SMAKS: Shallow-Marine Architecture Knowledge Store

Fluvial, Eolian & Shallow-Marine Research Group http://frg.leeds.ac.uk/ SMAKS: Shallow-Marine Architecture Knowledge Store River A database storing aspects of paralic & shallow-marine sedimentary architecture that can be applied to reservoir characterization & prediction. The database serves as a tool with which to achieve the following primary goals: deltas Ÿ generate quantitative facies models for bespoke coastal & shallow-marine wave-influenced sedimentary systems that act as subsurface reservoir bodies; estuaries and Ÿ guide well correlation of shallow-marine sandstone bodies; Increasing fluvial sediment supply wave- lagoons tide-

Increasing marine sediment supply dominated dominated Ÿ condition object- and pixel-based stochastic reservoir models; shorelines estuaries Wave Tide Ÿ predict the likely heterogeneity of geophysically imaged geobodies; Increasing relative wave influence Ÿ inform interpretation of lithologies observed in core and predict 3D architecture. Increasing relative tidal influence

vf f m c vc silt

clay sand granules

Sedimentary architectural expression of a shoreface parasequence, Cretaceous Blackhawk Formation, Book Cliffs, Utah, USA Fluvial, Eolian & Shallow-Marine contact: Dr Luca Colombera Research Group email: [email protected] School of Earth and Environment contact: Prof Nigel Mountney email: [email protected] University of Leeds, LS2 9JT UK web: http://frg.leeds.ac.uk/ SMAKS

Fluvial, Eolian & Shallow-Marine Research Group http://frg.leeds.ac.uk/

Introduction: Shallow-Marine Architecture Knowledge Store (SMAKS) The Shallow-Marine Architecture Knowledge Store The SMAKS permits the quantitative characterization (SMAKS) is a relational database devised for the of modern and ancient shallow-marine and paralic storage of hard and soft data on the sedimentary clastic depositional systems. It aims to serves as a architecture of ancient shallow-marine and paralic repository of analogue information for hydrocarbon- siliciclastic successions, and on the geomorphological bearing successions, and as a research tool, organization of corresponding modern environments. applicable to aid the development of facies models or The database allows incorporation of data from the to assess the sensitivity of depositional systems to published literature, which are uploaded to a common particular controlling factors, for example. standard to ensure consistency in data definition. The database incorporates data on geological entities of DT 2 DT 1 varied nature and scale (i.e., surfaces, depositional DT 3 AE 2 AE 3 tracts, architectural elements, sequence stratigraphic AE 1 DT 4 units, facies units, geomorphic elements), including depositional-tract architectural-element attributes that characterize their type, geometry, boundary boundary spatial relations, hierarchical relations, and temporal SMAKS surface significance. Furthermore, geological entities are assigned to depositional systems, or to parts thereof, that can be classified on multiple parameters (e.g., shelf width, delta catchment area) tied to metadata Above. Idealized example of the definition of SMAKS (e.g., data types, data sources). depositional tracts (DT), architectural elements (AE) & surfaces.

Depositional contain Surfaces tracts ANCIENT

contain deﬁne contain bound MODERN ANCIENT Sequence stratigraphic surfaces Geomorphic Architectural elements elements bound

Tidal ﬂat contain Sequence Highstand Systems Tract stratigraphic units

Tidal-creek complex parasequence 3 parasequence 2 contain parasequence 1

Tidal creek 10 m Tidal-creek ﬁll Facies units SMAKS intertidal entities and 5 m LEGEND subtidal relationships Entity relationship

0 m clay silt sand gravel Above. Ranks of sedimentary and geomorphic units of the SMAKS database. Page 2 SMAKS

Fluvial, Eolian & Shallow-Marine Research Group http://frg.leeds.ac.uk/

The SMAKS database methodology brings together How does SMAKS work? analogue datasets from different data types and Improvement in subsurface prediction of shallow- contexts, associated with different classes of paralic marine and paralic siliciclastic hydrocarbon reservoirs and shallow-marine depositional systems. is typically attempted through the characterization of This document (i) presents a brief description of the ancient and modern depositional systems that content database, (ii) illustrates the types of represent potential reservoir analogues. Analogue quantitative output that can be generated upon data are applied in scenarios of reservoir exploration, interrogation of the database through the development and production: (i) to predict the potential implementation of queries of geological significance, occurrence and size of stratigraphic traps; (ii) to predict and (iii) demonstrates how this information can be the seismic resolvability of sedimentary bodies; (iii) to used for purposes of subsurface characterization in erect conceptual reservoir models; (iv) to guide well- applied contexts. to-well correlations of sedimentary units; (v) to condition static reservoir models. Ancient and modern The sedimentary and geomorphological architecture analogues are generally characterized through a of preserved ancient successions and modern number of approaches and at multiple scales of environments are translated into the database in the observation (e.g., sedimentary facies and form of entries within tables organized in a relational architectural-element analysis of ancient outcrop schema. Some of these entries represent geological successions, mapping key stratal surfaces at outcrop entities (e.g., sedimentary units, surfaces) at different or in seismic data to erect a sequence stratigraphic scales of observation and which result from different, framework, analysis of aerial photographs or satellite although not mutually exclusive, approaches to imagery of modern environments). analogue characterization (e.g., facies analysis, architectural-element analysis, sequence stratigraphy). Other entries represent relationships Neogene between geological entities (unit transitions, surface Jurassic relationships). In this way, all the significant aspects of Permian clastic sedimentary architecture are considered in the Triassic database conceptual model. Quaternary Cretaceous Devonian Ordovician Paleogene Carboniferous Above. Distribution of SMAKS >220 analogues through geological time.

u o m . d nde d und ide te fin ide e t a e t fi in d ne Fwt F- m d o u F- d T n F r Fw T Wf Wt d d d e e e e v Wt fi t t i F- n r a a

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i i

m m

F W-

o o

d Fw Ft

W-

e W- e

v v

Wt e

W-

Wf T-

Fwt Ftw

Wft Tfw

Wf Tf Wtf Twf Progradational Aggradational Retrogradational Wt Tw Parasequence-set type N = 416 W T

. r d. d dom r iv e ate er . in u d u iv u d u m n e n r n e Fwt n o Fwt d t d d d d e a e . Ftw d i F Ft e fi in fi e t r Ft n n d fi fi e Fw n e m e e n F- v o e i d d F- e r d F- d i d t d T

Wt e Wf

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LST Systems-tract type TST HST N = 681 FSST Above. SMAKS output on the relative frequency of parasequences classified on process dominance across different types of parasequence sets and systems tracts. Page 3 SMAKS

Fluvial, Eolian & Shallow-Marine Research Group http://frg.leeds.ac.uk/

SMAKS analysis at the scale of architectural elements and lithofacies units To demonstrate the wide applicability of the database environments, on the hierarchical arrangement of in fields of both fundamental and applied research, architectural elements that form deltaic constructional example database output is presented that (i) includes units in Quaternary deltas, on the morphometry of data from wave-, tide-, and fluvial-dominated shallow modern and Quaternary tidal sand ridges, and on the seas and sedimentary successions, and (ii) covers a geometry of parasequence-scale nearshore wide depositional spectrum, from backshore to shelf- sandstone belts, either globally or for specific edge settings. Examples of the types of output that can depositional systems (e.g., the Upper Cretaceous be retrieved from SMAKS include information on the successions of the Western Interior Seaway, Utah, facies organization of different types of paralic sub- USA).

Mouth bar Washover fan Asymm. ripple Undefined Massive x-lamination Symm. ripple Massive x-lamination Undefined Planar horizontal lamination Trough or planar Horizontal x-bedding lamination or Planar Asymmetrical low-angle x-bedding ripple x-stratification Trough x-lamination x-bedding Trough Planar x-bedding x-bedding N = 123 N = 34

FORESHORE SHOREFACE OFFSHORE TRANSITION OFFSHORE mean high water mean low water

mean fairweather wave base

Offshore transition mean storm wave base 100% Foreshore Shoreface Shelf offshore 90% 80% Sedimentary structures 70% Hummocky or swaley cross-stratification Lenticular bedding 60% Trough or planar cross-bedding 50% Planar cross-bedding 40% Trough cross-bedding Horizontal lamination or low-angle cross-stratification 30% Planar horizontal lamination 20% Symmetrical ripple cross-lamination 10% Asymmetrical ripple cross-lamination Massive 0%

Bioturbation index 0 1 2 3 4 5 6 N = 1815

Above. SMAKS facies models quantifying the facies make-up of different types of shallow-marine sub-environments. Page 4 SMAKS

Fluvial, Eolian & Shallow-Marine Research Group http://frg.leeds.ac.uk/

How can SMAKS be applied for subsurface characterization?

The database design and standard 1.0 interquartile median have been structured with Prodelta Delta front Delta top range consideration of the variety of 0.8 Mouth bar mean approaches and data types that are 0.6 taken in studying the sedimentary geology of shallow-marine and paralic 0.4 depositional systems. The database allows for a convergence of datasets Net-to-gross ratio 0.2 from studies of outcrops, of the 0.0 N = 58 elements subsurface and of the modern seabed. n = 1164 facies This convergence permits the Prodelta Delta front Mouth bar reconciliation of facies analysis, 0.35 downdip transition architectural-element analysis, 0.3 sequence stratigraphy and 0.25 geomorphology. 0.2 0.15 SMAKS can be applied to characterize 0.1 subsurface reservoir successions for 0.05 Po Delta which only limited data are available. 0 0 0.2 0.4 0.6 0.8 1 Ferron Sandstone 'Last Chance Delta' The database can also provide hard Prodelta net-to-gross ratio data with which to constrain reservoir Delta-front net-to-gross ratio Ferron Sandstone 'Notom Delta’ models. Additionally, it can be used to Above. SMAKS output that quantifies the net-to-gross ratio of deltaic elements develop bespoke facies models. from selected analogues. Parasequence-set type 2.5 very coarse coarse medium ﬁne very ﬁne Aggradational Progradational Retrogradational n = 65 n = 241 n = 110 100% N = 103 undef. undef. undef. 2 80% Deltaic Deltaic Deltaic 60% D/S D/S 1.5 D/S 40%

Shoreface 1 20% Shoreface Shoreface

N = 416

Proportion of parasequences 0% 0.5 100% undef. undef. undef. undef. Grainsize standard deviation (phi) 80% Deltaic 0 Deltaic -1 0 1 2 3 4 Deltaic 60% Mean grainsize (phi) Deltaic D/S D/S D/S Tidal sand ridges East Bank, North Sea 40% D/S Western Yellow Sea Southern North Sea Shoreface Shoreface 20% Shoreface Korea Strait Eastern Yellow Sea Shoreface N = 681

Above. SMAKS output on grainsize statistics relating to the Proportion of parasequences 0% deposits of recent shelf tidal sand ridges. this type of output LST TST HST FSST contributes to the compilation of quantitative facies models, n = 118 n = 162 n = 376 n = 25 Systems-tract type which may find application as templates for assisting with sub-environment interpretation of ancient deposits. The Above. SMAKS output on the relative proportion of discrimination of grain-size domains can be applied to parasequences classified on environment of origin across predict expected reservoir quality. different types of parasequence sets and systems tracts. Page 5 SMAKS

Fluvial, Eolian & Shallow-Marine Research Group http://frg.leeds.ac.uk/

How can SMAKS be applied for subsurface characterization? The ability to query for sedimentological properties and analogues, which incorporate variability in sediment- to apply filters to SMAKS output permits the selection ological and stratigraphic properties, and are therefore of analogues that share user-specified characteristics, suitable for the quantification of associated which could be sedimentological characteristics or uncertainty. These serve as quantitative facies models parameters that describe the depositional context. The that can be used to predict reservoir heterogeneity, synthesis of quantitative information from multiple conditioning stochastic geocellular reservoir models, case studies results in the construction of composite and guide well-to-well correlations of sandbodies.

250000 element length width N = 279

200000

dominant tide

150000

100000

Sand-ridge length (m) 50000

0 Mesotidal Macrotidal

Above. SMAKS output on the geometry of architectural and geomorphic elements classified as shelf tidal sand ridges.

100000 80 IVF width

Thickness 10000 60

1000 40

100 20 Maximum estuary width (m) Incised-valley fill thickness (m) N = 143 10 0 10 100 1000 10000 100000 Active Passive Transform Estuary drainage area (km2 ) Continental margin type Macrotidal estuary Above. SMAKS output on the thickness of Quaternary Geomorphic element (N = 21) Mesotidal estuary incised-valley fills classified by type of continental margin Architectural element (N = 11) Microtidal estuary across which they developed. SMAKS stores information Undefined tidal range on >100 IVFs from both late Quaternary and ancient settings. The database quantifies the geometry and proportion of systems tracts, and of architectural elements Above. SMAKS output on the relationship between the width of different hierarchies within IVFs. Resultant bespoke of ’estuary’ architectural and geomorphic elements and the facies models aid subsurface characterization. size of the estuary catchment. Page 6 SMAKS

Fluvial, Eolian & Shallow-Marine Research Group http://frg.leeds.ac.uk/ SMAKS output SMAKS content All data stored within SMAKS can be filtered on SMAKS currently includes data associated with: analogue depositional-system parameters or Ÿ >220 case studies; associated architectural properties to match with a given subsurface system of interest. Example outputs Ÿ 581 subsets; from the SMAKS database are presented throughout Ÿ 815 classified depositional tracts; this document. Ÿ 4,892 architectural elements; In its most basic form, SMAKS output consists of quantitative information about: Ÿ 1,889 geomorphic elements; Ÿ proportions of genetic units within higher-scale Ÿ 2,354 geological surfaces; units or volumes; Ÿ 2,171 sequence stratigraphic units; Ÿ geometrical parameters of genetic units; Ÿ 38,684 facies units; Ÿ spatial relationships of genetic units in three Ÿ 86 datasets with substantial statistical summaries. dimensions. Over 500 additional peer-reviewed articles have been This output can be employed to generate information identified as containing architectural data suitable for directly applicable to subsurface problems, such as database input, which is on-going. Figures are correct plots of genetic-unit width-to-thickness aspect ratios, as of June 2020. tabulated genetic-unit transition statistics, statistical distributions of user-defined genetic-unit net-to-gross The following pages present example output to values. demonstrate how SMAKS can be applied.

1.0 1.0 1.0

0.8 0.8 0.8

0.6 0.6 0.6

0.4 0.4 0.4

0.2 0.2 0.2 in incised-valley fills 0.0 0.0 0.0 Fraction of fluvial deposits Fraction of tide-dominated Fraction of wave-dominated elements in incised-valley fills Enclosed/semi-encl. sea Open ocean elements in incised-valley fills Enclosed/semi-encl. Open ocean Enclosed/semi-encl. Open ocean N = 23, σ = 0.311 N = 26, σ = 0.294 N = 23, σ = 0.124 N = 26, σ = 0.321 N = 23, σ = 0.328 N = 26, σ = 0.301 Above. SMAKS output on the proportion of wave-, tide- and river-dominated deposits in incised-valley fills classified according to their physiographic setting.

105 Cross-shelf incised-valley ﬁlls 1.0

4 10 0.8

0.6 103 IVF width (m) 0.4

10 thickness ratio 0.01 0.1 1 10 0.2

Mean tidal range (m) Systems-tract-to-IVF Above. SMAKS output relating incised-valley fill (IVF) 0.0 width to mean tidal range at the shoreline. Information such LST TST HST as this can be used to help refine gross depositional N = 18 N = 18 N = 18 environment models in exploration targets. Where sand- prone geobodies are present in IVFs, knowledge of Above. SMAKS output on the relative preservation of regional tidal regime is important for predicting potential deposits associated with different systems tracts in cross- reservoir scale. shelf incised-valley fills. Page 7 SMAKS

Fluvial, Eolian & Shallow-Marine Research Group http://frg.leeds.ac.uk/

SMAKS application 1: analysis of delta lobe progradation and stacking 4

Burdekin 3 T 2 Delta lobe M Yellow River 1 Po W

Mean tidal range (m) Mississippi Ebro Rhô ne 0 0 0.2 0.4 0.6 0.8 1.0 Mean annual signiﬁcant wave height (m)

100k N = 38 parasequences N = 70 elements

10k Modiﬁed after Roberts et al. (2004) 1000 120 N = 375 parasequences N = 62 elements 100

100 Duration (yr)

80 10

60 1

Thickness (m) 40 N = 38 N = 24 N = 46 deltaic PS delta lobes

20 Type of sedimentary unit higher-order deltaic units 0 45

40 N = 48 N = 20 N = 375 N = 42 deltaic PS deltaic PS delta lobes 35 yr 30 2-10 3 10 25 Type of sedimentary unit higher-order deltaic units 20

SMAKS output quantifying the spatio-temporal significance Thickness (m) of different ranks of deltaic constructional units recognized 15 in the stratigraphy of active deltas; a comparison is made 10 with recent and ancient deltaic parasequences. Violin plots show distributions in the length of time over which these 5 types of units have developed and in their maximum 0 observed thickness. The boxes in the plots represent 10 100 1000 10k 100k interquartile ranges and horizontal bars represent medians. Duration (yr)

The scatterplot (D) shows the maximum thickness of both Deltaic parasequence (N = 38) Burdekin Po parasequences and deltaic units versus the duration of time Delta lobe (N = 34) Ebro Rhône over which they have developed. Higher-scale deltaic unit (N = 17) Mississippi Yellow River

Page 8 SMAKS

Fluvial, Eolian & Shallow-Marine Research Group http://frg.leeds.ac.uk/

SMAKS application 2: analysis of the geometry of shoreface parasequences T- Example classiﬁcations Parasequence attributes sstL deltaic, Fw sstT psT

shoreface, W pD

sR (+ ) Normal regressive evolution α with aggradation PS

datum close to palaeohorizontal α Forced regressive evolution sR (–)

PS PS pD

fs PS thickness (psT) PS progradation distance (pD)

Onshore deposits PS shallow-marine sandstone thickness (sstT) PS stratigraphic rise [aggradation/degradation] (sR) Shallow-water sands PS shallow-marine sandstone dip length (sstL) PS progradation angle (α) Oﬀshore/prodeltaic deposits Quantitative characterization of clastic parasequences in SMAKS.

600 Undeﬁned 500 F N = 151 400

300 Number of Wparasequences- Fw Ft 200

100 Fwt Ftw Deltaic F- 0 Shoreface Wft Tfw Wf Tf Wtf Twf

W Wt Tw T T- 0 N N = 1,163 Deltaic/shoreface N = 866 1 10 20 30 40 Environment type General process regime Detailed process regime Relative frequency of different classes of SMAKS clastic parasequences.

Deltaic (real/apparent) River dominated (real/apparent) 1M Deltaic (partial/unlimited) 1M River dominated (partial/unlimited) Deltaic/shoreface (real/apparent) Tide dominated (real/apparent) Deltaic/shoreface (partial/unlimited) Tide dominated (partial/unlimited) Shoreface (real/apparent) Wave dominated (real/apparent) Shoreface (partial/unlimited) Wave dominated (partial/unlimited) 100k 100k

10k 10k

1000 1000 sand dip length (km) sand dip length (km) Parasequence shallow-marine N = 407 Parasequence shallow-marine N = 328 100 100 0.1 1 10 100 0.1 1 10 100 Parasequence shallow-marine Parasequence shallow-marine sand thickness (m) sand thickness (m) Above. Geometry of different classes of parasequence-scale nearshore sandbodies. Page 9 SMAKS

Fluvial, Eolian & Shallow-Marine Research Group http://frg.leeds.ac.uk/

SMAKS application 3: controls on parasequence set stacking patterns Progradational parasequence set

ement displac 4 se in P decrea 3 2 fault plane 1 Aggradational parasequence set

4 Oﬀshore/prodeltaic deposits A 3 S 2 Shallow-water sands A 1 Onshore deposits Retrogradational parasequence set

BASINWARD 4 Modiﬁed after Zecchin et al. (2006) 3 2 Above. Idealized example illustrating a tectonically driven mechanism for the 1 co-variation of parasequence thickness and stacking pattern. After Van Wagoner et al. (1990) coastal-plain deposits shelf mudstone shallow-marine sandstone N parasequence 1M N = 386 N = 218

100k

P 60 n = 241

10k 40

A n = 65 20 1000 Parasequence thickness (m)

R Parasequence sand dip length (m) n = 110 0 100 N = 416 Progradational Aggradational Retrogradational Progradational Aggradational Retrogradational Parasequence-set type Parasequence-set type Above. SMAKS output on the geometry of clastic parasequences in parasequence sets classified on stacking pattern. SMAKS has been applied to investigate how N = 79 100k N = 81 30 accommodation, sediment supply and autogenic sediment-storage dynamics are recorded in the sedimentary architecture and stacking patterns of 20 10k shallow-marine sand bodies. Results are used to evaluate the validity of paradigms and models that are routinely used to explain and predict trends in the 10 anatomy and arrangement of parasequences. 1000 Data on 957 parasequences from 62 case studies of clastic, shallow-water successions are incorporated 0 in this analysis. Database outputs indicate which Parasequence stratigraphic rise (m) -5

Parasequence progradation distance (m) proxies of accommodation, sediment supply and 100 accommodation/sediment-supply ratio are Progradational Aggradational Retrogradational Progradational Aggradational Retrogradational Parasequence-set type Parasequence-set type significant as predictors of parasequence architecture, and allow for interpretations of the Above. SMAKS output on the progradation style of clastic importance of allogenic and autogenic factors. parasequences in parasequence sets classified on stacking Results have implications for how subsurface pattern. successions are interpreted from limited well data. Page 10 SMAKS

Fluvial, Eolian & Shallow-Marine Research Group http://frg.leeds.ac.uk/

SMAKS application 4: determination of the role of relative-sea-level change and rates of sediment delivery in governing shoreface sandstone trajectory

Analysis using the SMAKS database has yielded the 100k Progradation angle following novel insights: (i) parasequence thickness FORCED REGRESSION varies as a function of water depth, accommodation Sand dip length generation and erosional truncation, and these N = 9 variations are also reflected across types of systems 10k tracts and parasequence sets; (ii) the dip length of parasequence sand bodies demonstrates scaling with measures of accommodation/sediment supply ratio at multiple scales, partly in relation to the possible effect 1000 of sediment supply on progradation rates; (iii) in systems tracts, stratigraphic trends in parasequence R = 0.711 stacking due to autogenic mechanisms or to p = 0.032 acceleration or deceleration in relative sea-level 100 fluctuations are not revealed quantitatively; (iv) some Parasequence sand dip length (m) -0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 association is seen between the abundance of deltaic Negative parasequence progradation angle (°) or river-dominated parasequences and progradational 100k partial or unlimited length true or apparent length stacking; (v) positive but modest correlation is observed between measures of river-system size and R = –0.463 the dip length of shallow-marine parasequence sand p < 0.001 bodies. The resulting insights can be applied to guide 10k sequence stratigraphic interpretations of the rock record and the characterization of sub-seismic stratigraphic architectures of subsurface successions. The quantification presented in this work can be 1000 N = 121 referred to when attempting predictions of likely Sand dip length volume, geometry and compartmentalization of DEPOSITIONAL shallow-marine sand bodies, on the basis of REGRESSION Progradation angle constraints of accommodation and sediment supply 100 that may be available in subsurface studies, Parasequence sand dip length (m) 0.001 0.01 0.1 1 10 particularly from those based on regional seismic Positive parasequence progradation angle (°) stratigraphy and source-to-sink analyses. 100k n = 178 parasequences R = –0.402 Dunvegan Fm. 100k N = 23 depositional tracts p = 0.057

Frontier Fm. ‘Vernal delta’ Gallup Fm. Fox Hills Fm. Wall Creek Mb. Frontier Fm. Second Frontier Sst. Po 10k Rhône 10k R2 = 0.304 Ferron Sst. ‘Last Chance delta’ DEPOSITIONAL Ferron Sst. REGRESSION ‘Notom delta’

n = 273 parasequences PS fs Straight Cliﬀs Fm. N = 12 successions PS fs 1000 PS 0 50k 100k 150k 2 200k River-system drainage area (km ) Mean parasequence sand length (m) 1000 Mean parasequence sand length (m) 0.001 0.01 0.1 1

Cretaceous WIS Cretaceous WIS Depositional-tract shoreline trajectory (°) Quaternary delta (outcrop) (subsurface ± outcrop)

Above. SMAKS output on the relationship between feeder- Above. SMAKS output on relationships between regressive system type and dip length of deltaic parasequence shoreline trajectory (at parasequence and depositional-tract sandbodies. WIS = Western Interior Seaway, Cret., USA. scales) and dip length of parasequence sandbodies. Page 11 Fluvial, Eolian & Shallow-Marine Research Group http://frg.leeds.ac.uk/

Depositional tracts Mesotidal Macrotidal 250000 sea level N = 281

modern systemscoastal plain 200000

shoreface 150000 coastal plain offshore 100000 shoreface offshore transition offshore transition SMAKS ancient systems parasequence 50000 parasequence Shallow-Marine Architecture

offshore Sand-ridge length (m) parasequence HST 0 0 5000 10000 15000 20000 Knowledge Store Sand-ridge width (m) The Shallow-Marine Architecture Knowledge Store is a relational database devised for the storage of hard and soft data on the sedimentary architecture of ancient shallow-marine and paralic siliciclastic successions, and on the geomorphological organization of corresponding modern environments. The database allows incorporation of data from the published literature, which are uploaded to a common standard to ensure consistency in data definition. The database incorporates data on geological entities of varied nature and scale (i.e., surfaces, depositional tracts, architectural elements, sequence stratigraphic units, facies units, geomorphic elements), including attributes that characterize their type, geometry, spatial relations, hierarchical relations, and temporal significance. Geological entities are assigned to depositional systems, or to parts thereof, that can be classified on multiple parameters (e.g., shelf width, delta catchment area) tied to metadata (e.g., data types, data sources). Ÿ Examine data from wave-, tide-, and fluvial dominated shallow seas, from backshore to shelf-edge settings. Ÿ Quantitative characterization of modern and ancient shallow-marine and paralic clastic depositional systems. Ÿ Serves as a repository of analogue information for subsurface reservoir successions. Ÿ Can be applied to aid the development of depositional models for particular types of paralic and shallow-marine reservoirs. Ÿ Assess the sensitivity of depositional systems to particular controlling factors. Ÿ Predict element shape & size as a function of independent external controls (sea level history, basin type, subsidence rate). Ÿ Build bespoke facies models for particular classes of paralic and shallow-marine sedimentary succession.

SMAKS analogues

To enhance sponsor impact, FRG-ERG-SMRG has Above. Geographic distribution of some of the collaborated with external partner PDS to develop Ava Clastics, >220 analogue studies contained in SMAKS, as of a product that enables direct coupling of FAKTS & SMAKS with June 2020. Database population is on-going. modelling workflows: www.pds.group/ava-clastics/

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