PETROPHYSICAL PROPERTIES OF THE TENSLEEP
SANDSTONE AT SAGE CREEK FIELD, BIGHORN BASIN,
WYOMING
by
Ricky Adi Wibowo A thesis submitted to the Faculty and Board of Trustees of Colorado School of
Mines in partial fulfillment of the requirements for the degree of Doctor of Philosophy
(Geology).
Golden, Colorado
Date______
Signed:______Ricky Adi Wibowo
Approved:______Dr. Neil F. Hurley Thesis Advisor
Golden, Colorado
Date______
Dr. Murray Hitzman Professor and Interim Head, Department of Geology and Geological Engineering
ii ABSTRACT
The Tensleep Sandstone of Middle Pennsylvanian to Lower Permian age occurs
throughout central and north-central Wyoming. Eolian deposits dominate the upper half
of the 120 ft (37 m) thick formation. The lower half consists of mixed marine and eolian
sediments. Sedimentary structures, petrophysical properties, and genetic units are the
keys to define facies within the eolian system. Grain flow strata with loose grain packing
have better reservoir characteristics than more tightly packed wind ripple facies. Both
rock types are commonly found in porous and permeable eolian cross-stratified facies.
Related deposits, such as interdune, dolomitic sandstone, and marine facies, are lower
quality reservoirs when compared to the eolian cross-stratified sediments. Bounding surfaces of the first-, second- and third-order define compartmentalization in eolian dune deposits.
The study objectives are: (1) describe facies of the eolian and other associated deposits within the Tensleep Sandstone, including the signatures of eolian bounding surfaces, (2) describe small-scale heterogeneity within eolian deposits using petrophysical analyses based on capillary pressure, minipermeameter, laboratory nuclear magnetic resonance (NMR), and petrography, and (3) relate petrophysical analysis results
iii from one cored well to another non-cored well that has FMI (Formation Micro Imager) and CMR (Combinable Magnetic Resonance) logs.
The Sage Creek field area in the northern Bighorn basin, Wyoming, provides three different Tensleep data sets. Bear Canyon is a nearby excellent outcrop located about 7 mi (11 km) northeast of the field. A cored interval of the Tensleep Sandstone is available from the Fox #1 well and a complete log suite, including FMI and CMR logs, is available from the SCU #21 well.
The measured section at Bear Canyon suggests that the Tensleep Sandstone is divided into the eolian-dominated Upper Tensleep and mixed eolian-marine sediments of the Lower Tensleep. A detailed core description and petrophysical analyses of 18 samples from the Fox #1 well suggest that facies controls permeability and porosity.
Minipermeameter measurements sampled every 0.5 ft (15 cm), combined with mercury injection capillary pressure (MICP), nuclear magnetic resonance (NMR) tests, and petrographic analysis demonstrate the various facies within the Tensleep Sandstone.
T2 is a measure of the relaxation time of hydrogen protons subjected to NMR testing. Fast decay T2 distributions are related to wind ripples and commonly show
bimodal curves in the CMR logs. The grain flow facies has longer T2 times and a
unimodal distribution. Interdune, dolomitic sandstone and marine facies commonly show
similar T2 distributions, which involve fast decay times.
Petrophysical properties from the core relate to the same eolian intervals from a
different well with a CMR log. The combination of the FMI and CMR logs can be used
iv to define the eolian facies within the Tensleep Sandstone interval. The T2 distributions from the CMR log are used to define the grain flow and wind ripple strata, while the FMI log is used to determine bounding surfaces and facies within the eolian system.
v TABLE OF CONTENTS
Page
ABSTRACT……………………………………………………………………………iii
LIST OF FIGURES…………………………………………………………………....x
LIST OF TABLES…………………………………………………………………...xvi
ACKNOWLEDGMENTS…………………………………………………………..xvii
Chapter 1 INTRODUCTION…………………………………………………….… 1
1.2. Research Objectives…………………………………….…………..… 4 1.3. Previous Investigations…………………………………………….… 5 1.4. Research Contributions……………………………….…..………….. 8
Chapter 2 GEOLOGICAL SETTING……………………………….……………. 9
2.1. Study Area…………………………………………………………… 9 2.2. Stratigraphy and Sedimentology………………………………….… 10 2.2.1. Regional Stratigraphy………………………………………... 10 2.2.2. Tensleep Sandstone………………………………………….. 16 2.2.2.1. Paleogeographic Setting……………………………. 20 2.2.2.2. Eolian Processes………………………………….…. 24 2.2.2.3. Lithofacies…………………………………………… 29 2.2.2.4. Parasequences and Bounding Surfaces………….…... 33 2.2.2.5. Reservoir Heterogeneity…………………………….. 39 2.2.3. Local Stratigraphy……………………………………………. 44 2.3. Structural Geology…………….………………………………….… 46 2.3.1. Regional Structural Geology…………………………………. 46 2.3.2. Local Structural Geology…………………………………….. 48
vi Page
2.4. Petroleum Geology………….………………………………….…… 49
Chapter 3 OUTCROP STUDY: BEAR CANYON, PRYOR MOUNTAINS…… 57
3.1. Introduction.…….………….………………………………….……. 57 3.2. Location……….. …………………………………………..…….…. 59 3.3. Lithofacies Types…………………………………………..…….…. 60 3.4. Description of Measured Section…………………………..…….…. 63 3.5. Bounding Surfaces………………….….…………………………….. 70 3.6. Discussion…………………………………………………………… 72
Chapter 4 SAGE CREEK CREEK FIELD CORRELATION …….……………. 75
4.1. Index Map……….………..….……………………………..….……. 75 4.2. Correlation Framework……………………………………….……... 77 4.2.1. Well Log Signatures………..………………………………… 78 4.2.2. Comparison to Outcrop………………………………….…… 84 4.3. Discussion……………………………………………………..…….. 88
Chapter 5 SAGE CREEK FIELD: CORE DESCRIPTION, FOX #1….……….. 90
5.1. Introduction……………………………………………………….…..90 5.2. Location………………………………………………………….….. 91 5.3. Lithofacies Types……………….…………..………………….……. 91 5.3.1. Marine Sandstone...……………………………………….…. . 96 5.3.1.1. Physical Description ………………………………... 96 5.3.1.2. Discussion – Marine Sandstone……….……………. 102 5.3.2. Eolian Sandstone……………………………………………. 103 5.3.2.1. Physical Description………………….……………. 104 5.3.2.2. Wind Ripple Facies………………………………… 107 5.3.2.3. Grainflow Facies…………………….……………... 109 5.3.2.4. Grainfall Facies…………………….……………... 110 5.4. Bounding Surfaces……………………………………….………… 111 5.5. Core Analyses………………………………………………….…... 112 5.5.1. Conventional…………………………………………….….. 113
vii Page
5.5.2. Minipermeameter…………………………………………… 116 5.5.3. Capillary Pressure Analysis………………………………… 123 5.5.4. Nuclear Magnetic Resonance (NMR) Analysis…………….. 153 5.5.4.1 NMR T2 Distribution….……………………………. 155 5.5.4.2 NMR Porosity……....………………………………. 158 5.5.4.3 NMR T2 Cutoff…………..…………………………. 159 5.5.4.4 NMR Permeability ….……………………………… 163 5.5.4.5 NMR Pore Size Distribution..……….……………… 169 5.5.5 Dykstra-Parson Coefficient....……………………………….. 175 5.5.6 Petrography…………………....……………………………... 180 5.6. Discussion…………………………………………………………... 186
Chapter 6 SAGE CREEK FIELD: PETROPHYSICAL ANALYSIS, SAGE
CREEK UNIT (SCU) #21……….…………………………………….. 188
6.1. Location………………………………….…………………………. 188 6.2. Borehole Images Analysis……………………………………..…... 189 6.2.1. Introduction to Borehole Image Logs…………………….… 191 6.2.1.1 Dip Determination…………………………………... 192 6.2.1.2 Lithology Determination………………………….… 194 6.2.1.3 Removal of Structural Dip…………………………... 199 6.2.2. Description of Stratification……………………………….... 202 6.2.3. Bounding Surfaces……….………………………………..… 204 6.3. Combinable Magnetic Resonance (CMR) Analysis………………. 219 6.3.1. Introduction to NMR logging..……………………………… 220 6.3.2. Porosity……………………………………………………… 226 6.3.3. Porosity Result from the SCU #21 well…………………...… 229 6.3.4. Permeability…………………………………………………. 238 6.4. Discussion…………………………….…………………………….. 247
Chapter 7 DISCUSSION……………………………………………………..……. 250
Chapter 8 CONCLUSIONS AND RECOMMENDATIONS……………..…….. 260
viii Page
REFERENCES……………………………………….…………………………….. 263
Appendix A Measured Section at Bear Canyon
Appendix B Fox #1 Well Core Description and Photographs
Appendix C Fox #1 Well Data
Appendix D Core Analysis Report
Appendix E Sage Creek Unit #21 Well Data
(All appendices are in CD at the back of this dissertation)
ix LIST OF FIGURES
Page
Figure 1.1 Location map Sage Creek field………………………………………….... 3
Figure 2.1 Bighorn basin map ………..…………………………………………...... 11
Figure 2.2 Asymmetrical synclinal cross section……………..……………………... 12
Figure 2.3 Stratigraphic column of Bighorn basin …….………………………..…... 13
Figure 2.4 Stratigraphic chart of Bighorn, Wind River, and Powder River basins..… 17
Figure 2.5 Columnar section of stratigraphy at Tensleep Canyon………………….... 19
Figure 2.6 Pennsylvanian to Early Permian paleogeographic map………………….. 21
Figure 2.7 Eolian paleodispersal patterns in Bighorn basin…………………………. 22
Figure 2.8 Schematic air flow diagram over dunes……….…………………………. 25
Figure 2.9 Transgressive strata by climbing bedforms.…………………..………...... 28
Figure 2.10 Lithofacies of the Tensleep Sandstone with their interrelations…………. 30
Figure 2.11 Eolian bedforms of different hierarchy ……………….…………………. 35
Figure 2.12 Three orders of bounding surfaces ………………………………………. 35
Figure 2.13 Bounding surfaces in the Tensleep Sandstone ………..…………………. 36
Figure 2.14 Scales of reservoir heterogeneity ………………….……..………………. 40
Figure 2.15 Permeability heterogeneity due to stratification …………………………. 42
Figure 2.16 Permeability heterogeneity at bounding surfaces …………………..……. 43
Figure 2.17 Tensleep Sandstone type log at SCU #21 ……………….………………. 45
x Page
Figure 2.18 Structural map top of Dinwoody at Sage Creek ………………………… 49
Figure 2.19 Burial history of the Bighorn basin…………….………………………… 51
Figure 2.20 Structural contour map of Sage Creek……………………………………. 55
Figure 2.21 Origin of tilted oil-water contact in Sage Creek ………………………..... 56
Figure 3.1 Topographic map of Bear Canyon measured section area……………….. 58
Figure 3.2 Comparison to the section of Mankiewicz & Steidtmann (1979)……...… 60
Figure 3.3 Bear Canyon measured section column.…………………………………. 61
Figure 3.4 Line of measured section at Bear Canyon area.………………………….. 62
Figure 3.5 Tabular-planar cross-strata facies outcrop.……………………………..... 64
Figure 3.6 Interdune and dolomitic sandstone facies outcrop……………………….. 65
Figure 3.7 Grain flow and wind ripple facies outcrop……………………………….. 68
Figure 3.8 Large-scale deformed sandstone facies outcrop. …………………...……. 69
Figure 3.9 Photomosaic of the Tensleep Sandstone at Bear Canyon ...... …………. 71
Figure 4.1 Base map of Sage Creek field……………………………………………..76
Figure 4.2 SCU #21 well Tensleep Sandstone subdivisions…………………………. 79
Figure 4.3 SCU #7 well Tensleep Sandstone subdivisions..…………………………. 80
Figure 4.4 Isopach map of top Dinwoody to Tensleep ...... …………………….... 83
Figure 4.5 Structural map on top of T3 subzone in the Tensleep……………………. 85 Figure 4.6 Location map of measured section at Bear Canyon to Sage Creek...... 86 Figure 4.7. Correlation from Fox #1, SCU #21, and measured section at Bear Canyon ………………….……….…..……….……………………….….. 87
xi Page
Figure 5.1 Location map of Fox #1 well………………….……….…..….….…….. 92
Figure 5.2 Core profiles of Fox #1 well…..……………………………………….... 94
Figure 5.3 Core profiles and log display of the Fox #1 well…………...…………....95
Figure 5.4 Core photo of marine and dolomitic sandstone facies ...…...………….... 97
Figure 5.5 Core photo of interdune, sabkha, and dolomitic sandstone facies……….99
Figure 5.6 Core photo of TCS_WR at 3502-3504 ft core depth……………………. 100
Figure 5.7 Core photo of large-scale deformed lithofacies………………..……...... 101
Figure 5.8 Core photo of tabular-planar cross-stratified lithofacies..……..………... 105
Figure 5.9 Log display of Fox #1 well with the Tensleep subdivisions .…………... 114
Figure 5.10 k vs. φ of plugs from core lab……………….………………..………... 115
Figure 5.11 Cross plot k-miniperm vs. k-core lab……….………………..………... 117
Figure 5.12 Modified cross plot log 10 k-miniperm vs. k-core lab.………..……….....119
Figure 5.13 Modified cross plot k-miniperm vs. k-core lab...……….…………..…... 120
Figure 5.14 Permeability profiles based on log data…………..…….……….…..…... 122
Figure 5.15 Typical capillary pressure curve plot on semilog graph……………….... 126
Figure 5.16 Schematic figure of MICP apparatus …………………………………....127
Figure 5.17 Cross plot plugs φ vs. MICP φ………………………..….………………130
Figure 5.18 Capillary pressure curve of sample #6 ………………………………...... 132
Figure 5.19 MICP curves of interdune facies………………………………………... 135
Figure 5.20 MICP curves of grain flow and wind ripple facies.……………………... 136
Figure 5.21 Comparison of measured R35 to that estimated from Winland..………. 140
xii Page
Figure 5.22 Cross plot of measured R35 and estimated R35 from Winland Equation...... ………... 141
Figure 5.23 k and φ cores vs. R35 ………………………………………….………... 142
Figure 5.24 Cross plot of measured R35 and original Winland Equation.…………... 146
Figure 5.25 Plot of Hg saturation to determine the apex of Thomeer’s hyperbola…...148
Figure 5.26 The original log-log hyperbolic capillary plot…………………………... 151
Figure 5.27 Cross plot k-plugs vs. k-Swanson (MICP) ……………………………... 152
Figure 5.28 T2 distribution of saturated and partially saturated core from NMR tests...... 161
Figure 5.29 T2 peak and T2 cutoff variation…………..…………………………….. 162
Figure 5.30 Graphical comparison of SDR, Timur-Coates, and Coates model for permeability estimation…………….……..…………………………….. 167
Figure 5.31 A. Comparison T2 distribution and MICP pore size distribution of the interdune, and tabular-planar cross-stratified facies ……..…………...... 173
Figure 5.31 B. Comparison T2 distribution and MICP pore size distribution of the interdune, dolomitic sandstone and wind ripple facies..………………... 174
Figure 5.32 Probability plot using modified Dykstra-Parson approach.……………...178
Figure 5.33 Probability plot of all samples using modified Dykstra-Parson plot ….... 179
Figure 6.1 Location map of SCU #21 well ……………………………………….... 190
Figure 6.2 Schematic diagram of bedding planes in the borehole images ……..…... 195
Figure 6.3 FMI images of Tensleep Sandstone…..……………………………….....197
Figure 6.4 FMI images of Tensleep Sandstone…..……………………………….....198
Figure 6.5 Cumulative dip plot of “hotbeds” from the SCU #21 well ..………….... 201
xiii Page
Figure 6.6 Schematic internal stratification within the Tensleep Sandstone……….. 203
Figure 6.7 Expected FMI tadpole pattern of bounding surfaces.……...………….... 206
Figure 6.8 Interpreted dynamic image from the SCU #21 well ……....………….... 207
Figure 6.9 Interpreted dynamic image from the SCU #21 well ..……………..….... 208
Figure 6.10 Cumulative dip plot of all beds after rotation…….. ..……………..….... 209
Figure 6.11 Vector plot of all beds after rotation………………...……………..….... 210
Figure 6.12 Stereoplot and rose diagram of all beds ………………………………... 212
Figure 6.13 Stereoplot and rose diagram of 1.0-bounded set………………………... 213
Figure 6.14 Stereoplot and rose diagram of 2.0-bounded set………………………... 214
Figure 6.15 Stereoplot and rose diagram of 3.0-bounded set………………………... 215
Figure 6.16 Stereoplot and rose diagram of the Upper Tensleep…..………………....217
Figure 6.17 Stereoplot and rose diagram of the Lower Tensleep…..………………... 218
Figure 6.18 CMR tool and T2 time distribution diagram…………..………………... 222
Figure 6.19 Schematic figure of intergranular porosity..…………..………………... 224
Figure 6.20 Schematic diagram of the amplitude of T2 to the porosity……………... 228
Figure 6.21 Combination display of CMR and FMI logs of the Upper Tensleep….... 230
Figure 6.22 Porosity from CMR vs. cross plot density-neutron logs of SCU #21 well ...... …….….... 231
Figure 6.23 Porosity from CMR and traditional logs of SCU #21 well……………... 232
Figure 6.24 Porosity from CMR and traditional logs of SCU #21 well……………... 234
xiv Page
Figure 6.25 Combination display of CMR and FMI logs within the lower part of the Upper Tensleep ..……………………………………………..…...... 236
Figure 6.26 Compilation of permeability estimation based on models to k-CMR…... 241
Figure 6.27 Compilation of permeability estimation based on models with different coefficients…..……………………………………………….... 242
Figure 6.28 Combination display of CMR and FMI logs of the Lower Tensleep …... 243
Figure 6.29 Combination display of CMR and FMI logs of the upper part of the Lower Tensleep ……………………………………………………….... 244
Figure 6.30 Combination display of CMR and FMI logs of the upper part of the Upper Tensleep ……………………………………………………….... 245
xv LIST OF TABLES
Page
Table 5.1 Mercury injection capillary pressure (MICP) compilation data………… 133
Table 5.2 Compilation of pore throat radii of all samples ………………………… 144
Table 5.3 List of modified Winland equation resulting from the multiple regression analysis………………………………………………..……... 145 Table 5.4 Parameter used in Swanson’s coefficient and permeability…………….. 150
Table 5.5 NMR lab tabulation data ……………………..………………………….156
Table 5.6 Comparison T2 peak data from calculation and graphics………………. 171
Table 5.7 Incremental saturated data to be used in Dykstra-Parson probability plot...... 176 Table 5.8 Tabulation of Dykstra-Parson coefficient..…..…………………………. 181
Table 5.9 A. Petrographic data based on point count analysis..………………….... 184
Table 5.9 B. Petrographic data based on point count analysis..…………………… 185
Table 6.1 Comparison of TCMR, FFI, BFV, and permeability of eolian facies from the Fox #1 and SCU #21 wells……………………………………. 237 Table 7.1 Compilation from several methods used in this study to determine of eolian facies and associated deposits………………………………… 258 Table 7.2 Compilation from several methods used in this study to determine bounding surfaces within eolian system of the Tensleep Sandstone in Sage Creek field……………………………………………………… 259
xvi
xvii ACKNOWLEDGEMENTS
I would like to express gratitude to my advisor, Neil Hurley, for the direction and guidance he provided during this study. His insight and approach to geological and petrophysical problems will be a model for me through the rest of my career in geosciences. Sincere appreciation is also expressed to committee members Mary Carr,
John Warme, Max Peeters, Ramona Graves, Ning Lu and David Allen for their advice and review of my research and for being excellent teachers.
I benefited greatly from discussions with Alex Aviantara and would like to thank him for his contributions to this study. I gratefully thank David Allen, whose company
Schlumberger has generously supported this study. I express my gratitude to Phoenix
Production Company who provided all data from Sage Creek field.
My doctorate program at the Colorado School of Mines was made possible by the financial support provided by the Indonesian Oil and Gas Company (PERTAMINA). I am indebted to PERTAMINA for this great opportunity. I am also indebted to the Society of Professional Well Log Analysts (SPWLA) and American Association of Petroleum
Geologists (AAPG) for financial support in the form of student research grants.
Finally, I would like to dedicate this study to my wife Sari, to my kids Dito and
Dinda, for their patience, encouragement and support.
xvii 1
CHAPTER 1
INTRODUCTION
The Tensleep Sandstone of Middle Pennsylvanian to Lower Permian age is composed of eolian and marine sediments deposited throughout central and north-central
Wyoming. The formation is one of the major hydrocarbon producers in Wyoming, particularly in the Bighorn basin.
Studies of modern and ancient eolian systems have revealed the complex and heterogeneous nature of eolian deposits. Compartmentalization within eolian deposits is controlled by internal bounding surfaces that are the product of accumulation and preservation dynamics of eolian systems. In the late development stages of Tensleep reservoirs, understanding of compartmentalization and fluid flow within eolian systems is important to increase production rates, recoveries and the efficiency of EOR operations.
Within the Tensleep Sandstone, a hierarchy of heterogeneity types has been identified in outcrop and core. Large-scale heterogeneity, defined by sandstone-dolomite interbeds, is easily recognized using conventional logs. However, smaller-scale heterogeneity defined by erosional bounding surfaces and cross stratification, is more difficult to identify although they have a significant impact on EOR. They are not definable using conventional log suites. In order to improve our ability to define small- 2
scale heterogeneity within eolian strata, it is important to use logging tools that have high
vertical resolution and continuous core. Petrophysical analysis of various facies is
necessary to define small-scale heterogeneity in an eolian system.
Borehole images and nuclear magnetic resonance (NMR) logging tools have been
widely applied. Borehole images can detect fractures, facies types and paleocurrent
orientations. NMR tools can measure porosity, pore size, and permeability in the borehole. The combination of borehole image and NMR data with conventional data from another well, such as standard logging suites, core, and laboratory measurements, can be used to determine the facies heterogeneity from two different wells.
The Sage Creek field is located along the north-northeast edge of the Bighorn basin, Wyoming (Figure 1.1). This field produces mainly from the Tensleep Sandstone with lesser production from the Madison Limestone. Within this field there are two wells that are important to this study: (1) the Fox #1 well (Section 18-T57N-R97W) has a core drilled from the upper Tensleep through the lower Tensleep, and (2) the Sage Creek Unit
(SCU) #21 well (Section 7-T57N-R97W) has a complete log suite that includes
Schlumberger’s Formation MicroImager (FMI) and Combinable Magnetic Resonance
(CMR) logs. The wells are about 1.6 mi (3.2 km) apart with the Fox #1 in a downwind position to the south-southwest of SCU #21 (Figure 1.1).
In this study, a detailed core description of the Fox #1 well has been compared to
FMI and CMR data from the SCU #21 well. Petrophysical analysis includes mercury injection capillary pressure (MICP), minipermeameter, and NMR data from core plugs 3 . s r n a a v e i r
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from the Fox #1 well. Detailed stratigraphic cross sections within Sage Creek field have been used to correlate between the Fox #1 and SCU #21 wells. A nearby measured section has been used to improve facies analysis within the Tensleep Sandstone. All results are used as the basis for borehole image and NMR interpretation. The study quantifies, integrates, and analyses geological, petrophysical, and engineering data of the various eolian reservoir facies that are useful for oil recovery.
1.1 Research Objectives
The main objective of this study is to characterize petrophysical properties of the
Tensleep eolian reservoir at Sage Creek field. Other objectives are:
• Describe facies of the eolian and other associated deposits (grain flow, wind ripple,
marine carbonate, and interdune) within the Tensleep Sandstone at Sage Creek field,
including the signatures of the first-, second- and third-order bounding surfaces in the
eolian system using outcrops, cores, and borehole image logs.
• Describe small-scale heterogeneity within eolian deposits of the Tensleep Sandstone,
which are not definable using conventional log suites. Petrophysical analysis of the
various eolian facies includes capillary pressure, minipermeameter, conventional
core, and laboratory NMR. 5
• Describe the eolian Tensleep Sandstone interval with a detailed core description of
the Fox #1 well, its subsurface correlation to the other wells within the Sage Creek
field, and its comparison to the nearby outcrop measured section at Bear Canyon.
• Relate petrophysical analysis results from the Fox #1 core to the NMR-based well log
(CMR) from the SCU #21 well. Define the eolian facies variation in combination
with the FMI log.
1.3 Previous Investigations
The Tensleep Sandstone has been studied extensively by many authors. Several of
those investigations have a close relationship to the objectives of this research.
• Hubbert (1953) studied hydrodynamic flow and the controls on the tilted oil-water
contact in the Tensleep reservoir at Frannie field.
• Lawson and Smith (1966) and Simmons and Scholle (1990) believed that regional
uplift and tilting of the Tensleep Sandstone occurred in the area before deposition of
the Permian Phosphoria Formation.
• Stone (1967) cited the influence of hydrodynamic flow to the south and southwest as
the main cause of the tilted oil-water contact at Sage Creek and Frannie fields. 6
• Pedry (1975) strongly supported the idea that hydrodynamics was the main factor
causing tilting of the oil-water contact at Sage Creek field.
• Mankiewicz and Steidmann (1979) interpreted the lithologies and sedimentary
structures in the Tensleep Sandstone as both eolian and marine deposits. They also
described diagenesis in the Tensleep Sandstone.
• Andrews and Higgins (1984) suggested that the lower and upper Tensleep have
different characteristics based upon heterogeneities. The fabric of the depositional
facies primarily controls these heterogeneities, diagenesis, and fracturing, which must
be considered in reservoir studies.
• Wheeler (1986) described fluctuations of sea level as the major factor controlling
cycles and repetition of marine and eolian facies within the Tensleep Sandstone.
• Kerr (1989) and Kerr and Dott (1988) described parasequences within the Tensleep
Sandstone along the eastern margin of the Bighorn basin.
• Hurley (1994) introduced a new technique using borehole image data to determine
breaks in stratigraphy that record faults or unconformities in rock layers. One of his
case studies applied this technique to the Tensleep Sandstone.
• Shebl (1995) studied the impact of reservoir heterogeneity on fluid flow to show that
flow parallel to bounding surfaces is preferentially higher than flow across them.
• Dunn et al. (1996) and Carr-Crabaugh and Dunn (1996) studied anisotropy and
spatial variation of relative permeability and lithologic character of Tensleep
Sandstone reservoirs in the Bighorn and Wind River basins. 7
• Phoenix Production Company, as the owner and operator of Sage Creek field, hired
consultants to study the Tensleep Sandstone. Their work is summarized in the
unpublished report of the Sage Creek Tensleep Reservoir Study (Borah-Borah, 1996).
• Carr-Crabaugh et al. (1996) interpreted eolian reservoir architecture in the Tensleep
Sandstone using borehole images.
• Aviantara (2000) studied facies architecture of the Tensleep Sandstone in the eastern
Bighorn basin based upon parasequences that were correlated using outcrop and
subsurface data.
• Ciftci (2001) built a 3-D model of the eolian Tensleep Sandstone based on outcrop
data from the eastern Bighorn basin.
1.4 Research Contributions
This study has led to the following contributions to better understanding of eolian systems, particularly the Tensleep Sandstone in the Bighorn basin:
1. Various facies of eolian and associated deposits such as grain flow, wind ripple,
interdune, dolomitic sandstone, and marine, can be described using outcrops at Bear
Canyon, cores from the Fox #1 well, and borehole images of the SCU #21 well.
Loosely packed grain flow strata indicate better reservoir performance compared to 8
the more tightly packed wind ripple strata within the cross-stratified eolian facies.
The interdune, dolomitic sandstone and marine facies commonly act as impermeable
zones within the eolian systems.
2. The first-, second-, and third-order bounding surfaces in the eolian strata of the
Tensleep Sandstone can be recognized using detailed core descriptions and borehole
image log analysis.
3. Small-scale heterogeneity within the eolian sandstone can be determined using
minipermeameter measurements, capillary pressure, NMR tests, and petrographic
analysis that can be used to define petrophysical properties of the eolian facies and
associated deposits.
4. Petrophysical properties from one well can be used to compare the petrophysical
characteristics from another well that has a NMR-based log (CMR). The combination
of the FMI and CMR logs can be used to define the eolian facies within the Tensleep
Sandstone interval. The T2 distributions patterns from the CMR log are used to define
the grain flow and wind ripple strata, while the FMI log analysis are used to
determine bounding surfaces and facies within the eolian system. 9
CHAPTER 2
GEOLOGIC SETTING
2.1 Study Area
Sage Creek oil field lies at the border of Bighorn and Park Counties in the
northern part of the Bighorn basin, Wyoming. Oil has been produced primarily from the
Tensleep Sandstone, although some production comes from the Madison Limestone.
Other nearby fields that produce from the same zones include Garland and Byron fields,
located about 6 mi (10 km) south, and Frannie field located 2 mi (3 km) to the north
(Figure 1.1). The Sage Creek Tensleep oil accumulation is located on the southwest flank
of an asymmetric anticline that trends north-south in T57N-R97W and T57N-R98W.
Excellent outcrops of the Tensleep Sandstone lie about 10 mi (16 km) to the north, at
Bear Canyon in the foothills of the Pryor Mountains, Carbon County, Montana.
The Tensleep Sandstone is of Middle Pennsylvanian (Desmoinesian) to Lower
Permian (Wolfcampian) age (Branson, 1939; Henbest, 1954, 1956; Verville, 1957, 1970;
Brainerd and Keyte, 1927; Hoare and Burgess, 1960; Rhodes, 1963). As the major oil and gas reservoir in the Bighorn basin, this formation currently produces more oil than any other formation in Wyoming. Consequently, the Tensleep Sandstone is also the largest 10
enhanced oil recovery target in the state of Wyoming. The Tensleep and equivalent strata
have produced over one billion barrels of oil (Stone, 1967; Curry, 1984; Shebl, 1995).
The Tensleep Sandstone extends throughout the Bighorn basin in north-central
Wyoming and contiguous Montana (Figure 2.1). As a large intermontane basin that covers 10,000 mi2 (25,900 km2), this basin forms an asymmetrical syncline with the
structural axis near the west side (Figure 2.2). Major basement uplifts include the
Beartooth Mountains to the northwest, the Pryor Mountains to the north, the Bighorn
Mountains to the east and the Owl Creek Mountains to the south. The Montana
lineament, which trends transverse to the basin axis, completes the northern boundary of
the basin between the Pryor and Beartooth Mountains. The western margin is concealed
beneath the Absaroka Volcanic Plateau (Figure 2.1).
2.2 Stratigraphy
2.2.1 Regional Stratigraphy
This section about regional stratigraphy is adapted from Ciftci (2001). A nearly
complete Phanerozoic rock record is present in the Bighorn basin except for the Silurian
(Figure 2.3). This stratigraphic column lies on the complex Precambrian basement of the
Wyoming province. Basement served as a low relief platform for the accumulation of
cratonic sedimentary cover by transgressive and regressive cycles during the Paleozoic 11
110 109 108 107 N
B ea rt Pr oo yo th r M M Measured Section t t Bear Canyon s Montana 45 s X Wyoming Sage Creek field Study Area A’ A b B s a r i o g B k Cody i a h g h V o o o r r n l c n a M n t i B s c
P a l a s t i e a n u 44 Tensleep Worland A
Thermopolis
Owl C 0 20 mi reek Mts
0 12.5 km
Younger Rocks PreCambrian Paleozoic Rocks Eocene Volcanics
Figure 2.1. Bighorn basin, northern Wyoming and southern Montana. Major basement highs, Eocene volcanics and Montana lineament surround the basin and form its structural boundaries. Cross-section A-A’ is shown in Figure 2.2. After Fox and Dolton (1996). 12
s i
’ A - ’ A A
N E n e f t
i 0 l 0 0 . 0 0 0 0 1 5 o n i 0 t c m
e 0 s 0
0 s 3 m i k
o s m 5
r 2 0 . B I G H O R N M T S 1 6 C
n . i s b a n g h o r i . B
h e t
1 9 8 ) ( o f
o n m t o r o l f
l D n a i n d l a o x y n c
s
F
c
i l
r
B I G H O R N A S o
a z e
t c o
i f
e l r
t a A
e P E o c e n M e s o z i c P r e c a m b i n P a l e o c n m o n . i t y m a r s a g e n g x a y i e a
l T E A U p l a s c i t d i r v e o n
i s t e c e m s i
t s
o s v e r i c F
1 . W A R O K V L C N I P S 2 .
- e
A B S E g u r N
A S W i F 2 . t 0 0 n e 2 . i e
0 F e n 0 1 0 2 0 1 - - g u r i h o w s F 13
Figure 2.3. Stratigraphic column of the Bighorn basin, Wyoming and Montana. Modified after Fox and Dolton (1996).
14
(Boyd, 1993). Hence, Cambrian through Mississippian formations include shallow water
shelf carbonates and some scattered shales and transgressive sands. Late Mississippian
uplift of the Madison Limestone resulted in exposure and development of an extensive
karst surface which caps the early Paleozoic formations. Siliciclastic sediments and
carbonates of the Mississippian and Pennsylvanian Amsden Formation overlie this karst
surface owing to a shallow and brief marine incursion. From the Pennsylvanian to early
Permian, eolian and marine processes that deposited the Tensleep Sandstone dominated
the region. Ergs that originated in southern Montana migrated southward and covered
much of the Rocky Mountain region (Kerr and Dott, 1988). Towards the end of this
period, a major second order eustatic sea level low, together with the uplift of the
Greybull–Rosebud arch and paleo-Bighorn high, promoted fluvial processes in the region resulting in the development of a high-relief unconformity plane that caps the Tensleep
Sandstone (Vail and Mitchum, 1979; Morgan et al., 1978; Kerr et al., 1986).
The Goose Egg member of the Phosphoria Formation was deposited in incised channels as middle Permian transgression deposited evaporites, carbonates and silts in parts of the basin.
A general westerly regression took place during the Triassic when Chugwater red beds and evaporites were deposited on the continental shelf. Southerly tilting and truncation near the end of the Triassic produced a thinning of sediments to the north
(Snoke, 1997). Jurassic sediments ranging from red beds and evaporites of the Gypsum
Spring Formation to shallow marine sandstones, limestones and shales of the Sundance 15
Formation were unconformably deposited over the Chugwater Group. Non-marine
Morrison clastic sediments overlie the varicolored Jurassic strata (Stone, 1967). Marine deposition became dominant again in the Early Cretaceous. The Cloverly, Thermopolis and Mowry shales and sandstones were unconformably deposited during this period over the nonmarine facies of the Upper Jurassic. Continuous deposition occurred through the
Late Cretaceous as a series of rapid transgressions and regressions resulted in deposition of several Frontier sandstone wedges. Eastward marine withdrawal brought about the dominantly regressive Mesaverde clastic wedge (Stone, 1967). Initiation of the Laramide orogeny and the beginning of the Bighorn basin as we see it today probably corresponds to this time period (Blackstone, 1986; Snoke, 1997). Subsequently, the marine Lewis
Shale was deposited in the eastern portion of the basin, whereas the Meeteetse nonmarine sandstones, mudstones and coals were deposited to the west. Non-marine deposits of the
Lance Formation capped the Cretaceous strata before the major impact of Laramide orogenesis.
At the beginning of the Paleocene, Laramide orogenesis intensified.
Conglomerates and fluvial deposits of the Fort Union and Willwood Formations, derived from the debris of marginal basement uplifts, were deposited unconformably over the
Mesozoic strata. Lacustrine and fluvial sediments of mainly volcanogenic origin started to fill up the Bighorn basin following late Eocene igneous activity. However, these sediments were mostly removed by subsequent erosion during the late Pliocene and
Pleistocene to create the present-day topography (Mankiewicz and Steidtmann, 1979). 16
2.2.2 Tensleep Sandstone
The type locality of the Tensleep Sandstone occurs in outcrop exposures in
Tensleep Canyon (Keefer and Van Lieu, 1966). Most recent studies agree that the formation was deposited in a coastal plain setting under the influence of both eolian and marine environments and sea-level fluctuations (Fox et al., 1975; Morgan et al., 1978;
Desmond et al., 1984; Kerr et al., 1986; Wheeler, 1986; Rittersbacher, 1985; Kerr and
Dott, 1988; Kerr, 1989; Shebl, 1995; Carr-Crabaugh and Dunn, 1996; Aviantara, 2000;
Ciftci, 2001).
The Tensleep Sandstone lies conformably above the red beds and cherty carbonates of the Amsden Formation. The Goose Egg member of the Phosphoria
Formation unconformably overlies the Tensleep Sandstone in the form of red beds, shales, evaporites, and dolomites (Figure 2.4). Together with the Amsden Formation, the
Tensleep Sandstone constitutes a stratigraphic sequence which began with a sea-level lowstand. This lowstand system tract resulted in exposure of the Madison Limestone and formation of extensive karstic features on the upper part of the Mississippian limestones.
The basal transgressive sands of the Amsden Formation, known as the Darwin Sandstone member, locally overlie the karstic zone. This unit is overlain by the lower Amsden
Horseshoe Shale member, which grades upward into Amsden carbonates known as the
Ranchester Limestone member. Transgression of the Amsden sea was followed by 17
BIGHORN BASIN AND SYSTEM/SERIES EASTERN POWDER WIND RIVER BASIN RIVER BASIN
GUADALUPIAN PARK CITY AND
A N GOOSE EGG FORMATION I PHOSPHORIA M LEONARDIAN FORMATIONS P E R
WOLFCAMPIAN UPPER
VIRGILIAN
MISSOURIAN A N MIDDLE I TENSLEEP MINNELUSA
A N SANDSTONE FORMATION V DESMOINESIAN S Y L N
P E N RANCHESTER ATOKAN LIMESTONE O N I E N T HORSESHOE MORROWAN A
S D SHALE M LOWER R A M O
F DARWIN CHESTERIAN SANDSTONE A N P I MERAMECIAN S I S I I M OSAGIAN MADISON LIMESTONE
Figure 2.4 Stratigraphic chart showing generalized stratigraphy from Mississippian through Permian units in the Bighorn, Wind River and eastern Powder River basins. After Wheeler (1986). 18
the highstand system tract which is represented by the southward prograding erg system
of the Tensleep Sandstone.
Traditionally, the Tensleep Sandstone is divided into upper and lower intervals
(Mankiewicz and Steidtmann, 1979; Andrews and Higgins, 1984). The major difference
between the two parts is primarily the proportions of chemical and clastic rocks and the
amount of marine versus eolian dune processes (Figure 2.5). The upper part has a higher
proportion of clastic rocks due to dominance of eolian dune processes. Accordingly,
reservoir rock potential is higher in this part.
The lower Tensleep represents supratidal to subtidal depositional conditions with the domination of burrowed sandstones, fossiliferous dolomite, and dolomitic sandstones associated with subaqueous environments with minor thin eolian strata (Mankiewicz and
Steidtmann, 1979). The upper Tensleep is composed of large sets of eolian cross-strata
that are repeatedly punctuated by thin sandy to fossiliferous marine dolomite
(Mankiewicz and Steidtmann, 1979).
Within the upper Tensleep, the marine carbonate platform repeatedly transgressed
the eolian dune area, leaving a deposit that alternates between thick packages of eolian
sand and extensive thin marine facies (Mankiewicz and Steidtmann, 1979; Carr-
Crabaugh and Dunn, 1996). These pulses of marine sediment are interpreted to represent
short-lived regional fluctuations in relative sea-level (Kerr et al., 1986). As relative sea-
level continued to rise, the eolian-dominated shelf was inundated and reworked in a
marine environment. The marine system deposited sandy, fossiliferous 19
Goose Egg Formation
Upper Tensleep
10m 30 ft
Lower Tensleep 0 0
EXPLANATIONS
Eolian Sandstones
Marine, marginal marine and fluvial sandstones
Ranchester Limestone Dolostones
Mudstones Horseshoe Shale
Figure 2.5 Columnar section of the Goose Egg Formation, Tensleep Sandstone, and upper Amsden Formation at the type locality of the Tensleep Sandstone in Tensleep Canyon. After Kerr et al. (1986).
20
carbonates that were capped by sharp to erosional contacts with the overlying eolian
facies when the regressive cycle recommenced and the relative sea-level fell (Andrews
and Higgins, 1984; Wheeler, 1986; Kerr and Dott, 1988).
During the middle Pennsylvanian to lower Permian, one big eolian system
initiated in southern Montana and migrated south-southwestward to northeastern Utah
and northwestern Colorado. The Tensleep Sandstone prograded over the underlying
marine deposits (Amsden Formation) during the highstand of sea level (Kerr, 1989).
2.2.2.1 Paleogeographic Setting
During the Pennsylvanian to early Permian, Wyoming was approximately situated
5-20° north of the equator under arid climatic conditions (Figure 2.6) (Parrish and
Peterson, 1988; Kerr and Dott, 1988). Northeast trade winds that moved from subtropical highs to the equatorial low-pressure zone were probably the major factor controlling the migration and the internal dynamics of the erg system. Strong and consistent north- northeasterly winds associated with eolian deposits of the period have been interpreted by paleocurrent studies in the region (Figure 2.7) (Opdyke and Runcorn, 1960; Heckel,
1977; Parrish and Peterson, 1988; Kerr & Dott, 1988). However, variation in dominant wind direction and the marine influence on the depositional patterns are evident throughout the Tensleep Sandstone. 21
Montana X Sage Creek Wyoming
B ig h o r n B a s in
50 km
20 N
.. . . 10 N ...... …......
Equator
United States
SOUTH AMERICA AFRICA
Figure 2.6 Generalized Pennsylvanian to Early Permian paleogeographic map for sea-level lowstand. Dark gray represents the sea distribution. Stippled pattern indicates the eolian ergs. Arrows depict paleowind directions. Black arrow is the dominant wind direction and white arrow represents the monsoonal variation. From Parrish and Peterson (1988). The black areas in the inset map represent Paleozoic outcrops in the Bighorn basin area. Modified from Kerr and Dott (1988). 22
. t d o f e o t t D o t o n g i 1 9 7 ) a t p l n (
n d n i c
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e n s t m r r r a o n k e e e d i y o c e K m
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B A p e r ( n d ( s a n n a
i a o d i d e p l e l - t r d y k e a a p a r g p t n i n O m u s
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The paleogeographic location at the western margin of Laurentia, adjacent to two oceanic bodies, suggests the possibility of land-sea breezes which may have locally altered the dominant wind direction (Kerr and Dott, 1988) (Figure 2.6). Marine influence in the form of periodic flooding from the west and south resulted in switching of depositional conditions between shallow marine to eolian dune environments (Kerr et al.,
1986; Kerr, 1989; Carr-Crabaugh and Dunn, 1996). The monsoonal climate that developed following the Appalachian Orogeny introduced annual climatic seasonality that prevailed from the middle Pennsylvanian to early Permian (Parrish et al., 1983;
Phillips et al., 1985). This seasonality probably accounted for the observed north to east variations in the dominant paleo-wind direction (Figure 2.6) (Kerr and Dott, 1988; Carr-
Crabaugh and Dunn, 1996).
The source of the Tensleep Sandstone and the other components of the system is not well known. Lack of upwind sediment sources which could provide relatively mature quartz-rich sands is evident in the Pennsylvanian paleogeologic maps of the northern
Rockies. However, an early Pennsylvanian delta system in central Montana (Maughan,
1984) and several prograding deltaic sequences observed in the Amsden-Tensleep transition could be possible sources that discharged significant amounts of quartz-rich sand onto the Wyoming shelf (Figure 2.6) (Kerr and Dott, 1988; Ciftci, 2001).
24
2.2.2.2. Eolian Processes
This section is adapted from Ciftci (2001). Modern eolian environments have
been investigated worldwide during the last few decades. Basic eolian processes revealed
by these studies constitute the foundation of our understanding of ancient eolian deposits
today. Therefore, this section is intended to summarize these processes in order to
establish a background for better understanding of the concepts that will be discussed in
later sections.
In eolian systems, sand is transported by three main processes: saltation, surface
creep and suspension (Bagnold, 1941). Among them, saltation is the most effective way
of transportation and leads to the formation of eolian bedforms, such as wind ripples, dunes and much larger dune forms called draas (Wilson, 1972). If this moving sand loses its forward momentum, it starts to accumulate. Accumulation largely takes place on the downwind slope or lee face of a dune where flow separation creates a separation cell
(Figure 2.8). Significantly lowered grain transport rates occur within the separation cell as opposed to increased grain transport rate on the upwind slope or stoss slope of the
dune (Kocurek, 1996). Sand swept from the stoss slope is brought to this zone where it
accumulates (Figure 2.8). Continuous erosion of the stoss slope and accumulation on the
lee slope cause migration of the eolian bedforms.
During migration, accumulation on the lee slope occurs through three main
processes: grain fall, ripple climb and grain flow (Figure 2.8). Each process is associated 25
Figure 2.8. Air flow over dunes. (a) Dune in cross section with transverse flow, showing secondary air flow zones and relative transport rates (large arrows) (b) Accumulation processes under transverse flow conditions. From Kocurek (1996). 26
with a characteristic cross stratification type, grain fall stratification, climbing ripple
stratification and grain flow stratification, respectively (Hunter, 1977; Kocurek and
Fielder, 1982; Fryberger, 1990b).
Grain fall stratification develops in the zone of flow separation at the lee face of a
dune. Previously saltating sand grains lose much of their forward momentum mainly
because of reduced sediment transport rate and fall into this zone to accumulate (Hunter,
1977). Sedimentological outcomes are good sorting and intermediate packing without
very distinct lamination and grading.
Wind ripple stratification occurs on interdune flats, stoss sides of dunes and on lee
slopes that are inclined less steeply than the angle of repose. As the wind ripples climb
over the preceding deposits, they form millimeter scale inversely graded and tightly
packed laminae (Hunter, 1977).
Wind ripple stratification is commonly observable as sets that are centimeters thick and grade upward into grain fall stratification. Grain flow stratification takes place when deposition in the flow separation zone causes the slope to reach the angle of initial
yield. This triggers mass wasting processes on the lee slope in the form of slumps and
sandflows. No new stratification is formed by cohesive slump blocks. Preexisting
stratification is deformed. On the other hand, loosely packed, well-sorted and inversely graded grain flow stratification is formed by the flow of sand grains down the lee slope.
Thus, grain flow stratification interfingers with the grain fall stratification (Hunter, 1977).
Plane bed lamination under strong wind conditions (Hunter, 1977) and adhesion 27
structures of wet eolian systems (Kocurek and Fielder, 1982) are also observable in modern and ancient eolian environments, but these are relatively rare.
A migrating bedform that leaves an accumulation must move upward or climb with respect to an accumulation surface (Figure 2.9). In this situation, a time- transgressive stratum accumulates by the climbing bedform which crosses accumulation surfaces (Hunter, 1977). Examples would be single laminae for a climbing ripple or a set of cross strata for a dune. The angle of climb and its magnitude relative to the bedform’s stoss slope is an important parameter that influences the overall geometry of the climbing bedform structure. If the bedform is climbing with an angle that is the same as its windward slope, the angle is called the critical angle of climb. The higher and lower angles correspond to supercritical and subcritical angles of climb, respectively. Any subcritically climbing bedform will result in partial erosion of the deposits of the preceding bedform (Figure 2.9). Internal erosional surfaces created by these subcritically climbing bedforms are called bounding surfaces (Brookfield, 1977). The time gap represented by each bounding surface is extremely variable. Some represent only a few hours, whereas others are true surfaces of erosion that represent millions of years.
Moreover, some bounding surfaces are not really erosional surfaces. Instead, they represent a pause in sedimentation that allows bypassing of eolian bedforms without any accumulation (zero angle of climb) or erosion (negative angle of climb) (Fryberger,
1990a).
28
Sediment in transport Qi Transport Qo
Angle of climb Bedform (Subcritical) Migration
Accumulation Surface
ta Bounding ss-stra t of cro Surfaces Se et Fores
Figure 2.9. Generation of time transgressive strata by climbing bedforms. Qi and Qo represent sediment influx and outflux respectively where Qi>Qo. From Kocurek (1996). 29
2.2.2.3 Lithofacies
Several studies have concentrated on descriptions of Tensleep Sandstone lithofacies. These studies are mostly based on outcrop exposures and cores throughout the Wind River and Bighorn basins (Mankiewicz and Steidtmann, 1979; Andrews and
Higgins, 1984; Kerr et al., 1986; Kerr and Dott, 1988; Tanean, 1991; Vealey, 1991;
Shebl, 1995; Carr-Crabaugh and Dunn, 1996; Aviantara, 2000). The most recent description comes from Aviantara (2000) who identified five main facies from core and outcrop studies. Based on the governing depositional processes, these facies can be grouped as eolian facies and marine facies (Figure 2.10).
Tabular-planar cross-stratified sandstones are the most common lithofacies observed in the eolian facies group. These are characterized by very large scale cross bedded units, or sets, which are bounded by planar surfaces to form tabular bodies. This facies consists of well-rounded, well-sorted, fine to very fine-grained quartz arenites.
Grain flow stratification dominates the facies with a contribution of wind ripple stratification, where the lee face is at the angle of repose. Wind ripple stratification is commonly observable in the lower parts of the cross strata set with dips ranging from horizontal up to 12°. This grades upward into grain flow stratification with an increasing dip amount up to 27°. Grain fall strata are rare probably indicating a well-developed slipfaces, i.e., lee faces at or near the angle of repose (Kerr et al., 1986; Kerr and Dott,
1988; Aviantara, 2000; Hurley et al., in press). 30 s
e
i s s c e i e a i c F c a
a . e F
F n t
o e d t s e s a i d r f t i n t n a a 2 0 ) I r
S ( t
d
s d e - a i e s f r s i m t a o r a r r o s t f C n t e
s e i r - a s c s a D e a s
n i v i e o F a c l
r l a a e A p C F c
- n
r S u h e
a d l g n e i r u u g r o m e r b o t a r r a a n f I T T L M d e i f o d i M
. n s o i t a l e r r e n t i
r i h e t h t i w
o n e t n d s a S p e e l n s e T
h e t
o f
s e i c a h o f t i L
1 0 . 2 .
e
E C N E U Q E S A R A P g u r i F 31
In contrast to this interpretation, some authors suggested that grain flow
stratification dominates within tabular-planar cross-stratified sandstone facies (Kocurek and Dott, 1981; Tanean, 1991; Carr-Crabaugh and Dunn, 1996). According to these studies, grain fall stratification occurs in the upper portions of the lee slope and has a high potential of being truncated and eroded off by bedform climb and migration processes. It results in rare preservation of the grain fall stratification in the eolian deposits. On the other hand, grain flow is the most common process dominating the lee face deposition.
Therefore grain flow stratification abundantly occurs in the eolian deposits and it is the major constituent of the Tensleep eolian dune facies.
Isolated packages of trough cross-stratified eolian sandstones are locally observed within tabular-planar cross-stratified sandstones as evidence of variation in the wind regime (Figure 2.10). These packages are called trough cross-strata intrasets and cut into
the underlying tabular-planar cross-stratified sandstones. A relatively higher proportion
of wind ripple stratification is observable in intraset sandstones.
Interdune sandstones are commonly observed as lenses between tabular-planar cross-stratified sandstone sets, and are characterized by horizontal stratification (Figure
2.10). Well rounded, well sorted, fine to very fine grained quartz arenites of this facies are usually coarser grained than the other eolian facies. Wavy lamination and wind ripple stratification are the most common sedimentary structures. Subaqueous features such as wave rippled sandstones; laminated sandstones and dolostones are locally observable 32
indicating temporal standing water in interdune areas (Kerr et al., 1986; Kerr and Dott,
1988; Aviantara, 2000).
Large-scale deformed sandstone facies are associated with the tabular planar
cross-stratified sandstones (Figure 2.10). These display the same sedimentological
characteristics with contorted eolian cross stratification. This facies commonly occurs in
the upper portions of the eolian sandstones just below the marine deposits in each
parasequence. This occurrence suggests that the primary sedimentary structure is
deformed due to marine incursion (Kerr, 1989).
Marine facies include marine and dolomitic sandstones. They develop at the
bottom of each parasequence below the eolian cross-stratified sandstones (Figure 2.10).
The marine sandstone facies is composed of rounded, moderate to well-sorted, very fine
to fine grained quartz arenites. Wavy lamination, horizontal lamination, low angle cross
stratification (<5°) and biogenic traces suggest a shoreface or foreshore type of depositional environment. Dolomitic sandstone facies are gray, greenish gray to reddish gray with very fine grained, subrounded and well sorted sand grains that are embedded in a pervasive dolomite cement. Localized pyrite cement and anhydrite nodules are also observable. Horizontal and wavy laminations are common with subordinate structureless intervals and biogenic traces. These features probably suggest a siliciclastic sabkha or peritidal depositional environment.
33
2.2.2.4 Parasequences and Bounding Surfaces
A parasequence is defined as a relatively conformable succession of genetically
related beds or bedsets bounded by marine flooding surfaces and their correlative
surfaces (Posamentier and Vail, 1988). By this definition, a parasequence represents a
limited episode of sedimentation that produced a genetically related 3-D volume of
sedimentary rocks. Within the Tensleep Sandstone, parasequences are made up of eolian
and marine sandstone couplets. The characteristic repetition throughout the Tensleep
Sandstone is traceable in outcrop and throughout the subsurface of the Bighorn basin
(Carr-Crabaugh and Dunn, 1996; Hurley et al., in press). The marine sandstones (marine
sandstone facies and dolomitic sandstone facies) represent the flooding of a pre-existing eolian dune field with a decrease in the ratio of sediment supply to accommodation space.
The eolian sandstone (tabular-planar, large-scale deformed, and interdune sandstone) facies represents the outbuilding of the eolian dune field at a time when the ratio of sediment supply to accommodation space increased.
In the subsurface, parasequence identification can be done through well log calibration to cores and well log correlation. The tabular-planar sandstone facies has the most contrast in well log character between the marine sandstones and the eolian sandstones. Parasequence boundaries are usually placed at the base of the low porosity values from neutron or density log traces (Hurley et al., in press). 34
In eolian sediments, bounding surfaces are commonly recognized between parasequence boundaries. Brookfield (1977) identified three orders (first, second and third order) of bounding surfaces in ancient eolian sandstones based on their extent and regularity (Figures 2.11 and 2.12). This classification may be useful for application in a specific setting but may not mean the same thing everywhere. Hence, it should not be considered as a unique depositional model describing the origin of bounding surfaces.
This classification can be modified to suit a particular area (Kocurek, 1996; Fryberger,
1990; Aviantara, 2000). Thus, Aviantara (2000) developed a new bounding surface classification scheme for the Tensleep Sandstone based on Brookfield’s (1977) original classification. This scheme includes 0.0-, 1.0-, 2.0-, 3.0- and 0.1-bounding surfaces
(Figure 2.13) (Aviantara, 2000).
A 0.0-bounding surface constitutes the contact between the marine facies and the overlying eolian facies (Figure 2.13). This flat surface represents the re-initiation of eolian sediment accumulation that ceased for some period of time and was replaced by marine processes due to flooding of the area. This highest rank and most extensive bounding surface can be traced laterally for significant distances and is easily identified in subsurface data. Relatively higher resistance of underlying marine sediments promotes differential erosion. Therefore, 0.0-bounding surfaces commonly constitute valley bottoms or create extensive benches in outcrop exposures. In the subsurface, marine deposits commonly have low porosity and high resistivity. 35
2nd order 1st order Dune 3rd order
Draa
Figure 2.11. Eolian bedforms of different hierarchy. First, second and third order bounding surfaces are formed due to migrating trains of bedforms of different hierarchy. Figure illustrates formation of bounding surfaces according to the draa model. From Brookfield (1977).
Figure 2.12. Three orders of bounding surfaces and their generation by migrating bedforms. 36
Marine flooding surface 2.0 .0 2 2.0 .0 0.1 2
E 1.0 C
N 2.0 0.1 E 2.0 U 2.0 Q
E 2.0 S .0 2 0 1.0 A 2. 0 R 2. A P 1.0 2.0 2.0 2.0 2.0 0.0 Marine flooding surface
.0 0 2 2. 3.0 3.0 3.0 1.0
3.0 0 2. 3.0 0 2. 1.0 3.0
.0 0 2 . .0 3 3 .0 2 .0 3
Figure 2.13. Bounding surfaces and their interrelations observed in the Tensleep Sandstone. See Figure 2.10 for the associated lithofacies. Modified from Aviantara (2000). 37
A 1.0-bounding surface initiates and rises upward from the 0.0-bounding surfaces
(Figure 2.13). They correspond to Brookfield’s (1977) first order bounding surfaces and
are also called interdune surfaces (Kocurek, 1996) or stabilization surfaces (Fryberger,
1990). 1.0-bounding surfaces are subhorizontal, regionally extensive, low-relief planes
that cut across all underlying eolian cross stratification and lower rank bounding surfaces
(such as 2.0-, 3.0-, 0.1-bounding surfaces). In each of these sets, cross stratification is tangential to an underlying 1.0-bounding surface at the bottom and is truncated by the overlying 1.0-bounding surface at the top. Interdune deposits can occur between these sets along the 1.0-bounding surfaces. Although earlier approaches and some later authors have related the 1.0-bounding surfaces with deflation to the water table (Stokes, 1968;
Loope, 1984; Simson and Loope; 1985), it is widely accepted today that these surfaces represent the migration and accumulation of the main bedforms or the draas (Figures 2.11 and 2.12) (Brookfield, 1977 and 1992; McKee et al., 1977; Kocurek, 1981 and 1996;
Kerr and Dott, 1988; Fryberger, 1990a; Carr-Crabaugh and Dunn, 1996).
A 2.0-bounding surface is also called a second order surface (Brookfield, 1977), superposition surface (Kocurek, 1996), or stacking surface (Fryberger, 1990). They lie between first order surfaces and separate bundles of eolian cross-strata set. (Figure 2.13).
The process that forms these surfaces is the passage of dunes across draas (Brookfield,
1977 and 1992) or the migration of superimposed smaller-scale dunes across the lee face of the main bedform (Kocurek, 1996). They result from the partial erosion of a 38
superimposed bedform followed by stacking of a second bedform on the top of first, and
so on (Figure 2.12).
The 3.0-bounding surfaces or third order surfaces (Brookfield, 1977), or growth
bounding surfaces (Fryberger, 1990) are the reactivation surfaces (Kocurek, 1996) that
bound eolian cross-strata sets. In these sets, no or minor variation in the cross-strata dip direction is observable. The 3.0 surfaces represent a change in dune morphology caused by fluctuations in wind direction or speed, which results in ceased deposition or minor local erosion for a short period of time. This period is then followed by a new pattern of deposition that forms 3.0-bounding surfaces.
A 0.1-bounding surface or intraset bounding surface corresponds to the boundaries of medium- to large-scale trough cross-stratified eolian sandstone intra-sets that dip westward with east-west trending trough axes (Figure 2.13). These surfaces locally occur as scours within the upper portions of tabular-planar cross-strata sets. They commonly truncate 2.0- and 3.0-bounding surfaces at the bottom and are truncated by 1.0-bounding surfaces at the top. Wind ripple strata dominate the associated eolian sandstones with less common grain flow strata. These intrasets probably represent temporary variations of the wind regime that intensified the westward-directed wind component, possibly related to a monsoonal climate pattern (Figure 2.6).
39
2.2.2.5 Reservoir Heterogeneity
Although the Tensleep Sandstone has original oil-in-place volumes in the billions of barrels, recoveries as low as 15% have been documented in some fields (Peterson,
1990). These low recovery factors are the direct result of reservoir heterogeneity caused by permeability anisotropy and an advanced degree of depositional compartmentalization. Accumulation and preservation processes are the main cause of reservoir heterogeneity which is accentuated by later diagenesis. Furthermore, fractures that are common in anticlinal reservoirs also influence recoveries by altering the permeability and flow patterns.
Reservoir heterogeneity within the Tensleep Sandstone can be grouped into small- scale and large-scale heterogeneities (Figure 2.14) (Carr-Crabaugh and Dunn, 1996).
Small-scale heterogeneities are related to the depositional processes that took place during the accumulation of eolian strata. Grain fall, wind ripple and grain flow stratification have specific thickness, continuity, grain size, packing and sorting characteristics (Figure 2.14-D). Each responds differently to fluid flow. Bounding surfaces, on the other hand, are the locus of permeability barriers or baffles that strongly affect reservoir behavior. Carr-Crabaugh and Dunn (1996) and Humphreys (1996) studied this concept for the Tensleep Sandstone in the surface and subsurface. They sampled key bounding surfaces and measured the directional oil-water relative permeability. Significant directional variations in permeability were identified in association with the bounding surfaces (Figures 2.15 and 2.16). The contrast in grain 40 e
c 1.0
n 2.0 e u
q 1.0 3-70 m e (A) s a r a
P 1.0 0.0
1.0
2.0 1-20 m (B) 3.0
2.0 1.0
3.0
0.1-1.5 m (C)
3.0
1.5-10 cm (D) Grainfall Stratification Windripple Stratification
Figure 2.14. Scales of reservoir heterogeneity in the Tensleep Sandstone from highest (A) to lowest (D). Modified from Carr-Crabaugh et al. (1996). 41
packing across a bounding surface is the primary control of the variation. Bounding
surfaces commonly separate tightly packed wind ripple laminae from the underlying
loosely packed grain fall laminae. Tightly packed and highly cemented interdune facies
may also accompany the bounding surfaces, particularly in the case of 1.0-bounding
surfaces. This results in fluid flow being significantly lower across the bounding surface
than parallel to it. This subdivides the reservoir sandstones into flow compartments at
different scales defined by different orders of internal bounding surfaces (Figure 2.14)
(Aviantara, 2000; Carr-Crabaugh and Dunn, 1996; Humphreys, 1996; Shebl, 1995;
Teanen, 1991; Fryberger, 1990a; Kerr and Dott, 1988; Andrews and Higgins, 1984;
Emmett et al., 1971).
The 0.0 surfaces are formed by exposure of the carbonates. Large-scale
heterogeneities were introduced by preservation processes when marine flooding of the
Tensleep Sandstone resulted in the formation of sandy dolostone (Figure 2.14). This
caused the placement of eolian accumulations below the regional base level of erosion
and promoted preservation (Kocurek, 1996). The heavily cemented and dolomitic marine
facies within the Tensleep Sandstone contributes to compartmentalization by acting as
vertical barriers to fluid flow between eolian cross-stratified sandstone units. Fractures may allow fluid communication between discrete eolian sandstone units if they exist
(Carr-Crabaugh and Dunn, 1996; Aviantara, 2000; Emmett et al., 1971). 42
p o f e
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44
2.2.3 Local Stratigraphy
The Tensleep Sandstone at Sage Creek field consists of at least six different
reservoir layers. Each of these reservoirs may trap oil independently. The reservoir
subdivision used in this study is similar to that used by Borah-Borah (1996) with an
additional layer T6 at the base. The upper Tensleep Sandstone is divided into six different
reservoirs from top to bottom: upper Tensleep (T/T1), T2, T3, T4, T5 and T6 (Figure
2.17). The upper Tensleep, T2, and T3 are equivalent to Conoco and Marathon’s units A,
B, and C. The T4, T5 and T6 zones are equivalent to units D and E. The T and T1 have
been used in places for the upper Tensleep member, as there are two definable sands
which act as one reservoir.
The unconformable boundary between the Tensleep and the overlying Phosphoria
Formation is modified by regional progressive truncation of Tensleep sands to the south,
and by local downcutting of Phosphoria channels. Areas that were high prior to the
Phosphoria were often more deeply eroded, and the lower areas had thicker preserved
Tensleep sections (Borah-Borah, 1996).
The boundary with the underlying Amsden Formation is characterized by facies changes of increasing dolomite content in the Amsden section. Moving up to the
Tensleep, the percentage of sand increases, and the reservoirs becomes less marine influenced and more eolian. 45
Sage Creek #21 Sage Creek Field Big Horn, Wyoming
1880’FEL 1830’FNL section 7; T57N; R97W Elev. KB: 4154’; GL:4144’ API#: 49-003-20923 Date logged: 29 Mar 1996
Figure 2.17 Tensleep Sandstone type log at Sage Creek Unit (SCU) #21, shows the division of the Tensleep Sandstone into seven subzones modified from Borah-Borah (1996). It is equivalent to zones A through E of Conoco and Marathon’s unit.
46
Tensleep Sandstone reservoirs are characterized by a series of repetitive
depositional cycles related to sea-level fluctuations. The sandstones were deposited as sabkhas and beaches in the lower Tensleep, and mostly as preserved dunes in the upper
Tensleep. Sea-level rose, and these sands were covered by dolomites which filled the areas between sand bodies and eventually covered them as vertical seals for underlying reservoirs.
Dolomite interbeds affected the preservation of porosity and permeability in the underlying sands. The upper Tensleep, which has no dolomite cap, has higher average porosity and permeability than the lower Tensleep (Borah-Borah, 1996).
2.3. Structural Geology
2.3.1 Regional Structural Geology
The Bighorn basin is a northwest-trending, asymmetric structural basin with its
axis closer to the western and southwestern flanks (Curry, 1983). The basin is an oval
depression about 120 mi (192 km) long and 90 mi (144 km) wide and covers
approximately 10,000 mi2 (25,600 km2) on the cratonic shelf of northwestern Wyoming
and southwestern Montana. The basin is bounded by major mountain uplifts: the 47
Beartooth Mountains to the northwest, the Bighorn Mountains to the east, and the Owl
Creek-Bridger Mountains to the south. These uplifts expose Precambrian crystalline rocks in their cores, and thus create structural boundaries of the basin. On the west, the basin is bounded by the Eocene volcanic complex that forms the Absaroka Mountains.
Because many of the basin’s structural elements extend beneath the Absaroka Volcanics, the western basin margin is defined topographically rather than structurally.
For Paleozoic rocks, the Bighorn basin is not a true depositional basin, but is a
Laramide structural basin (Fanshawe, 1971; Coney, 1978; Dickinson and Snyder, 1978).
During the Lower Cambrian, the basin subsided and the Flathead Sandstone was deposited (Fanshawe, 1971). At the end of the Mississippian, weathering of the subaerally exposed surface led to karst topography in the uppermost Madison Formation
(Mallory, 1967; Fanshawe, 1971). Folding and erosion created a regional unconformity on the Tensleep Sandstone (Mallory, 1967; Simmons and Scholle, 1992) at the end of the
Pennsylvanian (Post-Desmoinesian). The western and northern parts of the basin were uplifted from this time to the early Permian, resulting in regional southward tilt and truncation of the Tensleep Sandstone (Thomas, 1965; Stone, 1967). The formation was eroded to a thickness of about 600 ft (180 m) in the southwest basin and 200 ft (60 m) in the northeast (Verville, 1957; Thomas, 1965). Laramide deformation reached the Bighorn basin area by the late Campanian, but the timing and duration of deformation varied for individual uplifts (Gries, 1983). Snoke (1993) believes the Laramide orogeny includes all structures from Late Cretaceous to early Eocene. The Laramide orogeny was completed 48
in most parts of Wyoming by the end of the Wasatchian (Lillegraven and Ostresh, 1988).
Laramide compression folded and thrust-faulted the sedimentary strata of the Bighorn
basin and formed many peripheral faulted, asymmetrical anticlinal folds along the basin
rim (Fox et al., 1975) (Figures 2.1 and 2.2).
2.3.2 Local Structural Geology
Sage Creek field is located on a well developed asymmetric fold in the northern
Bighorn basin of Wyoming. The structure trends northwest-southeast, parallel to the
Bighorn Mountain front, in T57N, R97-98W, Park and Bighorn counties. The structure
has about 500 ft (150 m) of structural closure. This anticline formed by deep thrust
faulting with movement towards the east. Movement along this thrust probably occurred
during the Laramide orogeny of Late Cretaceous to Early Tertiary age, as no stratigraphic
changes were noted due to activity along this fault in the stratigraphic section prior to the
Cretaceous Frontier, which crops out on the surface (Borah-Borah, 1996). Subsurface
correlation and seismic interpretation shows significant changes in dip and thickness of
reservoir intervals within the Tensleep section between some wells. It is likely that Sage
Creek anticline was cut by several northeast to southwest trending faults that have both
lateral and vertical movement (Figure 2.18). The similar pattern on an isopach map of the
Mowry to the Chugwater interval may suggest that these faults have had recurrent 49
R 98 W R 97 W
RONEY #1
BREHM GOVT #1 BREHM #15-1
S
a
g FEDERAL #2-1
e
1 FEDERAL #1-1 6 C 5 SCU #14 SCU #18
r
e
KLINDT e #1 GOVT BREHM SC SCU #1 DECKER #1 k
FOX MADISON SC #2 USA T PEDRY #1
h US PROD USA #1 PAN-AM #1 r
EFFIE KLINDT u #1 SCU #21 s DORO FOX #3 SCU #5 t
GOVT HILL F SCU #7 #1 7 a 8 SCU #8 SCU #17 SCU #19 u
l T
t
SCU #7 SCU #16 USA TEXAS #1 57
FOSTER BECKER #1-5 #1 N RICKETTS #1 FOSTER #1 BECKER-ANDERSON SCU #8 SCU #15 SCU #20 #1
LAUREN FEDERAL #1 McCRARY #1 PEDRY JOENS #13 SCU #10 SCU #13 JOENS #1 KIRK BARNDT #1 BARNDT #1 DILLON #1A WAGNER 13MARMIK BARNES #1 COLEY 17 #13-3 FOX #1 SCHWAB #1 SCU #11 MARTIN- HAGER #1 BREHM DILLON #1 SQ.DILLON #1 HAGER #1 EVERGREEN-WAGNER DEAVER IRRINGTON #1 #1 SCU #9 GOVT.WINER #1 SCU #12 GOVT. UNIT BARNDT #1 RICH-AJAX RICH-KIRK HAGER#2 #1 FLOOD RICHARDS #1 #1 #1 #3 RICH-AJAX #2 HAGER#1 RICHARDS#3A BREHN-FLOOD FEDERAL #1 WAGNER BARNDT #1 #5-24 #2 HUSKY GOVT #1 DAVIS #1 DAVIS RUTH-DAVIS BLANSCET-CHASE #2 #1 #1 STEFFENS #2 24 STEFFENS 20 GOVT.WAGNER DEAVER-FEDERAL STEFFENS UNIT #24-1 #24-2 GOVT STRIKER GOVT STRIKER #1 #2 #2 #1 BERRYMAN #2 BERRYMAN #1 GOVT STRIKER GOVT.WAGNER STEFFENS #3 DOVE UNIT #24-1 #2 BERRYMAN-WELLS #2 DOVE #1 #1 FLOYD-WELLS #1
0 0.2 0.4 0.6 0.8 1 mile
50
movement through time. This may have affected erosion of the upper Tensleep. These
faults control the distribution of oil in the field, and affect fluid flow within the reservoir
(Phoenix Production Co., 1993; Borah-Borah, 1996).
2.4 Petroleum Geology
Hydrocarbon source rocks for most of the oil and gas in the Bighorn basin fall into two geochemical groups: Permian Phosphoria Formation and Cretaceous Mowry,
Frontier, Mesaverde and Meeteetse Formations (Meissner et al., 1984; Gries et al., 1996).
The Permian Phosphoria Formation is probably the source of much of the Paleozoic oil in
the basin. Stone (1967) believed that all hydrocarbons in Paleozoic and Triassic
reservoirs of the Bighorn basin were derived from Phosphoria source rocks. The
conclusion is based on evidence such as the abundance of dark-colored, phosphatic,
organic-rich calcareous mudstone and shale interbeds within the Phosphoria Formation,
and live oil shows that occur on almost every marine facies sample of the Phosphoria
Formation in the Bighorn basin and elsewhere on Wyoming shelf. There is a good
geochemical relationship between commercially produced hydrocarbons from Paleozoic
and Triassic reservoirs to the Phosphoria source rock.
The maximum burial and the time of hydrocarbon generation of the Permian
strata through most of the basin occurred at the end of the Cretaceous period (Figure 51
2.19). Maturation of organic rich phosphatic shales of the Phosphoria Formation probably
corresponds to this time period (Heasler et al., 1996). Several authors suggested that
Phosphoria oil formed in western Wyoming and migrated as far as the eastern Powder
River basin (Sheldon, 1967; Claypool et al., 1978). Others agree on local generation
without invoking long distance migration (McCaleb and Willingham, 1967; Peterson,
1984).
Effective cap rocks for most Paleozoic and Triassic reservoirs in the Bighorn
basin are the calcareous shales, siltstones, and tight carbonates of the Dinwoody
Formation. Red shales and evaporites of the Triassic Chugwater Group, and also the fine-
grained impervious Goose Egg Formation could act as a good seal rock over Paleozoic
and Triassic reservoirs. All of these cap rocks become ineffective where they are intersected by faults, or where the erosion surface has cut so deeply that the Phosphoria source rocks were exposed and lost their capacity to generate hydrocarbons (Stone,
1967). In some areas, the impermeable red beds and evaporites of the lower Amsden
Formation could also become cap rocks. This condition sealed some hydrocarbons within the underlying Madison Limestone.
Through 1989, the Sage Creek Tensleep reservoir has produced 12.1 MMBO and
125 MMBW (Wyoming Geological Association, 1989). Currently twenty-three wells
produce about 390 BOPD and 13,600 BWPD. Under current operations the estimated
ultimate recovery (EUR) for the field is 15.4 MMBO, with the remaining reserves 52
Phosphoria Tensleep ) m k (
h t p e D
Age (MA)
Figure 2.19. Burial history diagram for the sedimentary column of the Bighorn basin. See Figure 2.3 for a complete listing of formation names. The Phosphoria Formation was rapidly buried at the end of the Mesozoic. From Heasler et al. (1996). 53
estimated at 3.3 MMBO (Borah-Borah, 1996). The current operator of the field is Equity
Oil Company.
Production in the Sage Creek field was first established in June 1948, with the completion of the Dorothy Fox #1 (Section 5, T57N-98W) in the Madison Limestone for
an initial potential of 732 BOPD and 44 BWPD. Soon after this well, the #2 Fox (Section
7, T57N-98W) was completed for 24 BOPD and 6 BWPD from the Madison. These two
wells have produced about 300 MBO. Several other unsuccessful completion attempts
were made in the Madison. Most recently, the SCU #21 well (Section 7, T57N-98W),
tested 25 BOPD and 1200 BWPD from the Madison.
The Tensleep Sandstone reservoir was discovered in July 1952, with the
completion of the Fox #3 (Section 7, 57N 98W, also known as SCU #3) for an initial
potential of 224 BOPD and 20% water cut. Subsequent Tensleep development led to 31
producers and 32 dry holes. Some characteristics of Tensleep reservoirs in Sage Creek
field are: average porosity from core is 15%; average permeability from core is 192 md;
average pay thickness is 100 ft; there is a tilted oil-water contact; the gas-oil ratio is 30:1; initial pressure was 1400 psi; there is a strong water drive. Oil characteristics are: oil gravity is 23.5o API; sulfur content is 2.85%; and nitrogen content is 0.198% (Borah-
Borah, 1996; Wyoming Geological Association, 1989).
Oil and gas resources in the Bighorn basin primarily occur in structural traps
around the basin margins with the contribution of less common stratigraphic traps (Gries
et al., 1996). Many structural traps have strong surface anticlinal expressions unless they 54
are deeply buried in the basin. Numerous formations, ranging in age from Cambrian to early Eocene, produce hydrocarbons from these traps. Madison, Tensleep, Phosphoria and Frontier are the principle formations that contribute to production. Among them, late
Paleozoic reservoirs hold 90% of the discovered reserves in the basin. Sandstone is the dominant reservoir rock except for carbonates of the Phosphoria Formation and Madison
Limestone.
Pedry (1975) and Stone (1967) proposed hydrodynamic flow as the main factor causing the tilted oil-water contact in Sage Creek (Figure 2.20). As an alternative, Todd
(1963) and Lawson and Smith (1966) suggested that oil had been in place in paleostructures that formed before the Laramide orogeny. Later deformation may have caused tilting of the oil-water contact (Borah-Borah, 1996) (Figure 2.21). 55
R 98 W R 97 W STRUCTURE CONTOURS TENSLEEP SANDSTONE
T 57 N
Figure 2.20 Structural contour map of Sage Creek field, showing general direction of hydrodynamic flow, postulated oil-water contact before hydrodynamic flow, and actual producing area within Tensleep Sandstone (from Stone, 1967). 56
Phosphoria Oil Oil
Oil
Early Migration Into Traps
Oil horia Phosp Oil Oil
Eocene Aged Thrust Tilts Oil/Water Contact
Figure 2.21 Origin of tilted oil-water contact in Sage Creek field, according to Borah- Borah (1996) based on Lawson and Smith (1966).
57
CHAPTER 3
OUTCROP STUDY: BEAR CANYON, PRYOR MOUNTAINS, MONTANA
3.1 Introduction
In order to look at lateral continuity of beds and the vertical stacking of facies, an outcrop study of the Bear Canyon area was conducted. A stratigraphic section 210 ft (64 m) in length was measured from the upper boundary of the Ranchester Limestone member of Amsden Formation through the entire Tensleep Sandstone.
3.2 Location
Bear Canyon is situated in the Pryor Mountains, about 7 mi (11 km) north of Sage
Creek field (Figure 3.1). The canyon is located in Section 4, T9S-R26E, Carbon County,
Montana. The location can easily be reached by vehicle via U.S. Highway 310. Bear
Canyon is only a 20 minute drive along a dirt road from the highway, or about a 45 minute drive from the city of Lovell, Wyoming.
Bear Canyon, one of several measured sections described by Mankiewicz and
Steidtmann (1979), is the northernmost location within their regional correlation. The exact location of the Mankiewicz and Steidtmann (1979) measured section 58
, 1 l l 1 (
i o v e m L
7
o m N r G f b o u t N a d I d h e M c o a a O r
e t r Y r
d i W b e n o n a
c e
b l ) i s o n i s t m i e c c k e
c m s
a
0 d s 5 e i 4 ( 2 u r s o n i a t e a B M
o c . L 0 a
. e r a a e r a n g u d y t s o u n d i r N o p u r r s c
) o f o u t p m a k
m
i
n y o l 6 a . m
v e C 1
a r ( 1 r a T e
: B
B
n o f o p i n t a 3 1 0 . o c m y
e y a c n S n .
i a p h i d m g h w a i C e
r H r 4 5
u a t s n a e o p g r f a a
T b o u t B
e : a 0 o n t n A 2
i M
M .
1 : I . n g , 3 . A i
o m r e C 0 f
) y o m g u r i k m F W 59
is unknown, but the comparison between measurements made in this study and their
section shows similarities (Figure 3.2).
The Tensleep Sandstone is exposed in a series of hills with an average elevation
of 300 ft (91 m). This characteristic makes the Bear Canyon outcrop an excellent location
for the study of Tensleep Sandstone in an interval equivalent to Sage Creek field.
Using a Jacob staff that was 5 ft (1.5 m) in length, I measured the section along a
line N 30oW. Dip and dip direction is 10o to the NNE. Total thickness of the section is
210 ft (64 m), with the starting point assumed to be the Ranchester Limestone member of
Amsden Formation (Figures 3.3 and 3.4).
A gamma ray scintillometer was used to measure gamma ray values every half
foot along the line of section. At each station, five readings were recorded. Results were
computed by eliminating the highest and lowest readings, then taking an average of the
three remaining readings. The GR profile is shown in the first column of Figure 3.3.
3.3 Lithofacies Types
All of the lithofacies types described in the previous chapter, except for the
intraset sandstones, are present in this outcrop. The upper eolian section and the lower
marine section can be seen from a distance (Figures 3.4 and 3.9). The tabular planar
cross-stratified sandstone facies are characterized by large to very large cross-bedded units, which are bounded by planar surfaces to form tabular bodies. This facies consists 60
Mankiewicz and Steidtmann (1979) This Study
110
105 ) p n e a e i l 100 l o s 15 m e
n y e t l p T n e
a e r n l i e )
95 s m p n o p a n e i ( d T U
o l r e e (
90 p p U
85 0 r e t e
r 80 m e t 6 0 M e
75 ) l a d i p t p e 70 b e e u l s e
s l ) s e n - t o n e a n i e r T p
T
u r 65 a r s r
e e m &
( n o w a o w i L l o L
60 ( e
55
50
45
Figure 3.2 Comparison of measured section at Bear Canyon, Section 3-4, T9S-R26E, Carbon County, Montana. Modified from Mankiewicz and Steidtmann (1979).
61
250
GR Profile
200 p e e l n n s a e i T l
r o e p e 150 p U
100 Marine Sandstone Facies
Tabular-planar Cross-stratified Facies p e e l
e Large Scale Deformed Sandstone Facies n n s i e r T Interdune Facies
r a
50 e w m o L
0 0 100 200 300
Figure 3.3 Bear Canyon measured section of this study showing the distribution of eolian and marine lithofacies. Far left is GR scintillometer profile. 62
Reserved for Figure 3.4 63
of well-rounded, well-sorted, fine to very fine-grained quartz arenites. This facies dominates the upper part of the section (Figure 3.5). The second most abundant facies is marine sandstones, characterized by light gray to light brown sands, with distinct sedimentary structures such as wavy lamination, horizontal lamination and low-angle cross stratification. Evidence of organic activity in the form of burrows is very common.
This facies dominates the lower part of Tensleep interval (Figure 3.6). However, at the very top of the Upper Tensleep, this facies appears just before the dolomitic sandstone facies that caps the Upper Tensleep and makes a rigid dolomitic sandstone layer that can be traced along the entire Bear Canyon area.
The interdune facies is present in the section as thinly bedded (1-3 ft), horizontal stratification, and wavy lamination, with biogenic traces on top of the beds. The wet conditions caused by the rising water table led to the formation of early evaporitic cements (Krystinik, 1990). All of these factors made the interdune facies in this area tend to stand out in outcrop relief because they are more heavily cemented than the surrounding cross-stratified sets (Figure 3.6).
3.4 Description of the Measured Section
Appendix A shows the detailed measured section and the profile. In this chapter, the major features observed are discussed. The starting point of the section is part of the 64
reserved for figure 3.5 65
reserved for figure 3.6 66
Ranchester Limestone member of the Amsden Formation. It consists of limestone and
dolomitic sandstone, hard, massive but fractured, white to very light brown or gray. The
contact with the overlying Tensleep was picked at the dolomitic sandstone with white to
very light brown/yellowish white color, with sedimentary structures being parallel to
lamination. This dolomitic sandstone is not as hard as the Ranchester Limestone member.
Wavy and horizontal laminations with low-angle cross stratification dominate the
rest of the section, until the dolomite layer at about 100 ft (30 m) from the bottom. This
layer could easily be traced over the entire Bear Canyon area, as the end-marker of
marine Tensleep deposits (Figures 3.6 and 3.9).
In Bear Canyon, the boundary between marine facies and eolian facies is marked
by the end of dominantly dolomitic sandstones with dolomite layers at the top of each
bed to sandstone with lighter color and less dolomite cement. The GR profile shows that
the eolian facies exhibits consistently lower GR values compared to the marine facies.
The presence of organic activity (burrows) within the marine interval indicates a very shallow water to shoreface or tidally influenced environment. The structureless and parallel lamination in beds within suggests siliciclastic sabkha or peritidal depositional environment.
Tabular-planar cross-stratified sandstones are the most common lithofacies
observed in the eolian facies group (Figure 3.7). These are characterized by very large-
scale cross-bedded units, or sets, which are bounded by planar surfaces to form tabular
bodies. This facies consists of well-rounded, well-sorted, fine to very fine-grained quartz 67
arenites. Grain flow stratification dominates the facies with some wind ripple
stratification. Wind ripple stratification is commonly observable in the lower parts of the
cross strata sets with dips ranging from horizontal up to 12° (Figure 3.7).
Interdune sandstones are commonly observed as lenses between tabular-planar cross-stratified sandstone sets, and are characterized by horizontal layers. Well rounded, well sorted, fine to very fine grained quartz arenites of this facies are usually coarser grained than the other eolian facies. Wavy lamination and wind ripple stratification are the most common sedimentary structures. Subaqueous features such as wave rippled sandstones, laminated sandstones, and dolostones are locally observable indicating standing water in interdune areas (Kerr et al., 1986; Kerr and Dott, 1988; Aviantara,
2000). Early cementation by evaporite and/or dolomite makes this facies tend to stand out in outcrop (Figure 3.6).
Large-scale deformed sandstone facies are present near the top of the section.
These are associated with tabular planar cross-stratified sandstones (Figure 3.8). This facies commonly occurs in the upper portions of the eolian sandstones just below marine
deposits in each parasequence. This occurrence suggests that the primary sedimentary
structure is deformed due to marine incursion (Kerr, 1989).
The development of the eolian system at Bear Canyon is thin compared to other
Tensleep outcrops (Mankiewicz and Steidtmann, 1979). The total eolian thickness in the
section is only about 70 feet (21 m), and a single set could reach as much as 20 68
reserved for figure 3.7 69
reserved for figure 3.8 70
ft (6 m) thick. This is thinner than the outcrop at the Alkali Creek that reaches 110 ft
(33.5 m) total, with single sets as thick as 50 ft (17 m) (Aviantara, 2000; Ciftci, 2001).
Intrasets, as described by Aviantara (2000) and Ciftci (2001) do not appear in the
Bear Canyon section. The presence of interdunes and deformed beds in the section
suggests that standing water was common at times during deposition.
The gamma ray scintillometer signatures of these lithofacies show a higher value
for marine sandstone facies compared to eolian sands. In general, the eolian interval in
Bear Canyon showed a blocky profile, with grain flow dominated sandstones have the
lowest GR readings. In contrast, interdune sandstone facies have the high GR readings,
and lower parts of the tabular-planar cross-stratified sets are intermediate, as a result of the gradation from wind-ripple dominated strata at the base to the grain flow-dominated strata at the top of a set. On the other hand, the general profiles of marine sandstone facies show a serrated profile with overall value lower than eolian facies (Figures 3.3).
3.5 Bounding Surfaces
Because this study has only one measured section, there was not enough control to properly define bounding surfaces. Future work in Bear Canyon could use closely spaced measured sections to study lateral variability in sandstone layers. Figure 3.9 is a 71
Reserved for figure 3.9 72
photomosaic of the northern wall of Bear Canyon. The boundary between marine and eolian facies, a 0.0-bounding surface, is shown.
3.6 Discussion
Mankiewicz and Steidtmann (1979) stated that the Tensleep Sandstone shows major differences between the Upper and Lower portions, related primarily to proportions of chemical and clastic rock and to sabkha versus eolian dune depositional processes. The lower Tensleep was deposited under supratidal, intertidal, and subtidal to lagoonal conditions. Dunes are rare, and the rocks contain up to 35-weight percent detrital carbonate. Eolian intervals in this lower section are thin and are cemented primarily by dolomite.
The thickness of tabular-planar cross-strata sets in Upper Tensleep eolian interval is not more than 20 ft (6 m). This condition suggests the area had a lack of sediment supply or was located at the edge of the sand sea (erg). Another hypothesis is that the
Bear Canyon area was positioned in a tectonically stable area. The development of eolian facies could not reach a maximum due to the continuous erosion by the wind. Dunn et al.
(1996) suggested that individual dolostone-bounded eolian units generally thicken to the west of the Bighorn basin and show significant local variation in thickness across the basin. They suggested that local thickness variations might be caused by subtle differences in local subsidence rates. The same local variations in subsidence affected the 73
thickness of the dolomitic units and, ultimately, the degree of differential erosion into the
dolomites and sandstones during lowstand exposure. This is one hypothesis that could be
applied to the Bear Canyon area.
In order for sediments to be preserved in the rock record, the sediments must be
placed below some base level of erosion. Both depositional and postdepositional
processes controlled the continuity of individual marine dolomitic units. If the rate of
sediment supply outpaced the rate of sea-level rise, then the marine units were restricted
to the western portions of the basin. Conversely, if the rate of sea-level rise was
significantly greater than the rate of sediment supply, then the marine incursion extended
far to the east. The higher frequency of marine incursions on the western side of the
Bighorn basin resulted in thinner individual sequences on average, which are more
dominated by interdune accumulations than the equivalent strata in the southeastern
Bighorn basin (Dunn et al., 1996). The Bear Canyon area seemingly had a lack of
sediment supply compared to the rise of sea level at the time the Lower Tensleep was
deposited.
It has been recognized for some time that the heavily cemented marine dolomitic
units can contribute to compartmentalization in Tensleep reservoirs by acting as vertical
barriers to fluid flow between the eolian cross-stratified sandstones (Dunn et al., 1996).
The presence of dolomitic sandstone layers within the Tensleep interval and the thickness decrease of the eolian facies seem to make the Bear Canyon Tensleep a less attractive reservoir than equivalent intervals from different places within the Bighorn basin. 74
However, fracturing of the dolomitic units, which is common along the axes of structures, does allow fluid communication between the eolian sandstones (Emmet et al., 1971;
Dunn et al., 1996).
The Bear Canyon measured section provided the opportunity to see the reservoir facies at Sage Creek field in outcrop. The GR log from the measured section will be compared to wells in Sage Creek field in a later chapter. 75
CHAPTER 4
SAGE CREEK FIELD CORRELATION
In order to show the distribution of reservoir rocks within the Tensleep Sandstone
at Sage Creek field, it is necessary to construct a series of cross sections in a grid across
the field. The sections represent northwest-southeast (NW-SE) and southwest-northeast
(SW-NE) lines, which are transverse and parallel to the general southwest trend of the paleowind direction in the Bighorn basin.
4.1 Index Map
Figure 4.1 shows the grid of cross sections within Sage Creek field. Those cross sections are labeled A-A’ through K-K’ for NE-SW directions, and L-L’ through S-S’ for
NW-SE directions. There are 19 cross sections built which include 72 wells located in T
57 N – R 97 W and T 57 N – R 98 W.
Well logs were provided by Phoenix Production Co., and MJ System raster log files. The SCU #21 well log is in digital format provided by Schlumberger, and the Fox
#1 well log was digitized by Center Line Data of Denver. The remaining well logs used in this study are mostly in raster log format and/ or duplication of hardcopy prints of the 76
R 98 W R 97 W
R S RONEY #1 BREHM GOVT #1 BREHM #15-1
’ FEDERAL #2-1 A
FEDERAL #1-1 SCU #14 SCU #18 .
P Q O
KLINDT . C
#1 GOVT BREHM SC O N SCU #1
C DECKER #1 A R K
O ’ ’ FOX MADISON R H SC #2 B USA C
A PEDRY #1 ’ P G US PROD USA #1 PAN-AM E B I #1 EFFIE KLINDT #1 SCU #21 ’ DORO FOX D #3 O SCU #5 SCU #19 GOVT HILL GOV’T WOLD SCU #7 #1 #1
SCU #17 B SCU #8 ’ SCU #7 SCU #16 USA TEXAS #1 F L ’ T FOSTER BECKER G #1-5 #1 RICKETTS ’ #1 57 FOSTER BECKER-ANDERSONH #1 SCU #8 SCU #15 SCU #20 #1 R N C ’ LAUREN FEDERAL McCRARY #1 #1 PEDRY JOENS S #13 ’ N E SCU #10 SCU #13 JOENS #1 KIRK ’ Q BARNDT I #1 BARNDT #1 DILLON #1A ’ WAGNER COLEY MARMIK BARNES #1 #13-3 FOX #1 ’ SCHWAB #1 SCU #11 MARTIN-J D HAGER #1 M BREHM HAGER #1 G DILLON #1 SQ.DILLON #1 EVERGREEN-WAGNER DEAVER IRRINGTON #1 #1 SCU #9 GOVT.WINER #1 H SCU #12 F BARNDT #1 RICH-KIRK RICH-AJAX #1 HAGER#2 AJAX FLOOD RICHARDS #1 GOVT. UNIT #1 #3 RICH-AJAX #1 N #2 HAGER#1 ’ RICHARDS#3A FEDERAL #5-24 BREHN-FLOOD #1 WAGNER BARNDT #1 #2 DAVIS ’ HUSKY GOVT #1 #1 DAVIS RUTH-DAVIS K BLANSCET-CHASE #2 #1 #1 I VANSET-CHASE #1 GOVT.WAGNER STEFFENS BRABEC UNIT #24-1 #24-2 GOVT STRIKER GOVT STRIKER 24-1 #2 BERRYMAN DEAVER-FEDERAL P #1 #2 #1 BERRYMAN O ’ J #1 STEFFENS M ’ GOVT.WAGNER #24-1 GOVT STRIKER UNIT #24-1 #3 DOVE BERRYMAN-WELLS’ #2 DOVE #1 #1 FLOYD-WELLS L #1 K ’ 0 0.2 0.4 0.6 0.8 1 mile 77
original log. The cross sections are not reproduced in this study because there was not enough time to develop digital versions. However, Appendix F shows all of the interpreted log tops. The work cross sections will be incorporated into a full-field study of Sage Creek that will be done by a future student.
4.2 Correlation Framework
The cross-sections are built based on the strategy of revealing as much as possible concerning the correlation of reservoir units and bounding surfaces within the Upper
Tensleep eolian section. Availability of logs within the field and the interval covered by the logs were also factors in constructing the sections.
The base of the Upper Tensleep eolian section is used as the datum for these cross sections. The purpose is to show the original base level of the eolian system within the
Sage Creek field area. Erosion at the top of the Tensleep affects the distribution of potential reservoirs in the upper part of eolian system; therefore, the top of the Tensleep is not a good datum.
The wells were correlated from the Dinwoody through Tensleep intervals, The
Dinwoody, Phosphoria, Tensleep and Amsden (Ranchester Limestone Member) tops were picked. The Tensleep was subdivided into seven zones (Figure 4.2 and 4.3) in each well. 78
4.2.1 Well Log Signatures
The Dinwoody (Triassic) is a greenish-gray, anhydritric unit capped by anhydrite.
This zone ranges in thickness from 20-40 ft (6-12 m) and forms an effective hydrocarbon seal over the entire area. Although it has no hydrocarbon producing potential, as an impermeable layer it plays an important role as the seal of potential reservoirs underneath.
The Permian Phosphoria Formation consists of dolomite, cherty shaly siltstones, and anhydrite throughout the region. It fills in paleotopography developed on top of the
Tensleep after its erosion. The interval contains more and thicker anhydrite in the northern half of the area. The contact with the overlying Dinwoody is usually marked by
a blocky shape with low gamma ray (GR) and low porosity log (density/neutron/sonic)
readings (Figures 4.2 and 4.3).
Each of the seven Tensleep subzones overlies a low porosity, usually high gamma
ray dolomite which grades downward into sandstone with variable porosity and low
gamma ray signature (Figures 4.2 and 4.3). In the northern part of the area, the dolomite
which separates subzone T from subzone T1 commonly displays a low gamma ray
character but still forms a reliable marker. The dolomites in each zone represent shallow
marine deposits laid down during marine transgressions. Each of the seven zones
represents a parasequence bounded by marine transgressions during the development of
Tensleep Sandstone. Subzones T through T2 are dominated by eolian deposits and are 79
Sage Creek #21 Sage Creek Field Big Horn, Wyoming
1880’FEL 1830’FNL section 7; T57N; R97W Elev. KB: 4154’; GL:4144’ API#: 49-003-20923 Date logged: 29 Mar 1996
Figure 4.2 Tensleep Sandstone type log at Sage Creek Unit (SCU) #21, shows the division of the Tensleep Sandstone into seven subzones. Modified from Borah-Borah (1996).
80
RADIOACTIVITY LOG COMPANY: SUN RAY OIL CORPORATION WELL : SAGE CREEK UNIT No. 7 FIELD : SAGE CREEK COUNTY : BIG HORN STATE: WYO LOCATION: SW-SW-SW SECTION 7-57N-97W LOG MEAS. FROM K.B. ELEV. 4183 ft DRLG MEAS. FROM K.B. ELEV. 4183 ft PERM. DATUM G.R. ELEV. 4171 ft
DINWOODY 3 3 0 0 PHOSPHORIA
TENSLEEP (T) (T1) P E ) S L n a i E N l 3 T 4 o
0 0 (T2) ( e P E R U
(T3) ) e E P n i r 3 S L 5 a 0 0 m
(T4) E N - T
n R a i E l o W ( e O (T5) L
(T6) AMSDEN Figure 4.3 Tensleep Sandstone log from Sage Creek Unit (SCU) #7, shows the division within Tensleep Sandstone into seven subzones. This is an example of the reservoir zonation from an older gamma ray - neutron log. Modified after Borah-Borah (1996). 81
categorized as the Upper Tensleep, whereas subzones T3 through T6 are dominated by
eolian to marine and tidal/subtidal environment and are categorized as the Lower
Tensleep.
In general, zone T2 is thicker than T and T1, and is almost always more porous.
Zones T and T1 may be completely composed of dolomite or the sands contained within
them may be cemented with anhydrite/dolomite, lowering average porosity readings, as
well as net porosity footage within each zone. Zone T2 most consistently shows the best
reservoir parameters. It has a good low GR reading and almost always has the best
porosity reading compared to other intervals. Because of its great thickness, zone T2 may
be an amalgamated of more than one parasequence. Zones T3 – T6 are dominated by
mixed eolian, shallow marine, and tidal to subtidal or sabkha environments. There is
variability in thickness and porosity development, lithologies are commonly dolomite and
anhydrite cemented. Impermeable intervals occur between layers.
Dolomite intervals mark the base of parasequence sets within the Tensleep throughout the Bighorn basin. Kerr and Dott (1988) described subzones within the
Tensleep Sandstone that decrease in number from south to north due to progressive truncation at the base of the Phosphoria and Goose Egg member on the top of eolian
Tensleep. Aviantara (2000) reported six parasequences within the Tensleep Sandstone at
Byron field, about 12 mi (7.5 km) southeast of Sage Creek field.
Correlation of bounding surfaces within the eolian section of the Tensleep is done by correlating the 0.0 surfaces or marine units that are usually characterized by high GR, 82
low porosity, and high resistivity values. The important parameters used to pick the log signatures for first order bounding surfaces are the interval thickness between surfaces, which vary from 3-60 ft (1-18 m), and the tendencies for surfaces to climb at angles of 1 to 3 degrees parallel to the wind direction. The wind direction in general is south- southwest in the study area. Climbing surfaces resulted in at least 18 ft (5.5 m) upward climb for every 1000 ft (305 m) distance. This equals about 45 ft (14 m) higher on half mile well spacing. With these concepts in mind, the correlation framework of Sage Creek field was built and the distribution of bounding surfaces provided the key to explain the heterogeneity of reservoir distribution within the eolian Tensleep Sandstone at Sage
Creek field.
The contact between the Tensleep and Phosphoria is generally picked at the top of the uppermost low gamma ray unit in the Tensleep. High GR and porosity readings near this zone are generally included in the Phosphoria, which is known to contain phosphatic, cherty silty carbonate units near the base. The contact itself is truncated and highly irregular in nature. Topography developed on it not only from inherited topography on the Upper Tensleep dunes, but also from pre-Permian erosion by southward- southeastward flowing streams. Because this erosion formed a major valley through the area, the upper zones of the Tensleep may be missing, thus leaving lower zones such as
T1 or T2 exposed immediately below the contact. An isopach map of top Dinwoody to top of Tensleep (Figure 4.4) shows the rough and irregular contact over the top of 83
R 98 W R 97 W
RONEY #1
BREHM GOVT #1 BREHM #15-1 86 64 6 0 80 70 FEDERAL #2-1 5 57 4 0 5 0 0 40 FEDERAL #1-1 SCU #14 52 SCU #18 59 38 . O
KLINDT . C
#1 GOVT BREHM SC O N SCU #1 C 65 DECKER #1 50 47 R K O FOX MADISON R H SC #2 USA
5 A 72 PEDRY #1 P 0 G US PROD 80 USA #1 PAN-AM B I 78 #1 EFFIE KLINDT 60 80 #1 70 SCU #21 55 DORO FOX #3 SCU #5 42 44 64 5 SCU #19 GOVT HILL GOV’T WOLD SCU #7 0 #1 #1 32 4 64 0 SCU #17 4 SCU #8 6 5 0 3 0 0 42 50 0
SCU #7 SCU #16 USA TEXAS #1 56 T FOSTER 64 60 BECKER #1-5 #1 RICKETTS #1 66 57 FOSTER 44 BECKER-ANDERSON #1 SCU #8 SCU #15 SCU #20 #1 44 N 76 69 68 56 66 LAUREN FEDERAL McCRARY #1 #1 PEDRY JOENS #13 68 73 SCU #10 SCU #13 JOENS #1 KIRK 62 BARNDT 77 76 #1 50 BARNDT #1 DILLON #1A WAGNER MARMIK BARNES #1 79 COLEY #13-3 84 80 FOX #1 74 50 60 SCHWAB #1 SCU #11 MARTIN- 72 HAGER #1 0 84 BREHM 92 65 7 DILLON #1 SQ.DILLON #1 HAGER #1 EVERGREEN-WAGNER DEAVER IRRINGTON 80 #1 #1 78 80 SCU #9 GOVT.WINER #1 54 SCU #12 42 94 BARNDT #1 79 RICH-KIRK HAGER#2 RICH-AJAX #1 AJAX FLOOD RICHARDS #1 GOVT. UNIT #1 #3 85 RICH-AJAX #1 78 90 90 88 #2 84 HAGER#1 RICHARDS#3A FEDERAL 9 82 #5-24 BREHN-FLOOD 0 0 #1 WAGNER BARNDT #1 9 7 #2 0 DAVIS HUSKY GOVT #1 #1 80RUTH-DAVIS DAVIS #1 BLANSCET-CHASE 58 72 84 #2 86 #1 89 88 GOVT.WAGNER STEFFENS DAVIS-FED BRABEC UNIT #24-1 #24-2 GOVT STRIKER 83 24-1 #2 GOVT STRIKER 92BERRYMAN #1 64 #1 #2 66 BERRYMAN 75 #1 STEFFENS GOVT.WAGNER #24-1 GOVT STRIKER UNIT #24-1 #3 DOVE #2 BERRYMAN-WELLS 68 DOVE #1 #1 FLOYD-WELLS 7 #1 9 0 74 70 80 75 90 1 0 80 00 0 0.2 0.4 0.6 0.8 1 mile 84
Tensleep. The isopach map reflects the valley shape that is elongated to the south- southwest and thickens to the south.
A Tensleep structure map was constructed on the top of the T3 marker (base of
Upper Tensleep eolian interval) rather than the top of the Tensleep in order to eliminate
the effect of erosional topography on the top of the Tensleep. Figure 2.16 in the previous
chapter shows the closure at the base of the Dinwoody Formation on seismic data.
Interestingly, this pattern is very similar to the top of the T3 marker within the Tensleep
(Figure 4.5). It is a broad northwest-oriented anticlinal feature bounded on its narrow,
steeply dipping east limb, and its broad, more gently dipping west limb. North-northwest
trending high-angle reverse faults compartmentalize productive zones to the west and unproductive zones to the east of the fault.
4.2.2 Comparison to Outcrop
The measured section at Bear Canyon is situated about 7 mi (11 km) to the north of Sage Creek field. At this location, the total thickness of the Tensleep Sandstone interval is about 190 ft (58 m), compared to the average thickness of the comparable interval at Sage Creek field which is about 225 ft (69 m).
Figure 4.6 shows a schematic correlation of the Tensleep Sandstone from the subsurface of the Fox #1 well on the southwest flank, the SCU #21 well on top of the 85
R 98 W R 97 W
RONEY #1
BREHM GOVT #1 BREHM #15-1
663 947
1
2
0
0
FEDERAL #2-1 1200
FEDERAL #1-1 SCU #14 SCU #18 1129
906 . 1276
1 O 0 KLINDT . 0 C
0
#1 GOVT BREHM SC O N SCU #1
C 1343 DECKER #1
362 742 R K O 6 8 FOX MADISON
4 0 0 H 0 SC #2 USA 0 0
A R 1350 0 1286 PEDRY #1 P G US PROD USA #1 PAN-AM B I 1335 #1 1 3 EFFIE KLINDT 0 #1 SCU #21 0 500DORO FOX 1324 #3 SCU #5 620 765 SCU #19 GOVT HILL GOV’T WOLD SCU #7 #1 #1 940 500 1 SCU #17 1 1 2 SCU #8 0 1 0 0 0 0 9 0 0 0 650 829 0
SCU #7 SCU #16 USA TEXAS #1 731 1000 T FOSTER 891 BECKER #1-5 #1 RICKETTS 1125 #1 635 57 FOSTER BECKER-ANDERSON #1 SCU #8 SCU #15 271 523 SCU #20 #1 1 N 1 650 0 1121 855 1046 0 1 LAUREN FEDERAL McCRARY #1 9 0 0 0 #1 0 PEDRY JOENS 0 #13 1189 390 6 714 JOENS #1 0 SCU #10 SCU #13 0 805 KIRK BARNDT 915 #1 BARNDT #1 DILLON #1A WAGNER COLEY #13-3 MARMIK BARNES #1 626 851 9 651 380 FOX #1 0 SCHWAB #1 SCU #11 0 MARTIN- 293 710 HAGER #1 1040 340 BREHM 942 DILLON #1 SQ.DILLON #1 HAGER #1 EVERGREEN-WAGNER DEAVER IRRINGTON #1 #1 572 648 SCU #9 GOVT.WINER #1 228 SCU #12 236 672 820 BARNDT #1 801RICH-KIRK HAGER#2 200 RICH-AJAX #1 AJAX FLOOD RICHARDS #1 GOVT. UNIT #1 #3 540 732RICH-AJAX #1 312 785 #2 10 678 HAGER#1 0 RICHARDS#3A FEDERAL 5 634 #5-24 BREHN-FLOOD 00 #1 WAGNER BARNDT #1 #2 400 DAVIS HUSKY GOVT #1 #1 RUTH-DAVIS BLANSCET-CHASE 181 41 100 413 DAVIS #1 0 249 30 #2 139 #1 0 0 326 2 (100) 00 GOVT.WAGNER STEFFENS BRABEC UNIT #24-1 #24-2 GOVT STRIKER 4 235 24-1 #2 GOVT STRIKER BERRYMAN DEAVER-FEDERAL #1 #2 #1 (18) (130) (151) BERRYMAN (200) #1 100 STEFFENS GOVT.WAGNER #24-1 GOVT STRIKER 0 UNIT #24-1 #3 DOVE (121) #2 BERRYMAN-WELLS DOVE #1 #1 FLOYD-WELLS #1 (370) (268) (176) (100 (78) ( ) 20 (106) 0)
0 0.2 0.4 0.6 0.8 1 mile
86
BEAR CANYON MEASURED SECTION E E
6 5 2 2
R R RONEY #1 MONTANA R 98 W R 97 W WYOMING . O . C
O N C R K O
H SCU #21
A R P G I GOV’T WOLD #1 B SCU #7 SAGE CREEK SCU #15 FIELD T 57 FOX #1 N GOVT.WINER #1
DEAVER-FEDERAL #1
0 0.4 0.8 1.2 1.6 2 mi
Figure 4.6 Location map showing the distance of Bear Canyon measured section area to Sage Creek field. The cross section correlating Fox #1 well and SCU #21 well to measured section is shown in the next figure.
87
Reserved for figure 4.7 88
structure, and to the Bear Canyon measured section. Note the thickness decrease of the
Lower Tensleep towards Bear Canyon. GR readings from a scintillometer device at Bear
Canyon correlate to GR readings of subsurface well logs. The signatures of the GR can be easily used to correlate the bounding surfaces within the eolian Tensleep interval. The first order bounding surfaces tend to have high GR readings that reflect the downgraded porosity values due to cementing by dolomite at the surfaces during deposition. This may be related to high uranium content in dolomite cements that causes higher gamma ray readings. It may also related to clay content within the interdune facies that commonly occur between eolian dunes and at the base of the next eolian system (see explanation in previous chapter and Figures 2.10 and 2.13).
Hydrocarbon reservoirs of the Upper Tensleep (subzones T through T2) have the best reservoir parameters in the subsurface. Thick eolian sandstones compare to subzones
T3 through T6 that have dominantly marine and tidal influence. Reservoir quality in the
Lower Tensleep is decreased by organic activity, soft sediment deformation, and early cementation with dolomite and anhydrite that can clearly be seen in outcrop.
4.3 Discussion
The most important result of the constructed grid of cross sections throughout the field is to define the productive zones within the Tensleep Sandstone. From seven 89
subzones of the Tensleep Sandstone, the most productive is the eolian interval of the
Upper Tensleep, particularly subzone T2. The Lower Tensleep (subzones T3 through
T6), which are dominated by marine to tidal environments, have decreased potential to become a hydrocarbon reservoir. It is possible that an eroded marine unit, or 0.0 surface exists within the T2 interval. There could be more than one cycle within the T2 subzone.
In general, the T through T6 subzones are operational or production units that are related to parasequences.
First order bounding surfaces within the Upper Tensleep eolian interval can be used to map eolian heterogeneity. 3-D simulation of outcrops of the Tensleep eolian system by Ciftci (2000) provided a good description of first and second order bounding surfaces that may compare to surfaces at Sage Creek field.
90
CHAPTER 5
SAGE CREEK FIELD: CORE DESCRIPTION, FOX #1
5.1 Introduction
The Fox #1 well was drilled by Sohio Oil Company on December 5, 1985, through March 20, 1986, to evaluate an a 20 acre spacing in the Sage Creek field, Big
Horn County, Wyoming. A repeat formation tester (RFT) survey performed through perforations on two intervals (3380 –3394 ft and 3422–3432 ft) showed that the well was dry. The well was subsequently plugged and abandoned (P&A). Interestingly, this well has a continuous core through the Tensleep Sandstone (interval 3346–3505 ft).
This well cored the Tensleep Sandstone from the overlying upper contact with the
Phosphoria Formation through the base of the Lower Tensleep marine interval. The well reached total depth (TD) at 3535 ft on December 17, 1985.
Phoenix Production Company was the field operator when this study began. The current operator of Sage Creek field is Equity Oil Company. Phoenix loaned all the data including the unslabbed core from this well. This well is important because of the continuous cored interval in the eolian and eolian-marine section of the Upper and Lower
Tensleep. 91
5.2 Location
The Fox #1 well is located 1819 ft from the south line (FSL), and 1766 ft from the
west line (FWL), in the SW NE SW quadrant of section 18, Township 57 North (T57N),
and Range 97 West (R97W), Big Horn County, Wyoming (Figure 5.1). This well is
located on the southwestern flank of Sage Creek anticline, surrounded by producing wells
at an average distance of 1000 ft.
5.3 Lithofacies Types
A detailed description of the cored interval within the Fox #1 well was done by
the author at United States Geological Survey (USGS) Core Facility in Denver. A
complete core description and profiles are found in Appendix B. The 4.5 in diameter core
is on loan from Phoenix Production Co. to CSM, and was cut with a preferential cutting
direction that was parallel to the dip direction in order to show more true dip than
apparent dip of cross strata.
A 159-foot core of Phosphoria (3 ft) and Tensleep (156 ft) was taken for detailed reservoir evaluation. Core Laboratories, Inc. (Appendix D) conducted core analysis of porosity and permeability for 96 core plugs. 92
R 98 W R 97 W
RONEY #1
BREHM GOVT #1 BREHM #15-1 INDEX MAP OF FEDERAL #2-1
SAGE CREEK FIELD . FEDERAL #1-1
SCU #14 O SCU #18 C .
O KLINDT N C R #1 GOVT BREHM SC SCU #1 DECKER #1 O K H
FOX MADISON SC #2 USA A R PEDRY #1 G I P US P RO D USA #1 PAN-AM B #1 EFFIE KLINDT #1 SCU #21 DORO FOX #3 SCU #5
SCU #19 GOVT HILL GOV’T WOLD SCU #7 #1 #1
SCU #8 SCU #17
SCU #7 SCU #16 USA TEXAS #1
FOSTER BECKER #1-5 #1 RICKETTS #1 FOSTER BECKER-ANDERSON #1 SCU #8 SCU #15 SCU #20 #1
LAUREN FEDERAL McCRA RY #1 #1 PEDRY JOENS #13 SCU #10 SCU #13 JOENS #1 KI RK BARNDT #1 BARNDT #1 DILLON #1A WAGNER COLEY #13-3 MARMIK BARNES #1 FOX #1 SCHWAB #1 SCU #11 MARTIN- HAGE R #1 SQ.DILLON #1 HAGE R #1 EVERGREEN-WAGNER DEAVE R IRRI NG TO N #1 #1 BREHM DILLON #1 SCU #9 GOVT.WINER #1 SCU #12 BARNDT #1 RICH-KIRK HAGE R# 2 RICH-AJAX #1 AJAX FLOOD RICHARDS #1 GOVT. UNIT #1 #3 RICH-AJAX #1 #2 HAGE R# 1 RICHARDS#3A FEDERAL #5-24 BREHN-FLOOD #1 WAGNER BARNDT #1 #2 DAVIS HUSKY GOVT #1 #1 DAVIS RUTH-DAVIS BLANSCET-CHASE #2 #1 #1
GOVT.WAGNER STEFFENS BRABEC UNIT #24-1 #24-2 GOVT STRIKER GOVT STRIKER 24-1 #2 BERRYMAN DEAVER-FEDERAL #1 #2 #1 BERRYMAN #1 STEFFENS GOVT.WAGNER #24-1 GOVT STRIKER T UNIT #24-1 #3 DOVE BERRYMAN-WELLS #2 DOVE #1 #1 FLOYD-WELLS #1 57 0 0.2 0.4 0.6 0.8 1 mile N
0 0.2 0.4 0.6 Mile 93
Correlation of the Fox #1 core with logs in other Sage Creek wells indicated that subzone T (the uppermost interval of the Upper Tensleep) is not present. The T1 subzone
(3360-3379 ft log depth) in this well correlates with a 4.5 ft porous zone in an otherwise dense dolomite. The T2 subzone (3379-3437 ft log depth), the primary producing horizon in the field, is a 58 ft thick very fine to fine grained eolian sandstone. The T3 and T4 subzones (3446-3462 ft log depth and 3468 ft -3484 ft log depth respectively) are porous zones within a sandy dolomite. The T5 subzone (3488-3510 ft log depth) is a porous zone of deformed eolian sandstone. The T6 subzone (3512 ft to TD log depth) is less than 2 ft thick and is a dense interval dominated by marine dolomite (see Figure 5.2 and Figure 5.3 for the well log response and minipermeameter data).
Five different facies have been encountered in the core data, which are tabular- planar cross strata, interdune sandstone, large-scale deformed dune sandstone, marine sandstone, and dolomitic sandstone. These facies correspond well with the measured section data at Bear Canyon (Chapter 3). Appendix B shows the detailed core description of the Fox #1 well.
As in the measured section at Bear Canyon, the Fox #1 core shows the general division of the upper and lower Tensleep. The upper part is dominated by eolian facies, while marine to tidal and sabkha deposits represent the lower Tensleep sandstone interval
(Figure 5.2). 94 A
I 3346 R O
H 3350
P Marine
S Dolomite O
H 3355 P
P Marine E 3360 E L S 3435 N CORE #3 1
E 3365 Dolomitic T T Sandstone Marine 3440 3370 Dolomitic SS Marine 3445 Marine Interdune 3 3375 T
3450 3380 Deformed Dolomitic SS Sandstone 3455 3385 CORE #3 CORE #4 3460 3390 Marine Interdune
3465 4
3395 T
CORE #1 3470 Dolomitic SS 3400 2
CORE #2 T Eolian Sandstone 3475 3405 Marine
CORE #4 3480 3410 CORE #5 Interdune Interdune 3485 3415 5
3490 T 3420 Eolian Sandstone 3495 Eolian Sandstone 3425 Interdune Deformed 3500 Sandstone 3430 Eolian Sandstone 3505 CORE #2 3435 3506 Marine T6 Figure 5.2 Core profiles of Fox #1 well (Sec.18, T57N-R97W), Sage Creek field, showing lithofacies types. Interval core segment numbers are on the left of profiles. Depth is in ft. A detailed core description and legend are in Appendix B. At left is upper Tensleep and at right is lower Tensleep.
95
Profiles GR D-N Por. 3350
st Phosphoria 1 dolomite Neutron
1 T1 # Density nd E 2 dolomite R O p C e e l ) s n n
3400 a i e l T
o r e e T2 ( p p 2 # U E R O C
rd
3 3 dolomite # E
3450 R
O T3 C
th )
4 dolomite p 4 e e # n e i l E r s R a
T4 n O e m C - T
th n r
5 dolomite a e i l w o 5 o e # ( L
E 3500
R T5 O C th 6 dolomite 0.001 10 0 50 100 150 0.3 0.2 0.1 0.0 -0.1 T6 0. 3 0. 2 0. 1 0 -0.1 Figure 5.3 Fox #1 well with GR/Density-Neutron porosity logs and permeability profiles from minipermeameter reading of Tensleep Sandstone. On the far left is core profiles and its segments. On the minipermeameter track, dots are core plugs permeability from Core Lab, solid and dotted line are permeability from minipermeameter with half foot increment. 96
5.3.1 Marine Sandstone
The Lower Tensleep represents deposition under more wet condition than the upper part, with very shallow standing water, to tidal influence and rising ground water due to marine incursion into the eolian dune field (Mankiewicz and Steidtmann, 1979;
Kerr and Dott, 1989). Although all lithofacies explained in the previous chapters are present, there are two dominant lithofacies in the Lower Tensleep: the marine sandstone facies and dolomitic sandstone facies.
5.3.1.1 Physical Description
The marine sandstone facies is characterized by wavy lamination, low angle cross strata, horizontal lamination, and is sometimes structureless. It is brown in color (oil stained), rounded, and moderately to well sorted, very fine to fine grained sandstone.
Dolomitic nodules, anhydrite nodules, burrows and bioturbation are present in the sand body. The interval also contains pyrite (black) material and thin laminations of greenish gray clay. The inferred depositional environment is shoreface to foreshore. Figure 5.4 shows a core photo of the marine sandstone facies from the Fox #1 well.
The dolomitic sandstone facies is characterized by a gray, greenish or reddish color, with subrounded, well-sorted, very fine-grained sandstone. Strata are wavy 97
Reserved for figure 5-4 98
laminated and sometimes structureless. The facies also shows pyrite non-existent rich material (black), moderate to heavily bioturbated, anhydrite nodules, and low to oil stain.
Figures 5.4 and 5.5 show core photos of the dolomitic sandstone facies from the Fox #1 well.
The marine facies, including marine sandstone and dolomitic sandstone, shows heavily bioturbated, algal/bacterial mat desiccation and biogenic structures of an unidentified type which correspond to a siliciclastic sabkha environment at Sage Creek field. This feature is similar to the lower Tensleep interval in the measured section at
Bear Canyon. These are interpreted as subaqueous deposits in hypersaline waters that were freshened periodically, allowing colonization by algae and the formation of algal mats.
The large-scale deformed dune sandstone facies, interdune sandstone facies, and tabular-planar cross strata facies are also present in the lower Tensleep. Small-scale bi- directionally cross-stratified sandstones overlie marine sandstones at the bottom of the cored interval (Figure 5.6). These also underlie the large-scale deformed sandstone facies
(Figure 5.7). This small-scale eolian facies within the lower Tensleep may represent either low amplitude eolian dunes migrating over a tidal flat, megaripples in tidal channels, or longshore bars (Mankiewicz and Steidtmann, 1979).
The interdune sandstone facies within this interval appears as crinkled or wavy lamination caused by the drying up of algal mats. Color is brown. Sands are rounded; moderately to well sorted, very fine to fine grained deposits. Anhydrite nodules are 99
Reserved for figure 5-5 100
Reserved for figure 5-6 101
Reserved for figure 5-7 102
present within the sandstone, and are also present as mineral fills in fractures or in
burrows. Figure 5.5 shows a core photo of interdune sandstone facies from the Fox #1
well.
The typical log response for this marine sandstone facies is corrugated with low porosity and low permeability (see Figure 5.3). Low GR values with better porosity are usually related to dolomitic sandstone facies. A higher GR value with very low porosity and corresponding permeability indicate the marine sandstone and interdune facies.
Facies interpretation from the core is well correlated with the measured section data.
Similar bed thickness variation and comparable GR values also appeared in the GR
profile from the measured section at Bear Canyon. These factors suggest that this lower
Tensleep interval is dominantly of marine to tidal origin.
5.3.1.2 Discussion – Marine Sandstones
The abundance of biogenic structures and organic activities in the form of
burrows and bioturbated strata within marine sandstone facies indicate a normal marine
salinity and relatively calm conditions. The presence of small-scale eolian facies indicates
that some eolian system could be developed in this area. The interdune sandstone facies
is characteristic of wet eolian systems (Crabaugh and Kocurek, 1993), therefore the
presence of interdune facies overlying the thin tabular-planar cross strata indicates that 103
the rising water table or marine incursion exceeded the sediment supply in the area. The dolomitic sandstone represents the tidal flat to sabkha depositional system. Within this lower Tensleep interval, they appear in form wavy laminated sediment cemented by dolomite with localized pyrite and anhydrite nodules. This lithofacies suggests that water influence always controlled the preservation of sediment. Kocurek and Havholm (1993) suggested that both hydrodynamic and aerodynamic conditions controlled preservation of the wet eolian system. Where the sediment supply is roughly balanced by the rate of the water table rise, there is little dry sand on the surface at any given time for dune building.
Such a substrate would characterize a sabkha or a wet-damp sand sheet. Conversely, where the sediment supply exceeds the water table rise, then dry sand exists on the surface, and it develops a dune complex (Crabaugh and Kocurek, 1993).
All lithofacies that have been observed from this lower Tensleep interval suggest wet conditions. The presence of 15 ft (4 m) of eolian sandstone (3492 to 3505 ft) in the form of small-scale tabular-planar bi-directional cross strata, topped by large-scale deformed sandstone facies and interdune facies (Figures 5.6 and 5.7), indicates that the water table was the most common factor controlling deposition at the time.
5.3.2 Eolian Sandstone
In general, Tensleep eolian sandstones are composed of rounded to subrounded, moderately to well sorted, fine to very fine quartz arenites. All sandstone intervals within 104
eolian intervals appear to be oil stained. When it is stained with oil in core, there is a
distinctive light brown to dark brown color. Other intervals that mainly consist of
dolomite or evaporitic sabkha condition are very light gray to gray or very light brown to
white in color.
All lithofacies explained in the previous chapter are also present in this interval.
The most common facies present is tabular-planar cross strata dune sandstone and large- deformed dune sandstone. The interdune, dolomitic sandstone, and marine sandstone facies are present as interbeds.
5.3.2.1 Physical Description
The tabular-planar cross strata facies is characterized by high-angle cross strata
(12o-27o), occasionally structureless, dominated by grainfall and wind ripple
stratification, thick bedded, brown in color, oil stained, rounded, moderately to well
sorted, very fine to fine grained sandstone. The grain size profile shows no regular trends.
Figure 5.8 shows core photos of tabular-planar cross strata facies from the Fox #1.
A blocky shape of the gamma ray log is a typical response for this type of facies.
Facies interpretation from the core is well correlated with the measured section data.
Similar thick-bedded, high-angle cross strata with grain flow deposits, which dominated 105
Reserved for figure 5-8 106
the upper part and wind ripples that dominated the lower part, were noted in the measured section at Bear Canyon. These factors strongly suggest that the facies is of eolian origin.
The large-scale deformed dune sandstone facies is characterized by contorted stratification, thick-bedded, brown color, rounded, moderately to well sorted very fine to fine-grained sandstone. No regular trend has been noticed in the grain size profile. The deformation was due to liquefaction by water coming from the sea or the rising of the ground water level. Organic activities in the form of burrows are very common and sometimes completely deformed the original stratification. In some places, cross stratification can be seen.
Interdune sandstone facies is characterized by crinkled or wavy lamination caused by the drying up of algal mats, brown color, rounded, moderately to well sorted, very fine to fine grained sandstone. Anhydrite nodules are present within the sandstone, and are also present as mineral fills in fractures or in burrows. Figure 5.8 shows a core photo of interdune sandstone facies from the Fox #1 well.
The dolomitic sandstone facies is characterized by a gray, greenish or reddish color, with subrounded, well sorted, very fine grained sandstone, and are wavy laminated with sometimes structureless strata. Pyrite and anhydrite nodules, and low to no oil stain occur. Anhydrite cement is also present as filling of fractures and early cementation of unidentified biogenic traces or burrows (see Core Photo Box #3, Appendix B). The dolomitic sandstone facies found in the upper Tensleep probably represent hypersaline ponds occurring in deflation sags between dune ridges. These ponds would be subject to 107
periodic flooding during storms or unusually high tides (Mankiewicz and Steidtmann,
1979).
Marine sandstone facies in the upper Tensleep are characterized by wavy lamination, low angle cross strata, horizontal lamination, and they are sometimes structureless. It is brown in color (oil stained) and light gray to greenish gray (no oil stained), rounded, and moderately to well sorted, very fine to fine grained sandstone.
Dolomite nodules, anhydrite nodules, burrows and bioturbation are present in the sand body. The interval also contains pyrite (black) material and thin laminations of greenish gray clay. The inferred depositional environment is shoreface to foreshore (see Core
Photo Box #4, Appendix B).
5.3.2.2 Wind Ripple Facies
Wind ripples are formed by saltation processes that result in very tightly packed sand grains that may be inversely graded upwards (Crabaugh and Dunn, 1996). These migrating ripples may be the major processes responsible for forming the “pinstripe” structure within dune sandstones (Ahlbrandt and Fryberger, 1982). Bagnold (1941) hypothesized that the segregation of grain sizes was produced by differential transport during periodic episodes of wind activity, the smaller grains outrunning the coarser ones, being deposited first, and then being mantled by coarser grains that were deposited later. 108
There are two types of wind ripple strata that can be found in eolian deposits: (1)
subcritically climbing translatent strata, each of which corresponds to a thin lamina left
by the passage of an individual ripple and are associated with incomplete ripple
preservation, and (2) supercritically climbing translatent strata that are characterized by
wavy laminae that parallel the depositional surface and are associated with complete
ripple preservation (Hunter, 1977). The bulk of Tensleep stratification produced by wind
ripple is the thin “pinstripes” left by the passage of successive individual subcritically
climbing ripples (Humphreys, 1996).
In the Fox #1 core, the wind ripple facies commonly occurs in dune deposits. The
tabular-planar cross strata is where wind ripple structures can commonly be found. They
are generally deposited as low-angle, thin (0.04 to 0.2 in), very distinct, inversely graded laminations, in very fine to fine grained sand. Oil stain within the sandstone clearly enhanced the visibility of the pinstripes in wind ripple facies, as the oil is trapped in finer grained sand.
This wind ripple facies commonly occurs at the base of eolian units just overlying the bounding surfaces, and gradually changes into grain flow stratification facies.
109
5.3.2.3 Grain flow Facies
Grainflow laminae result from avalanching on the lee face of the bedform, they are loosely packed, well sorted, coarsening–upward laminae. Grainflow stratification takes place when deposition in the flow separation zone causes the slopes to reach the angle of initial yield. This facies commonly occurs gradually overlying the wind ripple facies. The strata produced by a grainflow is a discrete package of sand, which dips at a high angle relative to wind ripple strata (Hunter, 1977).
Within the core, similar to wind ripples, these grainflow stratifications are found in tabular-planar cross strata. Grainflow stratification is also seen in large-scale deformed dune sandstone facies.
Grainflow strata are generally thicker than wind ripple laminae, have loose grain packing, and are coarser grained than other eolian stratification types (Hunter, 1977).
Within the cored interval, these strata are characterized by discrete, inversely graded, relatively thick (0.4 to 1.5 in), well sorted, sometimes wavy lamination. In the large- deformed dune sandstone facies, grainflow stratification almost always can be recognized.
The amount of wind ripple strata exceeds grain flow strata. This is attributed to the fact that the tops of the large dunes are truncated by overriding dunes, effectively preserving only the lower portions of the dune. Since the grainflow deposits are contained mostly in the upper portion of the dune, much of this type of stratification was destroyed 110
in the dune migration process. This leaves a deposit that is dominated by wind ripple lamination with small amounts of grainflow lamination occurring towards the tops of the dune sets.
5.3.2.4 Grainfall Facies
Grainfall lamination is produced in zones of flow separation, which occur on the leeward side of dune crests and are characterized by indistinct lamination and rapid lateral thickness changes in both a single grainfall deposit and in individual layers
(Hunter, 1977). The separation of the airflow entrains sand grains, which quickly fall out of suspension as the airflow loses strength. Grainfall deposits are usually the loosest packed of all eolian stratification types and are confined to the upper portions of bedforms (Hunter, 1977).
In the Fox #1 well, grainfall stratification was not observed within the Tensleep interval. Only two of the three main types of stratification were observed during this study. Grainfall deposits were not observed in the surface measured section or the core that was examined. This is attributed to two possible reasons: (1) grainfall strata occur in the upper portion of large dunes. Because eolian bedforms commonly show a low angle of climb (< 1o) (Crabaugh and Kocurek, 1993) only the lower portions of a dune’s lee face will be preserved. Thus the grainfall strata that likely existed within the dunes were 111
eroded during the preservation process, or (2) most grainfall strata has been reworked
into grainflow strata during oversteepening and subsequent slipface failure (Humphreys,
1996).
5.4 Bounding Surfaces
The 1.0-bounding surfaces are present where high-angle tabular-planar cross
strata are truncated by the same lithofacies with horizontal to very low-angle (< 5o)
laminae. Typically, Tensleep eolian cross strata are in tangential contact above, and
discordant contact below a 1.0-bounding surfaces (see Core Photo Box #7 through #11,
Appendix B). Interdune deposits at 3416.8 ft overlie the bounding surfaces. Such surfaces
are attributed to the migration and accumulation of the largest eolian bedforms (dunes or
draas) (see Core Photo Box #10 and #9, Appendix B).
The 1.0-bounding surface at 3423 ft (see Core Photo Box #11, Appendix B) has anhydrite cementation along the surfaces, presumably as a result of greater fluid flow parallel to the bounding surfaces than across them.
2.0-bounding surfaces separate bundles of eolian cross strata within a set. They
sweep downward and define trough cross-strata axes that plunge west southwestward at
the base of tabular-planar set. Since the core is not oriented, the strategy is to pick the
2.0-bounding surfaces as the bounding surfaces that occur at the base of the tabular- 112
planar lithofacies. Such an example is seen at 3428 ft (see Core Photo Box #11,
Appendix B).
3.0-bounding surfaces occur mostly high within the tabular-planar set. They separate eolian cross strata with minor variations in dip direction across the surface.
These surfaces bound strata that change upward from low-angle wind ripple laminae that roughly parallel the bounding surface they overlie, to high-angle wind ripple or grainflow laminae. Such an example is seen at 3409.5 ft (see Core Photo Box #9, Appendix B).
Erosional truncation of the higher-angle wind ripple or grainflow laminae by a 3.0- bounding surface indicates that the lee face was eroded back by winds moving along or up the lee face. The thin wind ripple laminae that overlie 3.0-surfaces are at approximately the same angle as the surface, and represent the onset of renewed deposition (Crabaugh and Dunn, 1996).
5.5 Core Analyses
A major goal of this study is to use well Fox #1 core data extensively to define its correlation with another well in Sage Creek field and to an outcrop study at Bear Canyon.
The availability of continuous core through the Tensleep Sandstone was an advantage to study petrophysical properties of the whole Tensleep deposition. A conventional log suite includes GR, density-neutron, resistivity, microresistivity, spectral GR, and Photoelectric 113
or PEF traces. Figure 5.9 shows the combination of several digitized log signatures and
Tensleep Sandstone subdivisions.
5.5.1 Conventional Core Analysis
A 159 ft core of Phosphoria (3 ft; 0.91 m) and Tensleep (156 ft; 47.6 m) was taken for detailed reservoir evaluation. Core Laboratories, Inc. (Appendix C) conducted core analysis of porosity and permeability on 96 out of 149 core plugs (CoreLab, 1985).
This analysis had been done on December 1985 using a conventional core analysis. Sohio
Petroleum Co. selected core plugs to be analyzed at the time. Comparing to the result of this study, the selection was targeted on productive reservoir interval, although several plugs came from the non-porous section.
Average permeability of 96 plugs from interval 3356 ft to 3506 ft is 172 mD, average porosity is 14%, and average residual oil saturation is 28.9%. Productive capacity is 15,138 mD/ft, and average total water saturation is 56% (Figure 5.10). A plot
of permeability against porosity resulted in the permeability equation:
k (permeability) = antilog ((0.2366) φ -1.6015) Eq. 5.1
114
Reserved for figure 5-9 115
Permeability vs.Porosity 10000 Core Lab data of 96 plugs
k=antilog((0.2366) φ -1.6015) 1000 ) ) d d 100 m m ( (
y y t t i i l l i i b b 10 a a e e m m r r e e P P 1
0.1
0.01 0% 5% 10% 15% 20% 25% Porosity (%)
Figure 5.10 Permeability vs. Porosity plot of 96 core plug of Fox #1 well. Recollection from Core Lab data 1986. 116
5.5.2 Minipermeameter
Core permeability measurements by Core Lab were available for 96 plugs from
3356 ft to 3506 ft core depth. In order to have more continuous permeability data along the core, this study used a probe minipermeameter (Jones, 1992). The measurements were performed on half-foot intervals along 3346 ft through 3506 ft core depth. This study also performed measurements on all 149 core plugs (including 96 plugs that had been measured by Core Lab) for calibration.
The measurements were made using the minipermeameter apparatus in the
Petroleum Engineering Department at the Colorado School of Mines. The core slab was placed in a tray, and then a nozzle was lowered onto a specified point on the core, emitting nitrogen air through the sample in spherical flow model. Each point was measured three times and the average was recorded into a spreadsheet.
Permeability measurements obtained from the minipermeameter apparatus were compared to the core permeability measurements (Figure 5.11). Minipermeameter permeability was taken on each end of the core plug, measured three times on each plug end, and averaged. Then the results were calibrated to the permeability measurements from Core Lab. There are two steps to make this calibration. First, cross plots between minipermeameter permeability (kmp) versus Core Lab analysis permeability (klab) were constructed. From Figure 5.11, the permeabilities less than 10 mD seemed to have 117
kmp-Minipermeameter Vs. klab-CoreLab 10000
1000 ) )
D D 100 m m ( (
b b a a
L L 10 e e r r o o C C
- -
b b 1 a a l l k k 0.1
0.01 0.01 0.1 1 10 100 1000 10000
k mp - Minipermeameter (mD)
Figure 5.11 Cross plot of minipermeameter permeability vs. Core Lab permeability for all plugs (96 samples) demonstrating a strong relationship, except for permeability less than 10 mD. 118
the greatest variation reading compared to the bulk of the data. This probably was due to limitations of the flowmeters used. Because of that, permeability values less than 10 mD were excluded in the second graph (Figure 5.12). A linear regression relationship between permeability from Core Lab versus permeability from the minipermeameter is:
log klab = 1.0938 log kmp – 0.2515 Eq. 5.2
correlation coefficient (R2) = 0.9744
where kmp = permeability from the minipermeameter (mD), klab = permeability from Core
Lab (mD). Second, the kmp were calculated using equation 5.2, then re plotted against the same klab (Figure 5.13). Another linear regression relationship between the two is :
log klab = 0.9917 log kmp – 0.25 Eq. 5.3
correlation coefficient (R2) = 0.9825
The formula (Eq. 5.3) then were used to calibrate all minipermeameter readings on half-foot increment of the slabbed core. This linear relationship strongly supports that the permeability obtained from minipermeameter has a very good correlation with permeability from Core Lab analysis. 119
Modified k-Minipermeameter Vs. k-CoreLab (<10mD meas. excluded)
4 ) ) D D m m ( ( 3
y = 1.0938x - 0.2515 b b a a 2 L L R = 0.9744 e e r r o o C C 2
- - b b a a l l k k
0 0 1 1 1 G G O O L L
0 0 1 2 3 4
LOG10 k mp - Minipermeameter (mD)
Figure 5.12 Cross plot of minipermeameter permeability vs. Core Lab permeability of plugs, excluding < 10 md, demonstrating a very strong relationship. The correlation coefficient (R2 =0.9744) and the equation used to correct the next graph to finalize the calibration between minipermeameter and Core Lab measurements. 120
Corrected
kmp-Minipermeameter Vs. klab-CoreLab Corrected, (<10mD meas. Excluded)
10000
y = 0.9917x - 0.25 ) ) 1000
D D 2
m m R = 0.9825 ( (
, , b b
a a 100 L L e e r r o o C C
- - 10 b b a a l l k k 1 1 10 100 1000 10000
k mpc- Corrected Minipermeameter (mD)
Figure 5.13 Cross plot of corrected minipermeameter permeability vs. Core Lab permeability from plugs, excluding permeabilities < 10 md, demonstrating a very strong relationship. The correlation coefficient (R2 =0.9825) and the equation used to calibrate all minipermeameter readings after averaging. 121
Minipermeameter readings provide a useful tool to calibrate core depth to log
depth. Calibration was done by relating the ups and downs of permeability values to the
“tight” intervals within the log, usually spikes in low GR, high resistivity, and density-
neutron porosity logs to each core interval. The result, from five core intervals are Core #
1 (3346–3399.4ft core depth) 5.5 ft has to be added to match the logs. Core # 2 (3400–
3435 ft core depth) 7 ft has to be added. Core # 3 (3435–3457 ft core depth) 3.5 ft has to
be added. Core # 4 (3457–3479 ft core depth) 4.5 ft has to be added. Core # 5 (3480–
3506.4 ft core depth) 7 ft (Figure 5.9).
An attempt to estimate the permeability based on φ and Swi (irreducible water
saturation) derived from well log was done using the Timur formula (Figure 5.14):
1/2 2.25 k = 100 (φ /Swi) Eq. 5.4
Where K (permeability) is in mD, φ is porosity from density-neutron logs, and Swi
1/2 is from Formula Swi =F/2000 (Eq. 5.5), where F (Formation factor) was derived from equation after Sethi (1979) as F=1.0/φ(2.05-φ) (Eq. 5.6) for clean granular formations.
Complete data tabulation for minipermeameter measurements and permeability
estimation from log data can be found in Appendix C. 122
Permeability Curves based on Log of Fox #1 well 3350
3400 ) ) t t f f ( (
h h t t p p e e 3450 D D
g g o o L L
3500
Miniperm plugs LOG_Timur 3550 0.1 1 10 100 1000 10000 Permeability (mD) Figure 5.14 Permeability curve of Fox #1 well, based on Timur formula (Eq. 5.4). Porosity and Swi were taken from log data. Permeability estimation are plot together with the permeability measurement from minipermeameter (line) and Core Lab data (triangle). 123
5.5.3 Capillary Pressure Analysis
Parts of this sub-chapter are modified from master of science theses by Karadavut
(2001) and Johnson (2001). “Two or more immiscible fluids in a porous media, such as reservoir rock, give rise to capillary forces. Because of the interfacial tension existing at the boundary between the fluids, the interface is curved and there is a pressure difference across the interface. This pressure difference is called capillary pressure.” (Brown, 1951).
The pressure difference across the interface between two immiscible fluids results from interactions of forces acting within (cohesive forces) and between (interfacial tension) fluids and their bounding solids (adhesive forces). This pressure difference (capillary pressure) can be defined as:
Pc = ∆P = Pnw - Pw Eq. 5.7
where,
Pc = Capillary pressure,
∆P = Pressure difference across the interface between two immiscible fluids,
Pnw = Pressure across the non-wetting fluid
Pw = Pressure across the wetting fluid
124
The pressure difference (capillary pressure) between the inside and outside of the surface can also be defined in terms of the radius of curvature of the surface and the tension (Vavra et al., 1993). The radius of curvature is a function of pore-throat size (r) and the contact angle (θ) between the fluids and the mineral grains for a reservoir rock.
So, capillary pressure can be calculated as follows:
2σ cosθ Pc = C Eq. 5.8 r
where,
σ = interfacial tension between the fluids, dynes/cm,
θ = wettability, contact angle between the fluids and the grain, degrees
r = effective pore-throat size, micron (µm),
Pc = capillary pressure, psia,
C = a constant to insure that the units are preserved
In an air-mercury capillary pressure test, capillary pressure can be viewed as the pressure required to drive mercury through a pore throat, with greater pressure being required as the pore throat becomes smaller (Jennings, 1987). Mercury injection-capillary pressure data are obtained by injecting mercury into sample plugs, at increasing pressure levels, to produce a plot of injection pressure vs. mercury saturation. This is also known as a mercury injection capillary pressure test or MICP test. Each capillary pressure curve 125
also represents a pore-throat size profile for the tested sample (Figure 5.15). The size and distribution of pore throats within the sample controls its capillary pressure characteristics, which in turn control fluid behavior in the pore system (Jennings, 1987).
Capillary pressure tests on samples can be run using a variety of wetting (e.g., brine or air) and non-wetting (e.g., oil or mercury) fluids. Air-mercury capillary pressure tests are more rapid, simpler, and less costly than the brine-oil capillary pressure tests
(Sneider, 1987). Hydrocarbon-brine capillary pressure relations can be estimated from the
air-mercury measurements using the appropriate values of σ and θ.
In this study, air-mercury capillary pressure tests were conducted on 18 samples
in the Schlumberger Doll Research facility at Ridgefield, Connecticut. Mercury injection-
capillary pressure data were obtained by injecting mercury into sample plugs to produce a
plot of injection pressure vs. mercury saturation.
In general the mercury injection apparatus (Figure 5.16) was calibrated before
running each mercury injection test. The purpose of the calibration is to determine the
error that results from the compressibility of mercury, the expansion of the steel in the
apparatus, and the compressibility of the air that is trapped in the apparatus. Calibration
data were obtained by carrying out a run without a sample in the test chamber. Test data
were obtained by carrying out another run with a sample in the test chamber. The
mercury volume and pressure readings were recorded during both calibration and test. 126
Irreducible Saturation, % 0 20 40 60 80 100 2000 0.05 Irreducible Saturation, S 0.10 1000 wi
0.25
s
n
o
r
c 0.50 i
m
,
s
t
a
100 1.0 o
r
h
T Displacement
e Pressure, Pd r
o
3.0 P
P f late au o
s
u
5.0 i
d
a 10 R 10
Entry 20 Pressure, Pe
2 40 100 80 60 40 20 0 Mercury Saturation, %
Figure 5.15 Typical capillary pressure curve plotted on a semilog graph. The curve also represents a pore-throat size profile for the sample. From Jennings (1987). 127
Pressure Gauge Observation Windows Psi
High-pressure nose
Vacuum gauge To vacuum pump
Supply pressure
Sample Chamber Observation (internal view) windows containing rock sample Handwheel micrometer dial Metering Mercury plunger reservoir
Measuring screw
Figure 5.16 Schematic figure of mercury-injection capillary pressure apparatus for obtaining mercury injection-capillary pressure data. From Jennings (1987).
128
In order to plot a capillary pressure curve, the mercury volume inside the plug has
to be calculated. To find the volume of mercury inside the plug, for each pressure step,
the mercury volume obtained during calibration of the apparatus is subtracted from the
volume of mercury obtained during running of the sample.
The dry samples were weighed using an analytical balance. Grain volume of the
plugs was calculated by dividing the weights of the plugs by the density of the plugs.
Wt GV = , Eq. 5.9 ρ m
where,
GV = Grain volume of the plug (cc),
Wt = Dry weight of the plug (g),
ρm = Matrix density of dolomite (2.87 g/cc).
Bulk volume of the plugs was measured during the test. Volume of mercury
required for filling the empty test chamber was recorded. The sample was placed in the chamber and mercury volume was recorded by pumping the mercury to the exact same level in the observation window. The sample bulk volume was the difference between the two volumes. 129
Pore volume for the plugs was obtained from the following equation by subtracting the grain volume from the bulk volume of the plug.
PV = BV – GV, Eq. 5.10
where,
PV = Pore volume of the plug (cc),
BV = Bulk volume of the plug (cc),
GV = Grain volume of the plug (cc).
Mercury saturation, for each pressure step, was obtained by dividing the mercury
volume inside the plug by the pore volume of the plug. Finally, porosity of the samples
was calculated using the following equation:
PV Porosity (φ) = Eq. 5.11 BV
Figure 5.17 shows the correlation between core-plug porosity and capillary pressure porosity for the 18 samples. Porosity values from the capillary pressure tests are considerably in good trend when compared to the core plug porosity. Values of 10 samples are less than the MICP measurement. The remaining 8 samples have a higher value for MICP (Table 5.1). The erroneous values of samples 13 and 14 may have been caused by the measurement of pore volume during the test. 130
MICP vs. Core Plug Porosity 30
IDS DSS TCS_GF 20 TCS_WR LDS_WR
MICP porosity, % MICP porosity, 10
U014 U013 0 0 5 10 15 20 25 30 Core Plug porosity, %
Figure 5.17 Cross plot of core plug porosity and MICP porosity, showing a good correlation except samples number 13 and 14. IDS=interdune; DSS=dolomitic sandstone; TCS_GF=tabular-planar cross strata_grain flow; TCS_WR=_wind ripple; LDS_WR=large-scale deformed strata_wind ripple. 131
The capillary pressure curve of a sample from tabular-planar grain flow facies is given in Figure 5.18. Mercury-injection pressure vs. mercury saturation data is also plotted on semi-log paper to make the interpretation easier (Figure 5.18B). An additional vertical scale of pore-throat radius (microns) is displayed next to injection pressure to estimate pore-throat size at a given pressure. The entry pressure, Pe, is the pressure at which the sample first begins to accept mercury into the pore system. This is a function of the mercury conforming to irregularities on the surface of the sample plug (Jennings,
1987; Figure 5.18B). Displacement pressure, Pd, is estimated by extending the slope of the plateau to the right side of the graph, and is interpreted to be the pressure at which mercury first imbibes into the rock (Jennings, 1987; Figure 5.18B; Table 5.1). The plateau is related to pore-throat sorting.
Pore-throat sorting (PTS) provides a dimensionless measure of pore geometry and the sorting of pore throats within a rock sample (Jennings, 1987). A horizontal plateau indicates good sorting (PTS = 1.0; perfect sorting), with sorting becoming poorer as the plateau steepens (PTS = 8.0; no sorting). Most rock samples fall between PTS values of
1.2 and 5.0. PTS values within the Tensleep reservoir interval were computed using the following equation adapted from a sorting coefficient equation developed by Trask
(1932):
3rd Quartile Pr essure PTS= Eq. 5.12 1st Quartile Pr essure 132
Reserved for table 5-1 133
0020U06 Sage Creek Fox#1
60000 Swi=0.27%; 100%-Sw=99.73% A Q =0.25x99.73%=24.9% 50000 1
P1 =7.6 psia
Q3 =0.75x99.73%=74.8% 40000 P =11.4 psia a 3 0.5 i
s PTS=(11.4/7.6)psia =1.23 P 30000 , e u r
s 20000 s e r P 10000
0
-10000 10 0 90 80 70 60 50 40 30 20 10 0 Mercury Saturation, %
0020U06 Sage Creek Fox#1
100000 B 10000
a 10 0 0 i s P
,
e 10 0 u r
s Pd =6.5 psia s 11.4 psia e
r 10
P 7.6 psia P =1.5 psia % % e 8 1 9 . . 4 4 7 2 Swi=0.27% 0.1 Q Q 10 0 90 80 3 70 60 50 40 30 1 20 10 0 Mercury Saturation, %
Figure 5.18 Capillary pressure curves of a sample # U06 (core depth 3401.3 ft) from TCS_GF facies. (A) Data are shown on a linear plot, (B) Data are shown on semilog plot. Significant parameters are more apparent on a semilog plot than a linear plot. Abbreviation: Swi= irreducible water saturation; Q1= Water saturation at first quartile pressure; Q3= Water saturation at third quartile pressure; PTS= Pore throat sorting.
134
The first and third-quartile pressures were obtained directly from the capillary
pressure curve and reflect the 25 and 75% mercury saturation pressures adjusted for
irreducible saturation (Jennings, 1987; Table 5.1). The mercury saturation at the first and
third-quartile pressures is obtained by multiplying the effective pore volume excluding
the irreducible water saturation (1-Swi) by 0.25 and 0.75, respectively (Figure 5.18A).
Figure 5.18A also illustrates how pore-throat sorting is calculated from a capillary
pressure curve. PTS does not always clearly indicate the porosity and permeability of a rock sample. PTS reflects the pore-throat heterogeneity within the sample.
Irreducible water saturation, Swi, is the percentage of the pore space that mercury
could not enter (Jennings, 1987). Air-mercury capillary pressure curves of the 18 samples
do not have Swi values because the maximum mercury-injection pressure is too high
(60,000 psig). Laboratory conditions were extreme, and they filled up all pore space.
Therefore, the wetting phase saturation at 50,000 psi injection pressure was taken as Swi
for all samples in the calculations of PTS (Figure 5.18B; Table 5.1).
Mercury capillary pressure curves for core plug samples illustrate a comparison of
reservoir quality and flow potential among Tensleep reservoir zones (Figures 5.19 and
5.20). Low displacement pressures and relatively flat initial slopes (plateaus) for the
tabular-planar cross-stratified grain flow samples suggest large and relatively uniform
pore throats. This is the highest reservoir quality and flow potential. Once a threshold
buoyancy pressure is obtained in this facies, oil will rapidly saturate the available 135
Compilation Pc vs. Mercury Sat (%) IDS = Interdune Facies 100000 U1 U02 10000 UV3 U04 U10 a a i i u11 s s U13 p p
1000 , , U14 e e r r U12 u u s s s s e e r r 100 P P
y y r r a a l l l l i i p p 10 a a C C
1
0.1 100 80 60 40 20 0 Mercury Saturation, %
Figure 5.19 MICP curves obtained from the interdune facies in the Tensleep Sandstone. MICP is shown on a semilog scale. Samples from interdune (IDS) facies show low displacement and relatively low slopes in the plateau, indicating that these zone could have good reservoir quality. In the samples # U10; U13; U14 of all interdunes, and U12 of dolomitic sandstones marine facies, have a higher displacement pressure, and more tight zones. 136
Compilation Pc vs. Mercury Sat (%) TCS_GF=Tabular-planar Cross stratified_Grain Flow TCS_WR=Tabular-planar Cross stratified_Wind Ripple LDS_WR=Large Deformed Cross stratified_Wind Ripple 100000 U05 U06 U07 10000 U08 UV9 U15 a a UV16 i i s s 1000 U17 p p
, , U18 e e r r u u s s s s e e r r 100 P P
y y r r a a l l l l i i p p a a 10 C C
1
0.1 100 80 60 40 20 0 Mercury Saturation, %
Figure 5.20 MICP curves obtained from the eolian facies in the Tensleep Sandstone. MICP is shown on a semilog scale. Samples from TCS_GF facies show low displacement and low slopes and are almost flat at the plateau. This indicates that these zones are very good reservoirs. Contrastingly, the TCS_WR and LDS_WR, considered to be more tight zones, show a much steeper slope on the plateau. 137
porosity up to the maximum capacity. The higher displacement pressures and greater slope of the plateau for the interdune facies samples suggest more variable pore throat sizes and a higher proportion of smaller pore throats relative to the tabular-planar facies.
The interdune facies look like good reservoir rock. The flat plateaus and lower displacement pressures indicate this. In the core description and log signatures, the interdune facies is generally tight and non-porous. However, the intensity of oil stained is somewhat comparable to the eolian tabular-planar stratification. Also the marine facies that was represented by dolomitic sandstone facies (sample # U12), showed some potential to become reservoir. According to the capillary pressure results the presence of dolomitic and anhydrite minerals may not always decrease the reservoir potential.
Several models based on MICP data were run. Detailed mercury capillary pressure and pore-throat radius curves with data spreadsheets for all core plugs are illustrated in Appendix D.
Pore-throat radius values at 35% mercury saturation from MICP determine the effective pore system that dominates flow through a rock (Kolodzie, 1980). Winland
(Amoco Production Company) developed an empirical relationship between porosity, air permeability, and pore-throat size corresponding to a mercury saturation of 35% (R35) for
322 samples that included both sandstones and carbonates (Pittmann, 1992).
Measurements for other mercury saturation percentages were also determined. However, regression results for values of porosity and permeability vs. pore-throat radius at 35% mercury saturation resulted in the highest correlation coefficient (Pittman, 1992). 138
Winland concluded, “That pore system has pore throat radii (called port size, or R35)
equal to or smaller than the pore throats entered when a rock is saturated 35% with a non-
wetting phase. After 35% of the pore system fills with a non-wetting phase fluid, the
remaining pore system does not contribute to flow. Instead, it contributes to storage.”
(Hartmann and Beaumont, 1999). The Winland equation was used and published by
Kolodzie (1980):
Log R35 = 0.732 + 0.588 log ka - 0.864 log φ Eq. 5.13
where R35 is expressed in microns, ka is uncorrected air permeability for Klinkenberg
effect in millidarcies, and φ is the porosity in percent.
R35 of a given rock type reflects both its depositional and diagenetic fabric and
influences fluid flow and reservoir performance (Hartmann and Coalson, 1990).
Pore-throat radius curves were derived from capillary pressure data for 18
samples (Appendix D) using equation 5.8. For air-mercury system, σ=480 dynes/cm,
θ=140o, and C=0.23. A simple relationship converts capillary pressure to pore throat radius:
107 r = Eq. 5.14 Pc
where r is in µm (microns) and Pc is in psia.(Pittman, 1992) 139
R35 values for each sample were calculated by using the above equation, with Pc
being the capillary pressure at 35% mercury saturation (Table 5.1). In some cases, the
corresponding value on the pore-throat radius scale was read (Appendix D). R35 values
were also estimated from core analysis porosity and permeability data by using the
Winland equation (Table 5.1).
Figure 5.21 illustrates measured (R35) and estimated (Winland equation) R35
curves for 18 samples from the Fox #1 well. In both of the curves, R35 values are greater
in TCS_GF facies than in other zones. This indicates that this facies has better reservoir
quality than any other zones within the eolian system.
R35 values for each porosity-permeability data pair can be estimated by solving the Winland equation. However, the Winland equation is based on empirical data.
Therefore, R35 values from capillary pressure tests and core plug porosity and permeability data for 18 sandstone samples were used to modify the equation to relate more closely to characteristics of the Tensleep sandstone reservoir.
Figure 5.22 illustrates the correlation between measured (R35) and estimated
(Winland equation) R35 values for 18 core plug samples. R35 values calculated from the
capillary pressure tests are a function of the matrix pore network within the reservoir and
are generally larger than those computed from the Winland equation.
Measured R35 values were plotted against core plug porosity and permeability
(Figure 5.23). The good relationship that exists between both permeability and R35 and
porosity and R35 for the core plug samples indicates that R35 values from the capillary 140
Measured vs. Estimated R35
3350
3375 01-IDS 02-IDS V03-IDS 04-IDS 05-TCS_GF 06-TCS_GF 3400 07-TCS_GF 10-IDS 08-TCS_GF 11-IDS V09-TCS_GF 3425
3450 12-DSS
3475 13-IDS 14-IDS Core Depth Sample, ft 15 & V16-TCS_G 3500 17-LDS_WR 18-TCS_WR
3525 Mod.Windland Measured
3550 0 5 10 15 20 Pore Throat in microns
Figure 5.21 Measured and estimated R35 for 18 samples from the Fox #1 well. Porosity and permeability data from the measured R35 were used to estimate R35 values using Winland equation. Larger R35 indicates a better reservoir quality. 141
reserved for figure 5-22 142
reserved for figure 5-23 143
pressure tests are related to both porosity and permeability. It was decided to modify the
coefficients of the empirically derived Winland equation using an approach suggested by
Pranter (1999). SigmaPlot5 software was used to run multiple regression, with log10
R35 data as the dependent variable and log10 k and log10 φ as the independent variables.
Multiple regression takes into account the relationships between φ and R35, k and R35 as
well as φ and k. The results depend on the relationships among all the variables that exist in the model. In this study, the interpretation was made on R20, R25, R30, R35, R40,
R45, R50, and R55 values. The results are given in Table 5.2.
The best correlation from the 18 samples comes from the R20 value (R-squared =
0.9461) (Table 5.3). However, the statistical coefficient for the R35 regression is also very high (R-squared = 0.8217), so this value will be used. The R35 value was used for two reasons: (1) the 342 samples used in Winland’s R35 correlation are more representative of the population of reservoir rocks in general, and (2) rock quality parameters are closely related to the R35 value (Jennings, 1987). The R35 value obtained in this analysis compares very well to the values obtained from the original Winland
Equation (Eq. 5.13) (Figure 5.24). The final equation describing the relationship follows the same units as Winland:
Log R35 = 1.4973 + 0.6742 Log k - 1.8343 Log φ Eq. 5.15
This relationship can be used to compute an R35 value for any other location in the well
that contains a porosity and permeability value. 144
reserved for Table 5-2 145
reserved for Table 5-3 146
reserved for figure 5-24 147
Pittman (1992) modified a technique to obtain the apex of Thomeer’s (1960) hyperbola as is discussed by Swanson (1981). The graphic used Hg saturation over capillary pressure on the “y” axis versus Hg saturation on the “x” axis (Figure 5.25). Using the same method as Pittman, this study ran multiple regression analysis with pore throats obtained at the “apex” (Rapex) of Thomeer’s hyperbola as the dependent variable and φ and permeability from core plug as independent variables from all eighteen samples. The result has very high R-squared number, 0.938, in the Winland modified formula as,
Log RApex = - 0.2307 + 0.3498 Log φ + 0.4053 Log k Eq. 5.16
This relationship can be also used to compute the Rapex value for any other location in the well that contains a porosity and permeability value (i.e., comparison to the NMR lab data).
Another useful item that can be obtained from capillary pressure data is permeability. Swanson (1978) developed a correlation that relates capillary pressure to permeability. To compare the MICP permeability result with another permeability from core plugs and NMR, Swanson permeabilities were calculated using the following equation:
2.005 S k = 355 b w P c A Eq. 5.17 148
reserved for figure 5-25 149
where kw = stressed brine permeability (mD), Pc = capillary pressure (psia), Sb = mercury saturation (% of bulk volume), and (Sb/Pc)A = the correlating parameter taken at the
vertex of the capillary pressure hyperbolic curve. To use unstressed air permeability, the
following correction is used.
1.186 kw = 0.292 ka Eq. 5.18
where ka = unstressed air permeability (mD).
On log-log paper, mercury saturation as a function of bulk volume vs. capillary
pressure was plotted. If the scales are equal, the 45 degree line that is tangent to the
hyperbola is known as the vertex; also known as Point “A” in Swanson’s (1978) equation
(Figure 5.26). The results of this analysis demonstrate a strong relationship between
unstressed Swanson permeability (ka) and Klinkenberg-corrected air permeability (Table
5.4 and Figure 5.27).
Permeability estimation using Swanson formula showed a good match to the Core
Lab plug permeability, especially for wind ripple facies of samples TCS_WR and
LDS_WR (Figure 5.27). Other facies (IDS, DSS, and TCS_GF), some of them were fall
within one cycle of logarithmic scale. This may related to the fact that Swanson using
samples from many environments, while the data from Fox #1 well only represents the
eolian sandstone. 150
reserved for table 5-4 151
reserved for figure 5-26 152
reserved for figure 5-27 153
5.5.4 Nuclear Magnetic Resonance (NMR) Analysis
NMR data have been used successfully to evaluate sandstone reservoirs for many
years. The laboratory NMR technology as a method to determine effective porosity,
permeability and irreducible water saturation has been widely accepted. As one of the
reservoir characterizations tools dating back to the 1960s, this technique had been much
improved in the late 80s and 1990s. Previous case studies on applications of the NMR
method were focusing on interpreting permeability estimates and effective porosity,
including the distinction between bound-water volumes and free-fluid index (Coates et
al., 1994, Hodgkins and Howard, 1999). The results from laboratory NMR
measurements were used to calibrate parameters such as T2 (transverse relaxation time) cutoff times used to estimate bound-water volume.
Kenyon (1989, 1992), Marschall et al. (1995), and Basan et al. (1995)
demonstrated that pore geometry links NMR core measurements with other measurements that detect pore-size distributions. These studies showed that the NMR
response offers valuable information about: (1) Pore-size distributions, and geometry of the pore structure, including the critical pore size that links this parameter to permeability. (2) Variation in the distribution of porosity elements, such as: total, effective, connected, macro- and micro- porosity. (3) Cutoff parameter for the interpretation of fluid saturations (Walsgrove et al., 1997). 154
Eighteen core plugs from the Fox #1 well were analyzed with the NMR
laboratory method. The analysis was performed by Schlumberger-Doll Research at
Ridgefield, Connecticut. Sample criteria were based on the eolian facies distribution with
an emphasis on a widespread porosity and permeability distribution. Accordingly,
samples for MICP analysis are identical to the NMR analysis for the purposes of
calibration and comparing the petrophysical properties from MICP to the NMR
laboratory techniques. Fifteen horizontal core plug samples from various eolian facies were chosen, and three vertical plugs that have equal depth to the horizontal plugs were also chosen.
Laboratory NMR analyses are made on brine-saturated samples. These samples are subjected to a powerful magnetic field that causes the hydrogen protons to orient themselves. A pulse is then transmitted causing the oriented protons to tip 90 degrees.
The amount of time for these protons to relax, or return to their original position, is called relaxation time and is a function of pore-size, connectivity and fluid composition
(Kenyon, 1992; Ausbrooks et al., 1999). In the case of these analyses, 5000 pulses were transmitted into each sample at a rate of one every 320 microseconds. Responses were recorded for a total time of 10 seconds.
There are two measurable values associated with hydrogen relaxation: T1, the
longitudinal relaxation time and T2, the transverse relaxation time. Because T2 relaxation
is measurable at logging speed up to 600 feet per hour, it is applied more often than T1,
which takes longer to acquire (Ausbrooks, 1999). 155
5.5.4.1 Nuclear Magnetic Resonance (NMR) T2 Distribution
The T2 relaxation time distribution is related to the pore-size distribution within
rocks. Small pores have small T2 values and large pores have large T2 values (Kenyon,
1992; Coates et al., 1999). The area under the T2 distribution curve is equal to the initial
amplitude of spin-echo train relaxation and can be directly related to porosity (Kenyon,
1992, Coates et al., 1999).
NMR measurements were made on 18 core plugs (Table 5.5) ranging in depth
from 3384.4 to 3503.2 ft core depths, or 3389.9 to 3510.2 ft log depths. Ranging in
porosity from 10.2% to 21.7% and 2.8 to 1711 millidarcies (mD) in permeability based
on conventional core analyses (Table 5.5).
NMR T2 distributions for all 18 samples show that there are several different pore
sizes in the rocks. Samples contain peaks situated between 100 and 400 ms, with
averages from 8 samples for interdune (IDS) facies at 235 ms. Averages of tabular-planar cross-strata grain-flow facies (TCS_GF) from 7 samples is 288 ms. The result for dolomitic sandstone facies (DSS) from 1 sample is 135 ms. The result from large-scale
deformed sandstone wind ripple facies (LDS_WR) from 1 sample is 215 ms. The result
from tabular-planar cross-strata wind ripple facies (TCS_WR) from 1 sample is 432 ms
(Table 5.5).
These T2 peak distributions reflect the pore-size distribution within the samples,
except for the anomalies on sample number 18, TCS_WR, which has a higher T2 time,
which is probably related to fractures that occurred when the plug was taken. 156
reserved for table 5-5 157
The interdune facies, which are dominated by sandy dolomite to dolomitic
sandstone and intensive early cementation by anhydrite and dolomite cement, made
smaller pore sizes within the rock. Therefore, the T2 values are smaller than the main
eolian bodies, which are represented by tabular-planar cross-strata facies. The marine and
dolomitic sandstone facies that represent tidal to sabkha environments showed a
distinctly shorter T2 distribution as a reflection of finer grain size and more intensive cementation by anhydrite. The irreducible water saturation based on NMR lab calculations also indicates a similar trend (Table 5.5). The interdune, dolomitic sandstone and marine facies have higher irreducible water saturations compared to eolian deposits of tabular-planar cross strata. Within the eolian system itself, the grain flow facies that has more loosely packed grains shows a lower irreducible water saturation compared to more tightly packed grains of the wind ripple facies.
NMR relaxation time (T2) distributions for 100% water-saturated samples mainly
occur between 100 to 400 ms. A faster relaxation related to smaller pore size, commonly
occurs below 100 ms (Hodgkins and Howard, 1999). In this study, smaller T2’s occur
between 10 to 40 ms. The averages of large pore sizes of interdune facies are between 60
and 700 ms, while TCS_GF of the main eolian body are between 90 to 900 ms. The
dolomitic sandstone sample has a large pore size distribution between 40 to 600 ms. The
large-scale deformed cross strata wind ripple facies has a distribution between 50 to 700
ms. The TCS_WR of sample 18 shows an anomaly with large pore sizes between 120 and 158
1100 ms. Indeed, this sample shows 3 different ‘humps’ on its incremental porosity
against relaxation time plot, reflecting three group of pore sizes within this sample. The
smallest might represents the irreducible saturation, the second might represent ‘true”
pore sizes of wind ripple association, and the slowest might represent fractures that cut
across the core plug.
5.5.4.2 NMR Porosity
The NMR signal amplitude is proportional to the number of hydrogen nuclei
associated with the pore fluids in the measurement volume. Therefore, the signal
amplitude is a measure of porosity. Because NMR measurements respond only to the
pore fluids, this is a direct measure of pore volume and is independent of mineralogy or
matrix properties.
There are two different measurements taken to calculate NMR porosity. First,
plugs were fully 100% saturated with a single fluid (brine) to obtain a “total porosity” or
connected porosity. Second, measurements are done on each sample after it is spun to
100 psi capillary pressure in air to obtain the clay-bound water or pore irreducible water.
The effective porosity or free-fluid porosity is determined by subtracting the amount of bound water that remains after the sample is centrifuged to 100 psi to the total porosity from 100% saturated measurement.
159
5.5.4.3 NMR T2 Cutoff
Porosity and pore size information may be used to estimate both free-fluid porosity and permeability. The NMR estimate of free-fluid porosity is referred to as the free-fluid saturation, ΦFF or unbound fluid volume (UFV). By definition, the free fluid is the fraction of the total fluid volume that we expect to be mobile. The estimation is based on the expectation that the free-fluid or movable oil will reside commonly in large pores, whereas the bound fluids reside mostly in small pores. Although, the large pores also contain bound water, but on a percentage of pore space basis, this is much smaller than for small pores where all fluid can be bound water (Peeters, personal comm., 2001). A T2 cutoff divides the NMR porosity into free fluid and bound fluid, ΦBF, or bound fluid volume (BFV). Because T2 values can be related to pore body sizes, a T2 value can be selected below which the corresponding fluids are expected to reside in small pores and thus immobile, and above which the corresponding fluids are expected to reside in larger pores, and thus can move freely. This T2 value is called the T2 cutoff (Coates et al, 1997,
1999). Through partitioning of the T2 distribution, the T2 cutoff divides total porosity into free-fluid (UFV) and bound-fluid porosity, or bulk volume irreducible (BFV).
Although capillary pressure, lithology, and pore characteristics all affect T2 cutoff values, common practice establishes local field values for T2 cutoffs. For example, 33 ms is generally appropriate for sandstones (Coates et al., 1997).
T2 cutoff determination on 18 samples in this study were done after analyzing samples in a fully brine water-saturated state, and the same sample in a partially saturated 160
state after being centrifuged to 100 psi capillary pressure in air. The T2 cutoff was
determined by relating the time decay of the T2 distribution cumulative curve (equal to total porosity) to the bound fluid porosity value. For example, on sample #U018 (Figure
5.28), the bound fluid volume saturation is 1.74%, and total porosity at 10 seconds
(10,000 ms) is 9.77%. The T2 cutoff of 54.9 ms is the decay time where 1.74% is
observed in the total porosity column. A T2 cutoff can also be determined graphically by
displaying both cumulative curves of saturated and partially saturated samples against T2
relaxation time. Project horizontally the cumulative curve of 100 psi to the left until it
intersects the cumulative saturated curve, then project down to the T2 time. The T2 value
of the intersection of this projection with the T2 axis is the T2 cutoff (Figure 5.28).
The T2 cutoff from Fox #1 cores range from 2.2 to 61.7 ms. The T2 cutoff for IDS
facies varies from 12 to 61.7 ms with an average of 41.9 ms. The marine DSS is 53.9 ms.
The TCS_GF varies from 2.2 to 40.7 ms with an average 21.2 ms. The LDS_WR is
38.95, and TCS_WR is 54.88 ms. Combined wind ripple facies (LDS and TCS) is 46.9
ms (see Table 5.5). The overall average for T2 cutoff is 35.07 ms, while the overall T2
peak average is 260 ms (Figure 5.29). However, the T2 cutoff is affected not only by
lithology, but also by several other factors, such as pore-wall chemistry, minor
paramagnetic or ferromagnetic components, texture, pore throat to body ratios, and other
factors not well understood (Coates et al., 1999). These factors can cause T2 cutoff to
vary among samples within a single lithology as illustrated in Figure 5.29. 161
Reserved for figure 5-28 162
T2 Peak & T2 Cutoff Variation 3360
T2 Peak 3380 T2 Cutoff 3384.4 3389.7 3392.5 3397.5 ) ) 3400 3401.3 t t 3403.9 f f ( (
3409.2V 3409.2 3412.6 h h 3415.5 t t p p 3420 e e D D
e e r r 3440 o o C C
3452.3 e e l l p p 3460 m m a a S S 3480 3482.3 3484.5
3494.7 3494.7V 3498.5 3500 3503.2
3520 33 35 260 1 10 100 1000 T2 Relaxation Time (ms)
Figure 5.29 T2 peak and T2 cutoff variation within this study. Laboratory derived T2 peak and cutoff values can vary. The blue line represents the average value of T2 cutoff, the red line represents the average value of T2 peak, and the blue dotted line represents the default T2 cutoff of 33 ms. 163
5.5.4.4 NMR Permeability
NMR relaxation properties of rock samples are dependent on porosity, pore size,
pore fluid properties, and mineralogy. The NMR estimate of permeability is based on
theoretical models that show that permeability increases with both increasing porosity
and increasing pore size (Timur, 1967, 1968; Ahmed et al, 1989; Allen, 1988; Coates et
al., 1999). NMR measures pore body size on almost all sandstones, and a strong correlation exists between pore body size and pore throat size. The fact is NMR actually measures pore surfaces/pore body size that we could relate to the pore size (throat), and permeability increases as connected porosity increases.
In the two most commonly used expressions, permeability is related to porosity to the power 4. This power of φ is somewhat arbitrary but is loosely derived from Archie’s
Law, the relationship of permeability to resistivity, and with an additional factor to account for NMR measuring pore body size not pore throat size (Coates et al., 1999).
The ratio between UFV and BFV can be defined by extrapolating the T2 signal amplitudes against the decay times. In the free fluid model (Coates formula), the size
parameter enters implicitly through the T2 cutoff, which determines the ratio of UFV to
BFV, where UFV is the free fluid volume and UFV= Φ -BFV. For the Coates model, in
its simplest form, the permeability k is given by
2 2 kCOT = [(Φ/C) x (UFV/BFV)] Eq. 5.19 164
NMR porosity is normally used for φ, and BFV is obtained through the cutoff method.
The NMR porosity, φ, used in this equation is ignoring shale effect (clay-bound fluid) or other material with clay-size pores (Peeters, personal comm., 2001). The coefficient C is a variable that is dependent on the process that created the formation and can be different for each formation. The commonly used number for sandstone is 10. Permeability is in mD and porosity is fractional.
In the other expression, the Mean T2 (or SDR) model, the size parameter enters
4 through the geometric (logarithmic) mean of the relaxation spectra, T2LM .
a2 a3 kSDR = a1(Φ) (T2LM) , Eq. 5.20
where Φ is NMR total porosity, T2LM is logarithmic mean of the T2 distribution,
a1 is parameter adjusted to match the NMR permeability to available measured
permeability (Kenyon, 1988). Common coefficient values for sandstones are a1=4, a2=4, and a3=2.
The use of these particular size parameters in the respective expression is based
on empirical considerations (Kenyon, 1988; Coates et al., 1999). T2LM is analogous to the
center of mass of a body in classical mechanics: it is the T2 value at the center of mass of
the distribution (Schlumberger, 1997). Permeability has units of millidarcies (mD) when
porosity is in decimal units and T2LM is in milliseconds (ms). 165
Another model equation commonly used when the rock is water-wet and light
hydrocarbon or oil-base mud filtrate is in the pore space, is the Timur-Coates model:
4 b2 b3 kTIM =b1.10 (ΦNMR) (UFV/BFV) Eq. 5.21
Where ktim is the permeability from the Timur-Coates model, ΦNMR is the NMR porosity, UFV is the NMR free-fluid volume and BFV is the NMR bound-fluid volume.
The coefficient values for sandstones are b1=1, b2=4, and b3=2. Permeability kTIM is in
mD and all porosities are fractional.
A literature review shows that the Coates model is more flexible than the Mean
T2 model. Through careful core calibration, the Coates model has been customized for successful use in different formations and reservoirs. As long as BFV does not include any hydrocarbon contribution, BFV is not affected by an additional liquid phase such as oil or oil filtrates, which is very important when analyzing hydrocarbon-bearing formations (Coates et al., 1999).
In the unflushed gas zone, the ΦNMR used for porosity in the Coates formula may be too low because of the low hydrogen index in such zones. Thus, ΦNMR must be
corrected, or an alternative porosity source should be used. Zones that maintain high
residual gas saturation at reservoir pressure will have BFV values that are too high and
thus, to a small degree, will yield permeability values that are too low. Heavier oils, 166
which normally have a very short T2 values, may be counted as BFV, thus causing permeability to be underestimated (Coates et al., 1999).
The Mean T2 model works very well in zones that containing only water.
However, if oils or oil filtrates are present, the mean T2 is skewed toward the bulk-liquid
T2, and permeability estimates are erroneous (Coates et al., 1999). In unflushed gas
zones, mean T2 values are too low relative to the flushed gas zone, and permeability is
underestimated. Because hydrocarbon effects on T2LM are not correctable, the Mean T2
model commonly fails for hydrocarbon-bearing formations (Coates et al., 1999).
In fractured formations, permeability estimates from both the Coates and SDR
models are too low because these models can only represent matrix permeability.
In this study, we tried all three models at T2 cutoffs determined from the data
sheet and T2LM. On the Coates and Timur-Coates models, we also modeled the
permeability estimation with several T2 cutoff experiments ranging from 20 to 90
milliseconds (Appendix D).
Results from 18 samples showed the Coates formula will match plug permeability
with a coefficient C equal to 16, instead of the normally 10 that causes an overestimate.
The Timur-Coates model works best with constant b1 equal to 0.15. The SDR model with
T2LM will match the available plug permeability with coefficient a1 equal to 7.5 (Figure
5.30).
The SDR model with a1=7.5 (Eq. 5.20) has a relatively good match with core
plug permeability except for measurements under 10 mD which were overestimated. 167
reserved for figure 5-30 168
Measurements on large pore sizes of the main eolian body of TCS_GF showed a variety
of differences in permeability estimation (sample # 5-9; 15-16, on Figure 5.30).
The Timur-Coates Model, using a T2 cutoff to extract the UFV and BFV, gave a
better estimation for measurements under 10 mD. The Timur-Coates Model used a
coefficient of b1 equal to 0.15 (Eq. 5.21). The interdune facies permeability differs mostly below 50 mD from the plug measurement. One exceptional occurs in that sample
U013 is 359 mD overestimated compared to the plug. The assumed smaller pore sizes in
the wind ripple facies within an eolian system appear to have a good match with the
Timur-Coates Model. They both fall within a range of less than 10 mD compared to the
plug permeability. The larger pore sizes of TCF_GF facies have a range of 20 to 600 mD,
with an exceptional value on vertical sample (UV09) that has more than 2000 mD
overestimated.
The Coates Model works best with a coefficient C equal to 16, instead of 10 as
commonly used (Eq. 5.19). The result is very similar to the Timur-Coates Model. The
Coates Model is very good estimator for smaller pore size, and is not a good estimator for
larger pores (Figure 5.30). A model with T2LM, such as in the SDR formula, counts the
UFV as the main pore sizes within the rock, which were true for the eolian TCS_GF
facies. The porosity-based formulas such as the Timur-Coates and Coates Models, do not
have good results like the SDR formula, especially on large pore sample. This is because the large pores that count as UFV provide little information about the throats that dominate permeability. In contrast, the Timur-Coates and Coates Models are excellent 169
permeability estimators for rock samples that are dominated by smaller pore sizes, e.g.,
interdune, dolomitic sandstone, marine, and wind ripple facies of this study.
5.5.4.5 NMR Pore Size Distribution
NMR relaxation time distributions measured on water-saturated rocks provide an accurate estimate of pore-size distribution (Kenyon et al, 1989, 1992, Hodgkins and
Howard, 1999; Coates et al., 1999). Relaxation rate constants are defined as:
1/T2 = ρ S/V Eq. 5.22
where T2 is the relaxation rate constant (in seconds), S/V is surface area to volume ratio
(micron-1), and ρ is the surface relaxivity (in microns/second). Because the rocks consist of an assembly of pore sizes, the measured total relaxation time can be rearranged into
distributions of relaxation time, where each relaxation time corresponds to a pore size
(Hodgkins and Howard, 1999). The parameter ρ, NMR surface relaxivity, measures the
ability of the surface to cause relaxation of proton magnetization and has dimensions of
length/time (Kenyon, 1992). Equation Eq. 5.22 shows that T2 responds to pore size because the dimensions of S/V are inverse length, essentially pore size. Small pores exhibit small values of T2, and large pores have large values of T2. When surface
relaxivity is known, NMR T2 can be converted to pore size through equation Eq. 5.22
(Kenyon, 1992). 170
MICP measures pore-throat size and capillary pressure. MICP directly measures
the percentage of pore space within a rock that can be filled with a given fluid when a
given amount of pressure is applied (Hodgkins and Howard, 1999; Ausbrooks et al.,
1999). These data are used to calculate pore-throat sizes, which in turn can be used to
calculate T2 pore-size distributions for sandstone. Marschall et al. (1995) used the
formula:
T2 = 1000r/2 ρe Eq. 5.23
where T2 is in ms, mercury injection pore radius r is in µm, and ρe is the effective
relaxivity in µm/s. Equation 5.23 is obtained by substituting the surface-to-volume ratio for a cylindrical tube, i.e., S/V = 2/r, into Equation 5.22. The effective relaxivity, ρe, is
introduced from equation 5.23 to account for the fact that NMR responds to pore “body”
size whereas MICP is controlled by the sizes of pore “throats.” Thus, ρe is proportional to
the product of the intrinsic relaxivity; ρ (Eq. 5.22) and a pore throat-to-body size ratio
(Marschall et al., 1995).
An effective relaxivity ρe that scales mercury pore radius r into T2 (Eq. 5.23) was
determined for each sample by finding a best match between the MICP and T2
distributions. The effective relaxivities used to calculate T2’s of each sample were
assigned through trial and error (Table 5.6). 171
Reserved for Table 5-6 172
The results from this T2 calculation can be used to create a pore-size distribution from an MICP database using the percentage of saturated pore-space and the size of pore- throats in a rock (Figure 5.31 a and b). Although the MICP curves are based on the pore- throat size, and the NMR is based on pore size, the effective relaxivity (ρe) can be used to
relate the two.
Pore size distributions that was created from the MICP data, indicate that the
eolian systems were controlled by a single pore size. The unimodal curves from MICP
pore throat size distribution are present not only on the eolian body of TCS_GF, but also
in interdune and marine dolomitic sandstone facies. Only one sample (U018) of
TCS_WR facies shows the bimodal curves. This sample also has bimodal curves on the
T2 distribution from NMR.
Values for the effective relaxivity (ρe) determined from the procedure are listed in
Table 5.6. The eolian TCS_GF facies have a ρe range from 9.7 to 16.6 µm/s, the
interdune facies have a ρe range from 3.8 to 9.5 µm/s, excluding samples U013 and
U014, which seem to have erroneous data. The marine/sabkha environment represented
by sample U012 has a ρe value of 12.9 µm/s. The wind ripple facies has ρe = 2.2 and 5.8
µm/s for both TCS_WR and LDS_WR respectively. This result is consistent with
previous studies which show that carbonate rocks generally have lower relaxivities than
sandstones (Marschall et al., 1995; Ausbrooks et al., 1999; Coates et al., 1999). 173
reserved for figure 5-31A 174
reserved for figure 5-31B 175
5.5.5 Dykstra-Parson Coefficient
In order to describe pore-size distribution from NMR lab studies, this research
tried a method that has been known in petroleum engineering as the Dykstra-Parson coefficient, which is a simple statistical measurement of reservoir heterogeneity. The
Dykstra-Parson coefficient, KDP, has been found to be a good indicator of the level of
heterogeneity (Jensen and Currie, 1990).
The technique of computing the KDP number described by Dykstra and Parson
th th (1950) requires estimating the 16 and 50 percentiles, k(16) and k(50) with k(16) < k(50),
from a set of ordered data. The data are assumed to be log-normally distributed. The
method calls for the data to be plotted on a log-normal probability plot and best-fit line to be drawn and used to established k(16) and k(50). The two percentile values are then used
to define the heterogeneity measure as:
KDP = 1 – [k(16) / k(50)] Eq. 5.24
where KDP is Dykstra-Parson Coefficient number, k(16) and k(50) are values of estimated
data on probability plot percentiles.
Data from the T2 distributions of core plugs have been normalized to incremental
porosity and represent the normal pore size distribution within the sample. In data
preparation, this study only used the incremental porosity values that appear as a
representation of bulk pore size within the rock. The zero values and incremental values that appeared at the end of the spreadsheet have been eliminated (Table 5.7). 176
reserved for table 5-7 177
In this study KaleidaGraph software (TM of Macintosh) was used to built 18
probability plots from each sample and determine the k(16) and k(50) values then calculate
the Dykstra-Parson coefficient (KDP) as in equation 5.24 (Figures 5.32 and 5.33).
The probability plot from KaleidaGraph has the X-axis scaled in probability
(between 0 and 100%), and the Y-axis is the percentage of the Y variable whose value is
less than the data point. The Y-axis displays the range of the data variables. The
probability plot gives rough information about the local density of the data and
symmetry. The plotted data points do not coincide, even if there are exact duplicates in
the data (KaleidaGraph Manual, 1990).
Results from this plotting are displayed in Table 5.8. The Dykstra-Parson coefficient represents the heterogeneity of the pore size distribution within the samples.
The higher number represents a uniform distribution or less heterogeneity. The TCS_GF facies from samples # 5-9 and 15-16 shows averages more than 0.8, which suggests that
the main eolian body consists of uniform grain size with little effect of cementation. The
interdune facies show a range from 0.52 to 0.96, which show how heterogeneous this
facies can be in terms of pore-size distribution. The marine DSS facies has KDP = 0.6, suggesting that marine influences affect the pore-size distribution of its deposition. Wind ripple facies of large-scale deformed cross-strata (LDS) and tabular-planar cross-strata
(TCS) have KDP equal to 0.62 and 0.77 respectively. The LDS_WR facies show more
heterogeneity than the TCS_WR because of the marine or ground water table that 178
reserved for figure 5-32 179
reserved for figure 5-33 180
causes its deformation. Additional information about the results, from three vertical plugs taken in the NMR lab (sample # V03, V09, V16) that are related to its horizontal plugs
(sample # 02, 08, 15), the vertical samples show less KDP values (Table 5.8). These values represent more heterogeneity of the vertical succession than its horizontal variation within the eolian strata.
5.5.6 Petrography
In this study, all samples that have been analyzed with MICP and NMR lab were also cut into thin sections. The thins sections were made in standard mode with blue epoxy impregnation to show that portion of the rock. Methods that have been used in this study were point count analysis. A standard 300 point count was run on one set of thin sections using a Zeiss polarizing microscope at Colorado School of Mines Petrography
Lab at Golden.
Modal analysis was undertaken by counting 300 points for mineral and porosity identification for 18 samples. Point counting was carried out using a stage interval of 0.5 mm and track spacing of 1 mm.
Porosity types identified included primary intergranular, secondary intergranular, and secondary intragranular. Microporosity was not counted, the textural character of each sample was described. Wentworth grain size class, from lower very fine (62-88 181
reserved for table 5-8 182
µm) to upper fine (177-250 µm), degree of sorting, and rounding was estimated for each sample during point count analysis. Based on the abundance of quartz grain (> 50%), they fall into quartz arenite (orthoquartzite) sandstone classification (Middleton, 1960;
Pettijohn, 1963). Complete petrography descriptions and photographs on each sample are attached in Appendix D.
The intergranular volume (IGV) measurement is based on the concept of how much porosity had been decreased during the time since deposition (Rittenhouse, 1971;
Pittman, 1979). It measures the total effect of compaction, reflecting both mechanical compaction and intergranular pressure solution. IGV is the sum of all cements, matrix material, and porosity in sandstones, and is easily calculated from petrographic data.
IGV values for each sample were calculated using point count data. A comparison of
IGV values with original depositional porosity helps to determine the effect of compaction on the reduction of porosity in Sage Creek Tensleep sandstones.
Depositional porosity for these sandstones is estimated to be approximately 46%.
Because initial porosity is equal to the intergranular volume at deposition, this value is used to compare to the present day IGV (mean 39.89%) in these sandstones to provide a relative measure of compaction.
The contact index (CI) was identified by Taylor (1950) and named by Pettijohn et al. (1972). This index refers to the average number of contacts per grain. CI was measured for one hundred grains per sample. CI values are listed in Table 5.9 A and B. 183
Grain contact geometry also provides a qualitative assessment of the degree of compaction. In order of increasing degree of compaction, these grain geometries are: (1) floating grains, (2) point/tangential grain contacts, (3) straight/long grain contacts, (4) concavo-convex grain contacts, and (5) sutured grain boundaries. This classification system was developed by Taylor (1950) and has been used by many authors (including
Wilson and McBride, 1988; Houseknecht, 1988) in compaction characterization studies
(Table 5.9A and B).
The IGV numbers of Tensleep Sandstone at Sage Creek are considered to be very high (mean = 39.89%). The original sandstone depositional porosity might have been around 46% for cubic arrangement of grains. Compare those average IGV values to the average present porosity in the Tensleep Sandstone of this study (16.2%). This suggests that compaction has reduced porosity by more than half of its original value.
The Contact Index number from all samples has an averages of 3.49 contacts per grain. This number agrees with the IGV, and suggests that compaction has reduced the porosity. As a result, the grains will be more in contact between each other. Another analysis of grain contact types also agrees by showing that long and concavo-convex contacts are the dominant types within Tensleep Sandstone at Sage Creek.
The classification based on the facies types of the samples suggests that interdune samples have an average IGV of 38.51% with CI of 3.71; TCS_GF has an average IGV of 42.96% with CI of 3.05; DSS has IGV of 37.99% and CI equal 4.05; LDS_WR has
35.22% and 3.6 CI; and TCS_WR has IGV of 35.96% and 3.63 CI. 184
Reserved for table 5-9A 185
reserved for table 5-9B 186
The IGV number for grain flow facies is consistently higher than wind ripple
facies, and the CI for grain flow is always lower than wind ripple. These facts suggest the
facies classification agrees with the petrographical data.
5.6 Discussion
One goal of this study is to examine wind ripple facies to see if they have less
reservoir capacity than grain flow facies. Core examination from well Fox #1 of Tensleep
Sandstone supports this hypothesis.
Minipermeameter measurements on core can be used to calibrate the core depth to
the log depth. The minipermeameter results, when calibrated to core plug permeabilities,
provide a high-resolution permeability profile.
MICP results and R35 modeling using the modified Winland equation provided a useful model of pore-size distribution. This approach can be translated to other wells with
MICP data to model permeability values.
Running the NMR analyses on the 18 eolian samples can be used to model the
appropriate T2 cutoff for eolian sandstone. The combination of MICP and NMR data
using ρe can be useful to integrate both measurements and determine the real value of
pore-size distribution within the eolian sandstone. This method could be extended to
other fields. 187
Facies classification based on core description has been strongly supported by
several experimental measurements on the core plugs. The MICP data could differentiate
the facies types by curves of Hg saturation versus capillary pressure. The modeling of
pore throat size and permeability could agree to the facies type and may become a model
for eolian sandstones elsewhere. Samples #13 and 14 did not provide good data. The
remaining 16 samples showed good quality data.
On the NMR lab data, sample #18 has anomalous values. The tight packing of
wind ripple facies has a long T2 time compared to the grain flow deposits. The long T2
values seem to be related to the fractures that appeared at some plug locations within the
core. The solution that had been taken was using the second “hump” of the T2
distribution diagram as the real wind ripple representation of T2 time.
The experiment using the Dysktra-Parson coefficient for T2 distributions time suggests another way to classify heterogeneity of the eolian facies.
The petrographic observations for all samples support the other results. Especially on MICP sample #13 & 14, and NMR lab sample #18, the petrography observation agreed with the previous assumption that wind ripple facies is more tightly packed than grain flow facies.
The results from this chapter relate to the following chapter on Sage Creek Unit
#21 well, where the models that have been done are applied. The NMR lab data on several facies within the eolian sands will be compared to the FMI and CMR log in this well. 188
CHAPTER 6
SAGE CREEK FIELD: BOREHOLE IMAGES AND CMR LOGS, SCU #21
6.1 Location
The Sage Creek Unit (SCU) #21 well was drilled on March 11, 1996, through
May 20, 1996, to evaluate a Madison prospect by Phoenix Production Co. in the Sage
Creek field, Big Horn County, Wyoming. Drill stem tests (DST) were performed through
perforations on three Tensleep Sandstone intervals (DST #1 at 2752 – 2780 ft; DST #2 at
2824 – 2852 ft, and DST #3 at 2918 - 2930 ft) and also on one Madison interval as DST
#4 at 3440 – 3498 ft. The well was declared an oil producer and was completed as a producing well from the Madison Formation. Schlumberger run a complete log suite on this well including Formation MicroImager (FMI) and Combinable Magnetic Resonance
(CMR) logs through the Tensleep Sandstone and Madison Formation.
5 The Kelly bushing (K.B.) elevation is 4154 ft, the 9 /8 in casing was set at 562 ft
and 7 in at 3,567 ft. This well penetrated Tensleep Sandstone interval from the overlying
upper contact to the Phosphoria Formation at 2762 ft through the base of the Lower
Tensleep marine interval at 3122 ft. The well reached total depth (TD) of 3635 ft in the
Madison Formation. 189
Phoenix Production Company was the operator when this study began. The current operator of Sage Creek field is Equity Oil Company. Schlumberger was the logging company that provided the data including the digital tape of this well.
The reason to study this well was the continuous FMI and CMR logs in the
Tensleep. This allowed us to examine petrophysical properties of the eolian and eolian- marine section of the Upper and Lower Tensleep simultaneously.
The SCU #21 well located 1830 ft from the north line (FNL), 1880 ft from the east line (FEL), in the NE SW NE quadrant of section 7, Township 57 North (T57N), and
Range 97 West (R97W), Big Horn County, Wyoming (Figure 6.1). This well is located on the southern part of the Sage Creek anticline crest. It is surrounded by non-Tensleep producing wells (Figure 6.1).
6.2 Borehole Images
The earliest attempts to image boreholes relied upon optical cameras. There are three different borehole imaging technologies available to date: optical, acoustical and electrical devices (Paillet et al., 1990). Although these tools are unlikely to ever completely replace coring, the rapid development of electronics and microcomputers has contributed to the advance of imaging technology through the increase in the ability to provide detailed images of the borehole (Paillet et al., 1990). Of the three borehole imaging techniques, electrical devices are the most popular borehole imaging have been 190
R 98 W R 97 W
RONEY #1
BREHM GOVT #1 BREHM #15-1 INDEX MAP OF FEDERAL #2-1
SAGE CREEK FIELD . FEDERAL #1-1
SCU #14 O SCU #18 C .
O KLINDT N C R #1 GOVT BREHM SC SCU #1 DECKER #1 O K H
FOX MADISON SC #2 USA A R PEDRY #1 G I P US P RO D USA #1 PAN-AM B #1 EFFIE KLINDT #1 SCU #21 DORO FOX #3 SCU #5
SCU #19 GOVT HILL GOV’T WOLD SCU #7 #1 #1
SCU #8 SCU #17
SCU #7 SCU #16 USA TEXAS #1
FOSTER BECKER #1-5 #1 RICKETTS #1 FOSTER BECKER-ANDERSON #1 SCU #8 SCU #15 SCU #20 #1
LAUREN FEDERAL McCRA RY #1 #1 PEDRY JOENS #13 SCU #10 SCU #13 JOENS #1 KI RK BARNDT #1 BARNDT #1 DILLON #1A WAGNER COLEY #13-3 MARMIK BARNES #1 FOX #1 SCHWAB #1 SCU #11 MARTIN- HAGE R #1 SQ.DILLON #1 HAGE R #1 EVERGREEN-WAGNER DEAVE R IRRI NG TO N #1 #1 BREHM DILLON #1 SCU #9 GOVT.WINER #1 SCU #12 BARNDT #1 RICH-KIRK HAGE R# 2 RICH-AJAX #1 AJAX FLOOD RICHARDS #1 GOVT. UNIT #1 #3 RICH-AJAX #1 #2 HAGE R# 1 RICHARDS#3A FEDERAL #5-24 BREHN-FLOOD #1 WAGNER BARNDT #1 #2 DAVIS HUSKY GOVT #1 #1 DAVIS RUTH-DAVIS BLANSCET-CHASE #2 #1 #1
GOVT.WAGNER STEFFENS BRABEC UNIT #24-1 #24-2 GOVT STRIKER GOVT STRIKER 24-1 #2 BERRYMAN DEAVER-FEDERAL #1 #2 #1 BERRYMAN #1 STEFFENS GOVT.WAGNER #24-1 GOVT STRIKER T UNIT #24-1 #3 DOVE BERRYMAN-WELLS #2 DOVE #1 #1 FLOYD-WELLS #1 57 0.8 1 mile N
0 0.2 0.4 0.6 Mile 191
used. The capability to detect thin beds is one of the reasons that petrophysicist prefer this
technique among others.
In this research, the only borehole imaging log available is FMI tool, one of the
electrical logging device. The following subchapter will focus on the application of
borehole imaging to eolian facies determination.
6.2.1 Introduction to the FMI
The Formation MicroImager (FMI) is the latest generation of the Formation
MicroScanner (FMS) tool from Schlumberger. Both are borehole imaging logs that have
been developed as advanced dipmeter tools. Dipmeter help us determine paleocurrent
directions in sandstones. This capability has increased our ability to detect bed
boundaries in subsurface formations (Bourke et al., 1989; Luthi and Banavar, 1988).
Examples of such tools, other than the two mentioned from Schlumberger, are
Halliburton’s EMI (Electrical MicroImager) and the Baker Atlas STAR device. The FMI
tool has a vertical resolution of 0.1 in (2.5 mm) that can be used to determine cross stratification orientation within eolian sandstone facies.
The FMI the tool emits electrical currents and measures variations in
microresistivity values that are then converted into color images. Different colored
images are related to different composition, textures, structures and fluid contents (Luthi
and Banavar, 1988; Bourke et al., 1989; Serra, 1989; Grace and Newberry, 1998). 192
FMI and FMS logs from Schlumberger are borehole images generated by microconductivity logging devices. The FMS is a four-pad microconductivity device covering roughly 40% of the borehole face in one run, while FMI is an eight-pad microconductivity device covering roughly two-thirds of the borehole face in one run.
Usually, a second run after a tool rotation of 45o is recommended to improve the
coverage.
Borehole imaging logs have already been proven as a powerful tool for
stratigraphic interpretation (Hurley, 1994; Hurley et al., 1994; Carr-Crabaugh et al., 1996;
Hurley, 1996; Aviantara, 2000). The image created is caused by differences in resistivity.
Clay-rich bedding and open fractures appear on the FMI log as dark traces because of
invaded drilling mud in the open fractures that generally have a higher conductivity than
the adjacent rock matrix. Crystalline rocks (dolomitic sandstone), sandstone and healed
fractures appear light in color as a result of high resistivity traces on the FMI log.
6.2.1.1 Dip Determination
The dipmeter has been used for many years to help determine paleocurrent
directions in sandstone. Using the conventional approach, an operator computes dips
using various correlation algorithms, then examines the “tadpoles” to look for patterns in
computed dips (Gilreath, 1987; Hocker et al., 1990). Various facies models are applied to
these patterns, and inferences are made about paleocurrent directions. 193
A traditional problem in dipmeter analysis has been the poor quality of the
computed dips. With borehole images, one no longer needs to depend entirely on dips
calculated by a correlation algorithm. Carr-Crabaugh et al. (1996) developed techniques
to determine dip directions based on borehole image data that depend heavily on hand- picked dips in borehole images. Also the problem for removal of structural dip has been solved (Carr-Crabaugh et al., 1996).
The first step in paleocurrent orientation is to obtain a dipmeter log in digital form. The data is then loaded onto an image analysis workstation and processed using
REVIEW/RECALL software from Baker Atlas. For display and analysis purposes, the
REVIEW/RECALL software can combine borehole image profiles with bedding plane and fracture intersections, gamma ray logs, caliper logs, porosity logs, resistivity logs, and dipmeter logs together in one display. As a result of the processing, static and dynamic images were created. Static images are created with one contrast setting of the resistivity values for the entire interval, while dynamic images are created with variable contrast of the resistivity values in a 5-ft moving window. The dynamic image enhances contrast for subtle differences in rocks and is useful for stratigraphic analysis and fracture interpretation. The operator can fit the traces of the beds or fractures with sinusoidal curves by handpicking the traces using the computer workstation. The handpicked traces of various bedding surface images will be recorded as dip direction and dip magnitude.
An ASCII file of the handpicked traces is transferred into EXCEL (TM Microsoft) for further analysis. 194
Figure 6.2 shows a schematic diagram of a vertical and horizontal borehole intersected by a planar feature such as a bedding plane or fracture. In the vertical well, the borehole image is cut along the line of true north to view in two dimensions. High angle fractures or bedding planes appear as high amplitude sinusoidal trace. In the horizontal well, the borehole images are cut along the top of the borehole to view in two dimensions. High angle fractures or bedding planes appear as low amplitude sinusoidal trace and horizontal bedding appears as a high amplitude sinusoidal trace.
6.2.1.2 Lithology Determination
The image created by the FMI log is caused by differences in resistivity. In the
Tensleep Sandstone, there are three lithology types that most commonly occur in the section: marine dolomitic sandstones and dolomites, interdune accumulations, and eolian cross strata (Carr-Crabaugh et al., 1996). These were determined on the basis of inclination and character of the bedding surfaces, and the associated gamma ray and porosity logs.
Structural dips should be determined in lithologies that were likely to be flat-lying upon deposition. Outcrop and core studies indicate that within the Tensleep, two facies are expected to contain flat-lying lithologies: the interdune accumulations and marine dolomitic sandstones (Carr-Crabaugh et al., 1996). The dolomitic sandstones are distinguished using gamma ray, density, and neutron logs. Compared to eolian 195 196
sandstones, the dolomitic sandstones have a little lower API on gamma ray, and a lower
porosity value on both density and neutron logs.
Interdune accumulations can be identified in high-quality FMI and FMS images
by the wavy-bedded nature of the individual laminae. Figures 6.3 and 6.4 are examples of
dynamic images from SCU #21 that show various lithologies within the Tensleep. The
lighter color with the wavy-bedded image combined with higher gamma ray, lower
porosity log and higher values of resistivity represent dolomitic sandstone facies (DSS).
This facies commonly occurs in a sabkha, tidal flat, or backshore type environment. The
marine dolomite usually has similar images and other logs features with the DSS, but
internal bedded structures are dimmed and are sometimes structureless. The interdune
facies also has similar images to DSS, the differences are the interdune sandstones
sometimes still show some higher values in porosity and almost always have the wavy-
bedded structures. The eolian section within borehole images usually displaying a darker
color than the marine or interdune facies, and the planar and tabular cross-stratification appears on the images. The differentiation between grain flow (GF) and wind ripple
(WR) facies within eolian sandstone is qualitatively based on the fact that WR is always developed at the base of one genetic eolian unit followed by GF. The upper part of eolian units is usually dominated by GF facies, which in the borehole images, sometimes does not show cross stratification anymore. An eolian compound cross-strata unit may be comprised not only by a set of WR and GF, but could also be stacks of several WR and
GF sets. This stacking can be shown in the borehole images as WR gradually changes 197
Eolian (Wind Ripple) Interdune
Eolian (Grain Flow)
Eolian (Wind Ripple)
Interdune
Marine Dolomite
Interdune
Eolian (Grain Flow) 198
Dolomitic Sandstone
Interdune
Marine Dolomite
Eolian Sandstone
Marine Dolomite
Dolomitic Sandstone
Marine Dolomite
Interdune 199
into GF, WR and WR stacking are followed by GF, or sometimes the GF facies occurs
without WR and is followed by another GF unit.
Structural dips should be determined in lithologies that were likely to be flat-lying
upon deposition. Outcrop and core studies conducted by many research studies indicate
that within the Tensleep, two facies are expected to contain flat-lying lithologies: the
interdune accumulations and marine dolomitic sandstones (Carr-Crabaugh et al., 1996).
The dips of the interdune accumulations and the marine dolomitic sandstones are combined to form a structural data set.
6.2.1.3 Removal of Structural Dip
The dip and dip direction of individual bedding planes represent a combination of original bedding plane orientation and of structural overprinting (Carr-Crabaugh et al.,
1996). Hurley (1994) demonstrated that borehole-imaging logs are particularly useful for dividing long sections into unconformity-bounded and fault-bounded dip domains through the use of dip-domain analysis. Analysis of the Tensleep Sandstone bedding- plane orientations was done by removing the structural dip using correction to the original bedding plane assumed to be flat-lying when it was deposited. Assumptions to be made were that all beds with gamma ray values more than 40 API unit were originally flat-lying upon deposition. The finer grains of interdune deposits and marine dolomitic 200
sandstone/siltstone are an example of this type of sediment. This research applied the term “hot beds” for this kind of beds.
The next step is plots all the “hot beds” dips on a cumulative dip plot to help define inflection points between the segments (Figure 6.5). The segment where the
Tensleep Sandstone interval lies within the SCU #21 well (between log depth 2733 ft to
3070 ft) has a mean bedding-plane orientation of 4.6o at 208o azimuth (based on 227 dips and a 10o cone of confidence about the mean). The next step is to rotate the entire data set from FMI images to compensate for the structural dip, using the Z&S software.
The cumulative dip plot of “hot beds” also showed that from log depth 2704 ft (in the Chugwater Formation) to 2733 ft (in the Dinwoody Formation) has a mean bedding- plane orientation of 10.4o at 153o azimuth (based on 45 dips and 10o cone). Another break at log depth 3070 ft (in the Ranchester Limestone of the Amsden Formation) showed that mean-bedding plane orientation from this point below is 10.9o dip at 191o azimuth (based on 45 dips and 10o cone) (Figure 6.5). The bottom part of the Lower Tensleep has a gradational contact with the Ranchester Limestone of the Amsden Formation. The boundary between the Lower Tensleep and the Amsden Formation was put at a log depth of 2988 ft based on the last appearance of lighter color dominated marine dolomite/limestone and dark color clay beds.
Analysis of the Tensleep Sandstone bedding-plane orientations indicates that the
Tensleep represents a single-dip structural dip domain in the SCU #21 well. The general dip domain azimuth is 208o (SSW). This agrees with other researcher who worked on the 201
Cumulative Dip Plot "Hot Beds" SCU #21 0
6.4o at 199o (73 dips, 10o cone) 50 Sample/Point # 75, Depth 2704 ft (in the Chugwater)
100 10.4o at 153o (45 dips, 10o cone)
150 Sample/Point # 144, Depth 2733 ft (in the Dinwood y)
200 # #
e e l l p p 250 o o m m 4.6 at 208 a a o S S (227 dips, 10 cone) 300
350
400 Sample/Point # 410, Depth 3070 ft (in the Amsden Fm.)
450 10.9o at 191o (45 dips, 10o cone)
500 0 1000 2000 3000 4000 5000 Cumulative Dip Plot Figure 6.5 Cumulative dip plot for "hot beds" (beds with GR API units more than 40) derived from FMI images. These were used to define structural dip correction. The Tensleep interval lies within one segment, suggested continuously sedimentation on one direction. 202
Tensleep Sandstone within the Big Horn basin (Mankiewicz and Steidtmann, 1979; Kerr
and Dott, 1989; Dunn et al., 1996; Carr-Crabaugh et al., 1996; Aviantara, 2000; and
Ciftci, 2001).
6.2.2 Description of Stratification
As discussed previously in Chapter 2 and Chapter 5, the Tensleep Sandstone is composed of a series of interbedded eolian sandstones in the Upper Tensleep and marine dolostone sequences in the Lower Tensleep section. Tensleep eolian units are composed of one to several sets of compound cross-strata. Each set is bounded by first-order bounding surfaces and represents the deposits of a single bedform as it migrates and climbs through time (Carr-Crabaugh et al., 1996).
The illustration of the hierarchy of erosional bounding surfaces observed in the
Tensleep Sandstone outcrops and cores reflects the depositional processes occurring in the dune field (Figure 6.6) as it was described by Carr-Crabaugh et al. (1996).
First order surfaces separate one set of cross-strata from another, and are produced by erosional processes within the interdune area between large bedforms
(Figure 6.6) (Brookfield, 1977; Kocurek, 1981; Rubin and Hunter; 1982; Carr-Crabaugh et al., 1996). Second-order surfaces are erosional surfaces that form as small superimposed bedforms migrate across the leeface of a larger bedform (Rubin and
Hunter, 1982; Carr-Crabaugh et al., 1996). Third-order reactivation surfaces form as a 203
; n g i t u t 1 9 6 ) W c ( -
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h e c 1 9 6 ) o f ( S
p 6 y s h i e 6 .
E e o n s p h r i t a N g u r l u m i e r F H 204
result of shifting winds that change bedform morphology and produce relatively synchronous bounding surfaces. A detailed description of Tensleep cross-stratification and discussion of bounding surface formation were given in Chapter 2.
6.2.3 Bounding Surfaces
The SCU #21 well is a conventional vertical well, therefore the borehole images of bed boundaries appear as follow: high angle fractures or bedding planes appear as high amplitude sinusoidal traces and the low angle fractures or bedding planes appear as low amplitude sinusoidal traces. The observations of bed boundaries were based on the character change within the images. The color changes, combined with other log signatures (GR, porosity, PEF) define whether the bedding planes are the bed boundaries or not.
The bed boundaries between marine dolomitic sandstone/siltstone and interdune accumulations to both underlying and overlying beds are not always sharp. Sometimes they are gradational.
Carr-Crabaugh et al. (1996) suggested that borehole imaging logs were able to identify the same hierarchy of erosional bounding surfaces in the subsurface as those observed in Tensleep outcrops. Within the borehole images, the bounding surfaces are identified by erosional truncation of laminae as well as by abrupt changes in foreset orientation. Criteria for classifying the erosional bounding surfaces were established 205
through outcrop and core study. Figure 6.7 illustrates the expected progression of foreset
tadpoles associated with each type of erosional bounding surface (Carr-Crabaugh et al.,
1996). Using this criteria, erosional bounding surfaces in the SCU #21 well were identified and classified according to this process-oriented hierarchy. Figures 6.8 and 6.9 illustrate a series of bounding surfaces and open fractures identified in the borehole image of the SCU #21 well. 1.0, 2.0 and 3.0 represent first-, second-, and third-order bounding surfaces, respectively.
The next step is to plot the bedding surfaces on cumulative dip plot (Hurley,
1994). The bedding-planes are numbered consecutively from top to bottom of the logged interval. The inflection points are visible between dip domains and commonly correspond to first-, second-, and third-order bounding surfaces (Figure 6.10).
In Figure 6.11, a vector plot of dip azimuth orientations from all bed boundaries within the Tensleep interval also show inflections that correspond to first-, second-, and third-order bounding surfaces. This vector plot suggests that the general trend of dip direction is to the southwest.
First-order bounding surfaces show a thickness range from 3.3 to 26.4 ft with an average thickness of 9.6 ft. A thickness range from 1 to 40 ft with an average thickness of
8.3 ft corresponds to the second-order bounding surfaces. Finally, the third-order bounding surfaces exhibit a thickness which ranges from 0.45 to 29.5 ft with an average thickness of 5.5 ft (see Table E.6.2 in Appendix E). 206
Figure 6.7 Comparison of types of erosional bounding surfaces observed in core and outcrop with the expected FMI tadpoles and borehole images. In the core and outcrop appearance, dashed line are wind ripple and solid lines are grain flow laminae (Modified after Carr- Crabaugh et al., 1996; Aviantara, 2000). 207
Azimuthal Reference Azimuthal Reference Dip Magnitude Dynamic image Dynamic image o o N E S W N N E S W N 20 40 3.0
1.0
2.0 1.0
3.0 1.0 3.0
2.0 1.0 3.0 3.0 3.0 3.0 2.0 2.0 1.0
Interdune
Marine Dolomite 1.0
2.0 3.0
3.0
Figure 6.8 Interpreted dynamic image from SCU #21 well (T57N, R97W), Sage Creek field. Lines trace the intersection of foresets with the borehole. The tadpoles indicate dip magnitude of the foresets and points indicate the dip direction. 1.0, 2.0, 3.0 represent first-, second- and third-order bounding surfaces, respectively. 208
Azimuthal Reference Azimuthal Reference Dip Magnitude Dynamic image Dynamic image o o N E S W N N E S W N 20 40
3.0
2.0 3.0 3.0 1.0 3.0
2.0 3.0 3.0 1.0
2.0 1.0 2.0 3.0 3.0 2.0 3.0 2.0
1.0
2.0 3.0
1.0 2.0 Figure 6.9 Interpreted dynamic image from SCU #21 well (T57N, R97W), Sage Creek field. Lines trace the intersection of foresets with the borehole. The tadpoles indicate dip magnitude of the foresets and points indicate the dip direction. 1.0, 2.0, 3.0 represent first-, second- and third-order bounding surfaces, respectively. 209
CUMULATIVE DIP_PLOT ALLBEDS_ROT SAGE CREEK UNIT #21
0
2717.9 - TOP DINWOODY
200 2749.8 - TOP PHOSPORIA 2 7 6 1 . 5 - TOP TENSLEEP 2763.7 - MARINE DOLOMITE 2770.4 - THIRD ORDER 2781.5 - FIRST ORDER 2785.6 - SECOND ORDER 2786.6 400 THIRD ORDER 2802.8 - SECOND ORDER DOLOMITE 2821.8 2823.7 - INTERDUNE/SABKHA 2842.6 - THIRD ORDER FI RST O RD ER 2844.95 - SECOND ORDER 2848.45 2852.9 - THIRD ORDER 600 FIRST ORDER - 2855.4 2860.8 - SECOND ORDER FIRST ORDER - 2868.6 2871.9 - SECOND ORDER # # 2877.8 - THIRD ORDER E E FIRST ORDER - 2874.5 L L FIRST ORDER - 2879.5 2884.9 - SECOND ORDER P P M M A A 800 DOLOMITE - 2902.2 S S 2912.7 - DOLOMITE THIRD ORDER - 2923.96 2924.9 - SECOND ORDER FIRST ORDER - 2929.4 2931.8 - DOLOMITIC SANDSTONE FIRST ORDER - 2936.8 THIRD ORDER - 2954.8 2960.1 - THIRD ORDER 1000
TOP AMSDEN - 2993.5 3033.6 3036.4 3060.4 3064.7 1200 3082.7 3103.2 TOP MADISON - 3195.2
1400
0 5000 10000 15000 CUMULATIVE DIP PLOT
Figure 6.10 Sage Creek Unit #21 well (T57N, R97W), Sage Creek field, Big Horn basin, Wyoming. Cumulative dip plot (Hurley, 1994) of FMI-derived bedding planes for all lithologies. Inflection points visible between dip domain indicate first-, second- or third- order bounding surfaces. Refer to Table E-6.1 in Appendix E for the correlation between depth and sample number. 210
V EC TO R PLO T ALLBED S_ RO T SC U # 2 1
N
Figure 6.11 SCU #21well (T57N, R97W), Sage Creek field, Big Horn basin, Wyoming. Vector plot of FMI-derived dip azimuth for all lithologies. Inflection points visible between vector domain indicate first-, second- or third-order bounding surfaces. Refer to Table E-6.2 in Appendix E for the correlation between depth and sample number to the dip azimuth. 211
Bed boundaries acquired from FMI images were analyzed using stereoplots of
poles and rose diagram for all lithologies, and 1.0-, 2.0- and 3.0-bounding surfaces within
Tensleep Sandstone. Figures 6.12 to 6.15 show stereoplots and rose diagrams of all
lithologies, 1.0-, 2.0-, and 3.0-bounding surfaces. Each figure shows a mean dip angle and dip direction. 779 bed boundaries have been analyzed from the top of the Tensleep at
2762 ft log depth to the bottom at 2988 ft. The main direction of the bed boundary has been identified from SCU #21 well as dip azimuth equal to 197.7o and dip 7.1o, and the rose diagram shows a vector mean of 194.53o (Figure 6.12). This result relates well with
the general trend of depositional direction of the Tensleep Sandstone in the northern part
of Big Horn basin from other studies (Mankiewicz and Steidtmann, 1979; Kerr and Dott,
1989; Dunn et al., 1996; Carr-Crabaugh et al., 1996; Aviantara, 2000; and Ciftci, 2001).
Fifteen 1.0-bounding surfaces have been encountered with a mean dip angle of
5.3o and a mean dip direction at 201.7o from Schmidt plots and a 198.03o direction from
the rose diagram (Figure 6.13). For the 2.0-bounding surfaces, there were nineteen
surfaces picked from images. The stereoplot shows a mean dip angle of 9.6o and a mean
dip direction of 194.4o from the Schmidt equal area plot. The rose diagram for 2.0-
bounding surfaces has 190.53o as the mean direction (Figure 6.14). And the thirty-eight
3.0-bounding surfaces have been presented with a mean dip angle of 11.2o and a mean
dip direction of 191.8o from the Schmidt plot and 189.19o mean direction from the rose
diagram (Figure 6.15). 212
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T t t
l 1 9 r l p o l
b a d a = a
A
o n . v e
a
i n s
t i N a s
c o r s a o n . o e
i t
) t H h i o e o j a T
g . p r i
t p o l 2 0 8 a B e / o o e
s A r p o u l
6
. d a d , 5 3 l
t l l 4 . l e ( a
i
l f o n e 1 9 0 . q u a o f e
v a k e r
r h e e b o u n d e e o r t o r e d t t u t t r s i
c 0 - n t c i m C
i 2 .
h e " v e
v e h m z t I
c n g e d s n A a S M o f a
a
, e o n ) p r F e b e S i i
e
e t
r m ,
c M D o f ) n t
e h o t r e h e i " p h e m t c
s a s s D i 9 7 W n g h e g r p n t i n e m t i R a e a
n l s u s , D h e i d i
e
P ( - r p r e a e p r d i e
o s 5 7 N r l
r T R o w a p e
B ( l a
) a
n e u r a l i
t o l B d l l s ( e P i
. d u c t s r e o u l t r
h i s w
T o n e
# 2 1 w h e . e o r t
n e t
r f
a e e e U t s d p l s e o t
C
d t l 1 9 S
c N a
h e e = t t
r
d . a o n t e N o r o f t z
c i a e b o u n d e t o n n i s
e n c 0 - h o r s
e i r a 2 . b u t o b e
i
n e I 4 r o f a t t
v e s e M e 8 0 . F u m d i m / h a o
o
c
o 8 r p o l s 4 t e
i o r c t s a c
s
u e a c e t i l r f o 2 1 5 . e 1 9 4 . v e 5 h a
y s u r v a
t l p o l h
s 3 . o r n o u t d
h e t
u t n a a o f e e
c T e n g
m A e h e o t
i o t t m a r V z n g l N ) e e
o n . h r n A A i h o p l o n t d t
d . a c e u t i A r p p c e e
r s i i t a l i e b o u n d i e m r a t i F D D M t h m z 0 - S s . d i c
a p e q u a ) s 2 . S a p m i E ( p A e d n ( d i
d i
a H 1 4
e r h e o u l 6 . n g . e n d t r A m i
a w a
e
o f e o r o w o l
t n e P L c y o m g u r a o t i n g l p l F W v e a p l 215
l r p a n , a h e i c u m d i s i
T t t
l 3 8 r l p o l
b a d a = a
A
o n . v e
a
i n s
t i N a s
c o r s a o n . o e
i t
) t H h i o e o j a T
g . p r i
t p o l 2 0 8 a B e / o o e
s A r p o u l
6
. d a d , 0 3 l
t l l 4 . l e ( a
i
l f o n e 1 9 8 . q u a o f e
v a k e r
r h e e b o u n d e e o r t o r e d t t u t t r s i
c 0 - n t c i m C
i 3 .
h e " v e
v e h m z t I
c n g e d s n A a S M o f a
a
, e o n ) p r F e b e S i i
e
e t
r m ,
c M D o f ) n t
e h o t r e h e i " p h e m t c
s a s s D i 9 7 W n g h e g r p n t i n e m t i R a e a
n l s u s , D h e i d i
e
P ( - r p r e a e p r d i e
o s 5 7 N r l
r T R o w a p e
B ( l a
) a
n e u r a l i
t o l B d l l s ( e P i
. d u c t s r e o u l t r
h i s w
T o n e
# 2 1 w h e . e o r t
n e t
r f
a e e e U t s d p l s e o t
C
d t l 3 8 S
c N a
h e e = t t
r
d . a o n t e N o r o f t z
c i a e b o u n d e t o n n i s
e n c 0 - h o r s
e i r a 3 . b u t o b e
i
n e I 8 r o f a t t
v e s e M e 7 8 . F u m d i m / h a o
o
c
o 4 r p o l s 8 t e
i o r c t s a c
s
u e a c e t i l r f o 2 1 3 . e 1 9 . v e 2 h a
y s u r v a
t l p o l h
s 4 . o r n o u t d
h e t
u t n a a o f e e
c T e n g
m A e h e o t
i o t t m a r V z n g l N ) e e
o n . h r n A A i h o p l o n t d t
d . a c e u t i A r p p c e e
r s i i t a l i e b o u n d i e m r a t i F D D M t h m z 0 - S s . d i c
a p e q u a ) s 3 . S a p m i E ( p A e d n ( d i
d i
a H 1 5
e r h e o u l 6 . n g . e n d t r A m i
a w a
e
o f e o r o w o l
t n e P L c y o m g u r a o t i n g l p l F W v e a p l 216
All bed boundaries from the Tensleep Sandstone interval have been plotted
separately between the dominantly eolian Upper Tensleep and dominantly marine Lower
Tensleep. Results from the eolian Upper Tensleep interval show a mean dip angle of 8.5o
with a mean dip azimuth of 200.7o and rose diagram resulted in 196.75o. The eolian-
marine section of Lower Tensleep has 5.1o of mean dip angle and 190.4o mean dip azimuth, while the rose diagram gave a vector direction of 189.41o (Figures 6.16 and
6.17). From these results, it is suggested that there were not any changes in terms of
depositional direction from Lower Tensleep through Upper Tensleep time.
The differences in numbers of bounding surfaces found in the Upper Tensleep
compared to the Lower Tensleep are related to the appearance of marine intervals within
the Lower Tensleep section. The eolian system could not develop normally due to marine
influences. The system was always in wet conditions and the sand only developed when
the sea regressed to the basin because of sea level fluctuation or seasonal dry climate. In
order to develop the eolian deposit, the supply of sediment had to be outbalanced the sea
water fluctuation. Soft sediment deformation is very common in the Lower Tensleep
interval at the SCU #21 well.
Another type of deformation encountered in the eolian Tensleep section in the
area was organic activity. Burrowing and bioturbation are the most active deformation
agents. As in the core description from the Fox #1 well and outcrop study at Bear 217
. l l a n l s A e
a e . r v a
o r i t r a r 4 7 2 e H
o f l
= n t g o n e
i i o r e
t N r " B q u a c
e e t b o u n d a d s
s d , v e
l d d t e b e i n i
h e f a t b e
e I k o h m h o t o f e
m c " M
r e 7 5 S r e F
, h e C n g t n t i
e o f
e r s 1 9 6 . c t u s
g e m n h a a p e p h e h e o r S s u t t s t
g r d i i , e c
a ) n m l i i m
p r a d i v e z r
e a e h e r u r n A
- t 9 7 W a r o s o n ) p e e i i R n e u c p e t R
i r
, a l c M D t ) s o w e d l
d r B i
( e
r . o r a 5 7 N s D
t f o u l
T s p ( n e w i d h e
i a t
e l o n e l
t l s D e n e e c e P ( r a h i e e o t r t T p l
s
N
l o r .
r a c s # 2 1 w B a h e
e d . t i n
e r o l U t e o n t a o f P z
C t i b e e s S
t s n c i h o r v e a
e a r b o u n d a n p h a e a
e o f d t e s e
l e m b e u e
4 7 2 u m l n s
c I e r p o l o r =
i
t v a T a
M c c
N r n t r F a e v e
e h a o t t p e m
o u t h e d
U s e T h o e
n h e 5 o t t u t a i p o l N o n . m
i i 8 1 . o l o n
t / o z e d . o r c
o f a 9 e a 7 e
t r o f p a s
t o t i d i s s d i p e o
2 6 7 . e 2 0 . a s 2 i y s
p i o p l l r h d e n d 8 . d i o r n
r
t a u t n a a e
e c t e o u l e A m e h e
i S t a r w m V
z n g l
) e ) n g l b o u n d a r n A A o f h e a o r n e d t A
a t c i A d a ( p p e
c s p i i
o t l i p l b e
d i F M D D v e
h m l p l
l
. l c a n g . l r l q u a i c S h e a m i A E ( A t e
T r
. H p o l y o m 1 6
v e r
o n o n . a i 6 . e a r W i
t A
t
s a a e o i c t
o w n , e o l s i e P L s g u r o j h i i F p o l b a p r T p o u l 218
. l l a g l s A i e
a e . r v a
i t B r a
r 3 0 7
e
o f l d ,
= l n t o n e
i e o r e
i t N r q u a " f c e e t
k b o u n d a d s s e v e
d t d e i b e r n
h e t a b e
C
e h m I o h o t c o f
m " g e M S
r 4 1
a e F ,
S h e e
n g t n t r , i o f
) e s 1 8 9 . c t u s
m n p h e h a p s e h e o r i s u t t t 9 7 W g r d i e c
a m n R m l
i i
, p r a d i v e z r
h e e - a e r u r n A r
t a e o s o n ) 5 7 N p e i i n e u c p e t T R i r
a l ( o w c M D t )
l s e l
d
d l r B a i ( e e
r . o r s s D
t f o u l i
p s n e w d h e
i a t e o n e l
h i t # 2 1 w D
e n e e c P ( T r a
e U e . o t r t s p l C
s N e
l o r S
i r
a c r t B a h e d . a t n
e o l t e o n t p a o f P z
e t i b e e e s
l
s b o u n d a n c i h o r v e n s
e d e a r n h a T e a
o b e f t e r
s
I e e m u e
3 0 7 u m M l
c o w F r p o l o r =
i
t v a L a
o c c
t N n t r
a n e s e v e i
e h a e r t a m o u t h e d
p o l m e T h
o
h e 9 n - o t t u t o f a
i N o n . m
i i 8 4 . o n o t
t / o l o z d . o r c e a 2 e a 4
e t o p l r p a e s o f t
i r d i s d i p e o s
e 2 0 4 . 1 9 0 . t a e s 2 y s p i i l h S r d
n d 0 . d i o r n
)
t a u t n a a e
c A e o u l e A m e ( h e
i
t a r w m V
z n g l
) e n g l r n A A o f h e b o u n d a a n g . o r n e d t
a i t c i A a p p d e
c s p i i o t l i p l
d i F D D M b e v e h m l p l
y o m
l . l c a l r l q u a c S h e a m i W E ( A A t
e
T r
. n , H p o l i
1 7
v e r
s o n o n . a i e 6 . a r i
t A
t s a b a a e o i c t
o w e o l n s e P L g u r o j o r h i i F p o l H p r T p o u l 219
Canyon, in the borehole images of SCU #21 could be found some kind of deformation to
the original eolian structure that might related to the organic activity.
Although the Lower Tensleep is dominantly marine, several preserved eolian
deposits can be found. Similar to the Fox #1 well and Bear Canyon measured section, the
presence of these small eolian systems must be related to a regional sea level drop or
unusual climatic changes that made deposition possible.
6.3. Combinable Magnetic Resonance (CMR) Analysis
The Combinable Magnetic Resonance (CMR) log is a borehole Nuclear Magnetic
Resonance (NMR) tool that provides measurements that yields different types of
porosity-related information. The log can tell how much fluid is in the formation, and also supply details about pore size distribution (Figure 6.18-A) that are usually not
available from conventional porosity logging tools.
The principles of NMR logging are similar to the NMR lab data that have been
described in an earlier chapter, NMR log response contains the same fundamental
petrophysical information as the NMR laboratory analysis, although various borehole
conditions commonly mask some of these properties (Walsgrove et al., 1997). In the case
of the log, the NMR response is complicated by borehole conditions, logging speed, and
the presence of multiple fluid phases. Consequently, discrimination between fluid and
pore-size effects is a necessary part of log interpretation (Walsgrove et al., 1997). The 220
signal-to-noise ratio (SNR) is the main difference between laboratory and downhole
measurements, with the downhole ratios being much higher. Tool motion is a
fundamental difference between laboratory and downhole conditions (Edwards, 1997).
6.3.1 Introduction to NMR logging
The first nuclear magnetic resonance (NMR) logging measurements were based
on a concept developed by Chevron Research. Early nuclear magnetic tools used large
coils, with strong currents, to produce a static magnetic field in the formation that
polarized the hydrogen nuclei (protons) in the water and hydrocarbons. The static
magnetic field would then be switched off and the polarized nuclei would precess in the
weak, but uniform, magnetic field of the earth. The precessing nuclei produced an exponentially decaying signal in the same coils used to produce the static magnetic field.
The signal then was used to compute the free-fluid index, FFI, which represents the porosity containing movable fluids (Allen et al., 1997).
Early tools only recorded the slow free-fluid parts of the relaxation decay signal, they used a large amount of energy to tip the polarized spinning hydrocarbon nuclei, and they were not combinable with other logging tools (Allen et al., 1997).
In the late 1980’s, the application of NMR technology gained momentum with a new class of NMR logging tools. The polarizing fields were now produced with high- strength permanent magnets built into the tools. There are two different designs of NMR 221
tools available commercially: (1) the Magnetic Resonance Imager Log (MRIL) is the trademark of NUMAR (now Halliburton Co.) that uses a combination of a bar magnet and longitudinal receiver coils to produce a 2-ft (60-cm) long, thin cylinder-shaped sensitive region concentric with and extending several inches away from the borehole. (2) the CMR, which is the trademark of Schlumberger (Allen et al., 1997).
The CMR tool (Figure 6.18-B) makes nuclear magnetic resonance (NMR) measurements that respond to the hydrogen nuclei contained in the pore fluids. These measurements contain information relating to both pore size and pore fluid properties.
Manipulating the hydrogen nuclei contained in fluid molecules of either water or hydrocarbons makes the NMR measurements. Many nuclei have a magnetic moment and therefore behave like bar magnets. They also have spin (i.e. angular momentum) that makes them behave like gyroscopes. These spinning magnetic nuclei can interact with external magnetic fields and produce measurable signals. The measured quantities are signal amplitude and relaxation rates. The hydrogen nuclei are first aligned with a magnetic field created by the tool and then subjected to radio frequency (rf) pulses that effectively makes them aligned perpendicular to the magnetic field. After the pulse has ended, the nuclei will again align themselves with the magnetic field. The primary measurement of the NMR log is the time it takes the nuclei to realign themselves back to the magnetic field (Schlumberger, 1997).
The signal amplitude is proportional to the number of hydrogen nuclei associated with the pore fluids in the measurement volume. Therefore, the signal amplitude is a 222
A
B
Figure 6.18 (A) NMR T2 time distributions provide the distribution of fluid components within water-filled sandstones. The T2 time distribution also reflects the pore size distribution of the formation. Shorter T2 components are from water that is bound to grain surfaces. (B) The CMR tool, combinable with other Schlumberger logging tools, pad mounted tool with excellent vertical resolution up to 6 in. The antenna acts as both a transmitter and receiver. 223
measure of porosity. Because the NMR measurements respond only to the pore fluids,
this is a direct measure of pore volume and is independent of mineralogy or matrix
properties.
Two principal relaxation times are associated with NMR measurements: the
longitudinal relaxation time (T1) and the transverse relaxation time (T2). Both of them
are related to pore size and pore fluid properties. Due to lengthy T1 cycle times, T2
measurements are used for most logging applications.
Porosity and pore size information may be used to estimate both producible
porosity and permeability. The NMR estimate of producible porosity is referred to as the
free-fluid porosity, ΦFF. The estimation is based on the expectation that the producible
fluids reside in large pores, whereas the bound fluids reside in small pores. A T2 cutoff
that divides the NMR porosity into free fluid and bound fluid, ΦBF, is applied to the T2
distribution (Figure 6.19).
The NMR estimate of permeability is based on the expectation that permeability
will increase with both porosity and pore size. One permeability model commonly
available in wellsite software is the Schlumberger-Doll Research (SDR) model:
a2 a3 k SDR = a1 (CMRP) (T2,LM) Eq. 6-1
Where k SDR is the permeability from SDR model, CMRP is the CMR porosity and T2,LM is the logarithmic mean T2. The commonly used coefficient values for
sandstones are a1=4, a2=4, a3=2. The SDR model is generally used when the rock is 224
Figure 6.19 Intergranular porosty. The pores between grains are occupied by fluids and fine layers of clay. The irreducible water (dark blue) is held against the sand grains by surface tension and cannot be produced. Clay-bound water (shaded dark blue) is also unproducible. Larger pores can contain free water (light blue), and in some cases there are pockets of oil (green) isolated from the sand grains by capillary water. The clay particles, and their associated clay-bound water layer, effectively reduce the diameter of the pore throats. This reduces the formation's ability to allow fluids to flow, thereby reducing permeability (Allen et al., 1997). 225
water-wet and water saturated as might be the case when there is complete flushing by a
water-base mud filtrate. Another model equation commonly used when the rock is water
wet and light hydrocarbon or oil-base mud filtrate is in the pore space, is the Timur-
Coates model:
4 b2 b3 k TIM = b1.10 (CMRP) (CMFF/BFV) Eq. 6-2
Where k TIM is the permeability from the Timur-Coates model, CMRP is the CMR
porosity, CMFF is the CMR free-fluid porosity and BFV is the CMR bound-fluid porosity. The coefficient values commonly used for sandstones are b1=1, b2=4, and b3=2.
Permeability has units of millidarcies (md) when porosity is in decimal units and
T2, LM is in milliseconds (ms).
The values of a1 and b1 are usually adjusted to match the CMR permeability to available measured permeabilities (i.e. cores, plugs, DSTs, etc.) (Schlumberger, 1997).
Another formula that is commonly used to calculate permeability is the Free Fluid
(or Coates) model. In its simplest form, permeability k is given by
2 2 k COT = [(Φ/C) x (CMFF/BFV)] Eq. 6-3
NMR porosity from Total CMR porosity (TCMR) is usually used for Φ, CMFF is
the fractional NMR free fluid volume and BFV is the fractional NMR bound fluid 226
volume which are obtained through the cutoff method. The coefficient C is a variable that
is dependent on the process that created the formation and can be different for each
formation, but the commonly used for sandstone is 10. Permeability is in md and porosity
is fractioned. This equation (Eq. 6-3) is commonly used with the MRIL tool (Coates et al., 1999).
6.3.2 Porosity from NMR
Porosity from the NMR log not only measures the volume of void space, but also allows some inferences to be made about pore size from measurement of relaxation rates.
This provides the ability to differentiate porosity into types of components such as movable fluid in large pores and bound fluids in small pores (Allen et al., 1997).
Irreducible water is the water that has been trapped between grains due to the adhesion from the surface of mineral grains. Within the sandstone formation, the spaces between grains are filled with clay particles, which has large surface-to-volume ratios.
Water will attach itself to the surfaces of clay particles, that will make a large volume of
water remain in the formation. In pure sands, similar to the eolian sandstones, the smaller
grains have an effect that is known as capillary-bound water.
NMR measurements produce two important things. The echo signal amplitudes depend on the volume of each fluid component. The decay rate, or T2 from each component, reflects the rate of relaxation, which is dominated by relaxation at the grain 227
surface. T2 is primarily related to the pore-to-surface ratios. Porosity is the sum of void spaces between grains that are filled with fluid. There is free-fluid porosity content that is producible, and clay- and/or capillary-bound fluid porosity, which are not producible.
These features can be distinguished by their T2 time distribution (Figure 6.20).
Hydrogen nuclei in the thin interlayer of clay water experience high NMR relaxation rates, because the water protons are close to grain surfaces and encounter the surfaces more often. The same scenario applies when pore volumes are small and the water is able to diffuse easily across the water-filled pore. Thus, water in small pores with large surface-to-volume ratios has fast relaxation rates and therefore short T2 porosity components. In contrary to this fast relaxation, water that occurs in larger pores with smaller surface-to-volume ratios, takes longer for hydrogen nuclei to diffuse across the surface. Free water, found in large pores, is not strongly bound to grain surfaces by surface tension. Longer T2 time components reflect the volume of free fluid in the formation. In some cases, when oil is trapped inside strongly water-wet pores, the oil molecules cannot diffuse past the oil-water interface to gain access to the grain surfaces.
The hydrogen nuclei in the oil relax at their bulk oil rate, which is usually slow depending its viscosity. This makes a good separation of the oil and water signals in the
NMR T2 distributions (Allen et al., 1997).
Porosity from other logging tools, such as the neutron log, has lithology effects that may result in high porosity measurements due to hydrogen content within the formation, which includes hydrogen from fluids and clay. The density tool, which uses 228
Figure 6.20 The amplitude of the NMR T2 measurement is directly proportional to porosity, and the decay rate is related to the pore sizes and the fluid type and viscosity in the pore space. Short T2 times generally indicate small pores with large surface-to-volume ratios and low permeability. Longer T2 times indicate larger pores with higher permeability. The example above shows two different samples with similar porosity, but different relaxation times, each with a distinct permeability (Allen et al., 1997). 229
gamma ray collisions with electrons in the formation to measure the porosity, will have
an error when the wrong grain density is applied, or wrong fluid density assumed, which
occurs with gas-filled pores.
Traditionally, simple averaging combines neutron and density porosity logs. In many cases, the lithology effects on the neutron porosity tend to cancel those on the density porosity, so that the average derived porosity is correct (Allen et al., 1997).
6.3.3 Results from the SCU #21 well
Figure 6.21 shows the combination display of NMR T2 distribution and FMI images with another log. The porosity content track shows a bulk porosity of total CMR
(TCMR) porosity which consists of free-fluid content (water and oil) and bound-fluid volume. Comparing this TCMR to the traditional neutron-density log shows that the density-neutron tools overestimate the formation porosity particularly in the main eolian sandstone deposits (Figure 6.22). The results may relate to the wrong application of formation grain density between sandstone matrix (2.65 g/cc), limestone matrix (2.71 g/cc), and dolomite matrix (2.85 g/cc). However, the porosity readings in different environments such as interdune and marine show an agreement between the NMR tool and traditional density-neutron tools (Figure 6.23).
In general, the Tensleep Sandstone interval in the SCU #21 well is comparable to
the same interval in the Fox #1 well. From correlations across Sage Creek field (see 230
s s . e o n n d t m i k ) a t c o a a y 3 n a r t
C t i
- b i I o f
o s u r f M o m m F o f i p o r C
T u t r
o n
c t e s n g . 2 u l i a g e T o w f
a t L
d e m y o m u l i
a f W o n . 3 ;
o r i t d e k n , o l a
i c c s
a u l r h e r c t t e
l b a e a n n c i g h t o t
i o r s l y N ( t
H i n t s l e 6 . e g i i b i k c a B c o n t a
e f a c
r d , m e t l r t y e i t i n i i f p e
s o s o m k e n d o r g e e a r d o l a P
C m
i n t n e 2 ;
i e I r g e k a a c M o n t S a m
F r c , t ) n d y n n d t a i
i a ,
y o s 9 7 W t 5 ; R o n e
v i k t , i p o r c t
s a i r n d s t s o r f 5 7 N a e n s
T i R d c
i t u i i 1 ; o n l i f # 2 1 (
k ) o m c b u t a i U o l r r t t C d
s , S n b o u n d - ( i d i
t d 2 L e n i d u n e T A r
U e C u m R k s n t e a s i M i e a n d r o N a p t
C e
d n d e 4 ; R p h o r e l a t g e G k a
a n s c d l s h o s e a e S
r u i r P T
l t l l e f e r n
h o w i a e s W e
y y , r t t f i i y l l
2 1 a s b i b i 6 . e p l
t a a s e a e e r d i m m r r g u r p a i e o g l F p e s p e 231
reserved for figure 6-22 232
reserved for figure 6-23 233
Chapter 4), the T1 interval of the Tensleep Sandstone is truncated at the Fox #1 well. A
complete sequence of the Tensleep interval appears at SCU #21. Comparison of the PEF
log as a matrix indicator from both wells shows that in term of lithology, the Tensleep
Sandstone comprises the similar matrix content at the Sage Creek field (Figure 6.24).
The T2 distribution reflects the pore size distribution. In the CMR log, each curve
showing T2 distribution is a reflection of the pore-size distribution at that depth. The
CMR log has a vertical resolution of 6 in. By observing the T2 time distribution along
cross beds that are separated by bounding surfaces, it can be used to determine the pattern
of pore size distribution within the eolian sandstone (Figure 6.25). The red arrow
represents a pattern of bigger pore sizes upward that might indicate changes from tighter
and more closely packed wind ripple facies to more loose and open packed grain flow
facies. Red arrow patterns could also indicate coarsening of grains upward or reversed
graded bedding. The blue arrow pattern represents a smaller pore-size distribution upward that indicates less porosity and permeability due to textural grain packing changes. This pattern could also be an indicator of grains fining upward or normal graded bedding facies. The process could occur during depositional events such as grain flow facies that are overlain by wind ripple intervals because of changing wind velocity, sediment source, climate or some other sedimentation processes. Another process that might cause this occurs after deposition, such as destruction by organic activity in the form of burrows or bioturbation. Water influenced marine flooding or rising groundwater that intensified early cementation on the depositional surface, could cause this pattern. 234
reserved for figure 6-24 235
o d d . e o n o n r w i s o t a d 3 S n o o o o o o o o o o o o o o o o o o o b a S i
b u t k e 2 1 2 2 1 2 1 2 1 1 2 3 3 2 3 3 3 3 3 D i e I D c d r r u p w t a s p i
y e
s o n s a d i i e n t p l c e e s a z b u t i f i m n . d i s r
i e
t u r e e s 2 s r . u r a s
d i 0
a p o r n g e o
e t z r i o n s m i s
u p
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t b i . o n s s a i n t n t e e d i e u t s t m 2 e s u d e r o l i t T s i e
p r e P e r
p l R r . o n s ) c m
M e o g a l
o g
C n t
l I
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v o l M . p r l e d l C n d r g h e
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o n
f i
e s o w t 6 r a r # 2 1 o c
a t o w r U n r b o u n d n d i e u p a C (
i
e s S i
d V g r e o n F i h e R t o n t
B i n d a . r a
u t a n d o m p d , o l r a r
e f s
) a s e l I
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M o r . p w l F o g u o l
l a
n d
c e
t a R
z n d r e i r a
s e
M k e t e R r a C
u g h M w d a ( p o r h e
C t b a
I r a n d e e F r o f a
F o t C s y - o w a N r l
r o n v e p l a a n t d s o n . e C e w i s
p s d i t p l e e e e e o n l b a u a l
d a o n p r s i q s e d n s n t i o i e r e
e
e s s T s T n a e r o n r t i n u s e b a b i i
o w s r o a
p e o w r , b u t n s o m C i a U L r
- r y s e C t t a s t u e u r w 2 5 d i
b l m
p a i
y 6 . n t
t T e d ,
i e e r r a e h e o s t f g u r f d p o l i o r a t F d i u p w P o n
236
The green arrow pattern might represent continuous deposition of the same facies in uninterrupted sedimentation.
The porosity distribution in the eolian sandstone is the reflection of its pore-size distribution. The smaller pore size with shorter T2 time distribution will trap more fluid than the larger ones. As discussed in the previous chapter concerning core data from the
Fox #1 well, the interdune together with dolomitic sandstone facies and wind ripple interval generally contain more bound-fluid volume than cross-stratified facies of the main eolian body. Table 6-1 displays a comparison of NMR porosity, free-fluid, bound- fluid volume, and permeability from the SCU #21 and Fox #1 wells. The petrophysical properties numbers of each eolian facies from both well are not equal. From TCS_GF facies, the CMR log of SCU #21 data show lower porosity and permeability distribution values compared to core data of Fox #1, with almost equal irreducible water saturation
(Swi) values (5.81% to 6.09%). The wind ripple facies show a different trend with CMR log has higher porosity and permeability distribution compared to core data. The free- fluid component is comparable with only about less than 1 pu difference between those data. The most significant difference in values was in Swi and permeability for wind ripple facies of those two wells. In these categories, the CMR log data almost doubled the
Swi and about six to seven magnitudes over the core data in permeability values. For interdune and marine facies, the comparable petrophysical properties from two wells show a similar trend to the TCS_GF, where core data from Fox #1 have larger porosity and permeability distribution with comparable Swi values. 237
reserved for table 6-1 238
The explanations for the differences between CMR log to the core data are, (1)
Borehole conditions during CMR acquisition may have affected the true formation
petrophysical condition such as signal-to-noise ratios. (2) The application of the default
T2 cutoff (33 ms) for the entire interval results in the irreducible water content that are
higher for formations with larger pore sizes and less for formations with smaller pore
sizes. (3) There is a low number of samples available for NMR lab testing (18 plugs)
compared to the CMR log that has 6 in vertical resolution. Wind ripple and marine
dolomitic sandstone sample from core are particularly limited.
6.3.4 Permeability from NMR
The NMR estimate of permeability is based on a combination of experimental and theoretical models and relationship (Kenyon et al., 1988). When all other factors are kept constant in these models and relationships, permeability increases as connected porosity increases. The unit of permeability, the Darcy, has dimensions of area, and from practical considerations in petrophysical applications, permeability can be considered as being proportional to the square of some geometrical size (Coates et al., 1997). The correlation between capillary pressure curves and permeability strongly supports The idea that the pertinent size is that of the pore throat (see Chapter 5). NMR measures pore body size, 239
but in almost all sandstones and some carbonates, a strong correlation exists between
pore body size and pore throat size (Coates et al., 1997).
The most common permeability expression uses a variation of φ4. This power of φ is somewhat arbitrary but is loosely derived from Archie’s Law, the relationship of permeability to resistivity. An additional factor accounts for the fact that NMR measures pore body sizes not pore throat size (Coates et al., 1997).
The commonly used permeability models are available in wellsite software, such
as Equation 6-1 (SDR model), Equation 6-2 (Timur-Coates model), and Equation 6-3
(Coates model). The SDR model is generally used when the rock is water-wet and water
saturated as might be the case when there is complete flushing by a water-based mud filtrate. The Timur-Coates model is generally used when the rock is water-wet and light hydrocarbon or oil-based mud filtrate is in the pore space of the rock (Schlumberger,
1997). The Coates model, also known as Free Fluid or Dual Water model, is basically similar to the Timur-Coates model. The only difference between the two is the value of coefficient parameter. The Coates model has been customized successfully in different formations and reservoirs, as long as BFV does not include any hydrocarbon contribution
(Coates et al., 1997).
In some cases, such as in unflushed gas zones, NMR porosity will read too low because of the low hydrogen index in those zones. Thus CMRP must be corrected, or an alternative porosity source should be used. As discussed previously, the density porosity tool might be the best alternative porosity source in such zones. 240
Within the SCU #21 well, the permeability estimation have been made using the
Timur-Coates model based on the assumption that the amount of residual dead oil that
might be trapped in the formation were still significant as in core sample of Fox #1 well.
Thus, the SDR model might give an erroneous result in such zones.
Permeability estimates in the Tensleep Sandstone based on the Timur-Coates and
Coates models were performed to be compared with core samples from the Fox #1 well.
Figures 6.26 and 6.27 show permeability results based on Timur-Coates and Coates
models with default coefficients and parameters from the NMR lab core measurements.
The application of coefficients based on core data from the Fox #1 well do not work as
well as the default coefficients. This is understandable, because the NMR lab studies used
a T2 cutoff independently for each sample. In the SCU #21 well, the T2 cutoff value for
sandstone (33 ms) is used for the whole interval.
The permeability curves based on the default Timur-Coates equation and applied to the CMR log has been combined with FFI and BFV, T2 distribution curve, and eolian bounding surfaces picked from FMI tadpole to determine the rock facies of the eolian sandstone. Comparable facies from NMR studies from the Fox #1 well were also correlated qualitatively to the petrophysical properties of similar facies that have been determined in SCU #21. Figures 6.28, 6.29, and 6.30 are examples of how we can determine qualitatively the facies based on the CMR and FMI log together.
Within the tabular-planar cross-stratified (TCS) eolian sandstone facies, wind ripple (WR) usually occur right over the bounding surfaces (1-, 2-, and 3-order). It 241
reserved for figure 6.26 242
reserved for figure 6.27 243
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s i s p a F d i a 246
generally has bimodal T2 distribution as well as interdune or marine facies. The bimodal distribution is characteristic of smaller grain size, resulting in small pore size. Hence, these facies have the capability to hold bound fluid more than the larger grains. In the
CMR log, the T2 distribution has bimodal curves with less porosity and permeability.
The bound-fluid volume, expressed as Swi (irreducible water), is higher compared to other facies in eolian deposits. FMI tadpoles help define the bounding surfaces within the section. With this correlation to the CMR bimodal T2 distribution, less porosity and permeability, we can assume the interval is occupied by WR facies.
The grain flow (GF) facies were characterized by loose packing, larger grains with high porosity and permeability compared to WR. Compared to the NMR lab analyses of core plugs in similar facies, this facies typically has unimodal distribution of
T2 and larger pore size distribution with lowest T2 times. In the CMR log, in conjunction with FMI images, the GF is the facies that occurs between bounding surfaces and has greater porosity and permeability, and tends to have the slowest T2 time distribution on its curves.
The marine (MAR), dolomitic sandstone (DSS), and interdune (IDS) facies are easily determined. They almost always have the least amount of porosity and permeability along the interval. They generally have a bimodal T2 pattern and sometimes do not have a pattern at all. The FMI images show the highest resistivity, which results in the lightest color of the images.
247
6.4 Discussion
CMR and FMI logs from the SCU #21 well can be used to determine the facies of eolian sandstone deposits in Sage Creek field. Comparison to similar facies that have been identified from core, NMR and MICP laboratory measurements in the Fox #1 well reveal some important keys to define the Tensleep Sandstone eolian strata.
The FMI images are an important tool to differentiate eolian strata in the well without core. Characteristics of strata can be determined by observation of images. The analysis of the strata orientation through bed azimuth and dip can be viewed as tadpoles.
Based on these features, the bounding surfaces of the eolian sandstones can be defined
(Carr-Crabaugh et al., 1996).
The patterns suggested by Carr-Crabaugh et al. (1996) (Figure 6.7) are not always exactly as they appear in the diagram. The dip magnitude differences between strata below and above the boundary could vary from several degrees to 30 degrees. In some cases, the boundary was picked from changes in the T2 time distribution curves.
This was based on the assumption that the wind ripple facies lies at the base of bounding surfaces, followed by grain flow and/or intercalation of WR and GF until the next bounding surface at the top. The application of this assumption should not mislead one to pick bounding surfaces every time the T2 distribution shows a WR characteristic, because sometimes WR and GF may be present together within a close interval as intercalated units. In that condition, the FMI images and the tadpoles could help the 248
determination of bounding surfaces. The changing of the images in color or in texture
could tell the changing of the facies. Also, the deflection of tadpoles will tell the
changing in direction or dip magnitude (see figures 6.28, 6.29, and 6.30).
Another kind of data that could be useful is porosity information from the CMR
log. In the porosity columns of composite CMR and FMI log of SCU #21 there are at
least three different kind of porosity that can be inferred, CMR porosity, free-fluid, and
bound-fluid volume of the formation (see Figures 6.25, 6.28, 6.29, and 6.30). In
conjunction with bounding surfaces and facies type, now we can identify strata with
smaller pore size such as WR compare to GF. Interdune, dolomitic sandstone and marine
facies are less producible than grain flow facies. They have generally less porosity and
permeability, and contain more bound fluid compared to the larger pore size of grain flow
interval.
The permeability curves based on the default Timur-Coates equation applied to the CMR log clearly shows the intervals that are producible and those intervals that act as barriers. All of these intervals are related to geologic features that reflect specific depositional processes. The interdune, dolomitic sandstone, and marine facies are commonly flat-lying and have the least porosity and permeability within the eolian complex. The wind ripple strata have less permeability and porosity and tend to act as baffles compared to the grain flow strata.
The composite display of CMR and FMI log together with other conventional log data provides a major advantage to determine the petrophysical properties of such a well. 249
In eolian deposits, which are commonly thought to be homogenous sandstone reservoirs, one can clearly differentiate facies from such logs.
The investigation of core data from the nearby Fox #1 well, shows a similar NMR character to the CMR log in the SCU #21 and comparable core features to the FMI images. Although the CMR permeability does not have capability to tell the permeability direction within the strata, the overall permeability value could be clearly seen within the eolian beds. Compared to the minipermeameter and core plug measurements, a combination of all of these data can be used to predict the parameter input in reservoir characterization of the Tensleep Sandstone.
250
CHAPTER 7
DISCUSSION
The Tensleep Sandstone at Sage Creek field was deposited in a predominantly
eolian environment. There is eolian-dominated sediment in the upper part and marine influence in the lower part. The Bear Canyon measured section suggests the thickness of the Lower Tensleep is about 90 ft (27 m) and the Upper Tensleep is about 100 ft (30.5 m). In the equivalent interval in the Sage Creek field is the Lower Tensleep varies from
85 to 110 ft (26 to 33.5 m), and the Upper Tensleep varies from 75 to 130 ft (23 to 40 m).
The individual tabular-planar cross-strata sets in the Upper Tensleep average 22 ft (6.7 m) in thickness and mostly reside in the T2 sub zone or the sub zone that overlies the
Lower Tensleep interval (see Figures 3.2; 4.2; 4.3; and 5.3).
Reservoir heterogeneity within the Tensleep Sandstone can be divided into two categories: (1) changes in rock characteristics during deposition, including facies changes and a hierarchy of bounding surfaces within the eolian system, and (2) modifications that changed the rock after deposition, including erosion and soil formation, diagenesis, cementation, dissolution, compaction, and fracturing (Mankiewicz and Steidtmann, 1979; 251
Kerr and Dott, 1988; Kocurek and Havholm, 1993; Shebl, 1995; Carr-Crabaugh et al,
1996; Aviantara, 2000).
Data from measured section and wells in the Sage Creek field provide physical
descriptions of the Tensleep Sandstone facies. In the outcrop, the interdune, marine and
dolomitic sandstone facies tend to stand out due to the early cementation by evaporite
and/or dolomites (see Chapter 3). Tabular-planar cross-stratified rocks are the most
common lithofacies within the eolian sandstones. Wind ripple stratification is commonly
observable in the lower part of cross-strata sets, followed gradually by the grain flow strata. The looser packing of grains frequently causes the pores of grain flow deposits to be less filled with authigenic cement and thus less resistant to mechanical weathering than the wind ripple laminae. This tends to cause the grain flow laminations to exhibit a recessed quality in outcrop with respect to the surrounding wind ripple deposits. The large-scale deformed facies occurs in the upper portion of the eolian sandstones just below marine deposits in each parasequence. This occurrence suggests that the primary sedimentary structure is deformed due to marine incursion (Kerr, 1989).
In the core, facies differentiation was based on sedimentary structure, grain texture, and petrophysical properties (see Chapter 5). The interdune, dolomitic sandstone and marine sandstones in general have similar features in term of burrows and traces of organic activity. They generally show horizontal strata or very low angle cross-strata, sometimes structureless and completely deformed by organic burrowing activity. The 252
wind ripple facies is characterized by inversely graded upward grains, very thin laminae variation and they form the classic “pinstripe” texture within the dune sandstones. Oil stain in wind ripple facies enhances the visibility of the pinstripes as the oil is trapped in finer grained sand. The wind ripples commonly occur above the bounding surfaces, which are gradually followed by grain flow facies. The grain flow strata are generally thicker than the wind ripple strata, loose packing, and have coarser grain size than other eolian stratification.
In the borehole images, the interdune facies shows a wavy bedded nature of individual laminae. The marine dolomite generally shows lighter color due to high resistivity. The dolomitic sandstone facies has similar conventional log signatures to the marine dolomite, but in borehole images, they tend to be less resistive than marine facies and appear as a darker color than marine intervals. The wind ripple and grain flow strata of eolian sandstones appear in borehole images as cross-bedded lamination, mostly less resistive with darker color than any other facies in Tensleep interval. The bounding surfaces determination using the tadpole patterns of the bed boundary (Carr-Crabaugh et al., 1996) is a first step to determine grain flow and wind ripple strata within the eolian set. The wind ripple laminae commonly reside just above the bounding surfaces, and are followed upward by the grain flow strata (Chapter 6). The next step is using the CMR log data to confirm the first step, since the wind ripple strata based on core experiments in the other well show the tendency to have faster T2 decay times and bimodal distribution than 253
grain flow. This would be the procedure to compare the wind ripple and grain flow
facies.
The accumulation of eolian sediments represents the net deposition of sediments
through time resulting in a three-dimensional body of sediment (Kocurek and Havholm,
1993; Carr-Crabaugh and Dunn, 1996). Observations of core data, outcrops, CMR logs and borehole images can be used to differentiate the facies distribution within the
Tensleep Sandstone. Large-scale heterogeneity within the eolian system depends on how
eolian facies are distributed in both the vertical and lateral sense and the interaction with
regional changes in climate, sea level, and sources of sediments. The small-scale
heterogeneity is mostly attributed to the variation in stratification type and bounding
surfaces within each of the main eolian sand bodies.
Preservation processes that took place after deposition are other factors that
control the reservoir capability of eolian sandstones. Wet and dry conditions during
deposition controlled the cementation process. The influence of water made the finer
grain portion of laminae retain the water by surface tension and capillary forces. Early
carbonate cementation took place on the surface of interdune, tidal-flat, and marine
environment deposits. It makes them major impermeable beds within the eolian system.
Petrographic analysis of core plug samples from the Fox #1 well show that the
proportion of intergranular volume compared to cement and matrix shows that grain flow
facies have the largest original intergranular volume with open packing between the 254
grains. The interdune environment has less intergranular volume with more cement and
matrix between the grains, decreasing their potential as reservoir rocks. The wind ripple
facies is like the interdune facies with more tight packing and cement. Both facies are
possible baffles to fluid flow within the eolian sandstone (see Table 5.9 A & B, Chapter
5).
Mercury injection capillary pressure (MICP) and NMR laboratory experiments on
18 core plugs show similar results. Minipermeameter profiles of core with half-foot increment have a good agreement to the permeability measurements from NMR, MICP, and even the permeability estimation based on irreducible water saturation and the porosity equation from log data. Eolian sandstones have low clay content that usually masks the attempt to model the permeability with only log data.
Running the NMR lab analyses on 18 eolian samples allowed us to select the appropriate T2 cutoffs. The combination of data from MICP and NMR lab using ρe value
can be useful to integrate both measurements and determine the real value of pore size
distribution within the eolian sandstone.
The MICP data could differentiate the facies types by curves of Hg saturation vs.
capillary pressure. The modeling of pore throat size and permeability could agree with
facies type and may become a model for eolian sandstone elsewhere.
The permeability estimation using FFI and BFV together with porosity from
NMR lab analyses led me to adjust the default parameter from its original value to C=16 255
with the Coates formula (Eq. 5.17), and b1=0.15 for the Timur-Coates formula (Eq. 5.19).
The SDR estimator (Eq. 5.18) has a good match with the conventional air-permeability plug if one uses a1=7.5 as the coefficient. The Timur-Coates and Coates models are good
estimators for lower permeability values, while the SDR formula is good for permeability
values greater than 10 md. This might be explained because the SDR formula counts the
UFV as the main pore sizes within the rock, which were true for eolian TCS_GF facies.
The Timur-Coates and Coates models will not work as well with large pore samples, because the large pores that count as UFV provide little information about the throats that dominate permeability. Modeling with several different T2 cutoffs reveals that 30 ms has the best overall match with plug porosity compared to the default value of 33 ms.
The investigation of CMR and FMI logs from the SCU #21 well, clearly can be
used to determine the facies of eolian sandstone deposits in Sage Creek field. Comparison
to the similar facies that have been identified from core, NMR and MICP laboratory
measurement of the nearby Fox #1 well reveal some important keys to define the
Tensleep Sandstone eolian strata.
The physical description of facies with borehole images can provide a very
detailed description of eolian strata. Characteristics of strata can be determined by
observation of images directly from its electrical resistive parameter. The analysis of the
strata orientation through bed azimuth and dip can be viewed as the conventional 256
tadpoles orientation as in dipmeter. Based on these features, the bounding surfaces of the
eolian sandstone interval can be defined (Carr-Crabaugh et al., 1996).
The T2 distribution of the CMR log can differentiate facies within the eolian
interval. Short T2 and bimodal curves represent the wind ripple facies. The grain flow
facies is shown by unimodal curves and longer T2 distribution times that represent a larger pore size distribution within this facies. The interdune, dolomitic sandstone of tidal environment, and marine carbonates have a common pattern with short T2 and generally
bimodal curves. The only thing that differentiates wind ripple from interdune and marine
facies is the FMI log. The WR facies is less resistive than the interdune or marine units,
and will appear on images as a darker color. The interdune also has wavy sedimentary
structures, but with higher electrical resistance, they appear as light color (white).
The vertical succession within the eolian sandstone interval can be seen on the
pattern of CMR T2 distribution. The red arrow patterns that trend upward from the fastest
time to the slowest distribution, indicate the gradually change of strata from wind ripple
at the bottom to grain flow at the top. The blue arrow patterns, show the opposite features
of the red ones. The green arrow pattern has the vertical succession of constant upward of
T2 distribution, and indicates the same pore size distribution within the interval (Figures
6-25, -28, -29, and –30). The T2 distribution patterns can be used to identify the bounding
surfaces within eolian intervals. With its correlative interval from borehole images, the 257
tops and bottoms of the pattern usually are the bounding surfaces that correlate with
deflection on the tadpoles pattern from bed boundaries position within the well.
The CMR log can differentiate porosity of the formation in detail. The composite
CMR and FMI log of SCU #21 has at least three different kinds of porosity that can be
inferred. The CMR porosity measures the free fluid and bound fluid volume of the
formation (see Figures 6-25, -28, -29, and –30). In conjunction with bounding surfaces
and facies type, now we can identify that strata with smaller pore size such as WR
compare to GF, interdune, dolomitic sandstone and marine facies which are less producible than grain flow facies. They have generally less porosity and permeability, and contain more bound fluid compared to the larger pore size of the grain flow interval.
Such information is very important in order to model reservoir characteristics of the
Tensleep Sandstone in the area.
The composite display of CMR and FMI log together with other conventional log
suites offers a major advantage to determine the petrophysical properties of such a well.
Eolian deposits, which are commonly thought to be homogeneous sandstone reservoirs,
can be clearly differentiated according to its strata composition using the combined CMR
and FMI logging suite.
Table 7.1 is the compilation of all methods used in this study to determine the
eolian and associated facies. Table 7.2 is the compilation of the same methods to
determine the bounding surfaces in the eolian system. 258
Reserved for table 7-1 259
reserved for table 7-2 260
CHAPTER 8
CONCLUSIONS
The description of each facies in eolian and associated deposits of the Tensleep
Sandstone interval in Sage Creek field can be determined using several methods. The outcrop measured section at Bear Canyon shows the general description of the Tensleep
Sandstone that consists of the Upper Tensleep, an eolian-dominated interval, and Lower
Tensleep, a mixed eolian-marine interval. This general division of the Tensleep
Sandstone could also be seen in the core description of the Fox #1 well and log analysis of the SCU #21 well.
Eolian and associated facies including bounding surfaces can be determined using a combination of measured sections, core descriptions, and log analysis. The measured section describes facies according to its features in the outcrop. The interdune, marine and dolomitic sandstones tend to stand out due to early cementation by anhydrite or dolomite. The eolian dune sets are generally tabular-planar cross-strata that consist of grain flow and wind ripple laminae. The differences in packing and pore size of grain flow and wind ripple facies resulted in heavier degrees of cementation in the tighter- 261
packed portions of laminae. The more cemented, tighter packed portions of laminae such as wind ripple, tends to be more resistant to weathering. Core examination showed that the interdune, marine dolomite and dolomitic sandstone facies are commonly bioturbated and sometimes reworked completely by organic activity. The eolian section is clearly seen by its cross-strata lamination. The wind ripple facies are distinct with pinstripe texture, and show reverse grading. The grain flow facies commonly has a higher cross- strata angle than the wind ripple facies. It appears to be both inverse and normal graded, and more loosely packed than the wind ripple strata. Borehole image interpretation of facies can be done in combination with other log data. The impermeable strata such as interdune, marine dolomite and dolomitic sandstone facies commonly have higher resistivity and are lighter in color. Wavy-bedded structures sometimes are still observable on the interdune facies. Bounding surfaces can be determined by using tadpole patterns, and the differences between wind ripple and grain flow facies can be confirmed with
CMR log data.
The small-scale heterogeneity within eolian sediments of the Tensleep Sandstone can be defined by petrophysical analysis of the various eolian facies using capillary pressure, minipermeameter, conventional core, and laboratory NMR. The MICP analysis showed that interdune, marine and dolomitic sandstone facies have similar petrophysical properties. With the same sample set, the laboratory NMR studies confirmed the results from MICP. The petrographic analysis on the same data set suggested that grain packing 262
of grain flow facies is less than the wind ripple facies. Interdune, dolomitic sandstone and
marine facies do not have the potential to become productive reservoirs within the eolian
system.
The T2 distribution of the CMR log from SCU #21 well and its related facies from
NMR lab test of the Fox #1 well show a distinct character of each recognized facies. The
faster T2 distribution is related to the wind ripple facies and generally shows bimodal
curves on its distribution. The grain flow facies has slower T2 times and a unimodal distribution. The interdune, dolomitic sandstone and marine facies commonly show similar T2 distributions. They have faster T2 times without any observable pattern within
their pore size distribution.
Permeability models have been done using several combination tools. In wells
with core data and conventional log suites, the MICP and NMR lab experiments can be
used to model permeability profiles. The application of the Timur equation based on log
porosity and irreducible water saturation has a good agreement to the minipermeameter
and laboratory results. The permeability estimation using FFI and BFV together with
porosity from NMR lab tests showed that default parameters had to be adjusted to C=16
with the Coates formula (Eq. 5.17), and b1=0.15 with the Timur-Coates formula (Eq.
5.19). The SDR estimator (Eq. 5.18) has a good match with the conventional air-
permeability if one uses a1=7.5 as the coefficient. 263
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