0.1 - 15 mD, respectively; Porten et al., 2016).

Figure 2.8: Schematic model of the relationship between flow-type structure, their resultant deposit texture, and associated reservoir properties. Hybrid event beds can exhibit permeability two orders of magnitude lower than high-and low-density turbidites of a given porosity. Reservoir quality decreases with both decreasing grain-size and increasing clay content (Porten et al., 2016).

Mudstones

Unconsolidated mud can exhibit high porosities (e.g. Revil and Cathles III, 1999). However, once compacted, mudstones typically exhibit low porosities (average 9%) and very-low permeabilities 0.09mD (Kilhams et al., 2012; Zhang et al., 2015), due to their fine grain-sizes and high concentrations of clay and ductile grains (Marchand et al., 2015).

Chapter 2:Deep-water depositional systems: Processes, products, and implications Detrital clays: Hero, and villain?

Somewhat counter-intuitively, bed types with moderate concentrations of clay particles often have better reservoir properties than clean sandstones after burial (Worden et al., 2000; Porten et al., 2016). With burial, the growth of quartz cement on grain surfaces replaces compaction as the dominant control on porosity and permeability loss (Fig. 2.9; Worden et al., 2000; Ajdukiewicz and Lander, 2010; Morad et al., 2010; Porten et al., 2016). Clay coatings of quartz grains inhibit the growth of quartz cement, resulting in facies containing clay grain coats having better reservoir properties than clean sandstones post- burial (e.g. Heald and Larese, 1974; Pittman and Larese, 1991; Ehrenberg, 1993). Therefore, after burial geobodies rich in proximal hybrid beds could be more attractive plays at a bed-scale than those rich in clean sandstone HDTs.

Figure 2.9: Conceptual model documenting changes in porosity, permeability, and quartz cement development during burial in discrete bed-types. Dashed line represents typical burial depth of reservoir sandstones on the Norwegian continental shelf (e.g. Ehrenberg, 1990). The evolution of reservoir quality with increasing burial is controlled by the original sediment texture and composition (and therefore its depositional processes) (Porten et al., 2016).

Chapter 2:Deep-water depositional systems: Processes, products, and implications Within fluvial and paralic environments it has been recognised that the types of detrital clay, and those formed during diagenesis, vary according to sub-environment and depositional processes (Fig. 2.10; e.g. Ketzer et al., 2002; Mansurbeg et al., 2008; Morad et al., 2010; Dowey et al., 2012; Griffiths et al., 2019). The clays present in each environment are strongly dependent on several factors including: sedimentary provenance and processes, regolith type and weathering rates, extent of the fluvial system, and width of the shelf (Fig. 2.10; Morad et al., 2010; Dowey et al., 2012; Griffiths et al., 2019). The different types of clay present within sandstones can strongly impact their reservoir quality during burial and compaction (Fig. 2.11). The presence of chlorite can act to maintain porosity and permeability by inhibiting quartz cementation (Anjos et al., 2003; Dowey et al., 2012), whereas the presence of illite or kaolinitic clays can have detrimental effects through the formation of pore occluding cements (Ketzer et al., 2002; Mansurbeg et al., 2008; Ajdukiewicz et al., 2010; Morad et al., 2010). Illite, in particular, can act to reduce permeability through grain coatings occluding pore throats (Fig. 2.11; Wilson, 1992; Marfil et al., 2003). Smectitic clays can have either detrimental or positive effects on porosity and permeability. During late diagenesis smectites can transform into illite or chlorite dependent on rock mineralogy and water geochemistry (McKinley et al., 1999); this is important to understand in deep-water systems as detrital smectite is relatively enriched in turbidites compared to deltaic and shallow marine environments (McKinley et al., 1999).

Chapter 2:Deep-water depositional systems: Processes, products, and implications

Figure 2.10: Clay, and clay-type distribution in the Ravenglass Estuary, U.K (Griffiths et al., 2019). Clay, particularly illite and kaolinite, is typically most concentrated in lower energy parts of the system such as mud-flats. Chlorite exhibits a similar trend but may also be enriched in some tidal bars and dunes due to the presence of chlorite lithic fragments.

Chapter 2:Deep-water depositional systems: Processes, products, and implications

Figure 2.11: Impact of clay minerals on porosity and permeability in the Rotliegendes sandstones (Worthington, 2003; after Wilson, 1992).

As shallow-marine environments are often staging areas for sediment en-route to deep-water systems (Fig. 2.10; Walker, 1992; Weltje and De Boer, 1993; Reading and Richards, 1994; Mutti et al., 2003; Koo et al., 2016; Poyatos-Moré et al., 2016; Cosgrove et al., 2018), the type of detrital grains and clays present in shallow-marine environments will influence which clays are developed in the deep-water system. Sediment dispersion in turbidity currents is strongly impacted by the hydrodynamic properties of the transported sediment, i.e., the grain shapes, sizes and densities (e.g. Pyles et al., 2013); similarly, different clay types have been shown to behave differently in turbidity currents, impacting their spatial distribution (Mansurbeg et al., 2008; Baas et al., 2016; Baker et al., 2017). Therefore clays with different hydrodynamic properties will be fractionated into different parts of lobes. This spatial fractionation of clays is likely to create variable reservoir qualities within a lobe after burial and compaction.

2.4 Components of deep-water depositional systems

Submarine channels

Submarine channels, and their genetically related fills, are the proximal parts of deep-water depositional systems through which sediment bypasses to the basin-floor. 43

Chapter 2:Deep-water depositional systems: Processes, products, and implications Submarine channel-fills are bound at their base by a major erosion surface, or canyon, which can be excavated over relatively short (e.g. Dakin et al., 2013), or long timescales (e.g. Hodgson et al., 2016). Once excavated, submarine channels are typically long-lived conduits for the transport of sediment to the basin-floors (McHargue et al., 2011; Sylvester et al., 2011; Hubbard et al., 2014; Bain and Hubbard, 2016; Hodgson et al., 2016); and experience multiple periods of aggradation and degradation. Channels are highly confined features and can be erosionally confined within a canyon, confined by external levees, or a combination of the two (Winn and Dott, 1979; Millington and Clark, 1995; Beaubouef, 2004; Kane et al., 2009; Kane and Hodgson, 2011; McHargue et al., 2011; Sylvester et al., 2011; Janocko et al., 2013; Di Celma et al., 2014; Morris et al., 2014; Hansen et al., 2017). Additionally, submarine channels are often confined internally within their bounding erosion surfaces, by internal levees, terraces, or debris flow deposits (Kane and Hodgson, 2011; Ortiz-Karpf et al., 2015; Morris et al., 2016; Hansen et al., 2017). This inherent heterogeneity in submarine channel-fills makes subsurface prediction of their architecture and reservoir quality challenging (Fig. 2.12; Kolla et al., 2001; Falivene et al., 2006; Mayall et al., 2006; Bakke et al., 2008; Barton et al., 2010; McHargue et al., 2011; Zhang et al., 2015).

Figure 2.12: Schematic depiction of heterogeneities which may be encountered in channel-fill deposits. Modified from Mayall et al. (2006).

Channel hierarchy

Using the conceptual models of several studies (e.g. Sprague et al., 2005; Di Celma et al., 2011; McHargue et al., 2011; Moody et al., 2012; Macauley and Hubbard, 2013) a coherent hierarchical framework can be established. Hierarchical packages with similar geometries, vertical and lateral stacking patterns, and bounding surfaces, are identified through the mapping of erosional surfaces (e.g. Sprague et al., 2002; Abreu et al., 2003;

Chapter 2:Deep-water depositional systems: Processes, products, and implications Sprague et al., 2005; Di Celma et al., 2011; McHargue et al., 2011; Macauley and Hubbard, 2013).

At greater than bed-scale the primary building blocks of submarine channel hierarchies are: channel elements of McHargue et al., (2011) and Macauley and Hubbard (2013; Fig. 2.13), elementary channels (Di Celma et al., 2011), the storey of Sprague et al., (2005) and the sub-stage of Mutti (1992) (Fig. 3). Channel elements have scales of 10’s of metres in thickness (~10 – 30 m), 10 – 100’s metres in width (~10 – 400 m), exhibit an erosional base and are typically considered the product of a single cycle of erosion and filling (Fig. 2.13; Sprague et al., 2002; Abreu et al., 2003). Two or more genetically-linked channel elements with a basal composite erosional surface, stacked vertically or horizontally, with similar depositional facies and architectures, form a channel complex (Fig. 2.13; Abreu et al., 2003; Sprague et al., 2005; Di Celma et al., 2011; Macauley and Hubbard, 2013). A channel-complex set consists of two or more stacked, genetically related channel complexes, is bounded by a composite erosional surface, may be levee bound at its base, and is capped by a regional abandonment surface stratigraphically above it (Fig. 2.13; Abreu et al., 2003; Sprague et al., 2005; Di Celma et al., 2011; McHargue et al., 2011; Macauley and Hubbard, 2013). The largest hierarchical element is the channel-complex system, comprising two or more stacked channel-complex sets, and bound by a basal composite erosional surface and an overlying regional abandonment surface (Abreu et al., 2003; Sprague et al., 2005).

Figure 2.13: Channel-fill hierarchy of the Tres Pasos Formation, Chile. Individual channel elements, identified through mappable erosion surfaces, with similar stacking patters form channel complexes. Stacked channel complexes form a channel-complex set (Macauley and Hubbard, 2013).

Chapter 2:Deep-water depositional systems: Processes, products, and implications Channel architecture

Outcrop studies of ancient channel-fills provide details of the facies, and sub- seismic architecture, of channel-fills. Channel-elements consist of three main sub- environments: channel axis, channel off-axis, and channel margin (Figs. 2.13, 2.14). Stratigraphically, channel-axis deposits are characterised by: a basal debrite which may or may not be present, lag deposits characterised by conglomerate or mudstone-clast-rich sandstones, thick-bedded high-density turbidites, and low-density turbidites (Figs. 2.13, 2.14; Walker, 1975; Clark and Pickering, 1996; Campion et al., 2000; Sullivan et al., 2000; Camacho et al., 2002; Eschard et al., 2003; Pyles et al., 2010; Di Celma et al., 2011; Macauley and Hubbard, 2013; Hubbard et al., 2014; Li et al., 2016). Channel margin positions are typically characterised by a thickening upward succession of low-density turbidites and siltstones which correspond to thick-bedded turbidites which were deposited in the channel axis (Fig. 2.13, 2.14; Sullivan et al., 2000; Macauley and Hubbard, 2013; Hubbard et al., 2014). Channel off-axis positions are less well defined, and typically comprise a mixture of facies from the channel axis and channel margin (Figs. 2.13, 2.14; Sullivan et al., 2000; Hubbard et al., 2014).

Figure 2.14: Architecture and facies distribution of the Gabriola channel element, Tres Pasos Formation, Chile (Hubbard et al., 2014).

Most outcrop studies are limited to primarily across-strike, oblique, or down-dip 2D data panels (e.g. Walker, 1966a; Walker, 1975; Campion et al., 2000; Sullivan et al., 2000; Moody et al., 2012; Macauley and Hubbard, 2013; Hubbard et al., 2014; Li et al., 46

Chapter 2:Deep-water depositional systems: Processes, products, and implications 2016). As such, it is challenging to predict facies and architectural information in three dimensions, which can strongly influence reservoir performance (Larue and Hovadik, 2006; Funk et al., 2012; Alpak et al., 2013; Hofstra et al., 2017; Jackson et al., 2019), outside of the outcrop plane. This is particularly challenging in dip-oriented transects for placing data into stratigraphic context (e.g. Malkowski et al., 2018). Despite this, few studies have been able to investigate the 3D architecture and stratigraphic evolution of channel-fills at outcrop; and those that do rely on extrapolation of lidar data from oblique sections (Pyles et al., 2010; Pyles et al., 2012). As such there is little information on the distribution, and continuity of facies and stratigraphic surfaces in 3D. Similarly, there is a bias in outcrop studies towards relatively small, coarse-grained, sand-rich foreland basins with small drainage basins, which are poor analogues for the comparatively large, fine-grained and mud-rich systems that typical of offshore passive margin settings fed by major drainage basins (Reading and Richards, 1994; Bouma, 2000; Stelting et al., 2000; Hubbard et al., 2005; Pickering and Corregidor, 2005b; Prélat et al., 2010).

The base of channels, at all hierarchical levels, is typically marked by an erosion surface and a genetically linked lag deposit associated with sediment bypass: a channel- base-drape. Here, we use the term channel-base-deposit, as drape implies deposition from dilute flows or hemipelagic settling; whereas these deposits are commonly deposited from highly energetic flows. Three styles of channel-base-deposit are commonly recognised: 1) Bypass deposits are characterised by highly heterogeneous composite lags developed at the base of the channel axis due to bypass-dominated flows, whereas channel-margin positions comprise siltstones from dilute parts of the bypassing flows (Fig. 2.15; Mutti and Normark, 1987; Barton et al., 2010; Hubbard et al., 2014; Stevenson et al., 2015; Li et al., 2016). 2) Convergent (e.g., Barton et al., 2010), or depositional deposits (e.g., Li et al., 2016) are characterised by deposition-dominated flows which deposited coarser sediment in the channel axis, and fractionated finer-grained sediment to the channel margins, resulting in lateral transitions from sandstone, to siltstone, respectively (Fig. 2.15; Walker, 1975; Barton et al., 2010; Alpak et al., 2013; Li et al., 2016). 3) Abandonment deposits, characterised by siltstone, or claystone, which form due to clastic-input shutdown (Fig. 2.15; e.g. Barton et al., 2010). These deposits can form major barriers to sandstone connectivity (Barton et al., 2010; Funk et al., 2012; Alpak et al., 2013; Alpak and van der Vlugt, 2014; Jackson et al., 2019), can be important for the recognition of bounding surfaces in subsurface data (Barton et al., 2010; Morris et al., 2016), and can be used to predict the presence of sandstone down-dip. Despite this, relatively little research has been published on their spatial distribution, facies, and formative processes.

Chapter 2:Deep-water depositional systems: Processes, products, and implications

Figure 2.15: Types of channel-base-deposit commonly identified in channel-fills (Alpak et al., 2013): A) Abandonment deposit formed due to reduction of clastic sedimentation. B) Convergent deposit formed due to higher-energy flows depositing sandstone in the channel-axis, whereas lower-energy flow components deposited LDTs and siltstones in the channel margins (see also Fig. 2.14). C) Bypass lag deposits formed from high- energy flows in which the majority of grain-sizes bypassed down-dip, leaving only the coarsest-grained fragments in the channel axis.

Chapter 2:Deep-water depositional systems: Processes, products, and implications

Figure 2.16: Surface and stratigraphic expressions of a channel-lobe transition zone, Fort Brown Formation, South Africa (Brooks et al., 2018).

Channel-lobe transition zones

The channel-lobe transition zone (CLTZ) of a deep-water system is the geographical area between well-defined channels and levees up-dip, and lobes down-dip (Fig. 2.16; Mutti and Normark, 1987; Wynn et al., 2002; Brooks et al., 2018; Maier et al., 2018). CLTZs are typically located both where flows become relatively unconfined, and at the base-of-slope (Mutti and Normark, 1987; Wynn et al., 2002a; Brooks et al., 2018), though their development can be influenced by active and inherited structures (Maier et al., 2018). CLTZs are characterised by an array of erosional and depositional features, including: isolated and amalgamated scours (Fig. 2.16; Wynn et al., 2002; Hofstra et al., 2015; Brooks et al., 2018; Maier et al., 2018); headless channels (Maier et al., 2018); mounds down-dip of scours (Wynn et al., 2002a); and sediment waves (Fig. 2.16; Wynn et al., 2002; Brooks et al., 2018; Hofstra et al., 2018; Maier et al., 2018). Most previous studies are drawn from modern seafloor data (Mutti and Normark, 1987; Palanques et al., 1995; Morris et al., 1998; Wynn et al., 2002a; Maier et al., 2018), and therefore lack stratigraphic

Chapter 2:Deep-water depositional systems: Processes, products, and implications and sedimentological detail to document CLTZ evolution through time. Recent outcrop studies have documented in detail sedimentological features which may be characteristic of CLTZs: sediment waves (Hofstra et al., 2018); upstream migrating bedforms (Postma et al., 2016); banded sandstones (Hofstra et al., 2018); coarse-grained lag deposits (Fig. 2.16; Brooks et al., 2018); and hybrid beds developed downstream of erosion (Fig. 2.16; Brooks et al., 2018). Similarly, the improved stratigraphic resolution of outcrop studies has revealed that the CLTZ of a system translates laterally and longitudinally through time (Fig. 2.16; Brooks et al., 2018); possibly in response to spatial changes in the position of the flow core in a “hose-like” effect (Hofstra et al., 2018).

Submarine lobes

Submarine lobes are convex-up deposits of gravity flows typically deposited down- dip of where flows exit confinement on the basin-floor; or within intraslope basins created by salt diapirism, faulting, or mass-transport deposits (Ricci-Lucchi, 1975; Mutti, 1977; Shanmugam and Moiola, 1988; Bouma and Wickens, 1994; Booth et al., 2003; Deptuck et al., 2008; Jegou et al., 2008; Prélat et al., 2009; Grundvåg et al., 2014; Oluboyo et al., 2014; Spychala et al., 2015; Picot et al., 2016; Doughty-Jones et al., 2017). Traditionally lobes were thought to be relatively simple, lobate features with radial facies associations. However, the advent of high-resolution seismic imaging, and detailed field studies have demonstrated that lobes can exhibit complex geometries and facies distributions (Fig. 2.17):

Chapter 2:Deep-water depositional systems: Processes, products, and implications

Figure 2.17: Geometry and facies interpretation of submarine lobes deposits of the Sea Lion Fan, North Falkland Basin, Falkland Islands (Dodd et al., 2019). Lobes exhibit highly irregular geometries including lobe fringe deposits “stranded” in the lobe axis, and kilometre-scale lobe-fingers extending from the frontal fringe.

1) Submarine fans were commonly thought to exhibit sheet-like architectures (e.g. Hesse, 1964; Ricci-Lucchi and Valmori, 1980; Tinterri et al., 2003; Remacha et al., 2005; Amy et al., 2007; Marini et al., 2015). However, seismic imaging, outcrop studies, and experimental studies, have since demonstrated that lobes typically stack compensationally in relatively unconfined basins, and confined basins where flows were not laterally confined

Chapter 2:Deep-water depositional systems: Processes, products, and implications (Mutti and Sonnino, 1981; Parsons et al., 2002; Gervais et al., 2006; Deptuck et al., 2008; Prélat et al., 2009; Marini et al., 2015; Picot et al., 2016; Doughty-Jones et al., 2017). Lobes which are strongly laterally contained sometimes exhibit sheet-like architectures (Ricci- Lucchi and Valmori, 1980; Talling et al., 2007a; Sumner et al., 2012; Marini et al., 2015); though stacking patterns can change in response to dynamic changes in confinement (Marini et al., 2015); 2) flow spreading and associated loss of energy results in HDTs (high- density turbidites) deposited in proximal areas and LDTs (low-density turbidites (LDTs) in lateral and distal areas (Prélat et al., 2009). However, focusing of flows can lead to the development on local zones of highly amalgamated HDTs isolated in or LDT-prone areas (Fig. 2.17; Hodgson et al., 2006), and the protrusion of HDTs into distal parts of the lobe in “lobe fingers” (Fig. 2.17; Groenenberg et al., 2010; see also: Dodd et al., 2019); longitudinal flow transformation from turbulent to transitional, or laminar, flow regimes results in the deposition of hybrid beds in distal parts of lobes (Hodgson, 2009; Kane and Pontén, 2012; Kane et al., 2017; Spychala et al., 2017b; Fonnesu et al., 2018; Pierce et al., 2018), increasing heterogeneity; 3) flow interaction with topography can result in highly heterogeneous deposits adjacent to slopes (Fig. 2.18). HDTCs are strongly steered by topography and deposit beds which onlap abruptly onto confining slopes (Fig. 2.18; Amy et al., 2004; Bakke et al., 2013). Deceleration of the flows can cause flow transformation, and deposition of hybrid beds, adjacent to the topography, increasing heterogeneity (Fig. 2.18; Barker et al., 2008; Patacci and Haughton, 2014; Southern et al., 2015). Conversely, LDTCs are less-affected by topography, and deposit thin-bedded drapes high-up on confining slopes (Muck and Underwood, 1990; Al Ja’aidi et al., 2004; Bakke et al., 2013; Spychala et al., 2017c). Flows impacting a confining margin can also be deflected back into the basin, which can shear and rework the deposits of the primary, undeflected, flow (Pickering and Hiscott, 1985; Kneller et al., 1991; Patacci et al., 2015; Tinterri et al., 2016; Tinterri et al., 2017; Spychala et al., 2017c).

Chapter 2:Deep-water depositional systems: Processes, products, and implications

Figure 2.18: Schematic illustration of flow interaction and transformation when interacting with counter- slopes. Larger magnitude flows may not transform due to high-velocities and low clay concentrations (B). Intermediate magnitude flows are likely to transform due to deceleration and elevated clay concentrations (C). D) Low magnitude flows decelerate slowly, exhibit competence-driven sedimentation, and do not transform due to low sediment concentrations (Patacci and Haughton, 2014).

Lobe hierarchy

Prélat et al. (2009) documented an outcrop-based lobe-stacking hierarchy from the Skoorsteenberg Fm. of the Tanqua depocentre, Karoo Basin, South Africa (Fig. 2.19). The hierarchy of architectural elements was defined by characterising both sandstone-prone successions and their bounding silt- and mudstone-rich intervals. Lobe elements comprise

Chapter 2:Deep-water depositional systems: Processes, products, and implications approximately 1 – 3 m thickness of sandstone bed(s), which are bounded by <0.02 m thickness of siltstone (Fig. 2.19; Prélat et al., 2009). Multiple lobe elements stack to form lobes, comprising 4 – 10 m thick interbedded sandstone packages encased in 0.2 – 2 m of laterally consistent, siltstone-prone, thin-bedded turbidites (Fig. 2.19; Prélat et al., 2009). One or more genetically related lobes stack to form a lobe complex, which are typically >30 m thick and separated by 2 – 20 m thick mudstones (Fig. 2.19).

Figure 2.19: Hierarchical scheme of turbidite deposits from the Tanqua depocentre. Four scales of elements: bed, lobe element, lobe and lobe complex are recognised (Prélat et al., 2009).

Subsequent publications (e.g. Marini et al., 2015) have continued to introduce new terms into submarine lobe hierarchical schemes (see also: Cullis et al., 2018); such that the ‘single lobes’ and ‘lobe sets’ of Marini et al., (2015) correspond to the ‘lobe elements’ and ‘lobes’ of Prélat et al., (2009), respectively. In this study, we adopt the terminology of Deptuck et al., (2008) and Prélat et al., (2009) as this seems to be the most robustly defined and most widely adopted (e.g. Macdonald et al., 2011; Burgreen and Graham, 2014; Grundvåg et al., 2014; Rotzien and Lowe, 2014; Collins et al., 2015; Eldrett et al., 2015; Le Heron et al., 2016).

Lobe sub-environments

Outcrop-based studies commonly organise lobes into sub-environments, defined by facies associations. The spatial and temporal distribution of these sub-environments is used to infer the architecture, stacking patterns, and evolution of deep-water systems (Fig. 2.20; Mutti, 1977; Prélat et al., 2009; Prélat and Hodgson, 2013; Burgreen and Graham, 2014; Grundvåg et al., 2014; Terlaky et al., 2016; Kane et al., 2017; Spychala et al., 2017b; Spychala et al., 2017c; Kuswandaru et al., 2018); and their facies associations can be used to

Chapter 2:Deep-water depositional systems: Processes, products, and implications construct gross depositional environment models from subsurface data (Kane and Pontén, 2012; Kilhams et al., 2012; Southern et al., 2017; Dodd et al., 2019). Three main sub- environments are typically recognised: lobe axis, lobe off-axis, and lobe fringe.

Lobe axis

Lobe axis deposits are characterised by relatively thick packages of high net-to- gross HDTs (Fig. 2.20; Prélat et al., 2009; Grundvåg et al., 2014; Spychala et al., 2017b; Kuswandaru et al., 2018; Dodd et al., 2019). Scouring and localised channelisation is common in proximal parts of lobe axis deposits (Bouma, 2000; Hodgson et al., 2006; Burgreen and Graham, 2014; Grundvåg et al., 2014; Stevenson et al., 2015; Terlaky et al., 2016). High-levels of amalgamation and entrainment of substrate result in large numbers of mudstone clasts, which may be aligned along amalgamation surfaces or distributed throughout beds (Prélat et al., 2009; Burgreen and Graham, 2014; Grundvåg et al., 2014; Terlaky et al., 2016).

Figure 2.20: Facies and flow-type distribution in submarine lobes. A) Idealised geometry and facies associations of submarine lobe sub-environments. B) Discrete flow processes which result in contrasting facies and architectures in the frontal and lateral fringes of a lobe (Spychala et al. 2017b).

Chapter 2:Deep-water depositional systems: Processes, products, and implications Lobe off-axis

Lobe off-axis positions are typically characterised by packages of structured sandstones, with localised structureless sandstones, and lower net-to-gross compared to the lobe axis (Fig. 2.20; Prélat et al., 2009; Grundvåg et al., 2014; Spychala et al., 2017b; Dodd et al., 2019). Amalgamation and scouring is less-common, and individual beds are typically thinner (Prélat et al., 2009; Burgreen and Graham, 2014; Grundvåg et al., 2014; Spychala et al., 2017b).

Lobe fringe

Lobe fringe deposits are the outer-most sandstone deposits of a lobe (Fig. 2.20), and as the sandstone pinchout is observed in lobe fringe deposits, they have become the subject of research to characterise stratigraphic traps (Marini et al., 2015; Nagatomo and Archer, 2015; Spychala et al., 2017a; Spychala et al., 2017b; Hansen et al., 2019). Traditionally lobe fringe deposits were thought of as a halo-like shape of LDTs encompassing the more sandstone-prone lobe axis and off-axis (Walker, 1966b; Mutti and Ricci-Lucchi, 1972; Mutti, 1977; Walker, 1978; Pickering, 1981). However, recent work has recognised disparities in facies and geometries between the lateral and frontal, or distal, fringes: 1) lateral fringes are typically characterised by thin-bedded, structured (typically rippled) LDTs (Fig. 2.20; Prélat et al., 2009; Marini et al., 2015; Spychala et al., 2017b); 2) frontal fringes exhibit a wide array of facies. Competence driven deposition from relatively dilute flows which had deposited much of their sediment load updip is interpreted to result in the deposition of LDTs (Fig. 2.20; Grundvåg et al., 2014; Kane et al., 2017; Spychala et al., 2017b). Focussing of HDTCs results in relatively thick, clean sandstones deposited in lobe-fingers (Kane et al., 2017), which can be identified in seismic amplitude maps (Fig. 2.17; Dodd et al., 2019). Increasingly there is also recognition of frontal fringes as hybrid bed prone (Fig. 2.20; Hodgson, 2009; Kane and Pontén, 2012; Kane et al., 2017; Spychala et al., 2017b; Fonnesu et al., 2018); resulting from longitudinal flow evolution due to flow collapse, and substrate entrainment associated bulking (Kane and Pontén, 2012; Kane et al., 2017; Fonnesu et al., 2018).

2.5 Bed-scale controls on reservoir quality distribution

Introduction

Numerous studies document the effects of architectural element stacking patterns and architecture on reservoir quality and fluid flow. At large-scales (e.g. reservoir model), the overall net:gross, stacking pattern of architectural elements, and structural elements 56

Chapter 2:Deep-water depositional systems: Processes, products, and implications exert the strongest controls on permeability (Funk et al., 2012; Amy et al., 2013; Kilhams et al., 2015; Hofstra et al., 2017; Jackson et al., 2019; Jo and Pyrcz, 2019). At the architectural element-scale (e.g. reservoir-model cell), the spatial distribution of facies and continuity of siltstone layers are primary restraints on permeability (Begg and King, 1985; Hamlin et al., 1996; Garland et al., 1999; Stephen et al., 2001; Falivene et al., 2006; Kilhams et al., 2012; Alpak et al., 2013; Amy et al., 2013; Martinius et al., 2017; Jackson et al., 2019). At pore- scale (e.g. core plug), in clastic deposits, the concentration and distribution of detrital and authigenic clays, grain-size, and packing of grains are a strong control on the permeability of a deposit (Fraser, 1935; Beard and Weyl, 1973; Revil and Cathles III, 1999; Lien et al., 2006; Morad et al., 2010; Porten et al., 2016).

Common “missing links” in reservoir characterisation are the bed- and lamina- scales (here referred to as “bed-scale”) (Fig. 2.21; Ringrose et al., 2005; Ringrose et al., 2008; Nordahl et al., 2014). Studies modelling at bed-scale have documented strong permeability anisotrpy within heterolithic- and laminated-sandstones, where fluid migration is primarily controlled by sedimentary structures and mudstone-sandstone ratios (Fig. 2.21; Weber, 1982; Huang et al., 1995; Pickup and Stephen, 2000; Elfenbein et al., 2005; Jackson et al., 2005; Ringrose et al., 2005; Nordahl et al., 2006; Nordahl et al., 2014; Martinius et al., 2017; Hao et al., 2019). These contrasts can strongly inhibit the migration of fluids through heterogenous reservoirs (Jackson et al., 2005; Ringrose et al., 2005; Ruvo et al., 2008; Nordahl et al., 2014; Martinius et al., 2017), result in capillary trapping of oil (Huang et al., 1995; Pickup and Stephen, 2000), and inhibit improved oil recovery techniques (Ringrose and Bentley, 2015; Martinius et al., 2017). Therefore, accounting for heterogeneity at a bed- scale can improve predictions of reservoir performance at larger scales, and provide better matches with production data (e.g. Elfenbein et al., 2005).

Modelling architectural elements

Bed-scale modelling has demonstrated that bed- and lamina-types can have a strong control on reservoir performance (Elfenbein et al., 2005; Jackson et al., 2005; Ringrose et al., 2005; Ruvo et al., 2008; Nordahl et al., 2014; Ringrose and Bentley, 2015; Martinius et al., 2017). However, most of this work has focused on fluvial or shallow- marine systems (Jackson et al., 2005; Ringrose et al., 2005; Nordahl et al., 2006; Nordahl et al., 2014; Martinius et al., 2017; Hao et al., 2019), and few examples are drawn from deep- water systems (Ruvo et al., 2008). There are numerous studies of how stacking patterns of deep-water architectural elements, and their geometries affect reservoir performance (Garland et al., 1999; Falivene et al., 2006; Larue and Hovadik, 2006; Funk et al., 2012; 57

Chapter 2:Deep-water depositional systems: Processes, products, and implications Alpak et al., 2013; Amy et al., 2013; Hofstra et al., 2017; Jackson et al., 2019; Jo and Pyrcz, 2019). However, relatively few of these studies document reservoir quality distribution in lobes, distinguish individual lithofacies or bed-types, or assess reservoir quality in discrete sub-environments (though see Amy et al., 2013; Hofstra et al., 2017), and those that do build only individual facies geomodels, and lack spatial context (Ruvo et al., 2008). Consequently there is limited knowledge of which heterogeneities matter most to permeability, and where and how they affect reservoir property distribution in submarine lobes.

Figure 2.21: Impact of mud-fraction on the permeability of sedimentary structures. Progressive increases in mud-fraction from flaser to lenticular bedding results in decreasing permeability. An increase in mud- fraction more-negatively affects vertical compared to horizontal permeability (Nordahl et al, 2006).

Bed-scale barriers

Bed-scale modelling has focused on case-studies characterizing the effect of lithofacies, particularly heterolithics, on permeability and upscaling this to larger hierarchical levels (Fig. 2.21; Ringrose et al., 2005; Nordahl et al., 2014; Martinius et al., 2017). As such, they often capture a range of heterogeneities making it challenging to distinguish how individual heterogeneities affect permeability (though see effect of mud- fraction in flaser to lenticular bedding in Nordahl et al., 2006, Fig. 1.21; and shale fraction in Hao et al., 2019).

Chapter 2:Deep-water depositional systems: Processes, products, and implications

Figure 2.22: The effect of siltstone fraction (x-axis) on permeability. Increasing the siltstone fraction of a model reduces the permeability. The most-abrupt decrease in permeability begins at a siltstone fraction of approximately 0.3 (Desbarats, 1987).

Siltstone layers

The effect of siltstone layers (frequently referred to as shale- or mudstone-layers) on reservoir performance has long been recognised (Zeito, 1965; Richardson et al., 1978; Haldorsen and Lake, 1984; Begg and King, 1985; Desbarats, 1987; Deutsch, 1989; Jackson and Muggeridge, 2000; Janssen and Bossie-Codreanu, 2005; Hao et al., 2019). Siltstone layers in field-scale models have been shown to reduce effective permeability exponentially with increasing coverage (Fig. 2.22; Begg and King, 1985b; Desbarats, 1987; McCarthy, 1991). However, these studies model numerous siltstone-layers in a thick succession allowing fluids to exploit interconnected sandstone flow pathways. Therefore, relatively

Chapter 2:Deep-water depositional systems: Processes, products, and implications little is known about the fundamental effects of how individual siltstone thickness in sandstones affects connectivity at bed or architectural element scales.

Mudstone-clasts

Mudstone clasts are common depositional features in almost all deep-water depositional environments (Fig. 2.23; Ricci-Lucchi, 1975; Johansson and Stow, 1995; Eschard et al., 2003; Haughton et al., 2003; Ito, 2008; Kane et al., 2009; Burgreen and Graham, 2014; Hubbard et al., 2014; Morris et al., 2016; Terlaky et al., 2016; Kane et al., 2017; Brooks et al., 2018); and have been demonstrated to reduce the effectiveness of improved oil recovery techniques in fluvial systems (Kashikara et al., 2010; Nardin et al., 2013). Despite their prevalence and implications, mudstone clasts are often grouped into structureless sandstone facies in studies, and often not accounted for in modelling (c.f. Kashikara et al., 2010). Similarly, little research considers the effect mudstone clasts can have on permeability, and studies that do are drawn from a similar dataset and primarily consider the 2D distribution of clasts (Bachu and Cuthiell, 1990; Bachu, 1991; Cuthiell et al., 1991).

Figure 2.23: Mudstone-clast-rich facies in a channel axis. Tres Pasos Formation, Chile.

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits CHAPTER 3: Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits Daniel Bell1*, Ian A. Kane1, Anna S. M. Pontén2, Stephen S. Flint3, David M. Hodgson4, and Bonita J. Barrett4

1 SedRESQ, School of Earth and Environmental Sciences, University of Manchester, Manchester, M13 9PL, U.K.

2 Equinor ASA, Research Center Rotvoll, NO-7005 Trondheim, Norway

3 Stratigraphy Group, School of Earth and Environmental Sciences, University of Manchester, Manchester, M13 9PL, U.K.

4 Stratigraphy Group, School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, U.K

3.1 Abstract Initial porosity and permeability in deep-water systems is controlled by primary sedimentary texture and mineralogy. Therefore, understanding the sedimentary processes that control changes in primary texture is critical for improved reservoir quality predictions. A well-constrained, exhumed submarine lobe in the Jaca Basin, and a submarine channel- fill element in the Aínsa Basin, northern Spain, were studied to characterize the depositional reservoir quality in axial to marginal/fringe positions. Construction of architectural panels and strategic sampling enabled analysis of the spatial changes in textural properties, and their relationship to reservoir quality distribution. Samples were analysed in thin-section to establish how depositional processes inferred from outcrop observations affect textural properties. Results show that high-density turbidites are concentrated in lobe- and channel-axis positions and exhibit good depositional reservoir quality. Lobe off- axis deposits contain high- and low-density turbidites and have moderate depositional reservoir quality. Conversely, low-density turbidites dominate lobe fringe and channel- margin positions and have relatively poor depositional reservoir quality. There is a sharp decrease in depositional reservoir quality between the lobe off-axis and lobe fringe due to: 1) an abrupt increase in matrix content; 2) an abrupt decrease in sandstone amalgamation; and 3) a decrease in grain-size. There is an abrupt increase in depositional reservoir quality from channel margin to channel axis corresponding to: 1) an increase in total sandstone thickness and amalgamation; 2) an increase in grain-size, 3) a decrease in matrix content. Rates of change of key properties are up to two orders of magnitude greater between channel-fill sub-environments compared to lobe sub-environments. Spatial variability in 61

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits properties of discrete architectural elements, and rates of changes, provides input to reservoir models during exploration, appraisal, and development phases of hydrocarbon fields.

3.2 Introduction Submarine fans represent large volumes of terrigenous sediment transported from the continental shelf to the slope and basin floor (e.g. Emmel and Curray, 1983; Piper et al., 1999; Talling et al., 2007; Prélat et al., 2010; Clare et al., 2014). Modern deep-marine systems are repositories for anthropogenically derived sediment and pollutants, and organic matter (e.g. Galy et al., 2007; Saller et al., 2008; Hodgson, 2009; Gwiazda et al., 2015), and buried systems form reservoirs for groundwater and hydrocarbons, as well as economic accumulations of minerals (e.g. Pettingill, 1998; Ruffell et al., 1998; Weimer et al., 2000; McKie et al., 2015). Consequently, understanding the distribution of depositional facies and their porosity and permeability is key to understanding the distribution of subsurface fluids and minerals (Lien et al., 2006; Porten et al., 2016; Southern et al., 2017).

The porosity of unconsolidated sediments is controlled by the grain-size, sorting and packing of grains (Fraser, 1935; Beard and Weyl, 1973; Hirst et al., 2002; Lien et al., 2006; Njoku and Pirmez, 2011; Porten et al., 2016), whereas detrital clay content, clay mineralogy, and clay distribution have a strong control on permeability (e.g. Wilson, 1992; Hirst et al., 2002; Lien et al., 2006; Ajdukiewicz et al., 2010; Dowey et al., 2012; Porten et al., 2016). These relationships are demonstrated in terrestrial and shallow-marine deposits (e.g. Pryor, 1973; Haile et al., 2017). However, the general inaccessibility of modern deep- water systems means the primary distribution of their textural characteristics is less-well understood.

Controls on reservoir quality operate on a range of scales. At the largest-scale, sandstone reservoir quality is determined by the volume of the deposit and connectivity, as elements include both sand and non-sand reservoir (e.g. Kerr and Jirik, 1990; Hardage et al., 1996; Afifi, 2005; Jolley et al., 2010; Kilhams et al., 2015; Lan et al., 2016). Within the sandstone portion of the reservoir, ‘quality’ is predominantly determined by grain-scale porosity and permeability (e.g. Fraser, 1935; Marzano, 1988; Ramm and Bjørlykke, 1994; Ehrenberg, 1997; Worden et al., 2000; Marchand et al., 2015; Porten et al., 2016), which is modified by eodiagenetic and mesodiagenetic processes (e.g. Ehrenberg, 1989; Pittman and Larese, 1991; Ramm and Bjørlykke, 1994; Ehrenberg, 1997; Worden et al., 2000). It is recognized that the primary texture of depositional facies in deep-water sandstones can also maintain a strong control even after diagenesis (Hirst et al., 2002; Lien et al., 2006; Njoku 62

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits and Pirmez, 2011; Kilhams et al., 2012; Marchand et al., 2015; Porten et al., 2016). “Depositional reservoir quality” is the initial reservoir potential of a sedimentary accumulation prior to post-depositional modification (Porten et al., 2016). The type of flow that generates a deposit has a strong influence on its texture (Hirst et al., 2002; Lien et al., 2006; Njoku and Pirmez, 2011; Kilhams et al., 2012; Porten et al., 2016; Kane et al., 2017). Therefore, the primary texture of deposits from discrete flow-types can also maintain a strong control during all stages of diagenesis (Hirst et al., 2002; Lien et al., 2006; Njoku and Pirmez, 2011; Kilhams et al., 2012; Marchand et al., 2015; Porten et al., 2016).

Figure 3.1: Locality maps. A) Location of study area in Spain; B) Regional locality map showing the two studied areas; C) Localities of the Gerbe channel-fill outcrops; D) Localities of Upper Broto, Lobe 1 outcrops. Image sources: Esri, DeLorme, HERE, MapmyIndia, OpenStreetMap contributors.

Deep-water systems consist of depositional elements, which are hierarchically organized (e.g. Mutti and Ricci-Lucchi, 1972; Mutti, 1985; Mutti and Normark, 1987; Clark and Pickering, 1996; Sprague et al., 2002; Deptuck et al., 2008; Prélat et al., 2009; Di Celma et al., 2011), the organization of which controls the overall size and connectivity of a reservoir. Architectural elements are determined by their size, architecture, bounding surfaces, and relationship to other architectural elements (e.g. Miall, 1985; Mutti and Normark, 1987; Clark and Pickering, 1996; Sprague et al., 2002; Prélat et al., 2009). Individual depositional facies have variable grain-scale textures, and therefore the spatial arrangement of these depositional facies within an architectural element will determine 63

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits reservoir potential distribution at that hierarchical level. The stacking of architectural elements and their inherited grain-scale texture allows prediction of reservoir quality at higher levels in the architectural hierarchy. Therefore, understanding facies distribution and grain-scale character is critical to improved prediction of reservoir distribution. Previous publications related to the integration of architectural- and grain-scale observations typically consider broad proximal-to-distal trends, or consider facies variability with limited spatial control (Hirst et al., 2002; Lien et al., 2006; Njoku and Pirmez, 2011; Kilhams et al., 2012; Marchand et al., 2015; Porten et al., 2016). Geochemical and mineralogical variations have been recognized within a deep-water channel complex and attributed to the primary texture (Aehnelt et al., 2013). However, no published work has attempted to constrain the depositional reservoir quality within a single architectural element. To assess this issue the following research questions will be addressed: 1) How can an architectural element be characterized at grain-scale? 2) How does reservoir potential vary spatially within an individual architectural element? 3) How do sediment gravity flow processes influence depositional reservoir quality and its distribution?

3.3 Geological setting

During the Early Eocene the Aínsa-Jaca Basin developed as an east-west trending, southward migrating foredeep (Puigdefàbregas et al., 1975; Mutti, 1984; Labaume et al., 1985; Mutti, 1985; Mutti et al., 1988; Muñoz, 1992; Teixell and García-Sansegundo, 1995). The deep-water deposits form the Hecho Group (Fig. 3.2; Mutti, 1985). The Aínsa Basin fill predominantly consists of submarine slope channel systems and mass-transport deposits, separated by marlstones (e.g. Mutti, 1977; Clark et al., 1992; Mutti, 1992; Clark and Pickering, 1996; Remacha et al., 2003; Pickering and Corregidor, 2005; Moody et al., 2012; Dakin et al., 2013; Bayliss and Pickering, 2015). The Gerbe System (Fig. 3.2) is interpreted as a canyon to lower-slope channel system (Mutti, 1992; Clark and Pickering, 1996), and consists of: 1) a lower unit that comprizes conglomerate lags, which is interpreted as sediment bypass-dominated; and 2) an upper unit that comprizes fining- upward channel-fill elements and records the aggradation and shutdown of the channel system (Mutti, 1992). This study analyzes one channel-fill element from the upper unit.

The Jaca Basin succession, which is separated from the exposed part of the Aínsa Basin by the Boltaña Anticline, is interpreted as a series of submarine fans, consisting of lobes and basin-plain deposits (Fig. 3.2; Mutti, 1977; Mutti, 1992; Remacha et al., 2005).

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits The stratigraphy of the basin-fill is constrained by nine regionally mapped ‘megabeds’ (Rupke, 1976; Labaume et al., 1987; Rosell and Wiezorek, 1989; Payros et al., 1999).

Figure 3.2: Stratigraphy and geological setting of the Aínsa-Jaca Basin fill. Regional depositional dip is from right to left, with tentative correlation across the Boltaña anticline following Das Gupta and Pickering (2008).

The lobe component of this study focuses on the Upper Broto System, immediately underlying the MT-4 megabed (see also: Mutti, 1992). The Upper Broto is interpreted as proximal lobes (Mutti, 1992), with distal hybrid bed dominated packages where depositional architecture is interpreted to have been influenced by topography (Remacha and Fernández, 2003; Remacha et al., 2005).

3.4 Methods Different stratigraphic correlations between the Aínsa and Jaca Basins have been proposed (Mutti, 1984; Mutti, 1985; Mutti, 1992; Remacha et al., 2003; Das Gupta and Pickering, 2008; Caja et al., 2010; Clark et al., 2017). Following Das Gupta and Pickering (2008), the Gerbe (Aínsa) and Broto (Jaca) Systems are considered as broadly equivalent and are studied here. Whilst uncertainty remains with this correlation, the two systems form part of the genetically related wider basin-fill, have the same burial history, and, for the puposes of this study, are comparable. Furthermore, linked channel-fills and lobes may accumulate diachronously (e.g. Hodgson et al., 2016), and challenges in correlating individual channel-fills with individual lobes at outcrop mean that sampling the exact time- equivalent stratigraphy may not be possible. One channel-fill element and one lobe were selected from the outcrops to be studied in detail. Detailed sedimentary logs and thin- section analysis were used to investigate spatial changes in architecture, facies and grain- scale texture within the channel-fill and lobe.

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits In the subsurface, reservoir intervals are typically sampled by core plugging at regular intervals, and are biased towards sandstone. These sampling protocols are not designed to capture variability at the architectural element scale. An alternative approach is to sample beds that conform to the mean average bed thickness in an architectural element. However, this would preferentially select thinner beds, which are more common than medium- or thick-bedded sandstone, but typically account for a smaller proportion of the overall sandstone content. Therefore, to characterize an architectural element at grain-scale a repeatable ‘stratigraphic sampling’ method was developed to sample an ‘average’ bed characteristic of the sampled succession (Fig. 3.3). The method is as follows: a logged section through an architectural element was sub-divided into three sections or ‘windows’ of equal thickness (steps 1 and 2, Fig. 3.3). Where a window boundary fell within a bed, the boundary was moved to the closest base or top of the nearest sandstone bed. The proportion of sandstone that the thickest and thinnest beds constituted in a window was calculated (step 3, Fig. 3.3). An average of the two was taken and converted back to a thickness (step 3 Fig. 3.3). The bed with a thickness that most closely corresponded to this calculated thickness was chosen to be sampled as an ‘average bed’ for the succession (step 4, Fig. 3.3). A sample of the selected bed was collected from the center of the bed, to avoid the coarse-grained base or fine-grained top. Sampling was designed to assess sedimentary process controls on the depositional reservoir quality of sandstones within architectural elements. Therefore, the texture of non-reservoir facies (e.g. mudstones) were not studied. However, the effects of these potential barriers to flow are considered in architectural element scale analysis.

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits

Figure 3.3: The workflow for a repeatable stratigraphic sampling method. Vertical scale in meters.

Thin-sections were point-counted using a petrographic microscope at 300 points per section (step 5, Fig. 3.3). The Gazzi-Dickinson method was used to determine composition (Gazzi, 1966; Dickinson, 1970; Ingersoll et al., 1984). The grain-size was determined by measuring the long axes of optically distinguishable grains. The median and D90 (90th percentile) grain-sizes are used for analysis as mean results were skewed by mudstone chips in some samples. Sorting was determined following Folk and Ward (1957) by measurement of the long and short axis of optically resolvable detrital grains. Detrital and authigenic clays were not distinguishable in thin-section; therefore, there is some uncertainty in inferring initial detrital clay contents. However, it is recognized that proportions of detrital matrix content in modern turbidites is variable between different bed-types (Sumner et al., 2012; Stevenson et al., 2014a; Stevenson et al., 2014b). Thinner-bedded, finer-grained distal deposits have higher detrital matrix contents compared to comparatively thicker-bedded, coarse grained deposits (Stevenson et al., 2014a; Stevenson et al., 2014b). As the clay content and trends are similar to those observed here the total clay proportion is likely to be a good indicator of original detrital clay content.

3.5 Facies Lithofacies are summarized in Table 3.1 and grouped into facies associations in Table 3.2:

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits

Table 3:1: Lithofacies observed in the study area

Facies Lithology Sedimentology Thickness Interpretation Facies (m) code Mudstone Silty claystone and Massive- to weakly-laminated. 0.01 – 2.5 Background sedimentation or LF1 clayey siltstone deposition from a dilute flow. Ripple Coarse-siltstone to Ripple cross-lamination, typically located in the 0.02 – 0.1 Traction plus fallout from a turbulent LF2 laminated fine-sandstone, rarely upper parts of the bed. Climbing ripples locally flow (Allen, 1982; Southard, 1991; sandstone medium-sandstone. observed. Commonly produces wavy bed tops. Mutti, 1992). Planar- Very fine- to medium- Laminated sandstone with 0.1 m – 1mm scale 0.04 – 0.5 Layer-by-layer deposition from LF3 laminated sandstone. alternating coarser – finer laminae. Laminae are repeated development and collapse of

sandstone typically parallel, rarely sub-parallel. Common near-bed traction carpets (Sumner et coarse-tail grading. Infrequent occurrence of al., 2008) and migration of low- plant fragments and mudstone chips aligned amplitude bed-waves (Best and with laminae. Bridge, 1992; Sumner et al., 2008). Structureless Very fine- to medium- Typically structureless and commonly normally- 0.05 – 0.5 Rapid settling from a high LF4 sandstone sandstone, rare graded or coarse-tail graded. Occasional concentration flow under hindered coarse-sandstone. mudstone chips occur, typically in fine- to settling conditions (e.g. Sanders, 1965; coarse-sandstone beds. Nummulites are Lowe, 1982; Mutti, 1992). infrequently observed. Mm-spaced Medium- to coarse- Laminated sandstone, laminae are 5 – 15 mm 0.1 – 0.5 Repeated collapse of traction carpets LF5

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits

laminated sandstone. thick, parallel to sub-parallel and typically below a high-density turbidity current sandstone coarser-grained than surrounding sandstone. (e.g. Mutti, 1992; Cartigny et al., Coarser laminae are typically inversely graded. 2013), or kinetic sieving within the traction carpet (e.g. Talling et al., 2012). Cross-bedded Medium- to very Centimeter- to decimeter-scale cross 0.4 – 0.65 Bed reworking by long-lived flows LF6 sandstone coarse-sandstone stratification. Foresets commonly contain clasts with relatively low depositional rates of mudstone or detrital material, with and near-bed concentrations which maximum grain-sizes of approximately 20 cm. bypassed basin-ward (Allen and The size of clasts reduces vertically up foresets. Friend, 1976; Mutti, 1992; Baas et al.,

69 Transition gradually to planar laminated 2004; Baas et al., 2011; Talling et al.,

sandstone over 5 – 10 cm at the top. 2012). Conglomerate Poorly sorted clasts of Clast supported structureless deposit. Often 0.35 – 1.3 Deposition from a highly LF7 pebbles and cobbles, subtle grading is present in the upper 30 cm. concentrated flow under hindered with infrequent Clasts are usually sub- to well-rounded and settling conditions (e.g. Walker, 1975; boulders (max. 36 include lithic fragments, quartz, limestone, Lowe, 1982), or frictional freezing cm). Poorly sorted mudstone and flint. (Mutti, 1992). sandstone matrix. Matrix- Poorly-sorted, clast- 0.2 – 25 0.2 – 25 Clast-rich, poorly-sorted, matrix LF8 supported rich matrix consisting supported beds are suggestive of en-

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits

chaotic deposits of sandstone, siltstone masse deposition from laminar (debris) and mudstone. flows with a high yield strength (e.g. Nardin et al., 1979).

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits

Table 3:2: Facies associations observed in the study area

Facies Description Interpretation association

FA1 An overall thinning- and fining-upwards succession 7 – 9 m thick Overall thinning- and fining-upward succession filling an incision is which fill a basal incision surface. Characterized by: LF8 at the base consistent with channel axis deposits (e.g. Mutti, 1977; Clark and overlain by interbedded LF2 and LF1; a sharp erosive contact to Pickering, 1996; Campion et al., 2000; Sullivan et al., 2000; amalgamated LF7; a sharp, erosive contact to thick-bedded, Beaubouef, 2004; McHargue et al., 2011; Hubbard et al., 2014; Li et amalgamated LF3, LF4 and LF6 containing abundant mudstone al., 2016). chips and lithic-fragments derived from LF7; a thinning- and fining-

71 upward succession of thin-bedded, non-amalgamated LF3 and LF2.

FA2 Thin-bedded and non-amalgamated LF3 and LF2 0.3 – 1.5 m thick. Thin-bedded deposits which are adjacent to, and pass into, thicker – LF8 may be locally present at the base of the association. Beds are bedded deposits of FA1. Consistent with channel margin deposits predominantly tabular and pass laterally into FA1. described elsewhere (Mutti, 1977; Clark and Pickering, 1996; Campion et al., 2000; Eschard et al., 2003; Beaubouef, 2004; Hubbard et al., 2014; Li et al., 2016).

FA3 Commonly amalgamated packages of LF4 and LF3, with localized Thick-bedded, structureless, laterally extensive beds which transition LF5, 4 – 6 m thick. Localized scouring on a centimeter- to meter- to thinner-bedded deposits on a 0.1 – 1 km scale and form packages scale, however bed geometries are typically tabular over 10’s – 100’s several meters in thickness are consistent with lobe axis deposits

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits

meters. (Prélat et al., 2009; Grundvåg et al., 2014; Marini et al., 2015).

FA4 Interbedded, infrequently amalgamated medium- and thin-bedded Medium- and thin-bedded structured sandstones deposited LF3 and LF2 packages 4 – 6 m thick. LF4 is infrequently observed. predominantly from low-density turbidity currents which form Beds typically have a sharp base and sharp top overlain by LF1. meter-scale packages are consistent with lobe off-axis deposits (e.g. Localized, decimeter-scale scouring is observed, however beds are Prélat et al., 2009). predominantly tabular at outcrop-scale.

FA5 Thin-bedded sandstone and siltstone packages 1 – 2.5 m thick Thin-bedded, rippled, sandstones deposited by dilute low-density dominated by LF2 and interbedded with LF1. LF3 is infrequently turbidity currents are commonly identified in lateral lobe fringe observed. Amalgamation is rare. Beds typically exhibit a sharp base, deposits (e.g. Prélat et al., 2009; Grundvåg et al., 2014; Marini et al.,

72 and sharp top overlain by LF1. Bed geometries are tabular to wavy. 2015; Kane et al., 2017; Spychala et al., 2017b). Similar facies in the

Jaca Basin have previously interpreted as lobe-fringe by Mutti (1977).

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits 3.6 Architectural element interpretations The geometrical relationships established in the stratigraphic correlations of Figures 3.4 and 3.5, and the facies associations described in Table 3.2, are used to interpret the environment of deposition of the Gerbe and Broto architectural elements.

Figure 3.4: Architectural panel of the Gerbe channel-fill element (channel-fill element 1 of this complex). The orientation is broadly across depositional strike based on geometry and paleocurrent analysis. The channel-form is defined by a major basal erosion-surface. This is overlain by a debrite attributed to channel- excavation.

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits

Figure 3.5: Architectural panels of Lobe 1 of the Upper Broto system: A) Depositional-dip correlation of Lobe 1, from lobe axis at Fanlo 2 to frontal lobe fringe at Yésero; B) Depositional-strike architecture of Lobe 1, from lobe axis at Fanlo 1 and Fanlo Track to lobe off-axis at A Lecina; C) Paleocurrents

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits measured in Lobe 1 suggest flow to the northwest, consistent with other studies within the basin (e.g. Mutti 1977, 1984, Remacha et al., 2005); D) Stratigraphic context of down depositonal-dip correlation panel showing Lobe 1 in relation to key marker beds.

Gerbe architectural element

The Gerbe channel-fill element is approximately 150 m wide, representing a near complete across depositional-strike transect as indicated by paleocurrent measurements (Fig. 3.4), and exhibits marked lateral facies changes between log localities (Fig. 3.4). The measured sections at localities (localities refer to measured sections herein) Gerbe 2 and Gerbe 3 are 8.5 m and 7.9 m thick respectively and are characterized by FA1 (Figs. 3.4, 3.6B and D). The Gerbe 1 and Gerbe 4 localities are 1.4 m and 1.1 m, respectively, and are characterized by FA2 (Figs. 3.4, 3.6A).

Broto architectural element

The Broto lobe (Lobe 1 of Chapter 7; Fig. 3.5), has a comparatively tabular geometry and is approximately 16 km in length and more than 0.9 km wide (Fig. 3.5A, B). The element exhibits more-gradual lateral facies changes compared to the Gerbe channel- fill element (Fig. 3.5A, B). The base and top of the architectural element are marked by a debrite (Figs. 3.5D, 3.6E) and a laterally persistent thin-bedded package that can be correlated on a kilometer-scale between outcrops (Fig. 3.6G), respectively. The Fanlo 1, Fanlo 2 and Fanlo Track localities predominantly consist of FA3, and are interpreted as lobe axis deposits (Fig. 3.5, 3.6E; e.g. Prélat et al., 2009). The A Lecina, Oto and Linás de Broto localities are characterized by FA4 and are interpreted as lobe off-axis (Fig. 3.6F; e.g. Prélat et al., 2009). The Yésero locality consists of FA5 and is interpreted as the lobe fringe (Fig. 3.6H; e.g. Prélat et al., 2009). The observed facies changes and geometries are consistent with lobes observed elsewhere (e.g. Prélat et al., 2009; Grundvåg et al., 2014; Marini et al., 2015; Kane et al., 2017; Spychala et al., 2017a), and have previously been interpreted as lobes within the Jaca Basin (Mutti, 1977; Mutti, 1992).

Gradual facies changes over 100’s – 1000’s meters in Lobe 1 contrast to distal deposits of the Upper Broto System (i.e. the basin plain, sensu Remacha et al., 2005). Northwest of Jaca (Fig. 3.1A) basin-plain deposits exhibit more tabular cross-sectional geometries, with less lateral variability, and do not form lobes (Remacha and Fernández, 2003; Remacha et al., 2005). An idealized basin-plain bed comprizes: a clean basal sandstone, overlain by a clast-rich, poorly-sorted division, followed by a thick mudstone cap with an upper-carbonate-rich division (Remacha and Fernández, 2003; Remacha et al., 75

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits 2005). Bases of basal clean sandstone divisions have flute and tool marks suggesting flow to the west/northwest. Upper surfaces of some sandstone beds have ripple cross laminations suggesting paleoflow to the north, interpreted to form due to flow deflection from the southern, carbonate slope (Remacha and Fernández, 2003; Remacha et al., 2005). Poorly sorted divisions are interpreted to form either through: repeated deposition and liquefaction of lamina from bores within deflected turbulent flows (Remacha and Fernndez, 2003, Remacha et al., 2005); or from turbulent flows which collapsed to form predominantly laminar flows during flow deflection (Chapter 7).

3.7 Results Architectural and textural data were collected for both the channel-fill element and lobe. Textural properties are split into facies associations for each architectural element to enable comparison of architectural and textural properties, and consequent depositional reservoir quality in different sub-environments within deep-water systems.

Composition

Siliciclastic detrital grains

Non-carbonate detrital grains consist of: monocrystalline quartz (6% – 23.7%), polycrystalline quartz (up to 4.3%), plagioclase feldspar (up to 14.3%), K-feldspar (trace), sedimentary rock fragments (up to 3.3%), metamorphic rock fragments (up to 3.7%), igneous rock fragments (up to 3.7%), muscovite (up to 1.3%), and trace minerals.

Carbonate detrital grains

Carbonate grains are common and can make up the largest group of detrital grains within a sample (6.3 – 27.3%). Carbonate grains consist of dolostone, sparitic limestone, micritic limestone, peloids, aggregate grains, and fossils. Fossils identified in thin section include foraminifera (benthic and planktonic), gastropods, algae, and echinoderm fragments.

Authigenic minerals

Calcite is the dominant authigenic mineral within the samples (19.7% – 38.3% of grains counted), present as both pore-filling cement and replacement of detrital grains. Minor amounts of authigenic quartz (typically <5%, but locally up to 12%) are identified, typically as overgrowths or pore-filling cement. Traces of authigenic plagioclase and oxide minerals are present, typically <1%. 76

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits

Figure 3.6: Facies association photos. A) Channel-margin facies: structured sandstones and siltstones deposited from low-density turbidity currents; B) channel-axis facies, from the base: pebbly mudstone, conglomerate, and cross-bedded sandstone. The cross-bedded sandstone has an erosional base and overlies the conglomerate, with evidence for substrate entrainment; C) channel-margin siltstones overlying pebbly- mudstone; D) channel-axis pebbly-mudstone; E) amalgamated, thick-bedded lobe axis sandstones. Onlap of beds onto the underlying debrite is observed to the right of the hammer (length 28 cm); F) medium-bedded 77

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits lobe off-axis; G) Thin-bedded package overlying Lobe 1 at Fanlo 2. Top of Lobe 1 is at the base of the hammer; H) Thin-bedded lobe-fringe sandstones and siltstones at Yésero.

Matrix minerals

Matrix-mineralogy is not optically resolvable. However, where present, matrix is typically identified between or coating larger grains. Pseudomatrix consisting of ductile grains (typically mudstone or micritic limestone) is commonly observed within samples.

Classification

A standard ternary plot of quartz-feldspar-lithic fragments indicates that most samples are categorized as sublitharenites (Fig. 3.7; see also: Das Gupta and Pickering, 2008; Caja et al., 2010). Linked channel and lobe deposits are shown to exhibit compositional differences (e.g. Stalder et al., 2017). Here, Gerbe samples are more quartz- rich, with some classified as quartz arenites, whereas Broto samples are more feldspar-rich (Fig. 3.7). This study primarily concerns textural properties and trends, and so composition is not discussed in depth. Compositional evolution, classification and provenance within the Hecho Group are reported in Fontana et al. (1989), Zuffa et al. (1995), Das Gupta and Pickering, (2008), and Caja et al. (2010).

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits

Figure 3.7: QFL (Quartz, Feldspar, Lithic fragments) plots from the 36 point-counted thin- sections, assigned to each study area. Most samples are classified as sub-litharenites. However, the Gerbe samples are typically more quartz-rich and feldspar-poor compared to Lobe 1 samples. Ternary plot after Pettijohn et al. (1972).

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits

Basi Net sandstone Sandston %Amalgam Median grain-size D90 Sorting Mean Mean Locality n thickness (m) e % ated (mm) (mm) (F&W) matrix% authigenic% Aíns Gerbe 1 0.425 31.3 14.286 0.090 0.127 0.225 25.675 31.900 a Aíns Gerbe 2 3.360 39.3 15.385 0.098 0.161 0.181 19.633 39.467 a Aíns Gerbe 3 3.680 46.5 39.394 0.109 0.155 0.205 14.433 47.667 a Aíns

80 Gerbe 4 0.040 3.6 0.000 0.041 0.053 0.245 34.333 36.900

a Jaca Fanlo 2 5.510 90.0 78.378 0.150 0.212 0.204 7.556 36.111 Jaca Fanlo 1 3.100 77.1 67.742 0.175 0.285 0.134 8.556 31.222 Jaca Oto 2.895 68.9 38.095 0.096 0.141 0.188 15.778 35.889 Linás de Jaca 3.220 73.7 34.091 0.166 0.316 0.199 15.833 33.417 Broto Jaca Yésero 2 1.385 54.1 3.636 0.056 0.079 0.174 29.000 32.444 Jaca A Lecina 3.945 67.3 28.571 0.169 0.235 0.208 15.444 36.333 Fanlo Jaca 1.750 76.1 62.500 0.250 0.369 0.173 8.433 37.900 Track

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits

Table 3:3: Architectural and textural properties at each logged section

Basin Sub- Avg. sandstone Avg. Avg. Avg. median Avg. Avg. Avg. Avg. mean environment thickness (m) sandstone% %amalgamated grain-size D90 sorting mean authigenic% (mm) (mm) (F&W) matrix% Aínsa Channel-axis 3.520 42.9 27.389 0.103 0.158 0.193 17.033 43.567 Aínsa Channel- 0.233 17.4 7.143 0.065 0.090 0.235 30.004 34.400 margin Jaca Lobe axis 3.453 81.1 69.540 0.192 0.289 0.170 8.181 35.078

Jaca Lobe off-axis 3.353 70.0 33.586 0.143 0.230 0.198 15.685 35.213 Jaca Lobe fringe 1.385 54.1 3.636 0.056 0.079 0.174 29.000 32.444 Table 3:4: Architectural and textural properties of facies associations

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits

Figure 3.8: Spatial variation in textural and architectural properties within Lobe 1 and the Gerbe channel-fill element.

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits

Figure 3.9: Example grain-scale textures of lithofacies: A) High-density turbidite from lobe axis setting; B) High-density turbidite from lobe axis setting. A foram test is present at the top of the sample; C) Low- density turbidite from lobe off-axis setting; D) Low-density turbidite from lobe off-axis setting; E) Low- density turbidite from lobe fringe setting; F) Channel-axis conglomerate, with large fine-grained dolostone clast; G) Low-density turbidite from channel-axis setting; H) Ripple cross-laminated low-density turbidite from channel-margin setting; I) High-density turbidite from channel-axis setting.

Gerbe channel-fill element

Architectural- and bed-scale data

The thickness of the Gerbe channel-fill element increases from Gerbe 1 and 4 to Gerbe 2 and 3 respectively (Fig. 3.4). The proportion of amalgamated sandstone beds is similar between the channel-margin at Gerbe 1 and channel-axis at Gerbe 2; however, the amalgamation ratio is higher at Gerbe 3, and lower at Gerbe 4 (Figs. 3.8B; Tables 3.3, 3.4). Sandstone-percentage is similar in the channel-axis and channel-margins due to the debrite located in the channel-axis, however the total thickness of sandstone is greater in the channel-axis (Fig. 3.8B; Table 3.4).

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits Lateral variation in texture

Grain-size varies within the channel-fill sandstones (Figs. 3.8A, 3.9; Table 3.3). The median grain-size slightly increases from the western channel-margin Gerbe 1, into the channel-axis deposits of Gerbe 2 and 3 (440 µm/km; Figs. 3.8A, 3.10; Table 3.3). Median grain-size then decreases to the eastern channel-margin at Gerbe 4 (1130 µm/km; Fig. 3.8A; Table 3.3). The D90 (90th percentile of grain-size) shows a similar trend, increasing from Gerbe 1 to Gerbe 2 and 3 (1700 µm/km; Figs. 3.8A, 3.10; Table 3.3). The D90 at Gerbe 4 is finer than in other positions (Fig. 3.8A; Table 3.3). The optically-resolvable detrital grains of the channel-margin deposits are better sorted compared to the channel- axis deposits (Fig. 3.8A, Table 3.3). The authigenic mineral content increases from the channel-margins into the channel-axis positions (Fig. 3.8B; Table 3.4). Channel-margin deposits at Gerbe 1 and 4 have higher matrix content compared to channel-axis deposits at Gerbe 2 and 3 (Fig. 3.8B; Tables 3.3, 3.4). Matrix content increases from Gerbe 2 to 1, and Gerbe 3 to 4 at a rate of 310 %/km and 340 %/km respectively (Fig. 3.10).

Vertical textural variation

Textural properties also vary vertically within the Gerbe channel-fill element (Figs. 3.9, 3.11). Overlying the basal debrite, channel-axis deposits show an increase in grain-size (both median and D90) from thin-beds (>4 m on Figs. 3.11A, B) into the thicker-bedded, amalgamated conglomerate and sandstone (2 – 4 m on Figs. 3.11A, B). There is a fining upward profile into the thinner-bedded deposits in the upper 2 m (Figs. 3.11A, B). Channel-margin positions show a general fining upward trend in both median and D90 grain-sizes (Figs. 3.11A, B). Sorting improves upwards in both channel-axis and channel- margin deposits (Fig. 3.11B), a decrease in sorting at 5.2 m at Gerbe 2 is observed within the conglomerate sample. There is no clear trend to vertical variation in authigenic mineral content, however an upward decrease is observed at Gerbe 1 (Fig. 3.11D). There is a general upward increase in matrix content at all positions (Fig. 3.11E). At channel-axis positions matrix content decreases from the lower thin-bedded deposits into the thick- bedded amalgamated sandstones located between 2 and 4 m (Fig. 3.11E). Matrix content then shows a general increase upwards into the overlying thinner-bedded deposits (Fig. 3.11E).

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits

Figure 3.10: Schematic illustration of the spatial variation in architectural and textural properties within deep-water channel-fill elements and lobes. Within the lobe, textural and architectural properties vary most- strongly laterally. The channel-fill element shows strong trends in textural and architectural properties both laterally and vertically. The inferred reservoir quality decreases from lobe axis to lobe fringe, and from channel-axis to channel-margin. Reservoir quality also decreases vertically within the Gerbe channel-fill element, if the basal non-reservoir debrite is not included. The lateral gradient of change in properties is typically around two orders of magnitude greater within the channel-fill element compared to the lobe.

Lobe 1

Architectural data

The thickness of Lobe 1 decreases from 6.1 m in the most proximal position (Fanlo 2) to 2.6 m in the most distal position (Yésero; Fig. 3.5A). Thickness increases across depositional strike from Fanlo 1 to the lobe off-axis position of A Lecina (Fig. 3.5B). The proportion of amalgamated beds decreases down-dip from Fanlo 2 to Yésero (4.5%/km; Figs. 3.8D, 3.10; Table 3.3), and across strike from Fanlo 1 to A Lecina (Fig. 3.8F; Table 3.3). The degree of amalgamation higher in lobe axis deposits compared to lobe off-axis and lobe fringe deposits (Fig. 3.8D; Table 3.4). Sandstone-percentage decreases from Fanlo 2 to Yésero (2.8%/km; Figs. 3.8D, 3.10; Table 3.3). Across-strike, the sandstone- percentage decrease from Fanlo 1 to A Lecina is less pronounced (Fig. 3.8F; Table 3.3). Lobe axis deposits exhibit a higher sandstone proportion than lobe off-axis and lobe fringe deposits (Table 3.4).

Textural data

Textural properties vary spatially within Lobe 1 (Figs. 3.8C and E, 3.9; Table 3.3). Overall, median grain-sizes decrease down-dip from Fanlo 2 to Yésero (6 µm/km; Figs. 3.8C, 3.10; Table 3.3). Across strike, median grain-size decreases from Fanlo 1 and Fanlo Track, to A Lecina (Fig. 3.8E; Table 3.3). The D90 decreases down-dip from Fanlo 2 to Yesero (5 µm/km; Figs. 3.8A, 3.10; Table 3.3). D90 increases northwards, across strike 85

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits from Fanlo 1 to Fanlo Track, but is lower at A Lecina (Fig. 3.8E; Table 3.3). In both measurements of grain-size, there is a down-dip increase from Oto to Linás de Broto (Fig. 3.8C; Table 3.3). Sorting is relatively consistent throughout Lobe 1, with most samples categorized as moderately or moderately-well sorted (Figs. 3.8C, E; Table 3.3; sensu Folk and Ward, 1957).

The proportion of authigenic minerals shows little variation across Lobe 1 (Fig 3.8D, F; Table 3.3). Positions with the highest authigenic mineral contents are in proximal areas (Fanlo 2, Fanlo Track, A Lecina, and Oto; Figs. 3.8D, F; Table 3.3); however, Fanlo 1 has the lowest authigenic mineral content (Figs. 3.8D, F; Table 3.3). The proportion of matrix increases down-dip from Fanlo 2 to Yésero (Fig. 3.8D; Table 3.3). Matrix content also increases across-strike from Fanlo 1 to A Lecina (Fig. 3.8F; Table 3.3).

Lobe axis deposits exhibit the coarsest median grain-sizes compared to lobe off- axis and lobe fringe deposits (Figs. 3.8C and E, 3.9; Table 3.3); and coarser D90 grain-sizes compared to lobe off-axis deposits (Figs. 3.8C and E, 3.12B and C; Table 3.3). The lobe fringe has a much lower D90 (Figs. 3.8C, 3.12B and C; Table 3.3). Sorting increases from lobe axis deposits into lobe off-axis deposits, and decreases from lobe off-axis deposits into the lobe fringe deposits (Figs. 3.8C and E, and 3.12C and D; Table 3.4).

Lobe axis and lobe off-axis deposits exhibit marginally higher contents of authigenic minerals than the lobe fringe deposits (Fig. 3.12A; Table 3.4). Lobe axis deposits exhibit the lowest matrix contents, lobe off-axis deposits have medial matrix contents, and the lobe fringe deposits have the highest matrix content (Figs. 3.8D and F, 3.12A, B and D; Table 3.4). The rate of change is different between the lobe axis and lobe off-axis, and lobe off-axis and lobe fringe. Matrix content increases at 0.6 %/km between Fanlo 2 and Linás de Broto, compared to 3.8 %/km between Linás de Broto and Yesero (Lobe overall increase is 1.3 %/km; Figs. 3.8D, 3.10).

Comparison of textural properties

Scatter plots of textural properties suggest channel-margin and channel-axis deposits have different textural characteristics (Fig. 3.12). Higher proportions of matrix correspond to lower proportions of authigenic minerals in the Gerbe samples (Fig. 3.12A). Increased matrix content also corresponds to finer grain-sizes and better sorting of detrital grains in the samples (Fig. 3.12B, C). Decreases in grain-size are associated with improved sorting of detrital grains, and increased matrix content (Fig. 3.12B, D). Channel-margin deposits (Gerbe 1 and 4) have fine grain-sizes, high proportions of matrix, low proportions 86

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits of authigenic minerals and better sorting (Figs. 3.8A and B, 3.12; Table 3.4). Comparatively, channel-axis deposits exhibit coarser grain-sizes, lower proportions of matrix, higher proportions of authigenic minerals, and are more poorly sorted (Figs. 3.8A and B, 3.12; Table 3.4).

Figure 3.11: Vertical variation in textural properties at each Gerbe logged section. The top of each section is used as a datum. Grain-size typically decreases upwards within the channel fill (A and B). Within the channel-axis there is an apparent initial increase in grain-size. This is attributed to the upward transition from a package of thin-beds, interpreted as the deposits of the dilute tails of larger flows which bypassed the locality, to the main aggradational-fill of the channel. Sorting increases upwards within the channel-fill (C). The most poorly-sorted sample (~3.2 m Gerbe 2) is a conglomerate (LF6). Vertical changes in authigenic content are not strongly developed (D). The proportion of matrix increases upwards within the channel-fill (E). The initial decrease in the channel-axis represents the transition from the initial bypass-phase to the main aggradational-phase of sand deposition.

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits Lobe 1 exhibits a similar separation of textural properties. Increasing matrix content correlates with decreasing grain-size and better sorting (Fig. 3.12A, B, D). Matrix and authigenic mineral contents do not exhibit a strong relationship (Fig. 3.12A). Samples with coarser grain-sizes also exhibit poorer sorting compared to samples with finer grain- sizes (Fig. 3.12C). Separate groupings of lobe axis, lobe off-axis and lobe fringe samples suggests the sub-environments have distinct textural properties (Fig. 3.12) although this is likely to form part of a continuum.

Comparison of channel-fill element and lobe sub-environment deposits shows similarities between the different architectural elements (Fig. 3.12). Positions dominated by thinner-bedded deposits (channel-margin and lobe fringe) have finer grain-sizes, higher matrix content, are better sorted and have marginally lower authigenic mineral content compared to positions with thicker-bedded channel-axis and lobe axis deposits (Fig. 3.12; Table 3.4). Channel-axis and lobe off-axis deposits show the greatest range in textural properties (Fig. 3.12; Table 3.4), especially in grain-size and matrix content (Fig. 3.12; Table 3.4).

The rate of change of textural properties is typically around two orders of magnitude more abrupt in the channel-fill element (channel axis to channel margin) in comparison to the lobe (Fig. 3.10).

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits

Figure 3.12: Variation of textural properties within channel and lobe sub-environments. Samples are grouped by sub-environment interpretations. Channel margin and lobe fringe samples show overlap and consistently have comparatively finer grain-sizes and higher matrix contents. Channel axis and lobe off-axis samples overlap and exhibit a mix of grain-sizes and matrix contents. The lobe axis samples typically plot in a discrete area due to coarser grain-sizes and lower matrix contents.

3.8 Discussion

Spatial variation in depositional reservoir quality

The distribution of textural properties (grain-size, sorting and matrix content) within architectural elements is a first-order control on the initial depositional porosity and permeability of sandstones (e.g. Fraser, 1935; Beard and Weyl, 1973; Hirst et al., 2002; Lien et al., 2006; Njoku and Pirmez, 2011; Kilhams et al., 2012; Marchand et al., 2015; Porten et al., 2016; Southern et al., 2017) and provides insight into the depositional reservoir quality within the study area. The effects of post-depositional modification are not discussed unless explicitly stated.

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits Gerbe channel-fill element

Textural properties vary both laterally and vertically within the Gerbe channel-fill element (Figs. 3.8, 3.9, 3.10, 3.11, 3.12). Grain-size increases and matrix content decreases from channel-margins to channel-axis (Figs. 3.8, 3.10, 3.11, 3.12). In unconsolidated sand, as grain-size increases pore throats become larger and permeability increases (e.g. Beard and Weyl, 1973). However, changes in grain-size do not affect porosity within deposits with the same degree of sorting (Beard and Weyl, 1973). This suggests that initial permeability would have been higher in channel-axis deposits. Grain-size also decreases stratigraphically within the Gerbe channel-fill element (Fig. 3.11A, B), suggesting initial permeability decreased upwards. Sorting is better in the channel-margins, and also increases vertically within the channel-fill (Figs. 3.8, 3.11, 3.12). Well-sorted deposits exhibit higher porosity and permeability in unconsolidated sand as smaller grains fill intergranular space and block pore throats in poorly-sorted deposits (Beard and Weyl, 1973). However, the overall effect of sorting on reservoir quality is currently inconclusive, as grain-size and clay content often mask its effect (Lien et al., 2006; Porten et al., 2016; c.f. Njoku and Pirmez, 2011). This is likely an artefact of traditional point counting methods, which calculate sorting data from optically resolvable grains (i.e. not clays). Therefore, channel margin and lobe fringe deposits in which hydraulic fractionation resulted in well-sorted detrital grains, but with a high-matrix content, appear well-sorted. In contrast, the deposits of relatively poorly-stratified, high-density flows are likely to have poorer-sorting of detrital grains, but low-matrix contents. High matrix content in channel margin positions (Figs. 3.8, 3.10, 3.11, 3.12) likely reduced both initial porosity and permeability as detrital clay can impact reservoir quality by blocking pore throats and reducing permeability (Fraser, 1935; Hirst et al., 2002; Lien et al., 2006; Porten et al., 2016). Authigenic mineral content is highest in the channel axis (Fig. 3.8B), suggesting a higher initial porosity, and that fluid flow was greater in these deposits prior to mesodiagenesis, suggesting higher initial permeabilities.

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits

Figure 3.13: Flow process controls on channel-fill reservoir potential. The lower channel-axis is filled by debrites (E), which are poorly-sorted, mudstone-rich and low reservoir potential. Conglomerate (D), representative of a high-concentration, strongly bypassing flow. Reservoir potential in initial channel-axis deposits is high due to amalgamation of high-density turbidites (C and D). Decreases in amalgamation and 91

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits grain-size, and increases in matrix content vertically and laterally reduce depositional reservoir quality. The upper channel-fill element fill axis (A) and channel-margins (B) are dominated by non-amalgamated low- density turbidites and have poorer grain-scale reservoir potential.

Both sandstone-percentage and the proportion of amalgamated beds decrease from channel-margin to channel-axis (Fig. 3.8B, 3.10). Therefore, channel-axis deposits exhibit better depositional reservoir quality at both grain-scale (porosity and permeability) and architectural element scale (sandstone-percentage and amalgamation) compared to channel- margin deposits (Fig. 3.10).

Whilst the depositional reservoir quality of channel-axis sandstones is better compared to the channel margin, the channel-axis in this case contains a thick mudstone- rich debrite. This debrite would have poor reservoir properties (e.g. Hirst et al., 2002), and reduce the overall vertical permeability and depositional reservoir quality of the channel axis. However, incision of channel-fill element one by channel-fill elements two and three improves vertical connectivity of channel-axis sandstones in the channel-complex axis (Fig. 3.4).

Process controls on depositional reservoir quality distribution

Cycles of channel initiation, incision, and filling record a complicated waxing- waning history of flow energy, and associated sediment bypass and aggradation (e.g. Mutti and Normark, 1987; Mutti, 1992; Clark and Pickering, 1996; McHargue et al., 2011; Hubbard et al., 2014; Stevenson et al., 2015). The basal channel surface is interpreted to be excavated by a debris flow, or flows (e.g. Dakin et al., 2013), which deposited the debrite. The debrite is erosively overlain by siltstone and discontinuous thin sandstone beds, interpreted to represent a bypass-dominated channel-base-drape (e.g. Hubbard et al., 2014; Stevenson et al., 2015). Silt-prone drapes act as barriers to flow, but notable detrimental effects are only observed with cross-sectional drape coverages in excess of 60% (e.g. Barton et al., 2010). Subsequent channel-axis aggradation is dominated by amalgamated high-density turbidites (Figs. 3.4, 3.13), resulting in high sandstone-percentage and connectivity. The fill progressively thins and fines upward into thin-bedded low-density turbidites (Figs. 3.4, 3.13). Channel-margin deposits are characterized almost exclusively by low-density turbidites (Figs. 3.4, 3.13). Topography steers high-density turbidity currents more-strongly than low-density turbidity currents (e.g. Al Ja’aidi et al., 2004), and so focussing of high-density turbidity currents within the thalweg concentrates the best reservoir properties in the channel-axis (Figs. 3.10, 3.13). Low-density flows, or low-density parts of stratified flows, are able to surmount topography, depositing low-density turbidites 92

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits contemporaneously on the channel-margin (Fig. 3.13A, B; e.g. Hiscott et al., 1997). In later stages of channel aggradation, the channel-cut is partly-to-fully filled due to system back- stepping through relative sea-level rise, or other mechanisms, reducing flow-volume and sediment supply to the channel-fill (e.g. Mutti and Normark, 1987; Clark and Pickering, 1996; Campion et al., 2000; Gardner and Borer, 2000; McHargue et al., 2011; Di Celma et al., 2014; Hubbard et al., 2014; Hodgson et al., 2016). Reduction of sediment supply and smaller flow-volume means later flows reaching a given location are finer-grained, more- dilute and have poorer reservoir potential compared to earlier aggradational deposits.

Lobe 1

Within Lobe 1, the decrease in grain-size from lobe axis to lobe fringe positions (Figs. 3.8C, 3.9, 3.10, 3.12) suggests that initial permeability decreased away from the lobe axis. The proportion of matrix increases from lobe axis to lobe fringe (Figs. 3.8C, 3.12; see also: Hirst et al., 2002; Marchand et al., 2015; Kane et al., 2017; Fildani et al., 2018), which suggests the lobe-axis exhibited the highest initial porosity and permeability. Trends in sorting are weak in Lobe 1. Lobe off-axis deposits are generally better sorted than both lobe axis and lobe fringes, and therefore the original porosity may have been higher (Fig. 3.12C, D). However, as grain-size and matrix content are considered stronger controls on reservoir quality (Hirst et al., 2002; Lien et al., 2006; Porten et al., 2016), they are likely to overprint this parameter. At architectural-element scale, the sandstone-percentage and degree of amalgamation decrease away the from lobe axis to the lobe fringe (90 to 54% and 78.38 to 3.64% respectively; Figures 3.8D and F). This suggests lobe-axes had higher reservoir volume and connectivity. Authigenic mineral content is less variable than in the channel-fill element, but is slightly higher in lobe off-axis and lobe axis positions (Fig. 3.8D, F), suggesting increased fluid flow during diagenesis. Lobe axis deposits exhibit the best depositional reservoir quality at both grain- and architectural-scales (Fig. 3.10). Reservoir potential decreases slightly from lobe axis to lobe off-axis, at grain- and architectural-scale (Fig. 3.10). The relatively abrupt increase in matrix content, decrease in grain-size, decrease in sandstone-percentage, and decrease in amalgamation from lobe off-axis to lobe fringe (over a scale of 3.25 km) suggests that depositional reservoir quality and vertical connectivity within lobes decreases considerably from the lobe off-axis to the lobe fringe (Fig. 3.10). Where lobe fringe successions are reservoir prospects, they are likely to be challenging due to their (relatively) finer grain-size, increased matrix content, reduced thickness and poorer connectivity compared to more proximal positions (Kane and Pontén, 2012; Marchand et al., 2015; Southern et al., 2017; Fildani et al., 2018).

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits

Figure 3.14: Illustration of flow-process controls on reservoir potential within lobes. Lobe axis deposits (A) have high reservoir potential as they are dominated by amalgamated high-density turbidites with coarse grain-sizes and low matrix content. Lobe off-axis deposits (B and C) have moderate-to-high reservoir potential as they contain a mixture of high- and low-density turbidites. Low-density turbidites have finer grain-sizes and higher amounts of matrix compared to high-density turbidites, thus reducing their reservoir potential. Lobe-fringe deposits (D) contain abundant non-amalgamated low-density turbidites. Lobe-fringe low-density turbidites have fine grain-sizes and higher matrix content, reducing reservoir potential compared to lobe axis and lobe off-axis deposits.

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits Process controls on depositional reservoir quality distribution

Lobes exhibit lateral facies changes that reflect different sub-environments. Lobe axis deposits are dominated by high-density turbidites, lobe off-axis deposits contain a mixture of high- and low-density turbidites and lobe fringe deposits are dominated by low- density turbidites (Figs. 3.5, 3.14; e.g. Prélat et al., 2009). Lateral variation of textural properties and composition has been observed in experimental studies (e.g. Middleton, 1967; Garcia, 1994; Gladstone et al., 1998; Hodson and Alexander, 2010; Pyles et al., 2013) and in ancient deposits (Fig. 3.14; e.g. Hirst et al., 2002; Kane et al., 2017; Lien et al., 2006; Marchand et al., 2015; Porten et al., 2016; Southern et al., 2017; Fildani et al., 2018). Coarse grains are deposited by high-density turbidity currents in proximal positions whereas fines that reach the basin-floor are transported to distal positions in low-density turbidity currents (Fig. 3.14; e.g. Middleton, 1967). Enrichment of fine-grained material in the lobe fringes may be due to entrainment of substrate in the channel-lobe transition zone, and proximal lobe positions (Kane and Pontén, 2012; Fildani et al., 2018). As grain-size and matrix are strong controls on depositional reservoir quality, their segregation within flow deposits influences reservoir potential distribution within lobes (Figs. 3.10, 3.14).

Implications of detrital matrix distribution

Detrital matrix and ductile grains have a negative effect on the depositional reservoir quality by blocking pore throats (e.g. Fraser, 1935), and during compaction by forming a pseudomatrix (e.g. Marchand et al., 2015). However, clay coatings (predominantly chlorite) on grains can also act to preserve porosity and permeability by inhibiting the growth of authigenic quartz (e.g. Heald and Larese, 1974; Ehrenberg, 1993; Bloch et al., 2002; Anjos et al., 2003; Dowey et al., 2012). Authigenic quartz growth is accelerated in basins with higher heat flows (e.g. Walderhaug, 1994), such as the northern Norwegian Sea (e.g. Ritter et al., 2004). In these cases, deposits with higher matrix contents, whilst exhibiting lower initial porosity and permeability, may act to preserve the porosity and permeability present during deeper burial. Consequently, porosity and permeability in architectural element positions with lower matrix contents (e.g. lobe axis) are more likely to be reduced by authigenic quartz growth. A balance of the initial porosity and permeability, and that preserved from authigenic quartz, may favour medial values of grain-size and matrix content in these cases, such as lobe off-axis deposits. However, as temperature and compaction increase with burial the diagenetic overprint control on reservoir quality is likely to become stronger relative to the depositional control (see also: Porten et al., 2016). 95

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits 3.9 Conclusions Two deep-water architectural elements, a channel-fill element and a lobe, are characterized at grain-scale using quantitative methodology to map depositional reservoir quality spatially within individual architectural elements for the first time. Quantification of these data and their rates of change can be important parameters for sub-surface predictability and fluid flow simulation models. Textural and architectural properties show strong spatial variation in both elements. The distribution of initial depositional reservoir quality within, and between sub-environments is controlled by flow processes and their spatial and temporal evolution.

Within the channel-fill element, channel-axis deposits have the best depositional reservoir quality as they have the coarsest grain-size and lowest matrix content. However, depositional reservoir quality decreases upwards within the channel-axis, as the proportion of high-density turbidites decreases, and low-density turbidites increases as the channel-fill aggrades. Channel-margin deposits consist of low-density turbidites which have low reservoir potential due to their finer grain-sizes and high matrix content. Channel-axis deposits are also more amalgamated, and contain a greater thickness of sandstone, therefore they have better connectivity and volume compared to channel-margin deposits. Lobe axis deposits are dominated by high-density turbidites, which have better depositional reservoir quality compared to the lobe off-axis and lobe fringe as they have the coarsest grain-size, lowest matrix content, most amalgamation and highest net-to-gross. Lobe off- axis deposits contain a mixture of high- and low-density turbidites, giving moderate depositional reservoir quality. Lobe fringe deposits are characterized by low-density turbidites, which have the poorest depositional reservoir quality as they have the finest grain-size, highest matrix content, lowest degree of amalgamation and lowest net-to-gross. The rate of change in grain-size, matrix content and amalgamation increases from lobe off- axis to lobe fringe. This suggests reservoir potential decreases more abruptly from the lobe off-axis into the lobe fringe compared to from the lobe axis to lobe off-axis. However, in basin-fills with high heat-flow, sub-environments with increased detrital matrix and clay- coating of grains which inhibit authigenic quartz growth (e.g. lobe off-axis), may preserve initial porosity and permeability post-diagenesis. The studied deep-water architectural elements exhibit similar meso-scale facies, stacking patterns and lithofacies distributions to deep-water systems of different basins, ages and delivery systems. Quantified depositional reservoir quality distribution intimately ties to this predictable facies organisation and should therefore be predictable elsewhere.

Chapter 3:Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe deposits

Chapter 4:The effect of bed-scale heterogeneities on vertical permeability in clastic sandstones CHAPTER 4: The effect of bed-scale heterogeneities on vertical permeability in clastic sandstones Daniel Bell1, Anna S. M. Pontén2, Ian A. Kane1, Arnau Obradors Latre2, and Krishnakumar Nair2

1SedResQ, School of Earth and Environmental Sciences, University of Manchester, Manchester, M13 9PL, U.K.

2Equinor Research Center, 7053 Ranheim, Trondheim, Norway

4.1 Abstract Accurate prediction of permeability in sedimentary rocks is critical when accessing reservoir rocks for hydrocarbon or ground water extraction, thermal heat exchange, and the storage of carbon dioxide. Modelling can be used to characterise fluid flow from the pore-scale to the field-scale. However, few studies attempt to constrain or isolate the effects of bed-scale heterogeneity and barriers on permeability. Petrophysical numerical modelling was employed to constrain the effect of bed-scale heterogeneity on vertical connectivity. Two tests were performed on relatively thin (20 cm), and relatively thick (100 cm) sandstone bed models to test: 1) the effect of siltstone thickness; 2) the effect of mudstone-clast density. Results demonstrate that: 1) vertical permeability (Kv) reduces exponentially with increasing siltstone thickness; 2) thin siltstones (<4% model thickness) accommodate ~80% of Kv decay; 3) mudstone-clasts can considerably reduce Kv in a near linear manner in thinner-bedded sandstones. However, the relationship is inverse logarithmic in thicker-bedded sandstones, where Kv decays more slowly at clast densities <30% than above that threshold (0.36% Kv and 1.46% Kv, respectively, per 1% increase in mudstone-clast density; 4) Low mudstone-clast densities can adversely affect Kv. A 1% clast density in thin-bedded sandstones reduced Kv by 11 – 12%. The findings demonstrate that different barriers have contrasting effects on permeability, and should be accounted for individually. Accurate modelling of these heterogeneities at bed-scale can provide more-useful input into larger-scale models and simulator cells.

4.2 Introduction The stratigraphic record contains heterogeneity at multiple scales, ranging from pore/grain scale, bed, and architectural element (Beard and Weyl, 1973; Nagtegal, 1979; Fielding, 1986; Miall, 1988; Revil and Cathles III, 1999; Bridge and Tye, 2000; Hampson, 2000; Gibling, 2006; Haughton et al., 2009; Prélat et al., 2009; Mountney, 2012; Porten et al., 2016; Southern et al., 2017; Bell et al., 2018a; Haile et al., 2018), to system- and basin- scales (Alonso et al., 1990; Grant et al., 1996; Alves et al., 2002; McKie and Williams, 2009; 98

Chapter 4:The effect of bed-scale heterogeneities on vertical permeability in clastic sandstones Sømme et al., 2009; Dixon et al., 2010; Macauley and Hubbard, 2013; Oluboyo et al., 2014; Poyatos-Moré et al., 2016). The spatial organisation of these heterogeneities has been modelled to demonstrate their effects on fluid flow (Haldorsen and Chang, 1986; Bachu and Cuthiell, 1990; Jackson and Muggeridge, 2000; Ringrose and Bentley, 2015; Hofstra et al., 2017), and can affect the migration and trapping of hydrocarbons (Kerr and Jirik, 1990; Ringrose et al., 2005; Gainski et al., 2010; Amy et al., 2013; Nordahl et al., 2014; Ringrose and Bentley, 2015; Hofstra et al., 2017; Martinius et al., 2017), effective storage of CO2 in Carbon Capture and Storage projects (Verlaan et al., 1998; Gunter et al., 2004; Janssen and Bossie-Codreanu, 2005), and recharge and depletion rates of groundwater (Boggs et al., 1992; Ronayne et al., 2010; Srzic et al., 2013). At large-scales (e.g. reservoir model), the overall net:gross, stacking pattern of architectural elements, and structural elements exert the strongest controls on permeability (Funk et al., 2012; Kilhams et al., 2015; Hofstra et al., 2017). At the architectural element-scale (e.g. reservoir-model cell), the spatial distribution of facies and continuity of siltstone layers are primary restraints on permeability (Begg and King, 1985; Hamlin et al., 1996; Stephen et al., 2001; Kilhams et al., 2012; Alpak et al., 2013; Martinius et al., 2017). At pore-scale (e.g. core plug), in clastic deposits, the concentration and distribution of detrital and authigenic clays, grain-size, and packing of grains are a strong control on the permeability of deposit (Fraser, 1935; Beard and Weyl, 1973; Revil and Cathles III, 1999; Morad et al., 2010; Porten et al., 2016). The bed-scale bridges the gap between the architectural element- and grain-scales and incorporates heterogeneities from the two. For example, the distribution of pore-scale permeability in different lithofacies within a bed (e.g. Ringrose et al. 2005; Nordahl et al. 2006; Southern et al. 2017), and the degree of amalgamation or dispersed clasts between beds (e.g. Bachu and Cuthiell, 1990).

Bed-scale modelling typically focusses on upscaling lithofacies permeability to architectural element scales, and comparatively little work addresses the fundamental controls of simple barriers on vertical permeability (Kv) at the intra- and inter-bed-scale (Bachu and Cuthiell, 1990). Similarly, in many studies mudstone-clasts are not considered as a barrier, and are often grouped into structureless sandstone facies within beds, or interpreted simply as amalgamation surfaces when aligned along a surface. This study addresses the following research questions: 1) how can the effects of bed-scale barriers on fluid flow be modelled? 2) How does siltstone-drape thickness affect Kv? 3) How does mudstone-clast density affect Kv? And 4) do different types of barrier have contrasting effects on Kv?

Chapter 4:The effect of bed-scale heterogeneities on vertical permeability in clastic sandstones 4.3 Methods Beds were modelled using commercially available SBEDTM software. Each test comprised two sandstone beds separated by a barrier made of either siltstone or dispersed mudstone-clasts. Models had x- and y-dimensions of 30 cm; the z-dimension was the sum of sandstone thickness, and the siltstone or mudstone-clast layer thickness. Porosity and permeability of the sandstone and siltstone were stochastically modelled using rock property data from submarine lobe deposits of the X Field, North Sea (Table 4.1). Two tests were done for the siltstone-drape and mudstone-clast case studies, one with 20 cm (40 cm total sand) sandstone beds, and one with 100 cm sandstone beds (200 m total sand). Siltstone thickness was sequentially increased from 0.1 cm in the siltstone-drape test to a maximum of 5 cm and 20 cm, in the 20 cm and 100 cm sandstone bed thicknesses, respectively. In mudstone-clast tests a 5 cm thick layer was placed in between the two “clean” sandstones, and the mudstone clast density was sequentially increased from 0% to 100% with their distribution modelled stochastically (Fig. 4.1). As no specific mudstone- clast object exists in SBED, mudstone-clasts were modelled by editing shapes of bioturbation to be mm – cm in diameter ellipsoid “clasts” aligned with bedding (Fig. 4.1). Mudstone-clast density refers to density along layers, rather than in three dimensions, so gaps between clasts are often present vertically even in high mudstone-clast density models. Models were realised three times with separate stochastic models to constrain the effects of different mudstone-clast distributions, except the 100 cm sandstone bed siltstone thickness test where the effect of siltstone was well-constrained from the 20 cm sandstone bed thickness test.

100

Chapter 4:The effect of bed-scale heterogeneities on vertical permeability in clastic sandstones Table 4:1: Input parameters used in model realisations.

Input parameter Siltstone Sandstone

Minimum permeability (mD) 0.50 56.28

Maximum permability (mD) 32.39 1876.48

Mean permeability (mD) 14.05 737.99

Standard deviation 11.95 556.07

Minimum porosity 0.15 0.2

Maximum porosity 0.26 0.29

Mean porosity 0.18 0.24

Standard deviation 0.029 0.03

4.4 Results

Siltstone-drape test

Models were realised to test the effect of different siltstone thicknesses on sandstone connectivity. Two types of model were run: one with two 20 cm sandstone beds to simulate bed connectivity; and one with two 100 cm sandstones to simulate near architectural element scale connectivity.

20 cm sandstone beds

Beds without a siltstone division had the highest modelled Kv, at 475 mD (Fig. 4.2). As siltstone thickness is increased there is a concomitant exponential decrease in Kv, to a minimum of 37 mD in the 5 cm siltstone model (Fig. 4.2). The decrease in Kv is abrupt and near-linear between 0.1 and 1 cm siltstone thickness (Fig. 4.2). There is an inflection point at 1.25 cm siltstone, after which the decrease in Kv is again near-linear, with less-abrupt decreases in Kv with increasing siltstone thickness (Fig. 4.2). Thin siltstones also have a substantial effect on Kv: a siltstone thickness of 0.1 cm reduced Kv by 10% (Fig. 4.2); and 0.5 cm of siltstone reduced Kv by 50% (Fig. 4.2). There is little variability between models with the same input parameters, with all three models at a given siltstone thickness reducing Kv by the same amount ±1% (Fig. 4.2).

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Chapter 4:The effect of bed-scale heterogeneities on vertical permeability in clastic sandstones

Figure 4.1: Examples of SBEDTM models realised in the experiment. Columns from left to right show: 1) the 3D realisation of selected experiments with increasing clast density between sandstone beds; 2) the same clast realisation without sandstone; 3) The effect of increasing clast density on Kh; 4) Approximate analogue of clast density from core photographs. Note how the 3D density of clasts may be understimated when looking at 2D faces in core. Core photographs were selected from the Magnus, Scapa, and Brae fields. Core photographs contain British Geological Survey materials ©NERC 2019.

100 cm sandstone beds

The maximum modelled Kv with 100 cm sandstone beds above and below the siltstone layer was 461 mD in the model with no siltstone (Fig. 4.2). There is an exponential decrease in Kv to a minimum of 21 mD, as siltstone thickness is increased (Fig. 4.2). There is a near-linear trend of abruptly reduced Kv at low siltstone thicknesses between 0.1 and 5 102

Chapter 4:The effect of bed-scale heterogeneities on vertical permeability in clastic sandstones cm (Fig. 4.2). There is an inflection point at approximately 7.5 cm after which Kv reduced more gradually with increasing siltstone thickness in a near-linear trend (Fig. 4.2). Thicker siltstones (>5cm) reduce Kv more than thin siltstones (≤5 cm); however, Kv reduction is more abrupt at thinner siltstone thicknesses. Thin siltstones accommodate much of the reduction in Kv: a 0.1 cm siltstone reduced Kv by 2% (Fig. 4.2); a 0.5 cm siltstone reduced Kv by 16%; and a 2.5 cm siltstone reduced Kv by 49% (Fig. 4.2).

Figure 4.2: Graphs illustrating the effects of siltstone thickness and mudstone-clast density on Kv. A) The effect of increasing siltstone thickness has on Kv between two 20 cm thick sandstone beds. B) The percentage reduction of Kv with increasing siltstone thickness between two 20 cm sandstone beds compared to the highest modelled Kv (0 cm siltstone thickness). C) The effect of increasing siltstone thickness has on Kv between two 100 cm thick sandstone beds. D) The percentage reduction of Kv with increasing siltstone thickness in between two 100 cm sandstone beds compared to the highest modelled Kv (0 cm siltstone thickness).

Effect of a siltstone layer as a proportion of sandstone thickness

Increasing the thickness of a siltstone layer exponentially reduces Kv in both the 20 cm and 100 cm sandstone bed tests. However, siltstones of the same thickness have less of an effect on Kv in the 100 cm compared to the 20 cm sandstone tests. Plotting the respective thicknesses as a proportion of net sandstone thickness reveals that siltstone 103

Chapter 4:The effect of bed-scale heterogeneities on vertical permeability in clastic sandstones thickness exerts a control on Kv proportional to the thickness of the surrounding sandstone (Fig. 4.3). Low siltstone proportions reduce Kv substantially less than high proportions of siltstone (Fig. 4.3). However, there is an inflection point at approximately 4% siltstone thickness, where the rate of change at low proportions of siltstone, i.e. below 4%, is more abrupt (21% reduction in Kv per 1% increase in siltstone fraction) than at proportions above 4% (Fig. 4.3; 0.64% of Kv decrease per 1% increase in siltstone fraction).

Figure 4.3: A) The effect of siltstone as a proportion of sandstone thickness on Kv. B) The percentage reduction in Kv with increasing siltstone thickness as a proportion of model thickness compared to the highest modelled Kv (0% silt), here represented by the graph origin.

Mudstone-clast test

Models were realised to determine the effect of mudstone-clast density on connectivity between two sandstone beds. A 5 cm mudstone-clast-rich layer was used to separate sandstone beds (Fig. 4.1), which is comparable to the 5 cm siltstone thickness test. Two tests were performed, one with 20 cm sandstone beds, and one with 100 cm sandstone beds.

20 cm sandstone beds

The introduction of mudstone-clasts to the layer between two 20 cm sandstone beds (see Fig. 4.1) reduced Kv from a maximum of 475 mD, with no clasts, to a minimum of 48 mD, with 100% clast density, in a near-linear trend (Fig. 4.4). Very-low (≤1%) and very-high (>80%) clast densities diverge from this trend, with low clast densities having a more abrupt decrease in Kv compared to no clasts, and higher clast densities showing less abrupt changes between different densities (Fig. 4.4). Kv is reduced by: 11 – 12% at a clast density of 1%; 28 – 32% at clast densities of 20%; 45 – 55% at clast densities of 40%; 68 –

104

Chapter 4:The effect of bed-scale heterogeneities on vertical permeability in clastic sandstones 72% at clast densities of 60%; 82 – 84% at clast densities of 80%; and 86 – 89% at a clast density of 100% (Fig. 4.4). There is variability in the reduction of Kv in models with identical input parameters (Fig. 4.4). The highest variability between models is at mid- ranges of clast densities (e.g. a 40% clast density reduced Kv by 45 – 55%); whereas very- high, and very-low clast densities had less variability (Fig. 4.4; ranges of 1.4% and 2.2% in reduction of Kv at 1% and 90% mudstone-clast density, respectively).

100 cm sandstone beds

The maximum Kv between two 100 cm sandstone beds was 456 mD in the model with no clasts, and a minimum of 161 mD at 100% mudstone-clast density (Fig. 4.4). Low clast densities do not strongly reduce Kv (0.36% Kv per 1% increase in mudstone-clast density); for example clast densities of 20% and 30% reduced Kv by 6 – 7% and 9 – 12%, respectively (Fig. 4.4). Above clast densities of 30% Kv decreases more abruptly in a near- linear trend (1.46% Kv per 1% increase in mudstone-clast density): a clast density of 50% reduced Kv by 14 – 21%; a clast density of 60% reduced Kv by 31 – 37% (Fig. 4.4); a clast density of 80% reduced Kv by 47 – 54% (Fig. 4.4); and a clast density of 100% reduced Kv by 62 – 64% (Fig. 4.4). There is considerable variability in the reduction of Kv in the realisations of models. The greatest variability is seen in models with mudstone-clast densities between 30% and 90%, up to 8%; whereas low and high clast density models typically have lower ranges of values of less than 3% (Fig. 4.4).

4.5 Discussion

Effect of siltstone barriers on bed-scale connectivity

The lateral continuity of siltstone barriers, and the volume fraction of a reservoir they constitute, are recognised to affect the effective permeability of a reservoir (Begg and King, 1985; Desbarats, 1987; Deutsch, 1989; Stephen et al., 2001; Nordahl et al., 2006; Alpak et al., 2013; Amy et al., 2013; Hao et al., 2019). Here, we demonstrate that Kv is also affected by the thickness of such siltstones at a bed-scale (Fig. 4.2) and should be accounted for in reservoir assessments. Vertical permeability between two sandstone beds decreases exponentially with increasing siltstone thickness, and the presence of small thicknesses of siltstone can have a substantial negative effect on vertical connectivity at bed-scale and architectural element-scale (Fig. 4.2). Vertical permeability abruptly decreases with increasing siltstone thickness, up to an inflection point at approximately 4% of model thickness (see also: Hao et al. 2019); this is interpreted to represent the point at which siltstone permeability becomes the primary control on Kv (Fig. 4.2). This also suggests that 105

Chapter 4:The effect of bed-scale heterogeneities on vertical permeability in clastic sandstones thinner-bedded sandstone successions are more likely to be negatively affected by siltstones of a given thickness than thick-bedded successions. The decrease in Kv with increasing siltstone fraction here corresponds closely to the Harmonic mean of the model (Fig. 4.2), whereas the decrease in Kv in modelling of larger-scale discontinuous siltstones falls between the Harmonic and Arithmetic means (Desbarats, 1987; Deutsch, 1989). This is interpreted to represent the fluid pathways of discontinuous shales being complex, but highly permeable (e.g. Fig. 4.5); whereas the siltstones modelled here are simple and continuous which effectively inhibit the vertical migration of fluids.

Effect of mudstone-clasts on bed-scale connectivity

Mudstone-clasts are a small-scale heterogeneity common to many depositional systems (e.g. Johansson and Stow, 1995). Little work addresses their impact on fluid flow (Bachu and Cuthiell, 1990; Cuthiell et al., 1991; Kashikara et al., 2010); though it is recognised that mudstone-clast-prone zones can inhibit recovery from steam-assisted gravity drainage processes (Kashikara et al., 2010; Nardin et al., 2013). Here, increasing densities of mudstone-clasts inversely affects Kv (Fig. 4.2; see also: Bachu and Cuthiell, 1990). Kv in the 20 cm bed models is more strongly affected by mudstone-clasts of a given density distribution than the 100 cm bed models, suggesting thin-bedded sandstone successions are more-strongly affected by mudstone-clast horizons than thick-bedded sandstones (Fig. 4.4). In both tests there was considerable variability in Kv of models with identical input parameters. This establishes that the 3D distribution and organisation of mudstone-clasts of a given density can exert a control on the Kv of a sandstone body. Therefore, in sandstone-prone parts of sedimentary systems where mudstone-clasts are one of the main forms of heterogeneity (Bachu and Cuthiell, 1990; Haughton et al., 2003; Kane et al., 2009; Kashikara et al., 2010; Strobl, 2013; Hubbard et al., 2014), the distribution and density of clasts is likely to be a primary control on fluid flow (Fig. 4.6). The results modelled here are based on a 5 cm layer of mudstone-clasts, in nature mudstone-clast-rich beds can be decimetres-to-metres thick and are likely to have more-negative effects on Kv than the examples modelled here (Kashikara et al., 2010).

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Chapter 4:The effect of bed-scale heterogeneities on vertical permeability in clastic sandstones

Figure 4.4: The effect of increasing mudstone-clast density on Kv. A) The effect of a layer with increasing mudstone-clast density on a 40 cm sandstone bed. B) The percentage reduction of Kv with increasing mudstone-clast density (within a 5 cm layer) in a 40 cm sandstone bed compared to the highest modelled Kv (0% clast density). C) The effect of a layer with increasing mudstone-clast density on a 200 cm sandstone bed. D) The percentage reduction of Kv with increasing mudstone-clast density (within a 5 cm layer) in a 200 cm sandstone bed compared to the highest modelled Kv (0% clast density).

The contrasting gradients either-side of the inflection point at c.30% clast density is interpreted to represent the threshold at which the mudstone-clasts become a major barrier to fluid flow (Fig. 4.6). This demonstrates that the relationship between mudstone-clasts and fluid flow is non-linear, and suggests the relationship is linked to percolation theory (Desbarats, 1987; King, 1990; Ringrose et al., 2005). A similar trend is observed in modelling of multiple laterally discontinuous siltstones at 100’s m scale, where a critical threshold of 45% and 65% of the total model volume were recognised in 2D and 3D models, respectively, after which permeability was reduced substantially (Desbarats, 1987). This suggests, that a smaller scale, mudstone-clasts affect fluid flow in a similar way to discontinuous siltstone lenses.

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Chapter 4:The effect of bed-scale heterogeneities on vertical permeability in clastic sandstones

Figure 4.5: Schematic 2D illustration of how amalgamation affects pathways between two sandstones. Siltstone layers form relatively simple, but effective barriers to flow. Laterally, siltstone layers are commonly eroded to form an amalgamation of sandstone beds which allows fluids to migrate more effectively around low-permeability siltstones (e.g. Stephen et al., 2001). However, amalgamation surfaces and the deposits above them often contain aligned, or disperesed mudstone-clasts. These mudstone-clasts form permeable, but complicated, pathways for fluids to slowly migrate through, reducing the overall absolute permeability (e.g. Cuthiell et al., 1991).

Implications for modelling

Differences in trends

Increasing thickness of siltstone and density of mudstone-clasts, show contrasting relationships with Kv. Siltstone thickness affects Kv in an exponential relationship, whereas mudstone-clast density affects Kv in a logarithmic relationship (Figs. 4.2, 4.4). Siltstone layers affect Kv more negatively than mudstone-clasts. For example: a 1 cm siltstone in 2 m of sandstone has the approximately equivalent effect on Kv as a 5 cm layer with 60% density of clasts. Therefore mudstone-clasts should not be modelled using the same approach as siltstone layers, unless the relationship is calibrated with specific input parameters.

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Chapter 4:The effect of bed-scale heterogeneities on vertical permeability in clastic sandstones

Figure 4.6: Schematic illustration of two amalgamated sandstones with mudstone-clasts at the amalgamation surface in cross-section and plan view. Increased clast density reduces the percentage of high- permeability sandstone coverage, creating tortuous pathways for fluid flow, reducing the overall Kv.

Bed-scale modelling can be used to make better informed larger scale simulator cells (Ringrose et al., 2005; Ruvo et al., 2008; Nordahl et al., 2014; Martinius et al., 2017; Hao et al., 2019). Here we demonstrate that modelling of small-scale barriers and types of barriers can have major, and contrasting, effects on Kv. Siltstone layers create relatively impermeable barriers to flow (e.g. Haldorsen and Lake, 1984). However, in many systems these are discontinuous due to facies transitions, erosion and/or amalgamation (e.g. Fig. 4.5). This can allow connectivity in 3D between sandstone bodies increasing the absolute permeability of the system (Desbarats, 1987; Deutsch, 1989; Stephen et al., 2001; Amy et al., 2013). Commonly mudstone-clasts are aligned along amalgamation or erosion surfaces (e.g. Fig. 4.5), and/or are dispersed in the beds overlying them. The findings presented here suggest that these surfaces and layers can reduce the absolute permeability of connective zones by 1’s – 10’s of percent through the creation of convoluted, tortuous pathways for fluid flow (Figs. 4.5, 4.6), and should therefore be accounted for in modelling (see also: Kashikara et al., 2010).

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Chapter 4:The effect of bed-scale heterogeneities on vertical permeability in clastic sandstones 4.6 Conclusions Bed-scale modelling shows that siltstone and mudstone-clast barriers exert a strong control on vertical permeability between sandstone beds. Small-scale barriers have appreciable effects on Kv that can be carried into architectural element scales. Siltstone layers strongly impact the modelled Kv, in a relationship that is exponentially proportional to the thickness of sandstone. Thin siltstones (<4% of thickness) reduce Kv less than thicker siltstones, whereas Kv is affected more-abruptly by changes in siltstone thicknesses below 4% of model thickness. Increasing densities of mudstone-clasts inversely affect Kv. However, in relatively thinner-bedded packages (40 cm sandstone) mudstone clasts exert a near-linear inverse decrease in Kv with increasing density, and a 1% density of mudstone- clasts can reduce Kv by 11 – 12%. Conversely, thicker-bedded packages (200 cm sandstone) exhibit an inverse logarithmic trend with increasing clast-density, with low clast- densities reducing Kv less substantially (1% clast density reduces Kv by 1 – 2%). Models with identical input barriers for mudstone-clast realisations exhibit variability of up to 10% in Kv. This demonstrates the spatial organisation of mudstone-clasts in three dimensions can have an appreciable effect of Kv.

The contrasting trends in Kv reduction with increasing siltstone thickness and mudstone-clast density are interpreted to be inherited due to contrasting complexity of the barriers. At bed-scale, siltstones are often relatively simple continuous barriers which fluids must migrate through to reach the overlying sandstone. Conversely, mudstone-clasts form discontinuous layers which create tortuous, though high-permeability, pathways that fluids must navigate. At lower clast-densities the barrier is less-tortuous, with high Kv values, whereas at higher clast-densities the barrier is highly-tortuous, inhibiting Kv.

Mudstone-clasts are often grouped into structureless sandstone facies, and little attention is paid to their distribution and density. Results here suggest zones of mudstone- clasts can considerably reduce Kv, negatively effecting any reservoir predictions. Similarly, the clasts forming these tortuous pathways are likely to more-negatively affect highly- viscous fluids, and have been demonstrated to inhibit recovery from steam-assisted gravity drainage. Therefore understanding the distribution of these layers in 3D is important to enhanced recovery and prediction of reserovir quality.

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Chapter 5:Bed-scale modelling of deep-water lobes: which heterogeneities matter to flow? CHAPTER 5: Bed-scale modelling of deep-water lobes: which heterogeneities matter to flow? Daniel Bell1, Anna S. M. Pontén2, Ian A. Kane1, Arnau Obradors-Latre2, Krishnakumar Nair2, Camilla Thrana2, David M. Hodgson3, and Stephen S. Flint4

1 SedRESQ, School of Earth and Environmental Sciences, University of Manchester, Manchester, M13 9PL, U.K.

2 Equinor ASA, Research Center Rotvoll, NO-7005 Trondheim, Norway

3 Stratigraphy Group, School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, U.K

4 Stratigraphy Group, School of Earth and Environmental Sciences, University of Manchester, Manchester, M13 9PL, U.K.

5.1 Abstract The organisation of architectural elements that govern the volume and connectivity at the grid-cell scale, and textural properties of deep-water systems that control porosity and permeability at the core-plug scale, is well-recognised. However, modelling studies which address the intermediate bed-scale heterogeneities, and their influence on fluid flow at larger scales, are limited. Lobe 6 of Fan 3, Tanqua Depocentre, South Africa, is spatially well-constrained allowing confident interpretation of lobe sub-environments. This permits study of the spatial variability of bed-scale heterogeneity within sub-environments of an individual architectural element. Fifty-nine logged sections were modelled using SBEDTM, individually realised three times, and populated with reservoir rock-property data from the subsurface X Formation, North Sea. SBEDTM was used to upscale horizontal permeability (Kh) derived from core-plug measurements to vertical permeability (Kv) at bed- and architectural element-scale to determine which heterogeneities influence fluid flow. Results reveal that: 1) lobe axis and distal lobe finger positions exhibit the best upscaled Kv, whereas the lateral fringe has the poorest upscaled Kv; 2) off-axis and distal fringe positions exhibit similar upscaled Kv, implying that low density turbidites and hybrid beds exert similar controls on Kv; 3) the variable 3D distribution of mudstone clasts can result in up to 5.5% variability in permeability at architectural element scale. The implications are: i) bed-and lamina-scale heterogeneities can exert a strong control at architectural element scale; ii) vertical permeability varies strongly spatially within lobes; iii) good reservoir quality sands can extend into the distal lobe fringe, enabling migration pathways kilometres away

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Chapter 5:Bed-scale modelling of deep-water lobes: which heterogeneities matter to flow? from the lobe axis. This challenges the characterisation of distal lobe fringes as dominated by poor reservoir quality sands due to hybrid bed development.

5.2 Introduction Deep-water lobes are the ultimate sediment sink for large volumes of sand-grade material transported to the basin-floor. Consequently these deposits can form high-quality reservoirs for hydrocarbons and CO2 storage (Shanmugam and Moiola, 1988; Pettingill, 1998; Gibson-Poole et al., 2004; Saller et al., 2008; McKie et al., 2015; Babaei et al., 2016). However, lobe deposits contain heterogeneity at a range of scales which can strongly impact their porosity and permeability. At the inter grain scale, the grain type, size, sorting, and matrix affect depositional reservoir quality and are a product of the type of flow which transported the sediment, and its composition (Hirst et al., 2002; Lien et al., 2006; Njoku and Pirmez, 2011; Marchand et al., 2015; Porten et al., 2016; Bell et al., 2018a). At the architectural element scale the distribution of bed-types, the geometry of the geobody, the distribution and character of major bounding surfaces, and the lateral continuity of mudstones control reservoir quality (Stephen et al., 2001; Hofstra et al., 2017). At the depositional system scale, the stacking patterns of architectural elements and the overall net:gross, are strong controls on the reservoir quality (Kilhams et al., 2012; Jo and Pyrcz, 2019). A common “missing-link” in modelling heterogeneities is the bed-scale, where the spatial organisation of grain-scale textures and lamina-types associated with discrete depositional processes, and distribution of barriers within and between beds, can exert strong controls on effective permeability (Cuthiell et al., 1991; Southern et al., 2017; Bell et al., 2018a).

There is an abundance of studies which consider heterogeneities in bed types, architectural elements and stacking patterns of lobes (Mutti, 1977; Haughton et al., 2003; Prélat et al., 2009; Kane and Pontén, 2012; Grundvåg et al., 2014; Marini et al., 2015; Spychala et al., 2017b; Pierce et al., 2018; Bell et al., 2018b), but few of these studies model or discuss how discrete heterogeneities affect fluid flow (e.g. Garland et al., 1999; Pyrcz et al., 2005; Ruvo et al., 2008; Pyrcz et al., 2015; Hofstra et al., 2017). Consequently there is lack of integration of where and how these different types of heterogeneity affect effective permeability in lobe deposit.

Lobe deposits exhibit spatial heterogeneity in facies: from lobe axis deposits which may be characterised by structureless sandstones, through to structured sandstone off-axis deposits, to the finer-grained heterogeneous lobe fringes (Mutti, 1977; Prélat et al., 2009; Grundvåg et al., 2014; Spychala et al., 2017b). Lobe fringe facies and architecture, and

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Chapter 5:Bed-scale modelling of deep-water lobes: which heterogeneities matter to flow? associated reservoir properties, vary considerably, making the pinchout character of lobes important to stratigraphic trap prediction (McCaffrey and Kneller, 2001; Prather, 2003; Bakke et al., 2013; Spychala et al., 2017b; Hansen et al., 2019). Lateral lobe fringes are interpreted to be thinner and dominated by low-density turbidites, whereas frontal lobe fringes are commonly considered to be hybrid-bed prone, reducing their effective permeability compared to other lobe sub-environments (Hodgson, 2009; Grundvåg et al., 2014; Spychala et al., 2017b; Fonnesu et al., 2018; Kuswandaru et al., 2018).

In this study we utilise an extensive outcrop dataset from Fan 3 of the Tanqua Depocentre, Karoo Basin, South Africa, combined with a subsurface dataset from the X Formation, North Sea, to model the spatial distribution of effective permeability in lobe deposits. The following research questions are addressed: 1) how can we model architectural elements at bed-scale? 2) Which bed-scale heterogeneities matter most to flow? 3) How does vertical permeability (Kv) vary spatially within submarine lobes?

Figure 5.1: Workflow for developing models of sedimentary logs using SBEDTM. Key data input points and positions of quality control are identified.

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Chapter 5:Bed-scale modelling of deep-water lobes: which heterogeneities matter to flow? 5.3 Methods The dataset consists of models of 60 sedimentary logs made in the field which were realised using SBEDTM commercially available software (Fig. 5.1). Sedimentary logs used in the study were from Prélat et al. (2009), Prélat, (2010), and Kane et al. (2017). SBEDTM workflow is as follows:

1) Representative bedding templates, which define lamina geometry and character (e.g. ripple-laminated sandstone), were made for each of the main lithofacies identified in logged sections (Fig. 5.1). 2) Lamina-types were then created using porosity and horizontal permeability (Kh) data from core-plugs of the X Formation, North Sea. The 10th – 90th percentile range was used to eliminate outliers, and all permeability values of 0 were removed to reduce the effect of cementation (Fig. 5.1). 3) Lamina types were then entered into bedding templates (Fig. 5.1). 4) Properties of individual bedding templates were then stochastically modelled to give Kh and Kv (Fig. 5.1); and 5) Kh and Kv values were compared with data from the same lithofacies of the X Formation to ensure consistency (Fig. 5.1). 6) Sedimentary sections were then created by building “stacks” of bedding templates, with individual bedding templates edited to honour sedimentary facies (irregular basal contacts, lamina geometries, mudstone clasts etc.; Fig. 5.1). Stacks had x and y dimensions of 30 cm. The thickness of the model was varied depending on the thickness of the logged section. 7) Three of each stack were realised to allow for subtle differences in lamina arrangement, and clast distribution and orientation. Each stack was checked to ensure it honoured the original sedimentary log (Fig. 5.1). 8) Property distribution was stochastically modelled three times for each stack to reduce the risk of outliers (Fig. 5.1). 9) Single-phase upscaling of each stack was then performed to ascertain the effective permeability of each model (Fig. 5.1). Data were then checked for outliers or erroneous results.

5.4 Facies and model input Core-plug data were organised by bed-type. Conversely, input data for SBEDTM bedding templates is subdivided into lithofacies. Therefore, bed-types of the X Formation comprising similar lithofacies, and derived from similar depositional processes, were used to characterise each SBEDTM lithofacies. Bed-types and lithofacies are summarised in Table 5.1 and Figure 5.2. Sedimentary logs from two fringe-to-axis transects at Gemsbok Valley (Fig. 5.3C) and Skoorsteenberg (Fig. 5.3D) were made in SBEDTM and populated with representative facies and their corresponding Kh realisations.

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Chapter 5:Bed-scale modelling of deep-water lobes: which heterogeneities matter to flow?

SBEDTM and Description Subsurface bed-type Comparative Depositional outcrop lithofacies permeability processes

Siltstone. 0.01 – 0.2 m thick Laminated siltstone. Very low Deposition from dilute divisions of siltstone. low-density turbidity Present as caps of currents (Piper, 1972; Stow individual turbidites or as and Bowen, 1980). laminated “pinstripe” bedding.

Ripple-laminated 0.01 – 0.15 m thick Thin low-density Low Deposition from, and

115 sandstone. divisions of very fine- turbidites. tractional reworking of bed-

sandstone. Beds are ripple tops by, low-density cross laminated, typically on turbidite currents (Allen, the upper surfaces of beds, 1982; Southard, 1991; Jobe though climbing ripples are et al., 2012). locally observed within the bed.

Planar-laminated 0.05 – 1 m thick Thick low-density Low Deposition from low- sandstone. divisions of planar turbidites. density turbidity currents laminated sandstone. and migration of low-

Chapter 5:Bed-scale modelling of deep-water lobes: which heterogeneities matter to flow?

Laminae are typically amplitude bedforms (Best parallel, though uncommon and Bridge, 1992; Sumner et convoluted geometries are al., 2008). observed.

Structureless 0.05 – 3.8 m thick Thick high-density High High-density turbidity sandstone. divisions of apparently turbidites. For distal current with high-rates of structureless very fine- to structureless sandstones deposition (Lowe, 1982; fine-sandstone. Beds are permeability was capped at Mutti, 1992; Kneller and commonly amalgamated D80% to simulate lower Branney, 1995; Baas et al.,

116 and dewatered. permeability due to finer 2004).

grain-sizes (e.g. Beard and Weyl, 1973) in distal lobe deposits (e.g. Bell et al., 2018).

Argillaceous 0.04 – 0.45 m thick Argillaceous hybrid Moderate Aggraded under a flow sandstone. divisions of poorly sorted, beds transitional between mudstone- and organic- turbulent and laminar clast-rich sandstone. (Sylvester and Lowe, 2004; Haughton et al., 2009;

Chapter 5:Bed-scale modelling of deep-water lobes: which heterogeneities matter to flow?

Sumner et al., 2009; Baas et al., 2011; Kane and Pontén, 2012; Kane et al., 2017).

Muddy sandstone. 0.04 – 0.22 m thick Muddy hybrid beds Very low Deposition from a divisions of poorly sorted predominantly laminar flow mudstone- and organic- (Haughton et al., 2009; clast-rich sandstones, with Sumner et al., 2009; Baas et elevated clay contents al., 2011; Kane and Pontén, compared to argillaceous 2012), for example, quasi-

117 sandstone. Outsized gains laminar plug-flow (Baas et

are commonly observed al., 2011). (see Kane et al., 2017).

Chapter 5:Bed-scale modelling of deep-water lobes: which heterogeneities matter to flow?

Figure 5.2: Outcrop, and subsurface analogue, bed-type scheme used in the study.The right-hand side shows example core photos from the Skoorsteenberg Fm., and the Magnus, Scapa, and Brae fields, North Sea. North Sea core photographs contain British Geological Survey materials ©NERC 2019.

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Figure 5.3: Locality maps. A) Location of the study area in South Africa. B) Regional map showing the location of the two main study areas. C) Detailed map of the northern, Skoorsteenberg study area. D) Detailed map of the southern, Gemsbok Valley study area.

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Chapter 5:Bed-scale modelling of deep-water lobes: which heterogeneities matter to flow? 5.5 Geological setting

The Tanqua depocentre

The Tanqua depocentre is located in the southwest of the Karoo Basin. The basin developed due to dynamic mantle subsidence during the Permian (Pysklywec and Mitrovica, 1999; Tankard et al., 2009), before transitioning to a retroarc foreland basin during the Triassic associated with the development of the Cape Fold Belt (De Wit and Ransome, 1992; Veevers et al., 1994; Visser and Praekelt, 1996). The Karoo Supergroup, which records the deepening and subsequent fill of the Tanqua depocentre, comprises: the glacial Dwyka Group, the deep- to-shallow-water Ecca Group, and the fluvial Beaufort Group (Bouma and Wickens, 1994; Wickens, 1994; Johnson et al., 2001).

The Ecca Group in the Tanqua depocentre consists of: the Prince Albert, Whitehill, Tierberg, Skoorsteenberg, Kookfontein, and Waterford Formations (Bouma and Wickens, 1994; Wickens, 1994; Johnson et al., 2001; Wild et al., 2009; Poyatos-Moré et al., 2016). The Skoorsteenberg Formation is interpreted as four submarine fans (Fans 1 – 4), and an overlying slope succession termed Unit 5 (Bouma and Wickens, 1991; Johnson et al., 2001; Hodgson et al., 2006). Fan 3 of the Skoorsteenberg Formation is oriented approximately north-south with sediment dispersal predominantly towards the north (Hodgson et al., 2006). Fan 3 at Gemsbok Valley is characterised by compensationally stacked lobes and the width of the outcrop permits investigation of their lateral pinchouts (Prélat et al., 2009; Hansen et al., 2019). Outcrops around Skoorsteenberg characterise the frontal pinchout of Fan 3, and of the lobes which are mapped from the Gemsbok Valley area (Prélat et al., 2009; Prélat, 2010; Kane et al., 2017).

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Figure 5.4: Lobe sub-environment terminology used in the study.

Lobe 6

At Gemsbok Valley and Skoorsteenberg individual lobes are correlated (e.g. Prélat et al., 2009). However, in areas to the south of Gemsbok Valley, Fan 3 is highly amalgamated which prevents subdivision into lobes. Here we study Lobe 6, which is the uppermost lobe of Fan 3 at Skoorsteenberg and Gemsbok Valley.

In Gemsbok valley, Lobe 6 can be traced from its western lateral sandstone pinchout close to log Big_N, characterised by 0.29 m of rippled sandstone, into its axis 4.4 km to the east where the lobe is 5.47 m thick (Figs. 5.4, 5.5A). Intermediate localities show a gradual thickening, and transition from rippled and laminated sandstones, to structureless sandstones deposited under high-density flows in lobe off-axis positions (Fig. 5.5A; Prélat et al., 2009). Lobe 6 in logs Big_E and Klipspringer_E is 0.96 and 1.44 m thick, respectively, and comprises structureless sandstone with thin (<0.1 m) mudstone-clast-rich layers (Fig. 5.5A; Prélat, 2010). Off-axis positions (e.g. Fig. 5.4) of Lobe 6, observed in logs New_E and Lovers_W are 1.64 and 2.80 m thick, respectively, and are characterized by deposits of both high- and low-density turbidity currents, with thin (<0.1 m) layers of mudstone-clast-rich sandstone (Fig. 5.5A; Prélat, 2010). Lobe axis positions in logs Shell_W and Shell_E are 5.03 and 4.98 m thick respectively, and are characterised by amalgamated structureless sandstones with a thin (<0.1 m) mudstone-clast-rich layer 121

Chapter 5:Bed-scale modelling of deep-water lobes: which heterogeneities matter to flow? present in both logged sections (Fig. 5.5A). However, a 0.06 m thick siltstone was observed at Shell_W, and 0.15 m thick ripple- and planar-laminated deposits were described at Shell_W and Shell_E, respectively (Fig. 5.5A; Prélat, 2010). The thickest measured section of Lobe 6, at log McAl_E2, is 5.47 m and characterised by amalgamated high-density turbidites, with a 0.10 m thick mudstone-clast-rich layer (Fig. 5.5A; Prélat et al., 2009; Prélat, 2010).

At its distal pinchout, Lobe 6 has a lenticular geometry (Kane et al., 2017), interpreted to be a “lobe finger” caused by preferential flow focussing (e.g. Groenenberg et al., 2010; Figs. 5.4, 5.5B). The fringe of the lobe finger (e.g. Fig. 5.4), at SK20, is 2.15 m thick and comprises a mixture of muddy and argillaceous hybrid beds (c. 0.3 – 1 m; Fig. 5.5B). Hybrid beds decrease in abundance to the southwest towards the axis of the lobe finger (e.g. Fig. 5.4), and intermediate positions comprise a mixture of hybrid beds, and low- and high-density turbidites (e.g. SK16; Fig. 5.5B). The axis of the lobe finger (e.g. SK11) is up to 3.7 m thick and comprises cleaner, structureless sandstone, with localised laminated sandstone and argillaceous hybrid beds (Fig. 5.5B;). SK12, located 580 m north of the lobe- finger axis, comprises 0.05 – 0.1 m thick muddy hybrid beds at the base, stratigraphically overlain by 1.75 m thick structureless and 0.97 m thick laminated sandstone, respectively (Fig. 5.5B).

5.6 Results

Net-to-gross

Net-to-gross, where net comprises all non-siltstone facies, is consistently high (above 0.8) in all modelled sections. The minimum net-to-gross values are 0.85 and 0.82 from lobe-fringe positions Big_N and SK20, respectively. There is a general net-to-gross increase observed in both transects towards the axis of the lobe, or lobe-finger, to 0.99 at both McAl_E2 and SK20.

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Chapter 5:Bed-scale modelling of deep-water lobes: which heterogeneities matter to flow?

Figure 5.5: Stratigraphic cross-sections of Lobe 6 in the Gemsbok Valley (A), and Skoorsteenberg (B), areas.The upper panels show sedimentary logs, whilst the lower panels show the bedding and horizontal permeability realisations from SBEDTM. Sedimentary logs from Gemsbok Valley are reproduced from Prélat et al. (2009) and Prélat (2010), and Skoorsteenberg logs are reproduced from Kane et al. (2017).

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Chapter 5:Bed-scale modelling of deep-water lobes: which heterogeneities matter to flow? Vertical permeability

The Kh realisations of sedimentary logs in (Fig. 5.5) were upscaled using a single- phase, giving Kv values for each realisation. Stochastic modelling has inherent randomness, therefore the average of the three realisations is discussed, unless explicitly stated:

Gemsbok Valley transect

Eight graphical sedimentary logs were realised, from the lateral lobe fringe of Lobe 6 (west), to the lobe axis (east) (Figs. 5.5A, 5.6A).

The lowest Kv was 3.1mD in the lateral lobe-fringe at Big_N (Fig. 5.6A). Vertical permeability increased to 10.1 and 21.4 mD in realisations of lobe off-axis positions Big_E and Klipsringer_E 970 and 1510 m to the east of Big_N, respectively (Fig. 5.6A). There was a decrease in Kv to 8.9 mD at New_E and 5 mD at lobe off-axis positions Lovers_W, 360 and 860 m to the east of Klipspringer_E, respectively (Fig. 5.6A). At lobe axis positions Shell_W and Shell_E Kv realisations increased to 30.4 and 39.5 mD over distances of 560 and 810 m eastward of Lovers_W, respectively (Fig. 5.6A). The maximum realised Kv was 53.3 mD in the realisation of lobe axis position McAl_E2, which is located 1240 m to the east of Shell_E (Fig. 5.6A).

There was variability between realisations of models with identical input parameters (Fig. 5.6A). There is limited variability in lobe fringe and off-axis positions; realisations of Big_N had the lowest variability (0.5%), whereas realisations of Big_E had the highest (2.1%) in these lobe sub-environments (Fig. 5.6A). Realisations in the lobe axis had the greatest variability, Shell_W, Shell_E, and McAl_E2, exhibited variability of 1.5, 4.2, and 5.6%, respectively (Fig. 5.6A).

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Chapter 5:Bed-scale modelling of deep-water lobes: which heterogeneities matter to flow?

Figure 5.6: The net-to-gross and upscaled vertical permeability of each realisation in the Gemsbok Valley (A) and Skoorsteenberg (B) transects.Three realisations of each sedimentary log were made, and plotted. The thickness of the pink line reflects how variable these realisations were with respect to each other.

Skoorsteenberg transect

Seven sedimentary logs in a transect from fringe (SK20) to axis (SK11) were modelled using SBEDTM (Figs. 5.5B, 5.6B). The lowest Kv, 1.5mD, was located in the fringe of the lobe-finger at SK20 (Fig. 5.6B). Kv increased in lobe-finger off-axis positions to 3.9 and 7.4 mD, 440 and 785 m southwest of SK20 at SK19 and SK18, respectively (Fig. 5.6B). Kv decreased to 4.1 and 4.8mD in lobe-finger off-axis positions SK16 and SK14, 438 and 806

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Chapter 5:Bed-scale modelling of deep-water lobes: which heterogeneities matter to flow? m to the southwest, respectively (Fig. 5.6B). Kv decreased to 4.2mD over 830 m to the lobe-finger axis at SK12, but abruptly increased to 29mD to SK11 580 m to the south (Fig. 5.6B).

Variability between models was highest in models SK12 (4.2%), SK18 (2.1%), and SK 16 (1.3%). All other models had variability of ≤1% between each of their three realisations (Fig. 5.6B).

Spatial variability of reservoir quality in Lobe 6

To constrain how reservoir quality varies in Lobe 6, using subsurface analogue data, 51 logged sections from Prélat (2010), covering an area of 37 km2, were realised (Fig. 5.7A).

Spatial variability of Kv in Lobe 6

The highest realised Kv was at the lobe-axis position of McAl_E2 (53mD; Fig 5.7D). Kv decreased in model realisations to sandstone pinchout at the lateral fringe to the west at Square_E, and to the northwest in the frontal fringe at SK1 (Fig. 5.7D). Lobe-axis positions have generally higher Kv values (Figs. 5.7B,D); the area around Shell_W has values between 25 and 40mD, and 7 km to the northwest in areas around GN5 Kv values range between 15 and 35mD (Fig. 5.7D). Lobe off-axis areas, such as those around New_E and GF_600, typically exhibit lower Kv values, ranging between 8 and 20mD (Figs. 5.7B,D). Lobe fringes have the lowest Kv values. The sandstone part of the lateral lobe- fringe (e.g. Big_N) typically has Kv values <10mD, with a minimum of 3.1mD (Figs. 5.7B,D). The sandstone part of the frontal lobe-fringe (e.g. SK1 and SK20) has Kv values typically <5mD, with a minimum of 1.5mD.

The distal fringe of Lobe 6 exhibits variability in modelled Kv values (Fig. 5.7B, D). In the broadly across-depositional-strike section from lobe-finger fringe to lobe-finger axis Kv increases from 1.5mD at SK20 to 29mD 3000m to the southwest at SK11 (Figs. 5.7B,D). To the southwest of SK11, Kv decreased to 2mD at lobe-finger fringe position SK1 over 3700m (Figs. 5.7B,D). Lobe-finger off-axis positions are characterised by intermediate Kv values between 3 and 8mD (Figs. 5.7B,D).

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Chapter 5:Bed-scale modelling of deep-water lobes: which heterogeneities matter to flow?

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Chapter 5:Bed-scale modelling of deep-water lobes: which heterogeneities matter to flow? Figure 5.7: Spatial variability in Kv in Lobe 6. A) Satellite image showing locations of logged sections from Prélat (2010) which were modelled. B) Possible interpretation of Lobe 6. C) Spatial distribution of sandstone thickness in Lobe 6. D) Spatial distribution of Kv in Lobe 6.

Spatial variability of sandstone thickness in Lobe 6

Lobe 6 is thickest in Lobe axis positions, reaching a maximum of 6.37 m at GN5, but is generally 4 – 5.5 m thick (Figs. 5.7B,C). Lobe off-axis positions are characterised by the green colour of Figure 5.7C, are thinner than lobe-axis positions, and are typically 1 – 4 m thick. The lobe thins through the lobe fringe, which is typically <1m thick (Fig. 5.7C), to where the sandstone pinches out between Big_N and Square_E, and to the west of SK1 and GN16 (Figs. 5.7B,C).

Lobe 6 has a lenticular geometry at its distal fringe near Skoorsteenberg to the north (Figs. 5.5B, 5.7C). Lobe 6 thickens from 0.32 m at the western fringe of the lobe-finger (SK1) to 3.73 m in the lobe-finger axis at SK11 (Fig 5.7C). Lobe 6 then thins to 2.13 m at the eastern fringe of the lobe-finger at SK20 (Fig. 5.7C).

5.7 Discussion

Controls on the distribution of Kv values

Kv values vary in, and between, lobe sub-environments, which is interpreted to result from the spatial distribution of different bed-types and intra- and inter-bed baffles:

Bed-types

The highest Kv values are located in lobe axis positions (Figs. 5.6A, 5.7D). This is interpreted to be due to: 1) the high proportions of thick-bedded, high-density turbidites which typically exhibit good reservoir properties due to their relatively coarse grain-sizes and low detrital clay contents (Hirst et al., 2002; Lien et al., 2006; Marchand et al., 2015; Porten et al., 2016; Bell et al., 2018a); and 2) high net-to-gross and amalgamation resulting in good communication between event beds dues to the lack of siltstone baffles (Fig. 5.8; e.g. Begg and King, 1985; Desbarats, 1987; Deutsch, 1989; Stephen et al., 2001). Lobe off- axis positions contain a wider-range of Kv values (Figs. 5.6A, 5.7D). This is interpreted to be due to these positions having lower net-to-gross, and comprising a mixture of structureless and structured sandstones (Figs. 5.6A, 5.8), deposited under high- and low- density turbidity currents, respectively. Low-density turbidites are typically finer-grained, reducing their permeability compared to high-density turbidites (Hirst et al., 2002; Lien et

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Chapter 5:Bed-scale modelling of deep-water lobes: which heterogeneities matter to flow? al., 2006; Marchand et al., 2015; Porten et al., 2016; Bell et al., 2018a), and develop sedimentary structures which can act to inhibit migration of, and trap fluids (e.g. Ruvo et al., 2008). Focussing of flows is interpreted to have deposited localised structureless sandstones (e.g. “highly-amalgamated sheet turbidite zones” of Hodgson et al., (2006)) with high Kv in off-axis areas otherwise dominated by poor-quality low-density turbidites (Figs. 5.7D, 5.8). The lateral fringe of Lobe 6 has low Kv values (Figs. 5.6A, 5.7D) due to the prevalence of low-density, predominantly ripple-laminated, sandstones, which are typically linked with poorer reservoir quality (Fig. 5.8).

The distal-fringe of Lobe 6 contains several discrete bed-types (Figs. 5.6B, 5.8), and has a wide-range of Kv values (Figs. 5.6B, 5.7D). The highest Kv values (29mD), comparable to those of the lobe axis (25 – 53mD), were located in the axis of the lobe- finger at SK11 (Figs 5.6B, 5.7D). However, local deposition of low-density turbidites resulted in reduced Kv values in some models (e.g. SK9; Figs 5.6B, 5.7D). Lobe-finger off- axis deposits are sandstone-rich (0.85 – 0.92 sandstone fraction) and contain relatively thin low-density turbidites (Figs. 5.6B, 5.8). Lobe-finger off-axis positions exhibited relatively poor Kv values (4 – 5mD; Figs. 5.6B, 5.7D) which are attributed to the presence of argillaceous and muddy hybrid beds, which have moderate and very-poor permeability, respectively (Fig. 5.8; see also: Porten et al., 2016; Southern et al., 2017), inhibiting vertical flow. Sections where hybrid beds are absent have higher Kv values (e.g. SK17, 7mD; Fig. 5.6B). However, the low Kv compared to axial positions is here attributed predominantly to the greater thickness of siltstone and low-density turbidites in lobe-finger off-axis positions (Figs. 5.6B, 5.8). The lobe-finger fringe had very-poor Kv values (Fig. 5.7D) due to an absence of high-density turbidites, lower net-to-gross (e.g. SK20 0.82 sandstone fraction), and an abundance of argillaceous and muddy hybrid beds (Figs. 5.6B, 5.8) which have moderate and very-low permeability, respectively (see also: Porten et al., 2016; Southern et al., 2017).

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Figure 5.8: Schematic illustration of Kv distribution in a deep-water lobe deposit.The spatial organisation of bed-types, deposited by discrete flow-types, is a primary control on the distribution of high-permeability zones.

These findings demonstrate that even in a high net-to-gross system, there may be strong spatial heterogeneity of Kv in response to the distribution of discrete bed-types and sandstone quality (Fig. 5.8; see also: Porten et al., 2016; Bell et al., 2018a). Recent work has characterised the distal lobe fringe as hybrid-bed-prone (Hodgson, 2009; Grundvåg et al., 2014; Spychala et al., 2017b; Fonnesu et al., 2018; Kuswandaru et al., 2018), with the implication that these sub-environments have poor-reservoir quality. Here, deposits in the distal lobe-finger exhibited some of the highest measured Kv values, indicating distal lobe- fringes can host high-quality sandstones (Figs 5.6B, 5.7D). In this case study, whilst hybrid- bed-prone deposits do have lower Kv values compared to lobe-axis deposits, they exhibited Kv values comparable to low-density turbidite prone lobe off-axis deposits. These findings challenge the generalisation of the distal lobe-fringe as poor reservoir quality.

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Chapter 5:Bed-scale modelling of deep-water lobes: which heterogeneities matter to flow? Model variability

Realisations of models with identical input parameters resulted in variable Kv values, fundamentally due to the stochastic nature of the modeling. The lowest model variability was observed in models which were predominantly homogenous (e.g. SK11, Big_N), or were highly heterogeneous (e.g. SK20, SK17, and New_E; Figs. 5.6A,B). The highest model variability was recorded in models with limited heterogeneity, particularly those featuring clast-rich beds (SK14, Shell_E, and McAl_E2), where variability up to 5.6% was recorded (Figs. 5.6A,B). This suggests that the more heterogeneous a model is, the less influence an individual heterogeneity can exert. Similar observations were made by Hofstra et al., (2017) who recognised wide variability in breakthrough time of relatively homogenous lobe-axis deposits. However, addition of heterogeneity to each facies zone resulted in lower standard deviation of simulated breakthrough time, and faster breakthrough in the lobe axis (Hofstra et al., 2017). Mudstone-clasts are known to inhibit permeability (Cuthiell et al., 1991; Kashikara et al., 2010; Strobl, 2013), and the 3D distribution of clasts of a given density can influence their effect on permeability at a bed- scale (Fig. 5.8). Here, it is demonstrated that clast distribution can result in variability in vertical permeability at an architectural element scale.

Implications of lobe-fingers

Lobe 6 does not exhibit a simple lobate geometry (e.g. Prélat et al., 2009; Prélat, 2010; Kane et al., 2017; Fig. 5.7B). The lobe-finger at Skoorsteenberg extends from the “axis” of the lobe on a kilometre-scale (Fig. 5.7B). The exact distance is unknown as it is in the subcrop, however, finger-like geometries are observed on a kilometre-scale in subsurface studies (e.g. Dodd et al., 2019). Because these bodies can extend on a kilometre-scale, and their deposits can comprise high-permeability sandstone which is connected up-dip to the main body of the lobe (e.g. Spychala et al., 2017; Dodd et al., 2019; Figs. 5.7B,D), lobe- fingers can have the following reservoir implications: 1) lobe-fingers extending beyond the main body of the lobe may enable fluid migration into a trap (Fig. 5.9A); 2) lobe-fingers may extend beyond a predicted frontal stratigraphic trap, providing high-permeability pathways for the loss of fluids (Fig. 5.9B); 3) lateral fringes are less-prone to lobe-finger development. Therefore these plays may provide less-risk for trap development, but may have poorer permeability and connectivity (Fig. 5.9C; see also: Spychala et al., 2017).

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Chapter 5:Bed-scale modelling of deep-water lobes: which heterogeneities matter to flow?

Figure 5.9: Schematic model illustrating implications the study may have for hydrocarbon migration and prediction of stratigraphic traps. A) Lobe-fingers may extend into source areas, enabling migration of hydrocarbons through high-permeability lobe-finger axes to a trap located up-dip. B) Predicted distal-fringe stratigraphic trap may be breached if high-permeability sands are deposited in lobe-fingers beyond the predicted sandstone pinchout. C) Stratigraphic traps based on lateral lobe-fringe sandstone pinchouts may have less-risk due to lower abundance of lobe-fingers. 132

Chapter 5:Bed-scale modelling of deep-water lobes: which heterogeneities matter to flow? 5.8 Conclusions Bed-scale modelling of deep-water lobes revealed strong spatial variability in vertical permeability (Kv), and therefore likely reservoir quality. Kv varied between discrete lobe sub-environments. In proximal areas of the lobe, the lateral lobe fringe exhibited the poorest Kv, and off-axis positions were marginally higher. The lobe axis exhibited the highest Kv values in all models realised. In distal parts of the lobe, the hybrid-bed-prone lobe fringe exhibited the lowest realised Kv values. The distal part of the studied lobe is characterised by a lobe-finger. The fourth highest Kv values were realised in the axis of the lobe-finger, indicating that high-quality reservoir sandstones are capable of reaching the outer reaches of lobes on a kilometre-scale. This challenges a common notion that distal lobe fringes exhibit poor reservoir quality due to the abundance of hybrid beds.

Net-to-gross in all realised sections is greater than 0.8, this emphasises the control of sandstone quality on permeability, even in sandstone-rich systems. Axial positions exhibit good reservoir properties due to an abundance of structureless sandstones. However, localised heterogeneities such as mudstone-clasts can affect Kv by up to 5.5%. Conversely, off-axis positions and lateral fringe positions exhibit poor reservoir properties due to abundant low-density turbidites. Hybrid beds and low-density turbidites in the distal fringe of the lobe result in poor Kv values. However, high-permeability structureless sandstones were locally present in the lobe-finger. The findings of this study have strong implications for prediction of reservoir quality distribution in deep-water systems, and for the prediction and assessment of stratigraphic traps.

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Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system CHAPTER 6: Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system Daniel Bell1, Ian. A. Kane1, David M. Hodgson2, Anna S. M. Pontén3, Larissa A. S. Hansen2, and Stephen S. Flint1

1School of Earth and Environmental Sciences, University of Manchester, Oxford Road, Manchester, M139PL, U.K.

2Stratigraphy Group, School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, U.K

3Equinor ASA, Research Centre Rotvoll, NO-7005 Trondheim, Norway

6.1 Abstract Submarine slope channel systems have complicated 3D geometry and facies distributions, which is challenging to resolve using subsurface data. Outcrop analogues can help bridge this gap, although most exhumed systems only afford 2D constraints of the depositional architecture. A rare example of an accessible fine-grained slope channel complex set deposited in a tectonically quiescent basin that offers seismic-scale, down-dip and across- strike exposures is the Klein Hangklip area, Tanqua-Karoo Basin. Twenty-one detailed sedimentary logs and tracing of key surfaces across a 3km2 area reveal that: 1) basal channel elements in channel complexes infill relatively deep channel axes and have low aspect- ratios. Later channel elements are bound by relatively flat erosion surfaces and have high aspect-ratios; 2) channel axis facies are dominated by amalgamated, structureless and mud- clast rich sandstones, whereas channel margins are characterized by bedded, structureless and laminated sandstones; 3) stratigraphic architecture is consistent and predictable at seismic-scale both down-dip and across-strike in 3D; 4) channel-base-deposits exhibit spatial heterogeneity on 1 – 100’s m length-scales, which can inhibit accurate recognition and interpretations drawn from 1D or limited 2D datasets; and 5) channel-base-deposit character is linked to sediment bypass magnitude and longevity, which suggests time- partitioning is biased towards conduit excavation and maintenance in submarine channel- fills. The data presented provides insights into the stratigraphic evolution and architecture of slope channel-fills in fine-grained passive margin settings and can be utilised to improve predictions derived from lower resolution and 1D well data.

6.2 Introduction Submarine slope channels are conduits for some of the largest sediment transport events on Earth (e.g., Piper and Aksu, 1987; Gonzalez-Yajimovich et al., 2007; Talling et

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Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system al., 2007; Jobe et al., 2018), with individual flows up to an order of magnitude larger than the global annual flux of rivers to the ocean (Milliman and Syvitski, 1992; Talling et al., 2007b). Submarine gravity flows within these channels transport large quantities of organic carbon and anthropogenic pollutants to their ultimate sink on the basin-floor (Galy et al., 2007; Gwiazda et al., 2015; Kane and Clare, 2019). Slope channel-fills can act as valuable archives of past climatic and tectonic events (e.g., Mutti, 1984; Bruhn and Walker, 1997; Clark and Cartwright, 2009; Pickering and Bayliss, 2009; Covault and Graham, 2010; Hirst, 2012; Scotchman et al., 2015; Castelltort et al., 2017), and are common and important hydrocarbon reservoirs on continental margins around the world (e.g., Bruhn and Walker, 1997; Weimer et al., 2000; Kolla et al., 2001; Prather, 2003; Mayall et al., 2006; Zhang et al., 2015).

The evolution and character of slope channels is challenging to decipher using subsurface data, as they are often characterised by complicated 3D facies heterogeneity and depositional geometries. Outcrop analogues can help to bridge this scale gap, and provide data to populate 3D bodies mapped in seismic with stratigraphic and facies information (e.g., Bryant and Flint, 1992; Clark and Pickering, 1996; Campion et al., 2000; Sullivan et al., 2000; McCaffrey and Kneller, 2001; Hodgetts et al., 2004; Bakke et al., 2008; Bakke et al., 2013; Hofstra et al., 2017). Most outcrops only afford 2D constraints of the depositional architecture, which provides only limited information on how architecture and facies vary either laterally (across-strike) or longitudinally (down-dip) (e.g. Walker, 1966, 1975; Campion et al., 2000; Sullivan et al., 2000; Kane et al., 2009; Moody et al., 2012; Macauley and Hubbard, 2013; Bain and Hubbard, 2016; Li et al., 2016). Few outcrop-based studies are able to investigate the 3D architecture and stratigraphic evolution of submarine channel-fills at outcrop, and those that do rely on extrapolation of LiDAR data from oblique sections (Pyles et al., 2010; Pyles et al., 2012). Additionally, most outcrop analogues are from relatively small foreland basins with small drainage basins and coarse-grained sediment, which are poor analogues for the comparatively large, fine-grained and mud-rich systems that are common in offshore passive margin settings with large drainage basins (e.g. Reading and Richards, 1994; Bouma, 2000; Stelting et al., 2000; Hubbard et al., 2005; Pickering and Corregidor, 2005; Prélat et al., 2010; Kane and Pontén, 2012).

Channel-fills are commonly time transgressive (e.g. McHargue et al., 2011; Sylvester et al., 2011; Hubbard et al., 2014; Hodgson et al., 2016), formed by numerous energetic flows that excavated the channel. The preserved expression of flows that bypassed sediment further down-dip are composite erosion surfaces and associated heterogeneous channel-base-deposits. We utilise the term channel-base-deposit instead of the commonly 135

Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system used channel-base-drape (e.g. Barton et al., 2010), as a drape infers low-energy, or background, depositional processes, whereas the facies deposited commonly suggest repeated cycles of erosion, entrainment, and deposition by high-energy flows (e.g. Mutti and Normark, 1987). The nature of channel-base-deposits is commonly used to infer the characteristics of their parent flows, and can be useful in predicting the presence or absence of sandstone down-dip (Walker, 1975b; Mutti and Normark, 1987; Barton et al., 2010; Hubbard et al., 2014; Stevenson et al., 2015; Li et al., 2016).

Here, we document an exhumed Permian slope channel-complex-set (Unit 5, Skoorsteenberg Formation) that crops out in the Tanqua depocentre, Karoo Basin, South Africa (Fig. 1A,B). A series of depositional strike, depositional dip, and oblique oriented cliff-faces permit documentation of the lateral, longitudinal, and vertical architecture of channel-fills in a mud-rich, fine-grained system. The objectives of this study are: 1) to elucidate the stratigraphic evolution of the channel-complex-set; 2) to investigate the down- dip and across-strike architectural and facies variability within the channel-complex-set; 3) to document the facies and distribution of channel-base-deposits; and 4) to discuss the implications for reservoir connectivity and interpretation of subsurface data.

6.3 Geological setting The Karoo Basin developed during the Permian due to subsidence induced by mantle flow processes associated with subduction of the Palaeo-Pacific plate, before transitioning to a retro-arc foreland basin related to an adjacent fold and thrust belt, from approximately 250Ma (Cape Fold Belt; De Wit and Ransome, 1992; Veevers et al., 1994; Visser and Praekelt, 1996; Viglietti et al., 2017). The deposits of the Karoo Supergroup record basin deepening followed by shallowing from the Carboniferous to the Triassic (Bouma and Wickens, 1991; Wickens, 1994; Hodgson et al., 2006). Stratigraphically, the Karoo Supergroup comprises the glacial Dwyka Group, the deep- to shallow-marine Ecca Group and the non-marine Beaufort Group (Fig. 6.1D; Smith, 1990; Johnson et al., 1996). This study concerns the Ecca Group, which records a progradational, shallowing-upward succession of deep-water to shallow-marine sediments (Fig. 6.1D; Smith, 1990; Bouma and Wickens, 1994; Hodgson et al., 2006).

The Ecca Group in the Tanqua depocentre, located in the southwest of the Karoo Basin, comprises the Lower and Upper Ecca Group: The Lower Ecca Group consists of the shallow-marine Prince Albert and Whitehill Formations; the Upper Ecca Group includes the sand-starved basin-floor Tierberg Formation, the basin-floor to slope Skoorsteenberg Formation, and slope to shallow-marine Waterford Formation (Fig. 6.1D;

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Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system Bouma and Wickens, 1991; Bouma and Wickens, 1994; Johnson et al., 2001; Wild et al., 2005; Hodgson et al., 2006; Wild et al., 2009; Poyatos-Moré et al., 2016).

The Skoorsteenberg Formation is 450 m thick in the Tanqua Depocentre and comprises five sandstone-prone units. The lower four units are interpreted as a progradational succession of submarine fans (Fans 1 – 4), overlain by a fifth unit (Unit 5) interpreted as a base-of-slope to lower-slope system (Bouma and Wickens, 1991; Bouma and Wickens, 1994; Johnson et al., 2001; Wild et al., 2005; Hodgson et al., 2006; Prélat et al., 2009). Each fan is interpreted to represent a lowstand systems tract, and is overlain by regional fine-grained packages interpreted as the combined transgressive and highstand systems tracts (Goldhammer et al., 2000; Johnson et al., 2001; Hodgson et al., 2006).

This study focusses on Unit 5 in the Klein Hangklip (KHK) study area located in the south of the Tanqua depocentre (Fig. 6.1B, C). Here, the preserved stratigraphy is 55 m-thick, although Unit 5 is ~100 m-thick regionally, and is interpreted as a submarine slope environment consisting of lateral channel splay deposits, intraslope lobes, and channel-fills (Wild et al., 2005). The channel-fills are hierarchically organised and are interpreted as a series of channel complexes (Wild et al., 2005). A regional fine-grained unit separates Unit 5 from the underlying Fan 4, which is subdivided into sandstone-rich Upper and Lower Fan 4, which are separated by an extensive thin-bedded sub-unit (Hodgson et al., 2006; Spychala et al., 2017b; Hansen et al., 2019).

6.4 Methods and data set This study utilises twenty-one sedimentary logs measured at 1:20 scale. Logs are placed into stratigraphic context using seven correlation panels, three oriented along depositional-dip, and four oriented along depositional-strike (Fig. 6.1C). Correlations were made in the field by walking out key packages and surfaces. Aerial and UAV photographs were used to support correlations in areas difficult to access and were used to guide and supplement geometric interpretations observed in the field. Data collected include lithology, bed thickness and palaeocurrents (n=107) measured from ripple cross- lamination, wood-fragment long-axis orientation and channel incision surfaces.

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Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system

Figure 6.1: Locality maps and stratigraphic context of the study area: A) Location of the Tanqua depocentre, Karoo Basin in South Africa. B) Location of the Klein Hangklip outcrop. C) Positions of logged sections and stratigraphic panels at the Klein Hangklip outcrop. D) Summarised stratigraphic column of the Tanqua succession.

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Table 6:1: Lithofacies observed in the field area

Cod Lithofacies Thickne Grain-size Description Interpretation e ss (m)

F1 Siltstone 0.01 – 14 Fine- to Fine siltstones with interbedded coarse- Deposition from dilute low-density turbidity coarse- siltstone packages. Fine siltstone packages currents (Mutti, 1977; Sumner et al., 2012). siltstone appear structureless. Coarse-siltstone packages are well-bedded and often contain ripple cross-lamination.

139 F2 Laminated 0.05 – 1.5 Very fine- Alternating 0.1-to-1 mm-scale coarser and Layer-by-layer deposition from repeated

sandstone sandstone finer laminae. Plant fragments are development and collapse of near-bed traction occasionally present parallel to laminae. carpets (Sumner et al., 2008) and migration of Typically sharp bed tops and bases which low-amplitude bed-waves (Best and Bridge, 1992; can be amalgamated, but can be to/from Sumner et al., 2008). siltstone.

F3 Rippled 0.1 – 2.1 Very fine- Present as either individual beds or as part Deposition from long-lived, surging flows with sandstone sandstone of packages up to 7m thick. Typically high rates of sediment fallout (Allen, 1991; Baas consists of ripples with steep angles of climb et al., 2000; Kane and Hodgson, 2011; Jobe et al., interbedded with planar laminated sandstone 2012).

Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system

and infrequent climbing ripples with subcritical angles of climb. The lower division of the bed typically consists of laminated sandstone.

F4a Structureless 0.02 – 10 Very fine- Typically structureless and typically Rapid settling from a high concentration flow sandstone to lower ungraded to weakly normally-graded. F4a are (e.g., Lowe, 1982). F4b fine- well-bedded and typically <1m thick. F4b sandstone are thick amalgamated packages with poorly- defined bedding which form packages up to

140 10m thick. Commonly show evidence of

dewatering, though typically more evident in F4b. Mudstone chips may be locally present.

F5a Dunes 0.3 – 1 Lower Cross-bedded sandstones with foresets 10s Deposition and reworking from fast-moving, fine- of cm high. Foresets can be clast rich (F5a), long-lived, low-concentration turbidity currents F5b sandstone or clast poor (F5b). (Allen, 1970; Allen, 1982; Baas et al., 2004; Sumner et al., 2012; Talling et al., 2012).

F6 Mud clast-rich 0.05 – 4 Very fine- Present as either individual beds or as Deposition from high-concentration turbidity structureless to lower packages up to 6m thick. Typically ungraded currents which were erosive either locally or up fine- sandstone with abundant mm- to cm-scale

Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system

sandstone sandstone mudstone clasts throughout or aligned in depositional dip. discrete horizons within the bed.

F7 Argillaceous 0.1 – 0.4 Very fine- Typically observed as composite packages in Deposition from highly concentrated, erosive, sandstone to lower channel-base-deposits. Often mudstone- flows transitional between turbulent and laminar fine- clast-rich. Commonly scoured. flow regimes due to clast entrainment and sandstone breakup (Haughton et al., 2003; Baas et al., 2009; Kane and Pontén, 2012; Pierce et al., 2018).

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Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system 6.5 Facies and channel hierarchy The outcrops at Klein Hangklip are interpreted as submarine channel-fills containing turbidites (Wild et al., 2005).

Facies

Six lithofacies were identified, and are summarised in Table 6.1.

Figure 6.2: Representative photographs of lithofacies in the study area: A) Bedded siltstone (F1); B) Laminated sandstone (F2); C) Rippled sandstone (F3); D) Medium-bedded amalgamated sandstone (F4a); E) Mudstone-clast-rich thick-bedded amalgamated sandstone(F4b and F6); F) Dune-scale cross bedding (F5b); G) Mudstone-clasts concentrated on an erosion surface (F6).

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Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system Facies associations

The channel axis is typically the thickest part of a channel-fill, and predominantly consists of relatively thick-bedded, amalgamated F4a, F4b and F6 (Figs. 6.2, 6.3). The channel off-axis section is stratigraphically thinner and comprises comparatively thinner- bedded F4 and F4b and F2, with subordinate F6 (Figs. 6.2, 6.3). The channel margin area is comparatively thin and laterally extensive away from the channel axis (Fig. 6.3). The channel margin consists of comparatively thin-bedded F2 and F4a, with localised F1 and F3 (Figs. 6.2, 6.3).

Figure 6.3: Photopanel interpretation of an across-depositional-strike oriented cliff-face. KHK incises from the channel margin in the north to the channel axis in the south, where it may incise the top of Upper Fan 4. The channel axis (e.g. Log 3) is thicker and contains thick-bedded F6 and F4b in lower channel elements, and bedded F4a in upper channel elements. The off-axis (e.g. Log 2) is thinner and comprises bedded F4b in lower channel elements, and bedded F4a and F2 in upper channel elements. Channel margin positions (e.g. Log 1) comprise bedded F4a in lower channel elements, and bedded F2 in upper channel elements.

Channel hierarchy

Submarine slope channel-fills have been recognised to exhibit a hierarchy in their organisation (Fig. 6.4; e.g., Sprague et al., 2002; Sprague et al., 2005; Di Celma et al., 2011; McHargue et al., 2011; Moody et al., 2012; Macauley and Hubbard, 2013; Li et al., 2016). Following the approach of Sprague et al. (2002, 2005), from smallest to largest, the channel-fill consists of: beds/facies that share similar lithologies; channel elements, which

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Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system represent a single cycle of cut-and-fill (Fig. 6.4); channel complexes formed from two or more nested channel elements (Fig. 6.4); and channel complex sets formed by two or more stacked channel complexes (Fig. 6.4). This approach was applied to the Unit 5 succession using scale and stacking patterns, and by walking out bounding surfaces and channel-base- deposits across the outcrop, using aerial photography, and correlation of logs.

Figure 6.4: Schematic summary of the hierarchical arrangement applied to the Klein Hangklip channel-fill. The channel complex set is the largest hierarchical level observed. The channel complex set consists of two channel complexes, which each comprise four channel elements. Sub-environment geometries and facies distributions are schematically illustrated based on previous work (Mutti, 1977; Campion et al., 2000; Sullivan et al., 2000; Eschard et al., 2003; Beaubouef, 2004; Macauley and Hubbard, 2013).

6.6 Results

Architectural element descriptions

The architectural elements comprising the Klein Hangklip channel complex set are described below.

Channel complex 1: KHKC

KHKC is at least 890 m wide, has a maximum thickness of 32.9 m at Log 1 (Fig. 6.5), and thins and fines northwards (Panels 5, 6 and 7; Fig. 6.6). The minimum logged thickness of KHKC is 5.2 m at the channel margin position of Log 16 (Fig. 6.5), although KHKC visibly continues to thin to the north of that position. The outcrop of KHKC has a lenticular geometry (Figs. 6.3, 6.6), and represents approximately one half of the original channel complex (Fig. 6.6). KHKC incises into the underlying siltstones and locally incises Upper Fan 4 (Fig. 6.6). The maximum observed incision is 20.5 m. The base of KHKC is rarely exposed, though the channel-base-deposit is observed 100 m to the south of Log 19 where KHKC incises F3 facies of Upper Fan 4 (Fig. 6.7A). At this locality, the channel- 144

Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system base-deposit comprises: 1) a basal surface lined by mudstone clasts that is incisional into underlying sandstones, and overlain by: 2) 0.2 m of thin-bedded coarse siltstone, and 3) 1.1 m of lenticular thin-bedded sandstones, with rare localised mudstone clasts, and medium- bedded sandstones that subtly incise the thin-bedded sandstones (Fig. 6.7B). The upper surface of the channel-base-deposit is mudstone-clast-rich and is overlain by channel element 1 of KHKC: C1. Four channel elements are identified in KHKC:

(KHK) C1

C1 is lenticular in geometry with a maximum thickness of 10.2m at its axis at Log 20, and 4.1 m thick in the thinnest measured section, Log 18 (Fig. 6.3). C1 thins further northward, but the thicknesses of individual channel elements become challenging to constrain. The base of C1 is rarely exposed, except south of Log 19 (Fig. 6.7A) and at Log 3, where a 10 cm thick mudstone-clast-rich siltstone lag is observed below basal F4 of the channel-fill. In the channel axis (e.g., Log 3; Fig. 6.5) C1 comprises amalgamated, stacked F6 with frequent mudstone-clast-rich bed tops at the base, overlain by F4b (Fig. 6.3). F6 beds decrease in number and mudstone clasts reduce in size stratigraphically upwards (Figs. 6.3, 6.6). The channel margin of C1 primarily comprises F4a, though F2 and F3 are observed locally (Figs. 6.3, 6.6).

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Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system

Figure 6.5: Sedimentary logs and correlation panels from the study area. Refer to Fig. 1C for referencing.

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Figure 6.6: Depositional strike oriented correlation panels. Panels are arranged from proximal (bottom) to distal (top) to illustrate changes in facies and geometries. Inferred geometries are drawn from oblique oriented panels (e.g. Panel 1), walking of the outcrop, and analysis of aerial and drone photography.

(KHK) C2

C2 incises into C1 (Figs. 6.3, 6.6), is 16.8 m thick in its channel axis at Log 3 (Fig. 6.5), and thins to 6.2 m to the northeast at Log 18, and 3.5 m to the east at Log 13 (Fig. 6.8). The base of C2 incises into C1 and is marked by a channel-base-deposit with variable facies. In the westernmost logged sections, Logs 20 and 21, the channel-base-deposit of C2 is a basal mudstone-clast layer overlain by a 10 – 20 cm thick fine siltstone with localised

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Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system mudstone clasts. One kilometre down-dip to the east at Log 3 the base of C2 is characterised by amalgamated, mudstone-clast-rich sandstones that are locally eroded through a thin siltstone bed (Fig. 6.8). At Logs 4, 5, and 13, the channel-base-deposit of C2 is expressed as a clast-rich composite channel-base-deposit up to 1.5 m thick, composed of decimetre-scale rounded and angular sandstone clasts, remobilised bedded sandstones up to up to 1 m in length and abundant mudstone clasts centimetres to a metre in length with multiple composite scour surfaces. The deposit is also represented locally by a 30 cm thick clast-rich siltstone with thin-beds of discontinuous clay-rich sandstones; and as an amalgamation surface with the underlying sandstones of C1, mantled by mudstone clasts. The fill of C2 is spatially variable, both between channel axis and channel margin positions, and in different panels down depositional dip (Figs. 6.6, 6.8). Typically, the channel axis comprises F4b, with F6 in the lower 2 m locally observed (Figs. 6.6, 6.8). Up to 4.5 m of F3 is observed in the channel axis of the White House localities (Fig. 6.6; Panel 4). Bedding becomes clearer and less amalgamated into off-axis and channel margin positions (Fig. 6.3). This is accompanied by a decrease in bed thickness and degree of amalgamation, and an increase in F4a and F2 (Figs. 6.3, 6.6).

(KHK) C3

The basal erosion surface and channel-base-deposit of C3 are relatively flat-lying and identified in the field through an abrupt stratigraphic change in facies from thick- to relatively thin-bedded sandstones (Fig. 6.3). C3 has a tabular geometry compared to C1 and C2 (Figs. 6.3, 6.6). The fill of C3 has a maximum thickness of 7 m in the channel-complex axis at Log 3 (Fig. 6.5), but is typically 3 – 4 m thick elsewhere (Fig. 6.5). The channel-base- deposit of C3 is laterally variable, comprising a 5 – 20 cm siltstone at Logs 4, 5, 16, 18 and 20, a clast-rich siltstone at Logs 1, 2 and 21, and amalgamated thin-beds or sandstone at Logs 3, 12 and 15. The fill of C3 predominantly consists of F4a and F4b (e.g., Log 3; Fig. 6.3). Channel off-axis and axis positions contain F6, typically located near the base of the channel element (Figs. 6.3, 6.6). Bed thickness and degree of amalgamation decrease into channel margin positions, which comprise F2 and F4a, with rare F6 overlying the channel- base-deposit (Figs. 6.3, 6.6). In southern channel margin localities (Logs 4 and 5) the fill of C3 is dominated by F2, with localised F4a (Figs. 6.8, 6.9).

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Figure 6.7: Erosion surfaces and channel-base-deposits: A) Incision by KHKC into underlying stratigraphy near Log 19 on the north of Klein Hangklip. B) Inset of (A). Channel-complex-set basal deposit observed in a channel margin position. The deposit is 1.5 m thick and predominantly comprises thin-bedded sandstones deposited from dilute flows and medium-bedded sandstones which incise into underlying beds, deposited from larger flows. Lens cap circled for scale C) Sharp erosion surface between 149

Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system channel elements D1 and D2 which lacks a channel-base-deposit. D) Channel-base-deposit of D3 at its most composite, located on the outer bend of the channel-fill. The composite deposit is incised by overlying sandstone and laterally identified as a sandstone amalgamation surface. Lens cap circled. E) Typical non- composite character of the D3 channel-based-deposit observed at other localities. F) Thin-bedded channel element scale channel-base-deposit between D3 and D4. Hammer circled. G) Thin-bedded, coarse siltstone channel-base-deposit between channel elements D3 and D4. H) A c.30 cm thick siltstone-rich channel- base-deposit between channel elements C3 and C4.

(KHK) C4

KHK C4 is the uppermost channel element of the KHKC channel complex and has a relatively tabular geometry (Figs. 6.6, 6.8). The total thickness of C4 is unknown as the upper portion is poorly-exposed and therefore thicknesses are a minimum value. C4 is thickest in the channel axis at Log 17 (7 m; Fig. 5), the measured thickness in other localities is typically 3 – 5 m (Fig. 6.8). The C4 erosion surface and channel-base-deposit are rarely exposed, and variable where they are observed. The channel-base-deposit is typically a thin siltstone that may contain mudstone clasts (<10 cm, locally up to 30 cm; Fig. 6.7H), though the base may locally be an amalgamation surface. The facies of the C4 channel element fill is variable, particularly across strike. In axial positions, C4 comprises F4a with local F4b and F6 (Figs, 6.3, 6.6). Off-axis positions consist of F2 and F4a, with F4b and F6 locally present down dip (Figs. 6.6, 6.8). Channel margin positions predominantly comprise F2, with localised F4a (Figs. 6.3, 6.6). The south-eastern most position of C4, Log 5, has 2 m of F1 at the base and is overlain by 1 m of F3 (Fig. 6.9).

Channel complex 2: KHKD

The KHKD channel complex outcrops as a 2.7 km wide (minimum) oblique-strike oriented exposure (Panel 1; Figs. 6.5, 6.9) and does not outcrop on the north face of Klein Hangklip. KHKD is thickest (39 m) at Log 7 (Fig. 6.5) and thins east and west to 6 m and 4.5 m thick in the channel margins at Logs 10 and 6, respectively (Figs. 6.5, 6.8). The western channel-cut of KHKD is steeper than the eastern channel-cut (Figs. 6.8, 6.9). The western channel margin pinches out approximately 40 m to the west of Log 6 (Figs. 6.8, 6.9). The pinchout of the eastern margin is not observed due to the oblique nature of the outcrop, although the thinning and change of facies to predominantly laminated sandstone suggests it is located south of Logs 9 and 10. The channel axis of KHKD incises a maximum of approximately 22.5 m into the underlying fill of KHKC at Log 7 (Figs. 6.8, 6.9). The basal erosion surface and channel-base-deposit of KHKD are well-exposed across the outcrop (Fig. 6.9). In channel axis positions, the channel-base-deposit is 150

Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system composite and up to 2.5 m thick, and comprises F6, remobilised clasts that are commonly sheared (Fig. 6.10C); F1, which is widely incised; argillaceous sandstones (Fig. 6.10C); and F4b, which is locally amalgamated with underlying KHKC sandstones (Fig. 6.10D). The channel off-axis comprises a basal deposit 5 – 30 cm thick consisting of F1 and thin F4a, which are discontinuous and locally slumped (Fig. 6.10B). In channel margin positions, the channel-base-deposit predominantly comprises at least 10 cm of F1 with occasional mudstone clasts and lenticular very-fine sandstone beds. Four channel elements are identified in KHKD:

Figure 6.8: Depositional dip oriented panels from proximal (left) to distal (right). Facies are variable spatially, both in depositional dip and strike oriented directions.

(KHK) D1

KHK D1 is the oldest channel element in the KHKD channel complex. D1 is mapped over 2.7 km in Panel 1, and is best exposed on the southern face of the outcrop where the channel-fill was walked out and traced using aerial photographs where inaccessible (Figs. 6.8, 6.9). KHK D1 is up to 17 m thick in the channel axis at Log 7 (Fig. 6.5), and thins laterally to 2.5 m and 2.2 m in the western and eastern channel margins at Logs 6 and 10, respectively (Figs. 6.5, 6.8). In the west of the study area, D1 thins northwards from 9.5 m at Log 20, to 6.3 m at Log 21 over a distance of 70 m. The proportion of F4a decreases, which is accompanied by an increase in F2 (Fig. 6.6). On the southern outcrop face, the channel-base-deposit of D1 is 1.5 m thick and composite at Log 151

Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system 7 (Fig. 6.10C), becoming thinner and more silt-prone east and west to Logs 9 and 6, respectively. The facies distribution of D1 is asymmetric (Figs. 6.8, 6.9). In Logs 5 and 6 in the west, D1 predominantly consists of F2 (Figs. 6.8, 6.9), with abundant laminae-parallel plant fragments. The proportion of F4b and amalgamated F6 increase into the thickest parts of D1 at Logs 7 and 14, adjacent to the steep western channel-cut (Fig. 6.9). Thin (<10cm) layers of F1 wedge out from the steep western channel-cut (Fig 6.10B). F1 beds are incised by overlying deposits that contain abundant clasts of F1 towards the channel axis (Fig. 6.10B, C). The eastern channel-cut, from Log 9 to Log 8, has a shallower gradient (Fig. 6.8). The channel-fill exhibits a gradual decrease in F4b and F6, and a concurrent proportional increase in F2 to the east of Log 7 (Fig. 6.8). Stratigraphically within D1 the proportions of F4b and F6 decrease upwards with a concurrent increase in F2 (Figs. 6.8, 6.9).

(KHK) D2

KHK D2 has a subtle unconformable contact with D1 in logs and can be traced on aerial photos between Logs 13 and 14 (Fig. 6.9). The geometry of D2 is lenticular, thickening from east of Log 13 to Log 7, but is poorly observed to the east where cliffs are lichen-covered (Figs. 6.8, 6.9). The base of D2 is characterised by thin-bedded F2 of D1, overlain by thick-bedded F2 (Fig. 6.8D), and 1.2 m of F4b, respectively. The upper-fill of D2 comprises 3.3 m of 0.02 – 0.3 m thick bedded F6. The upper-fill contains localised 0.1 – 0.5 m thick scour-fills consisting of cm-scale beds of F4a and thin-bedded F6.

(KHK) D3

KHK D3 has a relatively tabular geometry, with thicknesses between 3.9 m and 1.2 m (Fig. 6.9). The channel-base-deposit of D3 is 0.1 – 0.3 m thick, flat-lying, laterally continuous, and consists predominantly of F1 which may be locally clast-rich. Localised amalgamation of thin-bedded F4a is also observed. However, adjacent to the steeper western channel cut the channel-base-deposit comprises an up to 30 cm thick composite deposit consisting of mudstone- and sandstone-clasts and argillaceous sandstones, though is laterally observed as a sandstone amalgamation surface over 2 – 3 m. In all cases the channel-base-deposit overlies a sandstone bed mantled with mudstone clasts. At Logs 13 and 7, D3 consists of F4b and F6 (Figs. 6.8, 6.9). The proportions of F4b and F6 decrease to the east and west with a concurrent increase in the proportion of F2 (Figs. 6.8, 6.9).

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Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system

Figure 6.9: Annotated photomosaic of an E-W oriented cliff face on the southern side of Klein Hangklip. KHKD incises into KHKC from west to east, cutting into channel margin facies of channel elements C2, C3, and C4. The channel axis of the KHKD channel complex comprises greater proportions of F4b and F6 compared to the channel off-axis and margin positions to the east and west. Facies distribution is asymmetric, with sharper pinchouts and facies transitions against the steeper western margin (outer bank) compared to the shallower eastern margin (inner bank). 153

Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system (KHK) D4

KHK D4 is the uppermost channel element identified in the KHKD channel complex. The thickness of D4 is variable in the field area, from 13 m at Log 7 to 1.4 m thick at Log 10 (Fig. 6.5); these are minimum recorded thicknesses due to modern erosion. The basal surface of D4 is relatively flat-lying, suggesting the channel element had an overall tabular geometry (Figs. 6.8, 6.9). The channel-base-deposit of D4 is typically characterised by fine-grained, thin-bedded F4a, which subtly incise into, and amalgamate with, the underlying sandstones of D3 (Fig. 6.8F, G). Locally, the channel-base-deposit comprises 10 cm of F1, which is clast-rich and overlain by centimetre- to decimetre-thick beds of F6. Where KHKD is thickest, D4 predominantly comprises F6b at the base, and localised F2 in the upper 2 – 3 m (Figs. 6.8, 6.9). Where KHKD thins to the east D4 consists of F4a and F4b, with localised F2 (Figs. 6.8. 6.9). Conversely, to the west D4 predominantly comprises F2 at Log 5 (Figs. 6.8, 6.9).

Figure 6.10: Lateral variability in facies of the KHKD channel-base-deposit. B) Channel complex scale channel-base-deposit in an off-axis position which comprises draping thin-bedded sandstones and slumped beds. Hammer circled. C) Highly composite channel complex channel-base-deposit in a channel axis position of KHKD1. D) Sharp, mudstone-clast-rich amalgamated erosion surface between channel complexes KHKC and KHKD

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Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system

Figure 6.11: Palaeocurrent data collected in the field. A) KHKC is constrained by its outcrop limits which are consistent with wood-fragment orientation. B) The orientation of KHK is constrained by the channel-cut at Log 13 and its outcrop limits, which are supported by preferred wood-fragment orientations.

Palaeocurrents

KHKC

Measurements from Logs 1, 12, and 20 suggest northward palaeoflow, whereas Logs 4 and 21 suggest southward and eastward palaeoflow, respectively (Fig. 6.9A). Long- axes of wood-fragments in Logs 4 and 15 are oriented east-west (Fig. 6.11A). The northward thinning of KHKC towards Logs 15, 16 and 18 suggests that the axis of the channel was situated south of those localities (Fig. 6.11A). The absence of KHKC in southeastern Logs 10 and 11 indicates the channel was located to the north of these positions. 155

Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system Channel margin facies observed in channel elements C3 and C4 at Logs 4 and 5 suggest the axis of these channel elements was positioned to the north (Figs. 6.9, 6.11A).

These data suggest KHKC was oriented northeast-southwest, with a north- eastward palaeoflow consistent with regional palaeocurrent observations, and is essentially straight at the scale of the outcrop (Fig. 6.11A). Variable ripple cross-lamination trends are interpreted to represent flows that over-spilled the channel axis, and which may have been deflected off confining slopes (e.g. Kane et al., 2010).

KHKD

The western margin of KHKD is well-constrained at Log 13, where the strike of the channel-cut is oriented northeast-southwest (Fig. 6.9, 6.11B). Long-axes of wood- fragments show preferred orientations to the east at Logs 13 and 20, and northeast at Log 7, respectively (Fig. 6.11B). At Log 11, the preferred wood-fragment orientation is east- southeast. The presence of KHKD at Logs 20 and 21, and eastward of Log 5, but absence at Logs 3 and 4 suggest that KHKD curved around these positions to the south (Fig. 6.11B). The absence of KHKD in localities on the north face of Klein Hangklip suggests that the channel lay to the south (Figs. 6.6, 6.11B). Exposure of KHKD is continuous along the east-west oriented southern face, suggesting that the orientation of KHKD is parallel to sub-parallel to the outcrop (see panel 1, Fig. 6.5; Fig. 6.11B). Log 10 contains a greater proportion of channel margin facies compared to Logs 9 and 11, which both show a thickening, and increase in channel axis facies (F4b, F6) in their respective directions (panel 1, Fig. 6.5B), suggesting that the channel margin is located to the south of these positions (Fig. 6.11B). The channel-cut and wood-fragment orientation at Logs 7 and 13 suggests that KHKD was sinuous at the scale of the outcrop (Fig. 6.11B). This is supported by facies asymmetry at the western margin (e.g. Pyles et al., 2010), and facies transitions between Logs 9, 10 and 11, which suggest that the channel axis curved around to the north of Log 10.

Channel architecture interpretations

Type-1: Low aspect ratio channel elements

KHKC1 and KHKC2, and KHKD1 and KHKD2 are the two lowermost channel elements in their respective channel complexes (Figs 6.6, 6.8). Each channel element is thickest in the channel complex axis, thins considerably towards the channel complex margin, and incises the underlying stratigraphy by between 5.5 and 22.5 m (Figs. 6.3, 6.9).

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Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system Basal erosion surfaces are sigmoidal in geometry, and typically mantled by mudstone clasts in the channel axis, which decrease in abundance to the channel margins (Figs. 6.6, 6.7, 6.10). In the channel axis, the channel-base-deposit is typically composite, up to 2.5 m thick and consists of clast-rich siltstone, discontinuous argillaceous sandstones, and localised rotated slide blocks (Fig. 6.10C). The channel-base-deposit in off-axis positions is more silt- rich with thin beds of sandstone, and localised metre-scale slide blocks (Fig. 6.10B); locally the channel-base-deposit is identified as a mudstone clast-rich amalgamation surface (Fig. 6.10D). In channel margin positions the channel-base-deposit is typically represented by 0.5 – 0.3 m of siltstone. The channel axis of low aspect ratio channel elements is characterised by amalgamated F4b with localised F6 near the base, F2 is sometimes observed in the upper few meters (Figs. 6.6, 6.8). Off-axis positions typically comprise F4a and F4b with increasing proportions of F2 towards the channel margin; F6 is rarely observed (Figs. 6.6, 6.8). The channel margins consist of F4a and F2 (Figs. 6.6, 6.8).

Type-2: High aspect ratio channel elements

KHKC3 and KHKC4, and KHKD3 and KHKD4 constitute the uppermost channel elements in their respective channel complexes (Figs. 6.6, 6.8). The channel elements are tabular in geometry and have comparatively high aspect ratios with relatively consistent thicknesses (typically 2 – 6 m), but locally have thicknesses between 1.2 m and 13 m (Figs. 6.6, 6.8). Basal erosion surfaces are typically tabular to sub-horizontal and commonly mantled by mudstone clasts (Figs. 6.7, 6.9). The associated channel-base-deposit is typically 0.05 – 0.3 m of siltstone with localised mudstone clasts, though it may be present as an amalgamation surface marked by mudstone clasts. Channel axis deposits of high aspect ratio channel elements consist of bedded F4a and uncommon F4b, with localised F6 and F2 at the base and top, respectively (Figs. 6.6, 6.3). Off-axis positions comprise comparatively thinner-bedded F4a and F2 (Figs. 6.6, 6.3). Channel margin positions are characterised by a proportional increase in F2 (Figs. 6.6, 6.3). F1 and F3 are observed in KHKC4 in south-eastern localities (Fig. 6.6).

Channel complex architecture

KHKC and KHKD are each composed of four channel elements, two low aspect ratio channel elements overlain by two high aspect ratio channel elements.

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Figure 6.12: Stratigraphic evolution of the KHK channel system. A) Erosion of the KHKC surface and prolonged bypass-dominated zone. B) Transition to deposition dominated flows and fill of KHKC1. C) Incision and subsequent fill of KHKD2. D) Shallow incision and fill of high aspect ratio channel elements KHK3 and 4. E) Prolonged bypass phase resulted in excavation of KHKD channel cut. F) Transition to deposition dominated flows and aggradation of KHKD1. G) Incision and fill of KHKD2. H) Shallow incision and deposition of the KHKD3 and D4 channel elements.

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Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system KHKC

Palaeocurrent directions, outcrop geometries and facies transitions suggest KHKC is relatively symmetrical and straight at the scale of the outcrop (Figs. 6.11A). The channel axis of each channel element in KHKC is situated in the channel complex axis (Fig. 6.6) suggesting aggradationally stacked channel elements with relatively symmetrical facies distribution. Channel margin positions are dominated by bedded F2 and F4a, with localised F1 and F3 (Figs. 6.3, 6.6). Off-axis positions are characterised by F2, F4a, infrequent F4 and rare F6 (Figs. 6.3, 6.6). Channel axis positions are dominated by F6 and F4b in the lower, low aspect ratio channel elements, but comprise bedded F4a and F4b with localised F6, and an upwards proportional increase in F2 (Figs. 6.3, 6.6).

KHKD

Palaeocurrents and outcrop geometries suggest that KHKD was sinuous at the scale of the outcrop (Fig. 6.11B). The channel-complex geometry is asymmetric, with a steeper western channel cut and shallower eastern channel cut (Figs. 6.8, 6.9). Each channel element is thickest and contains respectively higher proportions of F6 and F4b in positions in the channel axis immediately east of the western channel cut (Figs. 6.8, 6.9). Facies transitions to channel margins dominated by F2 are gradual to the east, but comparatively abrupt to the west against the steeper channel cut (Figs. 6.8, 6.9). The asymmetric channel element facies distribution suggests that the channel axes of successive channel elements were concentrated in the outer bank of the channel complex bend, and stacked aggradationally (Figs. 6.8, 6.9; see also Jobe et al., 2010; Labourdette and Bez, 2010; Li et al., 2016; Pyles et al., 2010). These relationships are strongest in low aspect ratio channel elements, D1 and D2 (Figs. 6.8, 6.9). The upper, high aspect ratio, channel elements D3 and D4 exhibit more laterally extensive deposits of F4a and F4b; however, F6 is only identified on the channel complex axis (Figs. 6.8, 6.9).

Distribution of channel-base-deposits

Low aspect ratio channel element channel-base-deposits typically have a relatively steep angular contact to underlying strata and exhibit facies asymmetry (e.g. Figs. 6.9, 6.10). Channel axis positions are characterised by relatively thick composite deposits (up to 2.5 m), comprising clast-rich siltstones, remobilised clasts of F4 and F6 up to 1.5 m in length, mudstone rafts, and amalgamated packages of F6 (Fig. 6.10C). Locally, channel-base- deposits are not composite, and are identified only as clast-rich amalgamation surfaces with the underlying channel element sandstones (Figs. 6.7C, 6.10C). Typically, off-axis positions 159

Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system exhibit a slightly thinner deposit, and contain localised slumped beds shed from the channel erosion surface (Fig. 6.10B). Channel margin positions are characterised by <30cm thick locally clast-rich, siltstone deposits that typically overlie a mudstone-clast-rich bed top. KHKD2 differs from other low aspect ratio channel elements as it lacks a preserved channel-base-deposit (Fig. 6.7C). The subtle erosion surface is marked by a sharp, sub- parallel, facies change from thin-bedded F4a to F4b (Fig. 6.7C).

High aspect ratio channel element channel-base-deposits are relatively flat-lying, and are less heterogeneous (Figs. 6.7F, G, H). They are typically characterised by siltstones up to 40 cm thick (Figs. 6.7F, G, H). The channel-base-deposit in channel axis positions frequently contains mm-cm -scale clasts of siltstone and commonly overlie a mudstone- clast-rich bed-top. Locally, the channel-base-deposit is marked by a clast-rich amalgamation surface. Channel off-axis and margin positions are comparatively clast-poor, though local beds of siltstone starved ripples are observed. The KHKD4 channel-base-deposit comprises 5 – 10 cm of thin-bedded coarse-siltstone to very fine-sandstone beds, and locally a <10 cm siltstone, which are subtly incised by overlying beds of the channel-fill (Figs. 6.7F, G). In contrast, the KHKD3 channel-base-deposit is locally composite adjacent to the steep KHKD channel-cut surface.

6.7 Discussion

Stratigraphic evolution

Incision and the resultant development of a composite channel complex-set erosion surface is the first recorded phase of channel evolution (Figs. 6.12A, 6.13). The development of the surface is likely to have been time-transgressive (Sylvester et al., 2011; Hodgson et al., 2016). However, the record of the development of the surface, and its formative processes, is obscured. The 1.5 m thick channel-base-deposit (Fig. 6.7A, B) is interpreted to have been deposited from relatively dilute parts of flows, which were primarily confined within the channel axis (e.g., Hubbard et al., 2014). These deposits suggest the erosion surface acted as a long-lived conduit for the bypass of sediment into the basin (Fig. 6.13; e.g., Hubbard et al., 2014; Stevenson et al., 2015). The nature of channel-base-deposits is used as a proxy for the energy and number of flows that bypassed the channel by bypassing, partially bypassing, and depositional flows;, and the duration of complete sediment-bypass, bypass-dominated, and depositional zones (sensu Stevenson et al., 2015). This approach assumes the preserved deposit is reflective of the time-averaged flow-processes during deposition, and that any material that was deposited is preserved.

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Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system The fill of KHKC records the transition from complete sediment bypass to a depositional zone (sensu Stevenson et al., 2015; Figs. 6.12B, 6.13), relative to the channel axis. The first stage of this aggradation is recorded by the strongly channelised fill of C1 (Fig. 6.12B). A subsequent phase of incision and filling is marked by channel element C2, indicating an increase in flow-energy, sediment bypass, and degradation of the slope (Fig. 6.13). Flows causing degradation of the slope were not necessarily larger (e.g. Sylvester et al., 2011), but were more erosive than flows leading to aggradation. The C2 channel-base- deposit is highly composite, suggesting there was a long-lived bypass-dominated zone before aggradation of the C2 fill (Fig. 6.13). The individual fills of C1 and C2 record a vertical decrease in evidence for flow bypass up stratigraphy (Fig. 6.13), from F6 and F4b at the base to F2 and F4a at the tops (Figs. 6.3, 6.6).

The upper-fill of C2 was partially incised as part of the formation of high aspect ratio channel element C3, indicating an increase in flow energy, erosion, and sediment bypass (Figs. 6.12D, 6.13). The C3 fill was also partially incised as part of the development of channel element C4. The thin siltstone-rich channel-base-deposits, small depth of incision, and less-composite nature suggests erosion and bypass was less pronounced and protracted, probably due to less-erosive flows, compared to the incisions related to C1 and C2 (Fig. 6.13). The fills of C3 and C4 are similar, and suggest a temporal decrease in flow energy (Figs. 6.12D, 6.13).

Following the fill of the KHKC channel complex, approximately 2 m of siltstone was deposited, representing a prolonged hiatus of sand supply to the area. The period of silt-prone deposition was ended by incision by the KHKD channel-cut (Fig. 6.12E) indicating an increase in flow energy and bypass (Fig. 6.13; e.g. Kneller, 2003); possibly driven by eustatic controls (e.g., Flint et al., 2011) and the overall progradation of the system (e.g., Hodgson et al., 2006). The highly composite channel-base-deposit, comprised of depositional and erosional features, at the base of the D1 channel axis suggests the channel axis was a long-lived bypass-dominated zone utilised by depositional, partially bypassing, and bypassing flows (Fig. 6.13; e.g., Hubbard et al., 2014; Stevenson et al., 2015).

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Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system

Figure 6.13: Schematic illustration of channel evolution and flow behaviour in the channel axis of respective channel complexes. Highly composite erosion surfaces and channel-base-deposits suggest long periods of time are stored in the excavation of channel cuts and prolonged bypass phases. However, most of the thickness of the channel-fill is represented by aggradational sandstones developed under strongly depositional flows. This suggests time-partitioning in submarine channels may be biased towards individual surfaces which occupy a small portion of the channel thickness.

A gradual transition to net-depositional flows resulted in the fill of the KHKD channel complex (Figs. 6.12F, 6.13). KHKD1 records an upward decrease in bypass (Fig. 6.13), typified by a reduction in F6 and bed amalgamation (Fig. 6.12F). Facies asymmetry, with F6 and F4b being more common adjacent to the steep-western channel-cut (Figs. 6.12F), suggests the highest energy flow components were located near the base of the outer-bank (secondary or helical flow; see Keevil et al., 2006; Imran et al., 2007; Peakall et al., 2007; Peakall and Sumner, 2015). Erosion of F1 lenses from the channel-cut in towards the channel axis (Fig. 6.10B, C) suggests flows were most energetic in the thalweg of the channel axis (Reimchen et al., 2016), and decelerated against the outer channel-cut (e.g., Keevil et al., 2006).

The incision related to the fill of D2 (Fig. 6.7G) is interpreted to represent erosion by bypassing flows. The channel-base-deposit related to D2 is sharp and simple, suggesting a short-lived bypass-dominated zone, or that subsequent flows eroded the initial channel- base-deposit (Fig. 6.13). The D2 fill records the aggradation of the channel by lower energy, depositional, flows (Fig. 6.13). However, the upper-fill of D2 contains thin-bedded scour-fills. This may be associated with a gradual increase in flow energy, and record the transition from depositional to partially bypassing flows, to those which fully bypassed, leading to incision of the D3 channel-cut (Figs. 6.12G, 6.13; see also package 2 of Pyles et al., 2010). The upper part of D2 is weakly incised, interpreted as a decrease in flow energy and sediment bypass compared to the incision of underlying channel elements (Fig. 6.13). The lack of incision and composite channel-base-deposit development suggest the amount, and duration, of sediment bypass was limited (Fig. 6.13). The channel-base-deposit is overlain by high aspect ratio channel element D3 (Fig. 6.12H, indicating flows became

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Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system deposition-dominated (Fig. 6.13). The fill of the D3 channel element was incised as part of the development of channel element D4 (Figs. 6.12H, 6.13). The incision is flat-lying compared to low aspect ratio channel elements, suggesting limited phases of bypassing and partially bypassing flows (Fig. 6.13). However, the channel-base-deposit is locally composite adjacent to the steep channel-cut of KHKD, which is located on the outer bend of the channel. This suggests that higher-energy parts of flows were concentrated at the outer-bend, and bypass and substrate remobilisation was more efficient in these locations. The subsequent aggradation of the D4 channel element reflects the transition to depositional flows (Fig. 6.13).

3D channel architecture

The KHK outcrop permits quasi-3D facies distribution to be recorded in a series of depositional dip- and strike-oriented panels (Figs. 6.6, 6.8). The KHKC channel complex shows no substantial down depositional-dip changes in geometry or sandstone distribution. However, subtle changes in facies are recorded in dip-oriented sections, from F4 to F2 to F4, and varying thickness and distribution of F6 (Figs. 6.4, 6.6). The KHKC channel complex is interpreted to be relatively straight at the scale of the outcrop. Channel complex KHKD, which is inferred to be sinuous, has a steeper western (outer-bank) channel cut, displays more pronounced across depositional-strike variability and has a greater proportion of F4b and F6 compared to the eastern side of the channel cut. These observations are made on a 0.1 – 1 km scale, in predominantly sandstone-filled channels; similar distributions were noted by Pyles et al. (2010). However, at a system-scale (i.e., over 10s – 100s of km), channel-fills may show major longitudinal facies variability in response to the dominance of different flow processes. In proximal areas, slumps and debris flows are more abundant, whereas in distal parts of the system deposits of high- and low-density turbidites are more commonly observed (De Ruig and Hubbard, 2006; Malkowski et al., 2018). Therefore, at system scale, flow processes, and methods of sediment mobilisation up-dip are likely to be the strongest control on heterogeneity. Channel sinuosity, and its effect on the inherited flow processes, is likely to determine local facies distribution and channel element geometries over longitudinal profiles of 0.1 – 1 km (e.g. De Ruig and Hubbard, 2006; Pyles et al., 2010; Reimchen et al., 2016; Malkowski et al., 2018).

Controls on channel element geometry

Each channel complex contains two low aspect ratio channel elements overlain by two high aspect ratio channel elements. Low aspect ratio channel elements have lenticular

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Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system geometries and facies distributions, and bed-thickness decreases from channel axis to channel margin. Highly erosive flows are interpreted to have incised the basal channel-cut (Fig. 6.13; Pyles et al., 2010; McHargue et al., 2011; Fildani et al., 2013; Hubbard et al., 2014; Hodgson et al., 2016). Subsequent flows became progressively confined, enhancing flow efficiency (sensu Mutti, 1992), increasing bypass and erosion, and further entrenching the channel (e.g., Hodgson et al., 2016). Development of thick, composite channel-base- deposits (Figs. 6.7A, 6.10B, C) is interpreted to represent a prolonged sediment bypass zone in the channel axis through the early stages of waning sediment supply (Fig. 6.13; e.g., Hubbard et al., 2014). This early stage of channel aggradation was likely characterised by numerous flows which were bypassing, partially bypassing, and depositional. The gradual transition to net-depositional flows is preserved in the channel-base-deposit where deposits of earlier depositional flows were eroded and remobilised by bypassing or partially bypassing flows (see also: Vendettuoli et al., 2019). Remobilised deposits and clasts of beds (Fig. 6.10B, C) suggest successive flows were transitional between depositional, and fully bypassing, remobilising beds (Fig. 6.13; e.g., Stevenson et al., 2015). This is possibly linked to smaller cycles of waxing and waning superimposed on the overall trend (e.g. Vendettuoli et al., 2019). KHKD2 diverged from other low aspect ratio channel elements as it lacks a composite channel-base-deposit (Fig. 6.7C). The subtle, amalgamated KHKD2 channel- base-deposit surface is interpreted to represent either: 1) a relatively rapid transition from near-complete bypass to deposition-dominated flows, inhibiting the development of a composite channel-base-deposit (Fig. 6.13); or 2) incision and erosion of the initial channel- base-deposit by later flows.

A gradual increase in the number of net-depositional flows resulted in initial aggradation and deposition of amalgamated F6 at the base of the channel complex axis (Fig. 6.13). Packages of F6 overlain by F4 at the base of channel-fills are interpreted to record the transition from bypassing, to partially bypassing, to depositional flows (sensu Stevenson et al., 2015). During aggradation higher-concentration flow components were more strongly affected by channel topography, and were contained in the channel axis where they rapidly deposited thick packages of F4b (e.g. Hubbard et al., 2014; Bell et al., 2018). Local changes in intra-channel topography and gradient may have resulted in subtle down-dip and across-strike variations in depositional facies caused by flow acceleration/deceleration, and entrainment of substrate. Dilute, low-concentration flow components were able to surmount channel topography to the channel margins, depositing thinner bedded F4a and F2 (Fig. 6.12; e.g., Campion et al., 2000). Disparity in deposit

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Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system thickness resulted in more-rapid fill of accommodation in the channel axis relative to the channel margin (see also: Hubbard et al., 2014).

Subsurface implications

Seismic data does not have the resolution to show complicated geometric relationships and small-scale features such as channel-base-deposits (Fig. 6.14; e.g., Alpak et al., 2013; Morris et al., 2016). Therefore, well-data are crucial in identifying them in the subsurface to build realistic geological models. Core logging and image log/dipmeter analysis are common ways to interpret channel-base-deposits and erosion surfaces (e.g., Barton et al., 2010; Morris et al., 2016). This case study reveals that these methods may prove challenging as: 1) highly composite channel-base-deposits are locally observed as clast-rich amalgamation surfaces, not suggestive of substantial bypass (Fig. 6.10, 6.14). Thus, small changes in well-placement could result in dramatically different core interpretations (Fig. 6.14); 2) siltstone bypass channel-base-deposits may be challenging to differentiate from abandonment or low-energy depositional drapes without identification of clasts or a mudstone-clast-rich basal surface (Fig. 6.14), which may influence the prediction of clastic deposition down-dip; 3) some erosion surfaces are characterised by subtle amalgamation surfaces and facies changes, which may not be interpreted as a major bounding surface (Figs. 6.7, 6.10, 6.14); and 4) high aspect ratio channel elements have relatively flat-lying erosion surfaces, which may make dip-meter identification challenging (Fig. 6.14).

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Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system

Figure 6.14: Comparison of scales of observation. A) Photopanel interpretation of the Klein Hangklip outcrop. B) Sedimentary logs collected from the outcrop, with key surface interpretations. C) Comparison to a Miocene channel complex set from the Taranaki Basin, New Zealand. Incision of a lower channel complex’s channel margin by a later, laterally offset, channel complex shows similar geometries to those observed at Klein Hangklip. Data sourced from the NZP&M Petroleum Exploration Dataset. D) 166

Chapter 6:Stratigraphic hierarchy and 3-D evolution of a submarine slope channel system Synthetic cores, drawn from logged data, of key stratigraphic positions illustrating the challenges of correctly identifying key channel surfaces in 1D datasets.

6.8 Conclusions The Klein Hangklip outcrop of Unit 5 of the Skoorsteenberg Formation permits high-resolution analysis of the architecture, facies, and stacking patterns of a submarine slope channel-complex-set. The channel-complex-set comprises two channel-complexes, a lower channel-complex which is straight at the scale of the outcrop, and a sinuous upper channel-complex which resulted in architectural- and facies-asymmetry. Each channel- complex consists of four channel-elements which are grouped into: 1) lower channel- elements which are i) low-aspect ratio, ii) incise up to 20 m into underlying stratigraphy, and iii) exhibit strong facies trends from abundant amalgamated structureless sandstone and mudstone-clast-rich facies in channel-axis positions to bedded structureless sandstone and laminated sandstones in channel-margin positions. 2) Upper-channel elements are i) high-aspect ratio, ii) do not incise deeply into underlying stratigraphy, and iii) have less- contrasting fills in channel-axis and channel-margin positions. Systematic facies changes are observed from comparatively thick-bedded amalgamated sandstones deposited from energetic flows in channel-axis deposits, to bedded, laminated sandstones in channel- margin positions. Conversely, positions in comparative down-depositional dip positions show subtle, but non-systematic heterogeneity in sandstone facies.

Channel-base-deposits are mapped in depositional-dip and strike sections, and are shown to exhibit spatial and temporal heterogeneity at 1’s – 100’s m length scales, which could inhibit accurate characterisation in subsurface and limited-outcrop studies. Depth of incision and composite nature of channel-base-deposits are used as proxies for the existence of long-lived bypass conduits. Data suggest that time-partitioning in the channel- fill is strongly biased towards excavation and maintenance of these conduits, whereas aggradation of the relatively thick-bedded sandstone-fills was comparatively short-lived.

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Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures CHAPTER 7: Topographic controls on the development of contemporaneous but contrasting basin-floor depositional architectures Daniel Bell1, Christopher J. Stevenson2, Ian A. Kane1, David M. Hodgson3, Miquel Poyatos-More4

1 SedRESQ, School of Earth and Environmental Sciences, University of Manchester, Manchester, M13 9PL, U.K.

2 School of Environmental Sciences, University of Liverpool, Liverpool, L69 3GP, U.K.

3 The Stratigraphy Group, School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, U.K.

4 Department of Geosciences, University of Oslo, 0371 Oslo, Norway

7.1 Abstract Sediment-laden gravity-driven-flow deposits on the basin floor are typically considered to form either discrete lobes that stack compensationally, or packages of laterally extensive beds, commonly termed “sheets”. These end-member stacking patterns are documented in several basin-fills. However, whether they can coexist in a single basin, or there are intermediate or transitional stacking patterns, is poorly understood. An analysis of depositional architecture and stacking patterns along a 70 km dip-oriented transect in the Upper Broto Turbidite System (Jaca Basin, south-central Pyrenees, Spain), which displays disparate stacking patterns in contemporaneous strata, is presented. Proximal and medial deposits are characterized by discrete packages of clean sandstones with sharp bed tops which exhibit predictable lateral and longitudinal facies changes, and are interpreted as lobes. Distal deposits comprise both relatively clean sandstones and hybrid beds that do not stack to form lobes. Instead, localized relatively thick hybrid beds are inferred to have inhibited the development of lobes. Hybrid beds developed under flows which were deflected and entrained carbonate mud substrate off a carbonate slope that bounded the basin to the south; evidence for this interpretation includes: 1) divergent paleoflow indicators and hummock-like features in individual beds; 2) a decrease in hybrid-bed thickness and abundance away from the lateral confining slope; 3) a carbonate-rich upper division, not seen in more proximal turbidites. The study demonstrates the co-occurrence of different styles of basin-floor stacking patterns in the same stratigraphic interval, and suggests that that characterization of deep-water systems as either lobes or sheets is a false dichotomy.

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Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures 7.2 Introduction Submarine fans are some of the largest sedimentary deposits on Earth (e.g., Barnes and Normark, 1985), can contain significant volumes of hydrocarbons (e.g., McKie et al., 2015), and are the ultimate sink for vast quantities of organic carbon (e.g., Cartapanis et al., 2016) and pollutants (e.g., Gwiazda et al., 2015). Despite the economic and environmental importance of submarine fans, their processes and products are relatively poorly understood, due to limitations associated with remote sensing and monitoring of modern systems, and challenges with imaging and sampling buried ancient systems. Consequently, uplifted ancient fans at outcrop represent an opportunity to study the architecture of these systems at a high resolution (e.g., Walker, 1966; Ricci-Lucchi and Valmori, 1980; Mutti and Sonnino, 1981; Hodgson et al., 2006; Grundvåg et al., 2014).

Sediment-laden gravity-driven flows develop deposits which are typically considered to stack in one of two end-member patterns on the basin floor: i) compensational lobes; or ii) individual laterally extensive beds, commonly termed “sheets” (referred to as tabular stacking herein; e.g., Ricci-Lucchi and Valmori, 1980; Mutti and Sonnino, 1981; Talling et al., 2007; Deptuck et al., 2008; Prélat et al., 2009; Marini et al., 2015; Fonnesu et al., 2018). Basin-floor lobes form discrete composite sand bodies with subtle convex-upward topography and display predictable changes in bed thickness and facies (e.g., Prélat et al., 2009; Grundvåg et al., 2014; Marini et al., 2015; Spychala et al., 2017a). Compensational stacking occurs where depositional relief causes subsequent flows to be routed to and deposited in adjacent topographic lows, as documented from outcrop (Mutti and Sonnino, 1981; Prélat et al., 2009; Prélat and Hodgson, 2013; Grundvåg et al., 2014; Marini et al., 2015); seismic and seabed imaging (Deptuck et al., 2008; Jegou et al., 2008; Saller et al., 2008; Straub et al., 2009; Picot et al., 2016) and experimental studies (Parsons et al., 2002). Tabular stacking has been described in basin settings where flows were fully contained, or laterally confined (e.g., Hesse, 1964; Ricci-Lucchi and Valmori, 1980; Ricci-Lucchi, 1984; Remacha and Fernández, 2003; Tinterri et al., 2003; Amy et al., 2007; Marini et al., 2015). Tabular beds can be traced over tens to hundreds of kilometers and can be basin-wide (e.g., Hirayama and Nakajima, 1977; Ricci-Lucchi and Valmori, 1980; Talling et al., 2007; Stevenson et al., 2014a). Deep-water depositional systems are usually considered to exhibit one style of stacking pattern or the other. However, recent studies recognize that different stacking patterns can develop at different stratigraphic levels in the same basin fill (Marini et al., 2015; Fonnesu et al., 2018). Here, we present for the first time a detailed study of two contrasting types of stacking pattern co-occurring in the same well-constrained stratigraphic interval of a confined basin. 169

Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures Confined basins are characterized by intrabasinal slopes and may include synsedimentary structural features, which can influence flow behavior, and therefore depositional processes and patterns (e.g., Haughton, 1994; Kneller and McCaffrey, 1995; Kneller and McCaffrey, 1999; Hodgson and Haughton, 2004; Remacha et al., 2005; Amy et al., 2007; Pickering and Bayliss, 2009; Kane et al., 2010; Muzzi Magalhaes and Tinterri, 2010; Tinterri et al., 2017). Hybrid beds are a common component of unconfined deep- water systems, and are identified predominantly in fringe locations (e.g., Haughton et al., 2003; Talling et al., 2004; Haughton et al., 2009; Hodgson, 2009; Kane and Pontén, 2012; Grundvåg et al., 2014; Kane et al., 2017; Spychala et al., 2017a; Spychala et al., 2017b; Fonnesu et al., 2018). However, recent work suggests that hybrid beds also form where flows interact with, and decelerate against, confining slopes (e.g., McCaffrey and Kneller, 2001; Muzzi Magalhaes and Tinterri, 2010; Patacci and Haughton, 2014; Fonnesu et al., 2015; Southern et al., 2015; Tinterri and Tagliaferri, 2015). These models generally do not incorporate the effects of slope substrate entrainment during flow deflection and transformation (although see "sandwich beds" of McCaffrey and Kneller, 2001), the deposits of which are discussed as an important process in generating basin-floor topography in distal settings.

This study examines stacking patterns and facies distributions of time-equivalent deep- water stratigraphy deposited in a confined, tectonically active basin: the Upper Broto Turbidite System of the Jaca Basin, northern Spain. The following research questions are addressed: 1) how are turbidites and other gravity-flow deposits distributed spatially in a basin that variably confined the parent flows spatially? 2) What is the spatial distribution of stacking patterns? 3) Where are hybrid beds developed, and how do they affect the facies distributions and stacking of basin-floor deposits? 4) What controlled the development of hybrid beds?

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Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures

Figure 7.1: Location and geological context of the study area. A) Location of the field area in Spain. B) Simplified geological map of the Hecho Group (adapted from Remacha et al., 2003). C) Paleogeographic map of the Pyrenean Foreland Basin during the Early Lutetian (modified from Dreyer et al., 1999).

7.3 Geological setting

The Jaca Basin (Fig. 7.1), located in the south-central Pyrenees, developed during the Early Eocene as an elongate east-west-trending foredeep approximately 175 km long and 40-50 km wide (Puigdefàbregas et al., 1975; Mutti, 1984; Labaume et al., 1985; Mutti, 1985; Mutti, 1992; Teixell and García-Sansegundo, 1995; Remacha and Fernández, 2003; Fernández et al., 2004; Millán-Garrido et al., 2006). The basin was bounded by the Pyrenean orogenic belt to the north, a carbonate-dominated ramp-type margin to the south, and the Boltaña Anticline and the Aínsa Basin to the east (Figs. 7.1C, 7.2; Puigdefàbregas et al., 1975; Labaume et al., 1985; Barnolas and Teixell, 1994). Fluvial-to- shallow-marine systems of the Tremp-Graus Basin, located to the east, fed clastic sediment into the Aínsa and Jaca Basins through structurally confined channels and canyons (Fig. 7.1C; e.g., Nijman and Nio, 1975; Mutti, 1984; Mutti et al., 1988; Mutti, 1992; Payros et al., 1999; Moody et al., 2012; Bayliss and Pickering, 2015). The fill of the Aínsa Basin is interpreted as a submarine slope succession (e.g., Mutti, 1977; Millington and Clark, 1995; Clark and Pickering, 1996; Pickering and Corregidor, 2005; Pickering and Bayliss, 2009; Moody et al., 2012), which delivered sediment to the basin-floor environments of the Jaca Basin (Figs. 7.1C, 7.2; Mutti, 1977; Mutti 1984; Mutti, 1985; Remacha and Fernández, 2003; Remacha et al., 2005).

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Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures The Hecho Group in the Jaca Basin comprises submarine-lobe and basin-plain deposits with paleocurrents predominantly to the northwest (Mutti, 1977; Mutti, 1992; Remacha et al., 2005; Clark et al., 2017). The deep-water stratigraphy in the Jaca Basin is constrained through nine carbonate-rich megabeds (named MT-1 to -9 to maintain consistency with nomenclature), which extend tens to hundreds of kilometers from southeast to northwest (Fig. 7.1B; e.g., Rupke, 1976; Seguret et al., 1984; Labaume et al., 1985; Labaume et al., 1987; Rosell and Wiezorek, 1989; Barnolas and Teixell, 1994; Payros et al., 1999). Locally, these deposits can be over 100 m thick and contain rafted blocks tens of meters thick and hundreds of meters wide. These distinctive beds can be mapped regionally and enable correlation between isolated outcrops (e.g., Remacha and Fernández, 2003).

Previous studies in the Jaca Basin have described both tabular stacking patterns (Remacha and Fernández, 2003; Tinterri et al., 2003; Remacha et al., 2005), and compensationally stacked lobes developed due to autogenic avulsion of feeder channels, or through structural controls (Mutti, 1992; Clark et al., 2017). Across-strike architecture is poorly constrained due to a relatively narrow outcrop belt trending approximately along depositional dip (Fig. 7.1B; e.g., Remacha and Fernández, 2003; Tinterri et al., 2003; Remacha et al., 2005). This study examines the strata of the Upper Broto turbidite system immediately underlying Megabed 4 (Fig. 7.2; MT-4).

7.4 Dataset and methods

The field area is located along a SE – NW transect between the villages of Fanlo and Ansó (Fig. 7.3). Exposures along road cuts, small gullies, and river valleys permit detailed study of stratigraphic sections and the ability to trace bed geometries over hundreds of meters. Sixteen sedimentary logs were collected over a 70 km depositional dip and 1.5 km depositional strike transect. Sections were logged at centimeter scale, including individual bed thicknesses and sedimentary textures. Sandstone packages were correlated using three marker beds in order to produce a robust correlation framework. These beds, in stratigraphic order, are: Db-1 (debrite-1), Db-2 and MT-4. MT-4 is mappable across the study area (e.g., Payros et al., 1999), Db-1 and Db-2 are locally present in the study area around Broto (Fig. 7.3). MT-4 has previously been used as a marker bed by Remacha and Fernández (2003), to constrain the same studied interval in distal localities. Paleocurrent readings (n = 166) were collected from flute and groove casts, and 3D ripple cross- lamination. Lithofacies are described and interpreted in Table 7.1.

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Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures

Figure 7.2: Stratigraphic column of the Pyrenean foreland basin fill. Nomenclature is given for the stratigraphy of the Jaca Basin (adapted from Remacha et al., 2003; Caja et al., 2010). Several correlation schemes for the Jaca turbidite systems with those of the Aínsa Basin have been proposed (e.g., Mutti, 1985; Das Gupta and Pickering, 2008; Caja et al., 2010; Clark et al., 2017).

7.5 Facies associations Correlation of bed packages, both down depositional dip and across strike, shows that they thicken and thin over hundreds to thousands of meters, passing from thick- bedded sandstones into fine-grained, thin-bedded heterolithic intervals. They have lobate geometries similar to those reported from basins where lobes are identified (Prélat et al., 2009; Grundvåg et al., 2014; Marini et al., 2015). Beds within lobes exhibit broadly tabular geometries on a tens to hundreds of meters scale where observed in outcrop, with localized decimeter- to meter-scale scouring. Between lobes, fine-grained and thin-bedded packages can be traced laterally over hundreds to thousands of meters between outcrops. These

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Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures packages are interpreted as either the distal lobe fringes of adjacent lobes, or as interlobe intervals related to reduced sediment supply to the basin (e.g., Prélat et al., 2009).

Figure 7.3: Satellite imagery of the field area. Proximal (B), distal (C) and medial (Acín; see part A) localities are shown. Transects W, X, Y, and Z are illustrated in Figs. 7.9, 7.12, and 7.13.

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Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin-floor depositional architectures Table 7:1: Summary of lithofacies observed in the study area.

Facies Lithology Sedimentology Thickness Interpretation (m) Structureless Very fine- to medium- Typically structureless and frequently 0.05 – 0.5 Rapid aggradation from a high- sandstone grained sandstone, rare normally graded or coarse-tail graded. concentration flow (Lowe, 1982; Mutti, coarse-grained Occasional mudstone chips occur, 1992; Kneller and Branney, 1995). sandstone. Siltstone caps typically in fine- to coarse-grained are infrequently present sandstone beds. Nummulites are in distal localities but are infrequently observed. not present in proximal localities.

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Stepped- Medium- to coarse- Laminated sandstone, laminae are 5 – 15 0.1 – 0.5 Repeated collapse of traction carpets planar- grained sandstone. mm thick, parallel to sub parallel and below a high-concentration turbidity laminated typically coarser grained than surrounding current (Talling et al., 2012; Cartigny et sandstone sandstone. Coarser laminae are typically al., 2013). inversely graded. Planar- Very fine- to medium- Laminated sandstone with µm – mm scale 0.04 – 0.5 Layer-by-layer deposition from repeated laminated grained sandstone. alternating coarser – finer laminae. development and collapse of near-bed sandstone Laminae are typically parallel, rarely sub traction carpets (Sumner et al., 2008) and parallel. Common coarse-tail grading. migration of low-amplitude bed waves Infrequent occurrence of plant fragments (Best and Bridge, 1992; Sumner et al., and mudstone chips aligned with laminae. 2008).

Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin-floor depositional architectures Ripple- Very fine- to fine- Ripple cross lamination, typically located 0.02 – 0.1 Tractional reworking beneath a dilute, laminated grained sandstone, rarely in the upper parts of the bed. Climbing slow-moving flow (Allen, 1982; sandstone medium-grained ripples locally observed. Commonly Southard, 1991). sandstone and coarse produces wavy bed tops. siltstone. Convolute Very fine- to fine- Deformed, folded, and overturned ripple 0.02 – 0.1 Liquefaction due to loading of overlying ripple cross grained sandstone. cross lamination. sediment (Allen, 1982), or shear stresses laminations caused by subsequent flow (Allen, 1982; McClelland et al., 2011; Tinterri et al., 2016). Hummock- Very fine- to fine- Decimeter- to meter-wavelength 0.02 – 0.15 Reworking of initial deposit of a bipartite

176 type bedforms grained sandstone. undulating bedforms. Typically consist of flow by a bypassing flow component smaller-scale wavy, convolute or ripple (Mutti, 1992; Tinterri et al., 2017), or cross-lamination. reworking of initial flow deposits by internal bores within a deflected flow (Pickering and Hiscott, 1985; Remacha et al., 2005). Argillaceous Poorly sorted, claystone- Beds have higher mud contents in the 0.05 – 0.3 Transitional flow deposit (Sylvester and sandstone and siltstone-rich matrix compared to relatively clean Lowe, 2004; Baas et al., 2009; Sumner et sandstone. sandstone beds. Infrequently contain al., 2009; Kane and Pontén, 2012). spheroidal or folded sandstone and mm- scale mudstone blebs. Where two argillaceous sandstones overlie each other,

Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin-floor depositional architectures delamination and shearing structures are sometimes observed. Poorly sorted Siltstone- and Commonly graded into mudstone; 0.05 – 3.2 Clast-rich, poorly sorted, matrix- mudstone sandstone-rich claystone however, infrequent non-graded, sharp- supported beds are suggestive of en-masse topped examples occur. Mudstone and deposition from laminar flows (e.g. siltstone clasts, and mudstone-armoured Nardin et al., 1979; Iverson, 1997; Sohn, Nummulites are frequently present. Clasts 2000). Beds which exhibit grading are are commonly present as sub rounded likely to have retained some level of balls or as plastically deformed layers. turbulence within the flow; and are Infrequent disaggregated and sheared therefore interpreted to have deposited layers are observed. Where overlying from a transitional-flow regime (Baas et

177 argillaceous sandstone, delamination and al., 2009; Sumner et al., 2012; Baas et al., shearing structures are sometimes 2013). observed. Carbonate- Carbonate-rich siltstone. Distinctive off-white colour. Exhibits a 0.02 – 0.3 Fine-grained carbonate hydraulically rich siltstone Rare carbonate-rich gradational base where overlying graded fractionated from siliciclastics, deposited mudstone. mudstones, but is often sharp where from dilute remnants of the flow overlying argillaceous sandstone. (Remacha and Fernández, 2003). Generally homogeneous texture. Matrix- Poorly sorted, clast-rich Clasts include: cm – m scale sandstone 0.2 – 25 “Freezing” of a flow with yield strength, supported matrix consisting of balls, m – 10s m scale sandstone rafts, dm i.e., a debris flow (e.g., Iverson et al., chaotic sandstone, siltstone and – m scale mudstone rafts. Sandstone rafts 2010). deposits mudstone. are frequently found at the top of the

Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin-floor depositional architectures beds. Mudstone Silt-rich mudstone Massive to weakly laminated. 0.01 – 2.5 Background sedimentation or deposition from a dilute flow.

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Figure 7.4: Bed-scale facies deposited from turbidity currents, typically, but not exclusivey identified in proximal and medial localities (Fig. 7.3). A) Thin-bedded sandstone with planar lamination at the base and ripple cross laminae towards the top. Identified basin-wide. B) Stepped planar laminae observed at the most proximal location, Fanlo 2. C) Planar-laminated fine-grained sandstone; D) structureless medium- grained sandstone with mudstone clasts. E) Coarse-grained lag on the upper surface of a scour. There is a grain-size break from relatively clean upper-fine sandstone to coarse and very coarse sandstone with abundant millimeter- and centimeter-scale mudstone clasts. F) Mudstone-draped scour observed at Fanlo 2.

Thick-bedded sandstones

Description

Thick-bedded sandstone facies form 1–5-m thick amalgamated packages comprising thick-bedded (> 0.3 m thick) structureless sandstones (Fig. 7.4D), and less- common planar-laminated sandstones (Fig. 7.4B, C). They are fine- to medium-grained and can be normally graded or ungraded. Mudstone clasts are frequently observed along amalgamation surfaces and near bed bases (Fig. 7.4C). Millimeter-scale lamination and 179

Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures centimeter- to decimeter-scale low-angle cross-lamination is observed at southeastern localities (Fig. 7.4B).

Interpretation

Structureless turbidite beds, and those with millimeter-scale lamination, are interpreted to represent deposition from high-concentration turbidity currents with relatively high rates of aggradation, preventing the development of tractional sedimentary structures (e.g., Kneller and Branney, 1995; Sumner et al., 2008; Talling et al., 2012). Common amalgamation, and entrainment of mudstone clasts in thick-bedded sandstones, indicates that the parent flows were highly energetic, and capable of eroding and entraining, and bypassing sediment during the passage of the flow (e.g., Lowe, 1982; Mutti, 1992; Kneller and Branney, 1995; Gladstone et al., 2002; Talling et al., 2012; Stevenson et al., 2014b; Stevenson et al., 2015). Thick-bedded sandstone-prone packages are therefore interpreted to represent lobe-axis environments (Walker, 1978; Gardner et al., 2003; Prélat et al., 2009; Grundvåg et al., 2014; Marini et al., 2015; Kane et al., 2017).

Medium-bedded sandstones

Description

Infrequently amalgamated 0.1–0.3-m-thick fine- to very fine-grained sandstones which typically have flat to subtly incisional bed bases. Planar lamination is common, particularly in the upper halves of the beds (Fig. 7.4C), whereas structureless sandstones are infrequently observed. Ripple cross-lamination and wavy-topped beds are common where normal grading at bed tops is present. Bed tops are usually sharp, but locally grade into fine siltstone.

Interpretation

Structured sandstones represent deposition and reworking by low-concentration turbidity currents, whilst structureless sandstones represent deposition from high- concentration turbidity currents. The mixture and preservation of both high- and low- concentration turbidity current deposits suggests a less-axial location of deposition compared to thick-bedded sandstones. Amalgamated structured sandstones with planar lamination and ripple cross-lamination have been interpreted to be associated with off-axis lobe environments, deposited by decelerating turbidity currents (Prélat et al., 2009; Marini

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Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures et al., 2015; Spychala et al., 2017c). Therefore, medium-bedded sandstone-prone packages are interpreted to represent lobe off-axis environments.

Thin-bedded sandstones

Description

Thin-bedded, fine- to very fine-grained sandstone beds (< 10 cm thick) are normally graded and occur interbedded with fine siltstones. Ripple cross-lamination and wavy-laminated bed tops are dominant, whereas planar lamination is less common (Fig. 7.4A). Typically, beds have a sharp decrease in grain-size from a lower sandstone to overlying silt-rich mudstone. Packages of thin-bedded sandstones are identified on a centimeter- to decimeter-scale within thicker-bedded packages, but are also identified as meter- to decameter-scale packages between thicker-bedded packages.

Interpretation

Thin-bedded, structured sandstones are interpreted to be deposited from low- concentration turbidity currents (Mutti, 1992; Jobe et al., 2012; Talling et al., 2012). Wavy bedforms are interpreted to form due to later flows filling the topography of previous ripple deposits (e.g., Jobe et al., 2012). The observations are consistent with facies of lobe- fringe settings (e.g., Mutti, 1977; Prélat et al., 2009; Marini et al., 2015; Spychala et al., 2017b), and similar to the facies near Linás de Broto and Yésero (Fig. 7.3B) described and interpreted in the same way (Mutti, 1977).

Hybrid beds

Description

Hybrid beds (Fig. 7.5) are 0.1-3.2 m thick and are described within an idealized vertical facies scheme consisting of six divisions. Division 1 (D1) Basal, relatively clean sandstone or coarse-grained siltstone that is typically structureless, with rare planar laminae; D2) A sharp contact to a rippled and/or wavy sandstone, which is typically clean, but is locally argillaceous; D3) A poorly sorted, matrix-supported argillaceous sandstone (see Table 7.1); D4) A poorly sorted mudstone division (see Table 7.1). The contact to the underlying argillaceous sandstone can be abrupt or graded (Fig. 7.5); D5) A gradational or abrupt contact to a silt-rich mudstone division, which can be up to 1.5 m thick; D6) A sharp to gradational contact to a white, normally graded carbonate-rich siltstone to

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Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures claystone (see Table 7.1). The above represents an idealized sequence, and in an individual bed one or more of D2 – D6 may be absent.

Interpretation

Hybrid beds have been interpreted as the deposits of flows transitional between turbulent and cohesive rheologies (e.g., Haughton et al., 2003; Talling et al., 2004; Haughton et al., 2009; Hodgson, 2009; Baas et al., 2011; Kane and Pontén, 2012; Kane et al., 2017; Southern et al., 2017; Pierce et al., 2018). The vertical assemblage of facies in hybrid beds here indicates temporal flow evolution from 1) high- or low-concentration turbulent; to 2) transitional and/or laminar; to 3) low-concentration turbulent flow regimes. Structureless and planar-laminated sandstones in D1 are interpreted to have been deposited by high- to low-concentration turbidity currents (Table 7.1). The ripple cross-laminated D2 indicates a flow with a turbulent component able to tractionally rework the bed. The sharp contact between D1 and D2 suggests that there was a hiatus in deposition. D3 and D4 were deposited by cohesive flows, representing the longitudinal transformation of the flow from turbulent to cohesive. D5 and D6 were likely deposited by a dilute turbidity current (e.g., Remacha et al., 2005), or as a result of suspension settling (Mutti, 1977; Remacha et al., 2005). The common grading of D4 into D5 suggests that the flow became more dilute at a fixed locality through time.

Beds with repeated, poorly sorted, deformed, clast-rich layers have also been attributed to cyclical bores in deflected flows depositing alternate relatively clean and muddier liquefied sand (Pickering and Hiscott, 1985; Remacha and Fernández, 2003; Remacha et al., 2005; Muzzi Magalhaes and Tinterri, 2010; Tinterri and Muzzi Magalhaes, 2011). In these process models, clean sandstones are attributed to weaker bores whereas liquefied sandstones are attributed to stronger bores. Massive divisions which are relatively clast-poor (e.g., D3), or with plastically deformed clasts are interpreted to form through cyclical wave loading and shearing caused by trains of strong internal waves (Remacha et al., 2005; Muzzi Magalhaes and Tinterri, 2010).

Deflected-flow facies

Description

Hummock-type bedforms are identified in distal localities, and exhibit convex-up low-angle laminae. However, thickening and thinning of laminae observed in hummocky cross-stratification (Harms et al., 1975) are not clearly observed here (Fig. 7.6C). 182

Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures Hummock-type bedforms can form a large proportion of an individual bed’s thickness (Fig. 7.6A, 7.6C), or can occur as a discrete upper division of a bed. Typically, beds with hummock-type bedforms comprise a lower, structureless division overlain by an upper, structured division and exhibit lenticular geometries, with amplitudes of 2–15 cm. Hummock-type bedforms have larger wavelengths (decimeter- to meter-scale) and amplitudes (up to 15 cm) than wavy bed tops, typically by up to an order of magnitude (Table 7.1).

Centimeter-scale convolute lamination (Fig. 7.6B) is rarely observed in proximal and medial localities (e.g., Fanlo 1), but is more common in distal localities where it is associated with hummock-type bedforms (e.g., Hecho N).

Figure 7.5: Selected hybrid-bed facies demonstrating the range of bed types observed. A) Thin hybrid bed with a thin siltstone basal division, overlain by a sharp break to D3 which has a sharp upper surface to 183

Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures D6. B) Hybrid bed with lower structureless sandstone with a ripple-cross-laminated top, overlain by a poorly sorted D3 and D4 which normally-grade upwards into D5 and D6. C) Lower structureless sandstone with a sharp upper contact with argillaceous sandstone D3. There is a sharp, sheared boundary between D3 and D4. D4 is gradational into D5 and D6. D) Outsized hybrid bed (Bed 2; Fig. 7.10). The basal 5 cm consists of a lag of very coarse-grained sandstone clasts, armored mudstone chips, and Foraminifera. Overlying is a poorly sorted division which fines gradationally upwards into D5 and D6. E) Inset of (part C) illustrating the sharp, sheared boundary between D3 and D4 with entrianment of clasts from D3. F) Example of D3 containing clasts of underlying D1.

Figure 7.6: Deflected flow deposits observed in the field area. A) Lenticular bedform observed at Hecho N (Fig. 7.3C). B) Convolute lamination observed at Acín (Fig. 7.3A). C) Hummock-type bedform observed at Hecho N.

Interpretation

Hummock-type bedforms have been identified in confined basins, and are interpreted to form as a result of flow deflection and reflection from a confining margin (Pickering and Hiscott, 1985; Remacha et al., 2005; Tinterri, 2011; Tinterri et al., 2017). Convolute lamination can form as a result of loading (Allen, 1982), or from shear stresses 184

Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures imparted on unconsolidated sediment by a later flow (Allen, 1982; McClelland et al., 2011; Tinterri et al., 2016). Development of both hummock-type bedforms and convolute laminae suggests that the bedforms developed through flow reworking of an unconsolidated bed, commonly observed in confined basins (e.g., Pickering and Hiscott, 1985; Tinterri et al., 2016), as opposed to loading.

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Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures Draped scour surfaces and coarse-grained lag deposits

Description

Scour surfaces observed in the field area range from decimeter- to meter-scale in depth and width (Fig. 7.4F). Scours are recognized in the southeast of the field area around Broto (Fig. 7.3), and decrease in scale and frequency to the northwest. The nature of the scour fills is variable, including mudstone (Fig. 7.4F), poorly sorted mudstone to coarse- grained sandstone, and thin beds. Commonly, scour surfaces are mantled with coarse- grained lags (Fig. 7.4E), particularly in thick-bedded packages. Locally, coarse-grained lags are identified as an abrupt grain-size increase near bed tops. Coarse-grained lag deposits are identified predominantly in the southeast of the field area around Sarvisé and Broto (Figs. 7.3, 7.4E).

Interpretation

Coarse-grained lag deposits and draped scour surfaces are interpreted as indicators of sediment bypass (e.g., Mutti and Normark, 1987; Mutti, 1992; Elliott, 2000; Gardner et al., 2003; Beaubouef, 2004; Kane et al., 2010; Stevenson et al., 2015). The presence of numerous lags and draped scour surfaces in the southeast suggests significant amounts of sediment transport and bypass through the proximal field area, to more distal localities in the northwest.

Debrites

Description

Two 0.3–25-m thick, poorly sorted units are identified in the southeast of the field area (Figs. 7.7, 7.8). The units consist of a poorly sorted sheared matrix consisting of: clay-, silt- and sand-grade material; Nummulites shells; sandstone “balls” (tens of centimeters in diameter) (Fig. 7.7); and rafts of turbidite beds 1 meter – tens of meters thick (Figs. 7.7, 7.8). Local entrainment of substrate into the units is observed (Fig. 7.7). The upper surfaces of these chaotic units locally undulate, with overlying beds onlapping on a decimeter to meter scale. In other locations, units have a comparatively flat top with relatively tabular sandstones overlying them.

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Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures Interpretation

Event beds with a mud-rich, poorly sorted, sheared matrix coupled with scattered clasts of varying sizes are characteristic of “en masse” emplacement by a debris flow; these beds are termed debris-flow deposits, or debrites (e.g., Nardin et al., 1979; Iverson, 1997; Talling et al., 2012). Decimeter- to meter-scale depositional relief above the debrites impacted routing of subsequent turbidity currents, with denser parts of flows depositing and onlapping the relief, whereas less-dense parts of the flows bypassed down-dip into the basin (e.g., Pickering and Corregidor, 2000; Armitage et al., 2009; Kneller et al., 2016).

Figure 7.7: Contact of Db-1 with substrate near the Yésero locality (Fig. 7.3). Local entrainment of substrate appears to occur through a stepped delamination process similar to that described in turbidites and hybrid beds (Butler and Tavarnelli, 2006; Eggenhuisen et al., 2011; Fonnesu et al., 2016).

Megabeds

Description

The MT-4 marker bed (Fig. 7.2) comprises a tripartite structure in the field area (Figs. 7.8 and 7.10), from base to top: 1) a debritic division; 2) a calcareous, graded sandstone division; and 3) a mudstone division. The debritic division is matrix supported, which consists of poorly sorted mudstone, siltstone, and sandstone, with infrequent Nummulite shells. Clasts in the debritic division vary from millimeter to meter scale. Clast shape is variable: sandstone and limestone cobbles are up to 20 cm in diameter; contorted mudstone rafts can be meters in length; rafts of sandstone and limestone (rich in shallow- marine foraminifera) can be up to several meters in length, and are often folded and 187

Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures sheared. Clast size decreases over tens of kilometers from northwest to southeast, where the debritic division pinches out (Fig. 7.10). The calcareous-sandstone division has a sharp erosional base, and consists of multiple amalgamated beds that form an overall normal grading from very coarse to very fine sandstone. The transition from the calcareous sandstone into the mudstone division is normally graded over approximately 0.3 – 0.8 m.

Figure 7.8: The El Chate Cliff section.A, B) Overview of the proximal stratigraphy in cliffs adjacent to the Fanlo 1 locality (Barranco El Chate Cliffs; Fig. 7.3). Several of the described sandstone lobes are observed (numbered), along with three marker beds (Db 1, Db 2, and MT-4). C) The transition of Lobe 6 from bypass-dominated features to deposition-dominated features is observed in the cliffs, potentially forming a sand-detached lobe (at least in two-dimensions). D) Line drawing of part C. 188

Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures Interpretation

Thick beds with this character have been termed “megabeds”. Megabeds in the Jaca Basin have been interpreted as “megaturbidites”, or “megabreccias” (Puigdefàbregas et al., 1975; Rupke, 1976; Johns et al., 1981; Labaume et al., 1987; Rosell and Wiezorek, 1989; Mutti, 1992; Payros et al., 1999); however, the term megaturbidite implies a singular transport process, which is misleading (e.g., Bouma, 1987). Therefore, herein the term “megabed” will be used. Megabeds in the Jaca Basin are traditionally thought to be deposited by bipartite gravity flows consisting of: 1) a basal grain flow or debris flow; and 2) an upper, turbulent flow (Rupke, 1976; Labaume et al., 1983; Puigdefàbregas, 1986; Rosell and Wiezorek, 1989; Mutti et al., 1999; Payros et al., 1999). Megabeds have been also interpreted to be similar to hybrid beds as they contain divisions deposited by both laminar and turbulent flows (Haughton et al., 2009; Fallgatter et al., 2016). The lateral facies changes observed (see also Rupke, 1976; Johns et al., 1981; Labaume et al., 1987; Rosell and Wiezorek, 1989; Payros et al., 1999) imply that the relative importance of particular depositional processes varies across the basin, notably an increase in the thickness of the turbidite division with respect to the basal debrite division towards the southeast. This may show the ability of the turbidity current to more easily surmount topography, compared to debris flows, and flow farther up the regional dip-slope into proximal parts of the basin relative to the clastic system (e.g., Muck and Underwood, 1990; Al Ja’aidi, 2000; Al Ja’aidi et al., 2004; Bakke et al., 2013). The distinctive facies of MT-4, and the ability to map it reliably over 70 km southeast to northwest, make it a marker bed that is confidently used to correlate turbidite packages between outcrops.

7.6 Paleocurrents Throughout the field area, sole structures indicate paleoflow to the northwest, which is consistent with published data (Figs. 7.9A, B; Rupke, 1976; Mutti, 1977; Mutti, 1992; Remacha and Fernández, 2003), and defines the approximate direction of depositional dip. Ripple cross-lamination is rare in proximal localities; where present it occurs on bed tops and indicates paleoflow to the northwest. In distal localities, ripple crests occur on the upper surfaces of D1 of hybrid beds and indicate paleoflow to the north (Figs. 7.9A and 7.9B), which is also consistent with previous studies (Remacha and Fernández, 2003; Remacha et al., 2005).

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Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures

Figure 7.9: Paleocurrents and evidence for flow deflection. A) Paleocurrent data collected in the field area. Proximal data are collected from flutes, grooves, and ripple crests which are consistent in trend and are grouped together (n = 57). Medial and distal localities are segregated by paleocurrent indicator. Data show that flute and groove marks (n = 103) diverge from ripple cross-lamination (n=6) directions in medial and distal locations. Flutes and grooves formed at the bed bases, whereas ripple cross-lamination formed on bed tops, suggesting that the initial and later stages of the flows had divergent paleoflow directions. Refer to Figure 1 for key to stratigraphy; map modfied from Remacha et al., (2003). B) Example of a single bed with divergent paleocurrent indicators at the bed base and bed top. This suggests that the initial flow was to the northwest, while a later, deflected flow component was to the north.

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Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures

Figure 7.10: Down-depositional-dip-oriented correlation panel from proximal to distal (right to left); note changes in horizontal scale. Log locations are shown in Fig. 7.3. Logs are tied to the basin-wide MT-4 marker bed. There is an overall fining and thinning at both bed scale and lobe scale between Fanlo 2 and Yésero 2. Lobes Ac1-4 at Acín are thicker bedded and coarser than at Yésero and Linás de Broto, suggesting that the flows which deposited these lobes bypassed the proximal area of the system. Beds in distal 191

Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures localities (west of Acín) do not form well-developed lobes. Lobe 4 is not observed in the panel as it pinches out to the north of Fanlo 1.

7.7 Facies variability and geometry

Proximal localities

Proximal facies variability and package geometries are documented in a depositional-dip-oriented correlation panel (W–W`; Fig. 7.10) and two strike-oriented correlation panels (X-X` Figs. 7.3B, 7.11; 1.25 and 2 km long; minimum distance due to shortening). At least six sandstone-prone lobes separated by fine-grained and/or thin- bedded packages are identified in the proximal area of the basin between Fanlo 2 and Yésero; Lobes 1 – 6 (Figs. 7.10, 7.11).

Lobe 1 immediately overlies Db-1 and is 2.5 – 6 m thick, (Figs. 7.8, 7.10, 7.11). Lobe 1 comprises thick-bedded sandstones in southeastern sections at Fanlo 2 and Fanlo 1 (Fig. 7.3). Eleven kilometers down-dip to the northwest, Lobe 1 transitions to medium- bedded sandstone facies at Linás de Broto, and to thin-bedded facies 3.5 km farther down- dip at Yésero 2 (Fig. 7.10). Lobe 1 is sandstone-prone and is of broadly consistent thickness at all localities, even with variable underlying topography created by Db-1. Onlap at a decimeter to meter scale is locally present and is typically associated with large clasts in the underlying Db-1 (Fig. 7.8).

Lobe 2 is 0.5 – 3 m thick and comprises thick-bedded sandstone facies at Fanlo 2 and Fanlo 1 and transitions to thin-bedded facies at Linás de Broto (Fig. 7.3). Across depositional strike, Lobe 2 scours into Lobe 1 and intervening thin beds at Fanlo Track (Fig. 7.11). Farther north, Lobe 2 thins and fines northward, and pinches out between A Lecina and El Bano (Fig. 7.11).

Lobe 3 thickens from 2.25 m of thick-bedded sandstone facies at Fanlo 2 to 4.25 m at Fanlo 1, with a concomitant increase in thin- and medium-bedded facies. Lobe 3 then thins northwest to Linás de Broto (Fig. 7.10). North of Fanlo 1, across depositional strike, Lobe 3 thins to 3 m of medium-bedded sandstone facies at Fanlo Track before pinching out between A Lecina and El Bano (Fig. 7.11).

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Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures

Figure 7.11: Stratigraphic interpretations of proximal lobes and geometry of Lobe 6. Lobes exhibit lateral facies changes on a kilometer scale. Lobe 6 is not observed at Fanlo 1, whereas it is observed to the north and south at Fanlo Track and El Chate Cliffs (Fig. 7.8) respectively. The stratigraphy can be walked 1.5 km to the west to Barranco El Chate, where Lobe 6 is 9 m thick.

Lobe 4 is best exposed at El Bano (Figs. 7.3, 7.11) where it comprises 4 m of medium- and thin-bedded sandstone facies. The lobe thins and fines to the south at A Lecina before pinching out south of Fanlo Track (Figs. 7.3, 7.11), and as such is not recorded in Figures 8 and 10. The thinning of Lobe 4 to the south, and its distribution of facies associations, suggest that its main depocenter lay to the north of El Bano (Figs. 7.3, 7.11).

Lobe 5 is subdivided into Lobe 5a and 5b in the El Chate cliff section (Fig. 7.8), where a thin-bedded package separates them; the two packages are grouped together elsewhere due to challenges in differentiating them at several locations. At Fanlo 2, Lobe 5 is a 9.5-m-thick package of thick-bedded sandstones intercalated with medium- and thin- 193

Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures bedded sandstones (Figs. 7.8, 7.10). Lobe 5 is 10.25 m thick at Fanlo 1. Lobe 5a is 4 m thick and consists of thick-bedded sandstone facies. Lobe 5b is 6.25 m thick and consists of medium- and thin-bedded sandstone facies. Lobe 5 thins to 3 m down-dip at Linás de Broto (Figs. 7.3, 7.10). Across strike to the north of Fanlo 1, Lobe 5 thins and fines laterally into a thin-bedded interval at Fanlo Track (Figs. 7.3, 7.11), and is no longer observed in A Lecina (Fig. 7.11).

Lobe 6 stratigraphically underlies MT-4, and is best exposed in the cliffs of the Barranco El Chate valley (Figs. 7.3, 7.8, 7.11). There, Lobe 6 abruptly thickens from a < 1- m-thick thin-bedded package at El Chate Cliffs (Figs. 7.8D, 7.11) into a 9-m-thick, thick- bedded sandstone package at Barranco El Chate 1 km to the west (Fig. 7.11). The Lobe 6 package consists of thick- and medium-bedded sandstones at Fanlo Track, A Lecina, and El Bano (Fig. 7.11). Across depositional-strike from Barranco El Chate, Lobe 6 thins to ∼ 3 m of thin-bedded sandstone northwards at Buesa (Fig. 7.11). Physical correlation to Linás de Broto and Yésero (1 and 2) is not possible; however, Lobe 6 is represented by one of the thin-bedded intervals immediately below MT-4. The base of Lobe 6 is typically scoured in the El Chate cliffs (Fig. 7.8), and the Barranco El Chate and Fanlo Track logged sections. Lobe 6 does not crop out at Fanlo 1 (Figs. 7.8, 7.11).

The distinctive scoured base to Lobe 6 is present to the south, north, and west of Fanlo 1 (Fig. 7.8), which implies that this locality represents a fine-grained sediment bypass-dominated zone (e.g., Stevenson et al., 2015). An alternative explanation is that Lobe 6 shows a lateral facies change to a thin-bedded, fine-grained package at Fanlo 1. However, this is not preferred as the facies would have to transition from relatively thick- bedded to thin-bedded and back to thick-bedded (El Chate Cliffs to Fanlo 1 to Fanlo Track), which is not commonly observed in lobes over short distances. The across-strike geometry of the resultant deposit from the El Chate Cliffs to Fanlo Track implies the updip part of the lobe has a “finger-like” geometry akin to those described from distal fringe deposits (e.g., Groenenberg et al., 2010).

Medial localities

Medial localities are typified by the Acín locality, approximately 20 km down-dip of the Yésero 2 locality (Figs. 7.3, 7.10). MT-4 constrains the stratigraphy, and in the absence of evidence of significant erosion, indicates that the deposits here are quasi- contemporaneous with those in proximal localities (Fanlo 2 to Yésero, Fig. 7.3). Four sharp-based and sharp-topped sandstone-prone packages in the section (Ac1-4; 4-7 m 194

Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures thick), which comprise thick-, medium- and thin-bedded sandstones, separated by tens of centimeters- to meter-scale thin-bedded or mudstone-prone intervals (Fig. 7.10), are interpreted as lobes. Bed types are dominated by high- and low-concentration turbidity current deposits; hybrid beds make up only 2% of beds (Fig. 7.12A). The Ac1-4 sandstone lobes are generally thicker, thicker-bedded, and coarser-grained than the sandstone lobes observed up-dip at the Linás de Broto and Yésero 2 localities.

Figure 7.12: Graphs illustrating the spatial variability of hybrid-bed abundance and proportional thickness: A) Down-dip from proximal localities to distal localities. B) Across strike in distal localities.

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Figure 7.13: Across-strike architectural panels at the distal locations of Ansó and Hecho (Fig. 7.3): A) The Ansó strike panel (A) is tied to the mudstone cap of MT-4. Tentative individual bed correlations are indicated by dotted lines. B) The Hecho panel is tied to the base of MT-4 as the top of the unit is difficult

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Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures to access. Individual bed correlations are challenging to make due to the disparity in facies between the two outcrops over relatively short distances.

Distal localities

Four sections were logged in a down-dip transect between the villages of Aragüés del Puerto and Ansó, and two in across-strike positions at Ansó and Hecho (Figs. 7.3, 7.10, 7.13). The studied stratigraphy, previously described in Remacha and Fernández, (2003), is correlated using the MT-4 megabed. The proportion and cumulative thickness of hybrid beds increases abruptly from Acín to Aragüés del Puerto (Figs. 7.10, 7.12A; see also Remacha and Fernández, 2003), but decreases northwards from Hecho South to Hecho North over 1 km (Figs. 7.3, 7.12B, 7.13). Sandstone bed thicknesses and grain-size do not change significantly from proximal areas (see also Remacha et al., 2005). However, total bed thicknesses do increase as D3 and D4 are developed in distal localities, and mudstone caps are also thicker (see also Remacha et al., 2005). Hummock-type bedforms and convolute ripple cross-laminae are identified in distal localities, in both turbidites and hybrid beds (Fig. 7.6).

Typically, beds and packages of beds (of similar thicknesses and facies) show significant changes in bed thickness, grain-size, and sedimentary textures on a kilometer scale between localities and are challenging to correlate (Figs. 7.10, 7.13). Hybrid beds can be highly variable in character over hundreds of meters (e.g., Fonnesu et al., 2015); therefore caution is needed when correlating beds based on facies alone. Only Beds 1 (3.2 m thick), 2 (3 m thick), and 3 (1.2 m thick) are tentatively correlated between localities in a down-dip direction (Fig. 7.10). There is ∼ 3 m of relatively thin-bedded stratigraphy between beds 1 and 2, which is consistent between localities in a down-dip orientation. However, Beds 1 and 2 are less correlatable across strike on a hundreds- to thousands of meters-scale (Fig. 7.13). There is a general northward bed-thinning over 400 m at Ansó, whereas from Hecho South to Hecho North (∼ 1 km) Beds 1-3 appear less distinctive (Figs. 7.3, 7.13). The proportion of hybrid beds also decreases and D6 is less common, indicating major bed-scale variability over relatively short distances (although potentially tectonically shortened by ∼ 30%; Teixell and García-Sansegundo, 1995).

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Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures 7.8 Discussion

Process transformations and products of flow deflection

Evidence and origin of flow deflection

Documented paleocurrent trends suggest variability in flow direction during single events (Fig. 7.9A, B). The consistent west and northwest orientation of sole structures indicates the primary direction of the lower (earlier) flow-components. By contrast, the ripple cross-lamination suggests that the upper (later), deflected flow-components flowed northwards. This suggests that the primary and deflected parts of the flows were divergent (see also Remacha et al., 2003; Remacha et al., 2005). Paleogeographic reconstructions of the Jaca Basin suggest a narrowing of the basin westward of Jaca, which is attributed to the development of axial thrust sheets and the influence of the Pamplona Fault that separated the Jaca Basin from the Basque Basin to the northwest (e.g., Mutti, 1985; Puigdefàbregas and Souquet, 1986; Puigdefàbregas et al., 1992; Payros et al., 1999; Remacha and Fernández, 2003). Distal narrowing of the basin likely caused an increase in flow interactions with basin-margin slopes. Higher-concentration parts of flows were strongly confined and “steered” by basinal topography (e.g., Muck and Underwood, 1990; Al Ja’aidi, 2000; McCaffrey and Kneller, 2001; Sinclair and Tomasso, 2002; Amy et al., 2004; Bakke et al., 2013; Stevenson et al., 2014a; Spychala et al., 2017c). In contrast, the upper, more dilute, parts of the flow were able to run up confining slopes and be deflected back into the basin to produce paleocurrent indicators divergent from those formed by the basal flow components (e.g., Pickering and Hiscott, 1985; Kneller et al., 1991; Kneller and McCaffrey, 1999; McCaffrey and Kneller, 2001; Hodgson and Haughton 2004; Remacha et al., 2005; Tinterri et al., 2017).

Generation of hybrid beds through flow deflection

Hybrid beds have been recognized in a wide range of deep-water sub- environments, and attributed to a variety of depositional processes (e.g., Talling et al., 2004; Baas et al., 2009; Haughton et al., 2009; Hodgson, 2009; Patacci and Haughton, 2014; Hovikoski et al., 2016; Tinterri et al., 2016; Kane et al., 2017). Here, poorly sorted divisions (D3 and D4) are interpreted to have been deposited from predominantly cohesive flows. Common sharp boundaries between different divisions (Fig. 7.5) imply rheological contrasts in the parent flows (Kane and Pontén, 2012). Instabilities in the flow, which imparted changes in velocity, sediment concentration, and fall-out rate, may have been 198

Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures caused by internal waves in the deflected flow (Patacci et al., 2015). Variations in flow concentration and velocity of deflected flows (e.g., Kneller et al., 1991) are likely to promote transitional flow behavior (e.g., Baas et al., 2009). Disaggregated and folded layers of clasts in D3 and D4 (Fig. 7.5) are interpreted to have been deposited from a flow transitional between turbulent and laminar flow regimes (Fig. 7.14B; sensu Baas et al., 2011). Clasts of lithology similar to that of underlying divisions are interpreted to have been eroded or entrained into an overriding laminar flow (Fig. 7.14B; see also Baas et al., 2011). Turbulent flow conditions are interpreted to have promoted deposition of relatively clean silts and sands, which were then entrained and carried in laminar flows (Fig. 7.14B).

Bores in a deflected flow are attributed to the formation of hummock-type bedforms (Pickering and Hiscott, 1985; Remacha et al., 2005; Tinterri et al., 2017), and convolute lamination (Tinterri et al., 2016). The lateral juxtaposition of convolute lamination, hummock-type bedforms, crudely laminated liquefied divisions, and hybrid beds has been interpreted as a continuum of facies formed due to flow deflection (Muzzi Magalhaes and Tinterri, 2010; Tinterri and Tagliaferri, 2015; Tinterri et al., 2016). Hybrid beds deposited from this process response are tripartite, including an overlying laminated division, and are interpreted to form due to flow deceleration against a slope (e.g., Tinterri et al., 2016). Here, the absence of crudely laminated liquefied divisions, and laminated divisions that overlie the poorly sorted divisions (i.e., D3 and D4) suggest that hybrid beds formed from the collapse and deflection of an individual flow, which transformed from turbulent to cohesive.

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Figure 7.14: Model to explain the facies, structures, and paleocurrents observed: A) Deflected flows with differing rheological properties rework and/or shear previous deposits. The initial deflected, turbulent, flow rework the bed top (2) of the non-deflected flow deposit (1) and is followed by deflected flows which entrained slope substrate, becoming cohesive (3). Later parts of the flow are more dilute and carbonate-rich (4). B) Schematic reconstruction of the depostion of a characteristic bed by a flow transitional between turbulent (TF) and laminar (LF) flow regimes.

Beds in confined basins with poorly sorted divisions featuring thin layers of siltstone or sandstone, and/or clasts, which may be present as folded or disaggregated layers, or dispersed through the bed, have also been interpreted to form through liquefaction of beds caused by flow deflection (Pickering and Hiscott, 1985; Remacha and Fernández, 2003; Remacha et al., 2005; Muzzi Magalhaes and Tinterri, 2010). Post depositional reworking of the clean sandstone divisions (e.g., D1 and D2) by successive internal waves or “bores” have been interpreted to develop fining-upwards divisions of sandstone-mudstone couplets from a progressively waning flow (Pickering and Hiscott, 1985; Remacha et al., 2005; Muzzi Magalhaes and Tinterri, 2010). Liquefaction of beds is attributed to shearing caused by internal waves in the flow (Pickering and Hiscott, 1985; Remacha and Fernández, 2003; Remacha et al., 2005; Muzzi Magalhaes and Tinterri, 2010). This mechanism fails to explain the entrainment of lower divisions into upper divisions observed here (Figs. 7.5E, F), as liquefaction would promote loading into underlying sediment. Furthermore, the common sharp contacts between divisions (Figs. 7.5A, B, C, E) imply that no significant liquefaction took place. Trains of bores have also been invoked to explain beds with abrupt contacts between poorly sorted divisions and mudstone forming 200

Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures through obliteration of primary fabrics (Remacha et al., 2005; Muzzi Magalhaes and Tinterri, 2010). However, we consider this mechanism unlikely as: 1) the most dilute part of the flow would be associated with the strongest bores; 2) no further bores depositing sandstone-mudstone couplets could occur; and 3) thin hybrid beds (e.g., Fig. 5A), deposited from smaller-magnitude flows or the dilute lateral fringes of flows, would require strong bores to form in small or dilute flows. The observations are more adequately explained by deposition from cohesive flows.

Role of slope substrate entrainment

The increase in the proportion of hybrid beds from proximal to distal localities (Fig. 12), and evidence of flow deflection (Figs. 7.9A, B), indicate changes in flow behavior and basin physiography. Slope-substrate clasts have been observed in hybrid beds of the Gres d’Annot system (McCaffrey and Kneller, 2001); however, these have not been linked to flow transformation. Here, we suggest that hybrid beds were generated distally in the Jaca Basin by flows interacting with the southern carbonate slope (Fig. 7.14). This interpretation is underpinned by three lines of evidence:

1) Frontal and lateral lobe fringes in proximal and medial locations (Fig. 7.3) lack hybrid beds, whereas they become significantly more abundant to the northwest of Acín (Figs. 7.10, 7.12). This suggests that the location of flow transformation lay northwest (basinward) of Acín. In distal locations, the northward decrease in hybrid-bed prevalence and thickness, for example from Hecho South to Hecho North (Figs. 7.12B, 7.13), suggests a local control on the development of hybrid beds.

2) Here, a ripple- or wavy-laminated division (D2) is identified above D1 (Fig. 7.5), which is normally occupied by banded or muddy sandstone in conventional hybrid-bed models (e.g., Haughton et al., 2009). Ripple and hummock-type bedforms are indicative of flows that tractionally reworked the bed (e.g., Walker, 1967; Allen, 1982; Southard, 1991; Remacha et al., 2005; Sumner et al., 2008; Baas et al., 2009; Tinterri et al., 2016), suggesting that D2 is a product of a separate or later flow component (Fig. 7.14). The deposition of D2 before the deposition of D3 and D4 suggests the deflected flows were longitudinally segregated (Fig. 7.14), with a forerunning turbulent-flow component that reworked the D1 deposits. This was followed by deposition of laminar- or transitional-flow components that deposited D3 and D4.

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Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures 3) The presence of D6 (Fig. 7.5) is interpreted to reflect substrate entrainment from the carbonate-rich southern slope, which shares mineralogical and biogenic content with carbonate observed in D6 (Mutti et al., 1972; Cámara and Klimowitz, 1985; Remacha et al., 2005). An alternative explanation is that the carbonate enrichment of flows occurred across the basin, or that D6 represents a hemipelagic drape (Mutti et al., 1972; Rupke, 1976; Mutti, 1977). However, the absence of D6 in proximal and medial localities (Fig. 7.10) would require either: 1) D6 to be eroded by every subsequent flow; or 2) the flow responsible bypassed in these localities in every case, which we consider implausible. The more- common occurrence of D6 in hybrid beds compared to turbidites suggests that deflected flows entrained carbonate-mud substrate, whereas a hemipelagic drape should be present in both hybrid beds and turbidites (see also Remacha et al., 2005). Furthermore, the common normal grading of D5 into D6 suggests a turbiditic origin where terrigenous and carbonate clay was hydraulically fractionated in the dilute parts of flows (Remacha et al., 2005).

In most basins featuring hybrid beds, the source of clay driving flow transformation can only be inferred (see also: Fonnesu et al., 2016), as the type of intrabasinal clay is similar to that in the flow, making it challenging or impossible to distinguish in outcrop or core. Here, D6 acts as a distinctive “tracer” near the location of flow transformation. This demonstrates that flow transformation can occur as a result of flows entraining substrate as they are deflected off intrabasinal slopes in confined settings.

Contemporaneous systems with different stacking patterns

Spatially distinct stacking patterns

Stacking patterns in the Upper Broto System have been described as tabular, where proximal and medial sheet-like lobes transition to the individual bed-scale stacking of the basin-plain environment (Mutti et al., 1999; Remacha and Fernández, 2003; Tinterri et al., 2003). However, the evidence outlined in this work suggests that individual bed correlation in both proximal and distal localities is, at best, challenging (see also Mutti, 1992). Stratigraphic changes in bed stacking patterns are attributed to changing confinement as a basin fills (e.g., Hodgson and Haughton, 2004; Marini et al., 2015; Fonnesu et al., 2018; Liu et al., 2018). Here, different lobe stacking styles are described in the same stratigraphic interval, and are interpreted to reflect different flow processes and depositional architectures from proximal to distal localities (see also Fonnesu et al., 2018).

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Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures Lobes are identified in proximal localities based on their geometries, facies, and facies transitions (Figs. 7.10; 7.11). The lateral and longitudinal offset of thick-bedded sandstone facies indicates that the depocenter of successive lobes moved away from the depositional relief of previous lobes, and stacked in a compensational manner (Figs. 7.11, 7.15B; e.g., Mutti and Sonnino, 1981; Parsons et al., 2002; Deptuck et al., 2008; Prélat et al., 2009; Marini et al., 2015; Picot et al., 2016). The identification of lobes medially within the basin, and bypass-dominated facies proximally, indicates that some lobes are the products of flows that bypassed proximal localities (Fig. 7.15). These interpretations are supported by longitudinal and lateral facies and thickness changes within the lobes identified (Figs. 7.10, 7.11).

In distal localities, beds do not form clear packages with lobate geometries as they do in proximal and medial locations (Fig. 7.13). Similarly, they do not exhibit persistent lateral and longitudinal trends in thickness and facies (e.g., lobe axis to lobe fringe) observed in proximal localities, and in other basins (e.g., Mutti and Sonnino, 1981; Prélat et al., 2009; Grundvåg et al., 2014; Marini et al., 2015; Spychala et al., 2017a). Some anomalously thick beds can be tentatively correlated (Fig. 7.10). However, it is not possible to confidently correlate most beds across these areas, particularly across depositional strike (Fig. 7.13B; cf. Remacha and Fernández, 2003), suggesting that beds may not be as tabular as previously suggested.

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Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures

Figure 7.15: Schematic interpretation of the Jaca Basin paleogeography during deposition of the Upper Broto turbidite system (A); B) Proximally, lobes stacked compensationally, and did not develop hybrid beds. The solid-color box is based on data presented in Fig. 7.11. C) Distally, flows interacted with the southern carbonate margin, which deflected flow components to the north. These deflected flows entrained carbonate-rich muddy slope material, increasing flow cohesion; these flows then deposited hybrid bed divisions D3 and D4 overlying the primary deposits not affected by the slope.

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Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures The outcrop belt is slightly oblique to the primary paleocurrent direction, and therefore some changes in architecture could be attributed to across-depositional-strike facies variations. However, irrespective of individual bed correlations and outcrop-belt orientation, this study recognizes differences in facies and stacking patterns between proximal, medial, and distal localities. The marked distribution of facies, bed types, and stacking patterns indicates a basinal control. The implications of these differences are that fundamentally different stacking styles can occur in the same stratigraphic interval of deep- water systems in confined basins.

A similar distribution of facies is observed in the Gottero Sandstone, Italy. Proximal localities are characterized by lobes, whereas distal localities comprise thick, basin-wide, tabular turbidites and hybrid beds in these basins (Fonnesu et al., 2018). It is interpreted that regular-size flows were relatively unconfined and formed proximal lobes, whereas large flows bypassed proximal localities (see also Wynn et al., 2002; Remacha et al., 2005), entrained large rafts of substrate, and deposited thick basin-wide turbidites and hybrid beds (Fonnesu et al., 2018). The distal deposits of the Upper Broto do not exhibit evidence of significant basin-floor erosion and entrainment, suggesting that highly energetic flows were not present. Some anonymously thick beds (1–3.2 m) in the Upper Broto could be associated with larger-volume flows into the basin (e.g., Remacha et al., 2005); however, the vast majority of beds are thinner than 1 m (Figs. 7.10, 7.13). Bed thickness increases in the Upper Broto are facilitated predominantly by the development of hybrid beds, the thickness of which are shown to be highly variable and strongly controlled by local topography (e.g., Sumner et al., 2012; Fonnesu et al., 2015). Therefore, it is suggested that facies distribution and hybrid-bed emplacement are controlled predominantly by flows interacting with a confining slope (Fig. 7.15), which does not necessitate, but does not preclude, larger flows.

The effect of deflected flows on stacking patterns

Hybrid beds, up to 3.2 m thick (post-compaction; Fig. 7.10), which thin and decrease in abundance away from the slope (Figs. 7.12B, 7.13; in this case, from south to north; see also Amy et al., 2004), are present in distal localities. These beds could have created, and/or healed, significant 3D topography on the contemporaneous seabed, influencing the routing of subsequent events (e.g., Remacha et al., 2005; Figs. 7.15C, 7.16). Beds with relatively thick mudstone caps are often associated with flow ponding (e.g., Pickering and Hiscott, 1985; Haughton, 1994; Remacha et al., 2005; Muzzi Magalhaes and

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Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures Tinterri, 2010), suggesting that some flows were deposited in bathymetric lows. Flows were deflected nearly perpendicular to the main paleocurrent of the primary flows, causing deflected-flow deposits to develop geometries and facies tracts perpendicular to those of the primary deposits (Figs. 7.15C, 7.16). This may have resulted in complicated 3D bed geometries, which can overlap the stacking pattern of the primary flow deposits (Figs. 7.15C, 7.16). This subtle topography was likely felt by the flows and drove deposition in the inherited topographic lows, developing complex bed-scale compensation patterns (Fig. 7.16).

Figure 7.16: Schematic illustration of how deflected cohesive flows can influence depositional topography. The relative across-strike orientation of the primary (orange) and deflected (purple) flows develop perpendicular to each other, creating subtle topography which could influence the architecture of subsequent flows.

7.9 Conclusions Well-constrained outcrops along a 70 km dip-oriented transect of an exhumed deep- water depositional system permit proximal-to-distal analysis of facies and stacking patterns. Contemporaneous but contrasting stacking pattern within the same stratigraphic interval is described in detail for the first time. Proximal localities are characterized by sandstone-rich lobes interpreted to stack compensationally. Distal localities are characterized by interbedded, comparatively tabular, clean sandstones and hybrid beds which do not stack to form lobes or well-defined tabular sheets.

Here, we present a system that generated hybrid beds through interaction with an intrabasinal confining slope. In most basins featuring hybrid beds, the source of clay responsible for flow transformation can only be inferred as the clay in the flow is 206

Chapter 7:Topographic controls on the development of contemporaneous but contrasting basin- floor depositional architectures compositionally similar to the clay present on the basin floor. Here, a locally derived and distinct carbonate-mud lithofacies demonstrates that entrainment of substrate from an adjacent slope is capable of causing flow transformation. The localized development of hybrid beds through entrainment of slope mud could create depositional relief that influenced flow behavior and deposit geometries, resulting in depositional architectures that diverge from traditional models of either lobe or tabular-sandstone stacking patterns. The co-development of different stacking patterns in the same stratigraphic interval suggests that a false dichotomy of lobes versus sheets to characterize basin-floor architectures could exist, and that the stratigraphic and process record of their transitions merit future investigations to better our understanding of submarine fan-architecture.

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Chapter 8:Synthesis

CHAPTER 8: Synthesis In this chapter the research questions which were asked in Chapter 2 are discussed in the context of the results presented in Chapters 3 – 7. Finally, future research questions and directions arising from, or complimented by, the results presented in this thesis are posed.

8.1 How does depositional reservoir quality vary spatially in submarine lobes and channel-fills? Depositional reservoir quality, the initial reservoir potential of a deposit prior to post-depositional modification, can be maintained post-burial and –diagenesis (e.g. Porten et al., 2016). Primary textural controls: grain-size, clay content, and sorting, have well established controls on porosity and permeability (Fraser, 1935; Beard and Weyl, 1973; Pryor, 1973; Revil and Cathles III, 1999), which exert a control on porosity and permeability post-burial (e.g. Hirst et al., 2002; Lien et al., 2006; Njoku and Pirmez, 2011; Porten et al., 2016). Despite knowledge of the general trends of how texture varies in channel-fills and lobes from numerous qualitative studies, these relationships have never been quantified. This study, which analysed a lobe in the Upper Broto System, and a channel element of the Gerbe System of the South Pyrenean Foreland Basin, provides quantitative analysis of these properties tied to individual architectural elements for the first time.

Results showed strong spatial changes in texture in both the lobe and channel-fill. In the lobe, grain-size decreased from the lobe axis to the distal fringe, in agreement with qualitative studies (Mutti, 1977; Pickering, 1981; Grundvåg et al., 2014; Marini et al., 2015; Spychala et al., 2017b). Similarly, there is an increase of matrix and ductile pseudomatrix from the lobe axis to distal fringe as inferred from other studies (Walker, 1966b; Marchand et al., 2015; Porten et al., 2016; Kane et al., 2017). These results suggest the lobe axis had a greater depositional reservoir quality comparative to the lobe off-axis and fringes, as inferred from subsurface studies (Marchand et al., 2015; Porten et al., 2016). Sorting did not reveal any strong trends in lobes. This may be due to the point counting method not being able to resolve clay grain-sizes, which are not included in the sorting calculation. Similar axial-to-margin trends in grain-size and matrix content are observed in the channel element fill, though the rate of change was around two magnitudes greater. Strong vertical trends were also recognised within the channel-fill, reflecting the complicated interplay of bypass and deposition during its fill (e.g. Hubbard et al., 2014). In Chapter 3, the channel- base-deposit is relatively fine-grained and matrix-rich, with poor depositional reservoir

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Chapter 8:Synthesis quality and would likely form an effective barrier to flow and connectivity. The sandstone fill of the axis has the coarsest grain-sizes and low matrix contents, therefore exhibiting good depositional reservoir quality. However, vertically within the channel-fill there is a fining-upward trend and concomitant increase in matrix, which would likely result in poorer reservoir quality.

How do sediment gravity flow processes control the distribution of depositional reservoir quality?

Deep-water depositional systems are host to numerous bed-types characterised by discrete depositional processes (Sanders, 1965; Middleton, 1967; Hampton, 1972; Lowe, 1982; Kneller and Branney, 1995; Haughton et al., 2003; Kane and Pontén, 2012). Discrete processes result in different depositional textures, which influence the depositional reservoir quality of a body of sedimentary rock (Hirst et al., 2002; Lien et al., 2006; Porten et al., 2016; Southern et al., 2017). Furthermore, the transport mechanism, concentration, and velocity of a flow governs whether it is depositional or bypassing, and how it interacts with substrate and confining topography (Muck and Underwood, 1990; Kneller, 1995; Bakke et al., 2013; Hubbard et al., 2014; Stevenson et al., 2014a).

In Chapter 3, HDTs deposited in the lobe and channel axes exhibited the greatest depositional reservoir quality. Outside of the lobe axis, the proportion of HDTs decreases, with a concomitant increase in LDTs. The LDTs are finer grained, likely resulting in poorer reservoir quality. Channel-fills typically exhibit a wider range of fill styles, and more abrupt changes in heterogeneity. In its axis, the Gerbe channel element comprises: a debrite at its base, which would exhibit very poor reservoir properties; overlying the debrite there is a siltstone-prone package with discontinuous thin-beds which is interpreted as a channel- base-deposit linked to sediment bypass; HDTs incised into, and deposited above the channel-base-deposit, and exhibited good depositional reservoir quality; overlying the HDTs were relatively thin-bedded, non-amalgamated, LDTs. The LDTs were finer-grained and had higher matrix contents, reducing their depositional reservoir quality. Channel margin deposits were dominated by LDTs with poor depositional reservoir quality. These findings demonstrate that spatial changes in depositional processes within individual architectural elements are likely to control depositional reservoir quality.

The depositional reservoir quality concept can be applied further. Channel base deposits were also observed at Klein Hangklip in Chapter 6. These deposits are interpreted to reflect the transition between channel degradation and aggradation. Flows which were highly depositional filled the channel with sandstone, whereas strongly bypassing flows 209

Chapter 8:Synthesis eroded these deposits, moving the sediment load to the basin-floor, and potentially draping the channel cut with the dilute, silty parts of the flow. Flows which were partially bypassing are likely to have remobilised previous deposits, and may have deposited the coarser fragments of their sediment load in the channel, resulting in a relatively poorly sorted channel base deposit. These channel base deposits would have poor depositional reservoir quality, acting as baffles to flow. However, local erosion of the channel base deposit, either by a flow which was erosive at its head and depositional in its body, or eroded and then filled by a subsequent flow, enable sandstone connectivity. Similarly, flows which are more erosive are able to entrain the mudstone caps of beds, resulting in thinner mudstone layers or amalgamated sandstones, improving reservoir quality (Chapter 4). Therefore, localities with higher levels of erosion and amalgamation, such as the lobe axis (see Chapter 3), are likely to exhibit higher reservoir potential compared to lobe fringe positions where lower energy flows did not erode into the substrate as much. Conversely, local erosion of substrate by higher energy flows may result in abundant mudstone clasts in otherwise structureless sandstones, reducing their vertical permeability (Chapters 4 and 5). These examples illustrate that the depositional reservoir concept has implications for, and can be applied to, prediction of sandstone quality, and also the presence and effectiveness of baffles and barriers to flow.

8.2 How do bed-scale barriers affect sandstone connectivity? Small scale heterogeneities have been recognised to exert a strong control on permeability and the performance of reservoirs (e.g. Weber, 1982; Haldorsen and Lake, 1984; Begg and King, 1985; Bachu and Cuthiell, 1990; Elfenbein et al., 2005; Jackson et al., 2005; Ringrose et al., 2005; Martinius et al., 2017). Most studies have focussed on modelling of tidal and shallow-marine sandstones (e.g. Nordahl et al., 2006), or of multiple discontinuous mudstones within a larger-scale model (e.g. Haldorsen and Chang, 1986). Conversely, relatively few authors have documented and discussed the effects of individual types of heterogeneity, such as the thickness of siltstone or density of mudstone clasts (though see: Bachu and Cuthiell, 1990; Kashikara et al., 2010; Hao et al., 2019).

How does siltstone thickness affect vertical permeability?

The volume fraction of siltstone within flaser to lenticular bedding is shown to exponentially affect vertical permeability in tidal sandstones (Ringrose et al., 2005; Nordahl et al., 2006). Similarly, Hao et al., (2019) showed an exponential decrease in Kv in realisations of interbedded sandstone and mudstone in core but provided little discussion

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Chapter 8:Synthesis of these results. In agreement with these findings, the results in Chapter 4 reveal an exponential decrease in Kv with increasing siltstone thickness in tests of varying sandstone thickness. Comparison of the two tests revealed that Kv is proportional to the thickness of siltstone. The decrease in Kv is non-linear, and 80% of the decrease in Kv is accounted for between 0 and 4% siltstone thickness, similar to the data presented in Hao et al., (2019). The implications of this are that some of the most important siltstones in a reservoir are likely to be relatively thin (see also: Garland et al., 1999). Conversely, these thinner silts may also be more likely to be eroded, reducing their overall effect on permeability in three dimensions (e.g. Stephen et al., 2001).

How does mudstone-clast density affect vertical permeability?

Mudstone clasts are common components of, though not limited to, deep-water depositional systems and have been recognised in a range of facies and depositional environments (e.g. Johansson and Stow, 1995). Despite this, very few studies consider the effect of mudstone clasts on permeability and reservoir quality (Bachu and Cuthiell, 1990; Cuthiell et al., 1991; Kashikara et al., 2010), and of these, the studies of Bachu and Cuthiell present essentially the same data and results. Kashikara et al., (2010) noted a decrease in Kv with increasing mudstone clast density, which conformed to a power average. However, these results only presented averages of multiple models for some mudstone clast densities, and individual models of others. Results from large-n simulations of mudstone clast density at two model thicknesses reveal decreasing Kv with increasing mudstone clast density (Chapter 4). Kv is more strongly affected in the thinner model, where a 1% density of clasts reduced Kv by ~10%, and Kv decreased in a near-linear trend. In the thicker model, Kv was less-affected at densities below ~30%, but Kv decreased more abruptly with increasing mudstone clast density above that threshold. This suggests an intrinsic change in the percolation threshold where flow pathways are reduced and become longer and more complicated as clast density increases, reducing the connectivity. Multiple realisations of individual models showed notable variability in models with identical input parameters (Chapter 4). The variability is particularly notable in models with intermediate densities of mudstone clasts, and decreases at high and low levels of clast density. This variability is attributed the random 3D distribution of each stochastically modelled mudstone clast model. Therefore, where mudstone clasts may exert a control on permeability multiple models should be produced to constrain minimum and maximum effects.

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Chapter 8:Synthesis Mudstone clasts can negatively affect permeability (Bachu and Cuthiell, 1990; Bachu, 1991; Cuthiell et al., 1991; Kashikara et al., 2010), and have been demonstrated to inhibit improved oil recovery techniques (e.g. Kashikara et al., 2010; Nardin et al., 2013). Despite this, mudstone clasts are commonly grouped into structureless sandstones in outcrop and subsurface studies, are not included in modelling, and are not captured in core plug analysis which is commonly biased towards clean sandstone (Kashikara et al., 2010). The results presented in Chapter 4 suggest that mudstone clasts should be incorporated into reservoir characterisation to better predict performance.

8.3 Which heterogeneities matter to flow in submarine lobes, and how are they distributed? Submarine lobe deposits contain numerous heterogeneities from grain- to system- scale (e.g. Mutti and Sonnino, 1981; Mutti and Normark, 1987; Garland et al., 1999; Haughton et al., 2003; Prélat et al., 2009; Kane and Pontén, 2012; Marchand et al., 2015; Porten et al., 2016; Terlaky et al., 2016). Despite this, there are few published studies which model the reservoir quality of lobe deposits (Garland et al., 1999; Stephen et al., 2001; Pyrcz et al., 2005; Gardiner, 2006; Scaglioni et al., 2006; Ruvo et al., 2008; Amy et al., 2013; Hofstra et al., 2017; Jo and Pyrcz, 2019). Of these studies, few consider lithofacies- and bed-scale heterogeneity (Stephen et al., 2001; Scaglioni et al., 2006; Ruvo et al., 2008), or scale this up to test the effects at architectural element scales (though see: Amy et al., 2013; Hofstra et al., 2017). Chapter 4 showed that small-scale heterogeneities can strongly influence permeability. Therefore, understanding the distribution and effects of these heterogeneities have on discrete sub-environments can be an important tool in reservoir quality prediction.

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Chapter 8:Synthesis Which bed-scale heterogeneities matter to flow?

Chapter 5 combined published data from the Tanqua Depocentre, Karoo Basin, South Africa, with subsurface analogue data from the North Sea to demonstrate how vertical permeability varies within different lobe sub-environments. Siltstones are commonly recognised as a key control on reservoir performance in deep-water reservoirs (Garland et al., 1999; Stephen et al., 2001; Gardiner, 2006; Scaglioni et al., 2006; Chapter 4). However, all models in Chapter 5 have net-to-gross above 0.8, and most are above 0.9, yet show substantial variability in modelled permeability. Models with high net-to-gross, but low permeabilities are typically LDT, or hybrid-bed-prone. This emphasises the role of sandstone quality in reservoir quality distribution, and depositional reservoir quality (Porten et al., 2016; Chapter 3), in addition to net-to-gross.

Mudstone clasts were also modelled. In most models, little variability was recognised between realisations. However, in logged sections of primarily structureless sandstones where mudstone clasts were one of the only forms of heterogeneity, up to 5.5% variability was recognised between models. These findings emphasise that the 3D organisation of mudstone clasts exerts a control on reservoir quality (Chapter 4), and that stochastic modelling can improve estimates of their effects which may have implications for improved oil recovery. The lack of model variability in more heterogeneous models emphasises that the more heterogeneous a body of rock is the less of an effect an individual heterogeneity exerts. However, in relatively homogeneous bodies of rock, individual heterogeneities exert a greater control, and can become the primary control on reservoir quality distribution.

How does vertical permeability (Kv) vary spatially within submarine lobes?

The well constrained stratigraphic framework of the Tanqua Basin enabled interpretation of the sub-environment of each modelled section. This allowed comparison of how Kv changed in response to different heterogeneities present in each sub- environment. The lobe axis had the best reservoir properties due to the abundance of structureless sandstones (see also: Hofstra et al., 2017). Lobe off-axis positions typically had poor values due to the presence of low-permeability LDTs, though some sections had intermediate values due to localised deposits of structureless sandstones. This interfingering of structured and structureless facies in the lobe can have implications for water breakthrough and sweep efficiency (Hofstra et al., 2017). The lateral fringe of the lobe had very-poor permeability as it consisted of ripple-laminated LDTs which had low 213

Chapter 8:Synthesis permeabilities in the subsurface analogue. The distal part of the lobe, in the frontal fringe, contained a wide range of permeability values. This was due to the frontal fringe of the lobe being characterised by a lobe-finger geometry (e.g. Groenenberg et al., 2010; Kane et al., 2017; Dodd et al., 2019). In the position most lateral to the axis of the lobe finger, permeability was very-poor due to an abundance of hybrid beds, and a comparatively low net-to-gross. In positions off the axis of the lobe finger, Kv remained low due to the presence of both hybrid beds and LDTs. The axis of the lobe finger contained thick structureless sandstones, giving it the highest Kv outside of the lobe axis. However, localised LDTs and hybrid beds can act to reduce this to levels similar to that of the off- axis positions. These findings again emphasise the important role of depositional reservoir quality, where the depositional processes strongly influence reservoir quality distribution within lobes. Furthermore, the frontal fringe has recently been characterised as poor reservoir quality due to the abundance of hybrid beds. However, the results presented here demonstrate that high-permeability sandstones are present in these environments, which can provide migration pathways for fluids such as hydrocarbons.

8.4 How are facies and architecture organised in three dimensions in submarine channel-fills, and how might this affect reservoir prediction? Submarine channel-fills are notoriously heterogeneous over short length scales (e.g. Walker, 1966a; Campion et al., 2000; Sullivan et al., 2000; Mayall et al., 2006; McHargue et al., 2011; Hubbard et al., 2014; Li et al., 2016). Therefore, outcrop studies are often used as analogues to predict architecture and reservoir performance in the subsurface (Sullivan et al., 2000; Alpak et al., 2013; Hofstra et al., 2018; Jackson et al., 2019). A common limitation of outcrop analogues is that they are limited to 2D strike or dip exposures, so understanding of how facies and architecture changes in three dimensions is limited. The Klein Hangklip outcrop, Tanqua depocentre, is an example of an exposed submarine channel-fill which enabled construction of multiple architectural panels to analyse heterogeneity in three-dimensions. Across depositional-strike panels show consistent trends from: thicker, thicker-bedded, packages of amalgamated structureless and mudstone-clast-rich sandstones in the channel axis deposited under HDTCs; to thinner, thinner-bedded, packages of predominantly laminated sandstones deposited by LDTCs. These depositional patterns are consistent with other documented examples (e.g. Campion et al., 2000; Sullivan et al., 2000; Hubbard et al., 2014; Li et al., 2016). Down depositional- dip oriented panels are rarer. The Tres Pasos Formation, Chile, provides approximately 40 km of down-dip exposure (e.g. Macauley and Hubbard, 2013). However, the weak sinuosity

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Chapter 8:Synthesis of the channel-fills means they protrude in and out of the plane of the outcrop, revealing predominantly oblique exposures of the channel-fills (Macauley and Hubbard, 2013; Hubbard et al., 2014). The Cerro Torro Formation, Chile, enables down-dip analysis of facies which reveal a systematic change from predominantly debritic up-dip, to turbiditic down-dip, and a down-dip decrease in bed-thickness (Malkowski et al., 2018). At smaller- scales, Pyles et al., (2010) show short length-scale (10s – 100s m) down-dip changes in response to channel sinuosity. A limitation of this study, however, is that is based on extrapolation of LiDAR. The data presented in Chapter 6 lies between these two scales (100s m – 1s km). The Klein Hangklip outcrop does not exhibit abrupt changes in facies, and is sandstone-prone in all logged sections. However, there are subtle variations between sandstone facies in comparable depositional environments in down-dip positions. These findings suggest that net-to-gross does not change substantially down-dip in relatively straight channels on a kilometre-scale. However, subtle variability in facies from HDTs, to LDTs, and mudstone-clast-rich beds are likely to influence the depositional reservoir quality of sandstones (Chapters 3 and 5), and influence the distribution and effectiveness of bed-scale barriers (Chapter 4).

How do the facies and spatial distribution of channel-base-deposits vary?

Channel-base-deposits are typically fine-grained, may be poorly sorted and clast- rich, and can act as barriers to flow in the subsurface (e.g. Barton et al., 2010; Alpak et al., 2013; Jackson et al., 2019). Despite this, few studies document their facies and spatial distribution in detail, and mostly discuss their formative processes (Walker, 1975b; Campion et al., 2000; Camacho et al., 2002; Barton et al., 2010; Hubbard et al., 2014; Li et al., 2016). Data presented in Chapter 6 shows short length-scale variability in facies of channel-base-deposits: From channel axis to channel margin, channel-base-deposits typically become less-composite, and more siltstone-prone. Similarly, stratigraphically within a channel fill of a given hierarchal level, channel-base-deposits of smaller hierarchical level channel-fills become less-composite upwards; and the channel-base- deposits of larger hierarchical levels are typically more composite than those of lower levels. These findings may enhance predictability of connectivity and siltstone-baffle distribution (e.g. Chapter 4) in channel-fills in the subsurface.

Mapping of the channel-base-deposits revealed that their facies can change abruptly over 10’s m, and that amalgamation of sandstone may locally remove any stratigraphic expression they have. In the subsurface, channel-base-deposits are commonly identified

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Chapter 8:Synthesis through dip-meter analysis. Erosion surfaces and their associated channel-base-deposits at Klein Hangklip are frequently relatively flat-lying. The implications of these observations are that these surfaces may be challenging to identify in the subsurface, impacting: 1) the effectiveness of correlation between wells; 2) hierarchical analysis; and 3) the prediction of sediment delivery, and therefore sandstone, down-dip.

Of note is that the Klein Hangklip case-study is drawn from a relatively tectonically quiescent basin. Basins with mobile substrate, such as those offshore West-Africa, or the Gulf of Mexico, may prove more challenging due to: local changes in the equilibrium profile; depositional gradient; bank stability; or confinement of the system etc. These variables may introduce a wider range of facies (e.g. mass-transport deposits), diachronous distribution of degradation and aggradation, changes in depositional processes due to flow acceleration or deceleration, and deposition or bypass due to loss or gain of confinement (e.g. Booth et al., 2003; Kneller, 2003; Mayall et al., 2010; Kane et al., 2012; Oluboyo et al., 2014; Ortiz-Karpf et al., 2015).

8.5 Do contemporaneous lobe deposits in a basin exhibit the same architectures and stacking patterns? Basin-floor lobe systems are commonly inferred to exhibit one style of stacking or another. In highly confined systems gravity flow deposits are interpreted to develop laterally continuous, tabular beds, which may be basin-wide (Ricci-Lucchi and Valmori, 1980; Remacha et al., 2005; Amy et al., 2007; Talling et al., 2007a; Marini et al., 2015; Southern et al., 2015; Fonnesu et al., 2018; Liu et al., 2018). Conversely, systems which are relatively unconfined develop lobes which may stack compensationally (Deptuck et al., 2008; Prélat et al., 2009; Marini et al., 2015; Picot et al., 2016), or longitudinally (Grundvåg et al., 2014; Picot et al., 2016). Many basins exhibit variable confinement of gravity flows along their depositional profiles, and few studies have constrained how this may affect the response of gravity flows, and the stacking patterns of their deposits.

The Jaca Basin, South Central Pyrenees, Spain, is an example of a basin in which flows were variably confined (Chapter 7). Investigation of facies, architecture, and stacking patterns, reveals contrasts between deposits in the proximal and distal parts of the basin. Proximal parts of the basin are characterised by sandstone-prone packages which show gradual transitions from relatively thick- to thin-bedded sandstones of 100’s to 1000’s m, interpreted as lobes. The lobe deposits show spatial variability in their thickest position, and the position of their thicker-bedded and amalgamated facies (i.e. lobe axis). In contrast,

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Chapter 8:Synthesis distal deposits in the study area do not form distinguishable packages of sandstone which exhibit predictable changes in facies and can be correlated between outcrops. Proximal lobe deposits lack hybrid beds, whereas distal deposits are hybrid bed prone. Additionally, deposits in distal positions reveal evidence for northward deflection of flows from a contemporaneous southern slope (e.g. Remacha et al., 2005). It is interpreted that the proximal deposits were relatively unconfined, and developed compensational stacking of lobes in response to the depositional relief of previous lobe deposits. Conversely, the distal deposits were partially confined by the lateral southern slope (e.g. Amy et al., 2004). Flow interaction with the lateral slope resulted in flow deflection and transformation. The deflected flows deposited hybrid beds overlying the primary, non-deflected, flow deposits. The localised development of metres-thick hybrid beds is interpreted to have inhibited the development of clearly defined lobe stacking patterns.

These findings demonstrate that there is a continuum of basin-floor stacking patterns, and that contrasting styles can develop contemporaneously within the same system (see also: Marini et al., 2015; Fonnesu et al., 2018). The distribution of contrasting styles of stacking are here strongly linked with flow process response to confining topography, and therefore may be applicable to the confined basins and mini-basins developed offshore many passive margins (e.g. Gulf of Mexico; Booth et al., 2003). Furthermore, hybrid beds, which are an important heterogeneity developed within deep- water systems, are commonly identified to form due to flow transformation: 1) longitudinally due to substrate entrainment and deceleration (e.g. Kane et al., 2017); or 2) due to deceleration against confining slopes (e.g. Patacci and Haughton, 2014). Here, hybrid beds are interpreted to develop due to deflection from a confining slope, which has implications for both reservoir quality (e.g. Chapter 5) prediction adjacent confining slopes, and the reconstruction of palaeogeographies where deflected hybrid beds can be used to infer nearby topography.

8.6 Future research directions

Depositional reservoir quality of unconfined submarine fans

The depositional reservoir quality of submarine lobe and channel-fill deposits was demonstrated to vary spatially between discrete sub-environments (Chapter 3). However, this stands as the only case-study which quantitatively documents this variability. Whilst the quantified spatial changes in texture may prove valuable for subsurface analogues, as the Upper Broto System was a relatively confined, foreland basin, it may be a poor analogue 217

Chapter 8:Synthesis for unconfined and passive margin systems. Similarly, the lobes in proximal part of the Upper Broto System lack hybrid beds, which are a common feature of submarine lobes. Therefore, further case studies analysing the depositional reservoir quality of lobes and channel-fills would provide a greater range of input values for modelling of rock properties in models. Well-constrained examples such as: the Skoorsteenberg Formation; Tres Pasos Formation; Ross and Gull Island Formations; Brushy Canyon Formation; Rosario Formation; and the Windermere Supergroup, for example, could provide a wider range of input values for risking of reservoir properties in the subsurface.

Depositional reservoir quality of modern systems

A drawback of using outcrop analogues to constrain depositional reservoir quality is that they are modified by diagenetic processes, making it challenging to differentiate detrital and authigenic clays, and the original porosity is destroyed. Use of high-resolution bathymetry, undersea probes, and box-cores, has enabled linkage of flow structure to deposits and architecture (e.g. Hage et al., 2018). Sampling of these deposits in strategic locations could enable analysis of the primary textural properties of discrete flow-types, and discrete sub-environments prior to diagenesis, and thus their true depositional reservoir quality.

Quantitative analysis of mudstone-clast distribution

Chapter 4 demonstrated that small-scale heterogeneities can have a strong control on permeability. Mudstone clasts are a common feature in many depositional environments, but are commonly included in structureless sandstone facies, or only qualitatively assessed (e.g. Johansson and Stow, 1995). Understanding, and quantifying the distribution of mudstone clasts, both spatially within geobodies, and calculating 3D densities and their effect on flow, could help with reservoir quality prediction and improved oil recovery techniques (e.g. steam assisted gravity drainage; Kashikara et al., 2010).

Multiscale modelling of deep-water depositional systems

The effects of bed-scale heterogeneities on vertical permeability have been demonstrated in Chapters 4 and 5. These scales of observation are often not accounted for in reservoir models, though have been demonstrated to exert a strong control (Ringrose et al., 2008; Martinius et al., 2017). Multiscale modelling approaches have commonly been utilised in tidal and fluvial reservoir settings (Elfenbein et al., 2005; Jackson et al., 2005; 218

Chapter 8:Synthesis Ringrose et al., 2005; Nordahl et al., 2006; Ringrose et al., 2008; Nordahl et al., 2014; Martinius et al., 2017). However, the use of multiscale modelling in deep-water systems, despite their strong heterogeneities, is still in its infancy where studies have tended to focus on one scale (Scaglioni et al., 2006; Ruvo et al., 2008; Amy et al., 2013; Hofstra et al., 2017). Future work could seek to integrate multiple scales of observation: beginning with bed- scale modelling utilising core-plug and core-logging data (e.g. Scaglioni et al., 2006); secondly outputs from bed-scale modelling, including Kv/Kh, could be implemented into architectural element scale modelling using architectures drawn from both core and seismic data, and outcrop analogues (Hofstra et al., 2017); these observations could then provide more informed input parameters, which honour the inherent heterogeneity of the systems, into reservoir grid models.

Quantitative analysis of channel-base-deposits

Channel-base deposits are a major control on connectivity and permeability in submarine-channel deposits (Barton et al., 2010; Alpak et al., 2013; Jackson et al., 2019). Most research has focussed on their formation (e.g. Mutti and Normark, 1987; Campion et al., 2000; Camacho et al., 2002; Hubbard et al., 2014; Li et al., 2016), or how their coverage affects connectivity (Alpak et al., 2013; Jackson et al., 2019). Aside from Barton et al. (2010), no published studies quantify channel-base-deposit distribution, which is a critical control on reservoir quality. Channel-base-deposits are often considered and modelled as a single facies. Here, the facies of the channel-base-deposits is demonstrated in Chapter 6 to show strong spatial variability and heterogeneity, including variable erosion and amalgamation which would enable vertical connectivity. Therefore, quantitatively constraining the coverage, distribution, and facies of channel-base-deposits could provide more-accurate input into reservoir models.

Discerning the transition from sheet-like to compensational stacking of lobes

Lobes are interpreted to exhibit a continuum of stacking patterns between sheet- like stacking, which forms in highly confined settings, and compensationally stacked lobes, which forms in relatively unconfined settings. Despite several outcrop studies (Marini et al., 2015; Liu et al., 2018), the transition between lobes, in which flows are focussed into topographic lows, and sheet-like stacking, in which flows were laterally confined within the basin is poorly constrained. The controlling factor is the relative confinement of the parent flows (i.e. the size of the flow vs. the size of the container). Relatively simple tests could be constructed to constrain this relationship quantitatively, either in a flume tank, or by 219

Chapter 8:Synthesis utilising a numerical modelling approach (e.g. Jo and Pyrcz, 2019). By beginning with unconfined, compensationally stacked lobes, and gradually increasing the confinement, the transition between deposits which form convex-up topography and which are affected by previous lobes, and those which form “basin-wide” tabular deposits could be identified.

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Chapter 9:Conclusions CHAPTER 9: Conclusions  The textural properties of a well-constrained channel element fill and lobe deposit are quantitatively investigated for the first time. Thin sections were made from samples of discrete sub-environments of a lobe and channel element fill of the Jaca and Aínsa Basins, respectively. Point counting of the grain-scale fabric of the samples revealed strong textural anisotropy: 1) channel-axis positions revealed lower matrix contents, but coarser grain-sizes, compared to channel-margin positions; 2) lobe axis positions had lower matrix contents, and coarser grain-sizes, compared to lobe off-axis and lobe fringe positions. The rates of change in the lobe are non-linear; grain-size decreases and matrix content increases more abruptly from the lobe off-axis to lobe fringe positions. These quantitative results can be used to improve prediction of reservoir properties in deep- water systems, and for improved input into reservoir models.  Reservoir models are often realised using the harmonic mean for permeability. Here it is demonstrated that small-scale discontinuous heterogeneities, which correspond to percolation theory, result in divergence from the harmonic mean. These heterogeneities should be realised in fine-scale models prior to use in coarse-scale models. Mudstone clasts are commonly incorporated into structureless sandstone facies, and not incorporated into reservoir models. Here, centimetre-scale layers of mudstone clasts are demonstrated to reduce permeability in metre-thick packages of sandstones, suggesting these heterogeneities should be incorporated into fine-scale models.  Bed-scale modelling of an exhumed deep-water lobe revealed strong spatial controls on vertical permeability. Recent studies have characterised distal lobe fringes as host to poor reservoir quality sandstones due to an abundance of hybrid beds. Here, these positions are also shown to host high permeability structureless sandstones which challenges this assumption. Furthermore, all realised models exhibit net-to-gross values above 0.8, which emphasises the role of bed-types on reservoir quality distribution, which should be accounted for in fine-scale reservoir models.  Architectural investigation of a submarine channel-fill revealed numerous heterogeneities which are sub-seismic in scale, and therefore difficult to realise in subsurface data. Sedimentary logs supported by aerial photography reveal that lateral facies trends are consistent and predictable. Channel margin positions are dominated by laminated, bedded sandstones, and do not show strong vertical trends. Channel axis positions show strong vertical facies trends, and are more prone to mudstone-clast-rich facies and thick- bedded amalgamated structureless sandstones at the base, and become thinner-bedded 221

Chapter 9:Conclusions and more prone to laminated sandstones vertically upwards. Longitudinal facies changes are less-consistent, although consistently sandstone-prone, lithofacies change several times in down-dip positions.

Channel-base-deposits show strong spatial heterogeneity. Channel-base-deposits of lower, deeply incisional, channel-elements are thick, highly composite in the channel- axis, though laterally may be amalgamated; whereas in channel margin positions are typically thin, silt-prone and less-composite. These deposits may form significant, but patchy, barriers to flow. Channel-base-deposits of upper, less-incisional, channel elements are typically silt-prone and relatively thin, show little spatial heterogeneity, and are laterally extensive. These deposits are likely to form less-effective barriers compared to channel-base deposits of incisional channel elements, but their lateral extent may result in them forming more effective barriers to flow.

 A new, novel method for the development of hybrid beds is proposed. A ripple cross- laminated division overlying the structureless sandstone division diverges from regional primary palaeocurrents, indicating a turbulent flow deflected from a contemporaneous adjacent slope. These divisions are overlain by argillaceous and muddy sandstones deposited from flows transitional between turbulent and laminar. These divisions are not identified in parts of the basin distal to the contemporaneous slope, indicating a local control on development. Therefore, it is interpreted that these components of flows impacted the slope, where they decelerated and collapsed or entrained clay from the slope. This resulted in flow transformation and the deposition of hybrid beds as the deflected flow reached the basin-floor.

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Chapter 11:Appendix A: Jaca Basin logged sections CHAPTER 11: Appendix A: Jaca Basin logged sections

Figure 11.1: A Lecina logged section

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Figure 11.2: Acín logged section

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Figure 11.3: Anso north logged section

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Figure 11.4: Anso south logged section 266

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Figure 11.5: Aragues del Puerto logged section.

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Figure 11.6: Barranco El Chate logged section

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Figure 11.7: Buesa logged section

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Figure 11.8: El Bano logged section

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Figure 11.9: Fanlo 1 logged section

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Figure 11.10: Fanlo 2 logged section.

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Figure 11.11: Fanlo Track logged section. 273

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Figure 11.12: Hecho north logged section.

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Figure 11.13: Hecho south logged section. 275

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Figure 11.14: Linas de Broto logged section. 276

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Figure 11.15: Urdues logged section.

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Figure 11.16: Yesero logged section.

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Figure 11.17: Yesero 2 logged section.

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Chapter 12:Appendix B: Klein Hangklip logged sections CHAPTER 12: Appendix B: Klein Hangklip logged sections

Figure 12.1: KHK Log 1.

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Figure 12.2: KHK Log 2.

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Figure 12.3: KHK Log 3.

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Figure 12.4: KHK Log 4.

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Figure 12.5: KHK Log 5.

Figure 12.6: KHK Log 6.

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Figure 12.7: KHK Log 7.

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Figure 12.8: KHK Log 8.

Figure 12.9: KHK Log 9.

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Figure 12.10: KHK Log 10.

Figure 12.11: KHK Log 11.

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Figure 12.12: KHK Log 12.

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Figure 12.13: KHK Log 13.

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Figure 12.14: KHK Log 14.

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Figure 12.15: KHK Log 15. 291

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Figure 12.16: KHK Log 16.

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Figure 12.17: KHK Log 17.

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Figure 12.18: KHK Log 18.

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Figure 12.19: KHK Log 19.

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Figure 12.20: KHK Log 20.

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Figure 12.21: KHK Log 21.

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Chapter 13:Appendix C: SBED

CHAPTER 13: Appendix C: SBED

13.1 Geometry modelling SBEDTM is a synthetic bedform modelling tool which is able to generate 3D numerical models of lithofacies and sedimentary structures (Wen et al., 1998). SBEDTM utilises the displacement of mathematical sine curves to mimic bedform migration, erosion, and deposition. Stochastic modelling using values for properties such as amplitude and wavelength enable the development of realistic, but variable bedforms in 3D (Wen et al., 1998; Ringrose et al., 2005; Nordahl et al., 2014). The method is based on a time series of elevation surfaces with the form (Ringrose et al., 2005):

푡 푥 푦 푧(푥, 푦) = 퐴푠푖푛 ( + 휃푥) + 퐵푠푖푛 ( + 휃푦) + 푔(푥, 푦) 퐿푥 퐿푦

Where: x and y = spatial coordinates t = nominal time

A and B = amplitudes of the bedform in current and crest directions

Lx and Ly = wavelengths of the bedform in the current and crest directions

θx and θy = initial phase angles g(x,y) = 2D Gaussian random function

After a determined sequence of surfaces z(x,y)t=n, a hiatus is simulated, allowing for erosion by a new time series set (Ringrose et al., 2005). Several different lamina-types can be simulated, for instance mud can be deposited in the troughs of sand ripples. A large number of simulations are made to build unique stratigraphy. The lamina in these models is then populated with values for porosity and permeability drawn from a two-dimensional Gaussian field, typically cross-correlated with those observed in core measurements (Ringrose et al., 2005).

13.2 Property modelling SBEDTM was used to predict permeability in a series of experiments. For simplicity single phase upscaling methods were used to predict flow speed in the model (Durlofsky, 2005; Nordahl et al., 2014). Local fixed boundary conditions were used, this limits flow 298

Chapter 13:Appendix C: SBED simulation to within the model boundaries rather than attempting to take into account flow outside of the model (Durlofsky, 2005; Nordahl et al., 2014). Darcy’s law measures the flow rate of a fluid through a porous medium, its viscosity, and the pressure drop over a given distance:

푘퐴(푝푏 − 푝푏) 푄 = − 휇퐿 Where: Q = total discharge (e.g. m3/s) k = permeability A = cross-sectional area of the medium pb – pa = total pressure drop µ = dynamic viscosity L = length over which the pressure drop takes place As described in Durlofsky (2005), the equation which governs single phase flow in the absence of gravity is formed by combining Darcy’s law, divided by area, and solved for u: 1 푢 = − 푘 ∙ ∇푝 µ With a statement of mass conservation: 휃 (∅휌) − ∇ ∙ (휌푢) + 푚̅ = 0 휃푡 The resulting equation, referred to as the pressure equation is given by: 휃 휌 (∅휌) − ∇ ∙ ( 푘 ∙ ∇휌) + 푚̅ = 0 휃푡 푘 Where: u = the Darcy velocity µ = viscosity k = the (symmetric positive definite) permeability tensor p = pressure t = time ∅ = porosity ρ = density m ̄ = source/sink term expressed as a mass flow rate per unit volume. As length is a variable in Darcy’s law, it is likely to exert some control on the experiments presented in chapters 4 and 5. However, as permeabilities differ by up to

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Chapter 13:Appendix C: SBED an order of magnitude between lithofacies, this control is likely to have a negligible effect on results.

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