Physical and Numerical Modeling of SAGD Under New Well Configurations

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2013-09-23 Physical and Numerical Modeling of SAGD Under New Well Configurations

Tavallali, Mohammad

Tavallali, M. (2013). Physical and Numerical Modeling of SAGD Under New Well Configurations (Unpublished doctoral thesis). University of Calgary, Calgary, AB. doi:10.11575/PRISM/27348 http://hdl.handle.net/11023/1002 doctoral thesis

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Physical and Numerical Modeling of SAGD Under New Well Configurations

Mohammad Tavallali

A THESIS

SUBMITTED TO THE FACULTY OF GRADUATE STUDIES

IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE

DEGREE OF DOCTOR OF PHILOSOPHY

DEPARTMENT OF CHEMICAL & PETROLEUM ENGINEERING

CALGARY, ALBERTA

SEPTEMBER, 2013

ABSTRACT

This research was aimed at investigating the effect of well configuration on SAGD performance and developing a methodology for optimizing the well configurations for different reservoir characteristics. The role of well configuration in determining the performance of SAGD operations was investigated with help of numerical and physical models. Since mid 1980’s, SAGD process feasibility has been field tested in many successful pilots and subsequently through several commercial projects in various bitumen and heavy oil reservoirs. Although SAGD has been demonstrated to be technically successful and economically viable, it still remains very energy intensive, extremely sensitive to geological and operational conditions, and an expensive oil recovery mechanism. Well configuration is one of the major factors which affects SAGD performance and requires greater consideration for process optimization. Several well patterns were numerically examined for Athabasca, Cold Lake and Lloydminster type of reservoirs. Numerical modeling was carried out using a commercial fully implicit thermal reservoir simulator, Computer Modeling Group (CMG) STARS. For each reservoir, one or two promising well patterns were selected for further evaluations in the 3-D physical model or future field pilots. Three well patterns including the Classic SAGD pattern, Reverse Horizontal Injector, and Inclined Injector, of which the last two emerged as most promising in the numerical study, were examined in a 3-D physical model for Athabasca and Cold Lake reservoirs. The physical model used in this study was a rectangular model that was designed based on the available dimensional analysis for a SAGD type of recovery mechanism. Two types of bitumen representing the Athabasca and Cold Lake reservoirs were used in the experiments. A total of seven physical model experiments were conducted, four of which used the classic two parallel horizontal wells configuration, which were considered the base case tests. Two experiments used the Reverse Horizontal Injector pattern and the last experiment tested the Inclined Injector pattern. The suggested well patterns provided operational and economical enhancement to the SAGD process over the standard well

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configuration and this research strongly suggests that both of them should be examined through field pilots in Athabasca/Cold Lake type of reservoirs. In order to develop further insight into the performance of different well patterns, the production profile of each experiment was history matched using CMG-STARS. Only the relative permeability curves, porosity, permeability, and the production constraint were changed to get the best match of the experimental results. Although it was possible to history match the production performance of these tests by changing the relative permeability curves, the need for considerable changes in relative permeability shows that the numerical model was not able capture the true hydrodynamic behavior of the modified well configurations.

ACKNOWLEDGEMENTS

It would not have been possible to complete this doctoral thesis without the help and support of the kind people around me, to only some of whom it is possible to give particular mention here.

First and foremost, I wish to express my sincere gratitude to Dr. Brij B. Maini and Dr. Thomas G. Harding for their generous guidance, encouragement, and support throughout the course of this study. This thesis would not have been possible without their unsurpassed knowledge and patience. I really feel privileged to have Dr Maini as my supervisor and Dr Harding as my Co-Supervisor during these years of study.

I would like to extend my thanks to Mr. Paul Stanislav for his helpful technical support during performing the experiments.

I owe my respectful gratitude to the official reviewers of this thesis, Dr. S.A. Mehta, Dr. M. Dong, Dr. G. Achari, and Dr. K. Asghari for their critically constructive comments, which saved me from many errors and definitely helped to improve the final manuscript.

I would like to acknowledge all the administrative support of the Department of Chemical and Petroleum Engineering during this research.

I’m practically grateful for the support of Computer Modeling Group for providing unlimited CMG’s license and for their technical support.

I must express my gratitude to Narges Bagheri, my best friend, for her continued support and encouragement during all of the ups and downs of my research.

I would like to thank my friends, Bashir Busahmin, Cheewee Sia, Farshid Shayganpour, and Rohollah Hashemi for their support during my research.

Finally, I wish to thank my dear parents for their patient love and permanent moral support.

DEDICATION

To my parents, my sisters Marjan, Mozhgan, and Mozhdeh, and my best friend Narges

TABLE OF CONTENTS

ABSTRACT...... ii ACKNOWLEDGEMENTS...... iv DEDICATIONS...... v TABLE OF CONTENTS...... vi LIST OF TABLES...... x LIST OF FIGURES ...... xi LIST OF SYMBOLES, ABBREVIATIONS, AND NUMENCLATURES ...... xx

CHAPTER 1: INTRODUCTION...... 1 1.1 Background ...... 2 1.2 Dimensional Analysis...... 9 1.3 Factors Affecting SAGD Performance...... 10 1.3.1 Reservoir Properties ...... 10 1.3.1.1 Reservoir Depth ...... 10 1.3.1.2 Pay Thickness, Oil Saturation, Grain Size, and Porosity...... 11 1.3.1.3 Permeability (kv, kh)...... 11 1.3.1.4 Bitumen viscosity...... 11 1.3.1.5 Heterogeneity...... 11 1.3.1.6 Wettability...... 12 1.3.1.7 Water Leg...... 13 1.3.1.8 Gas Cap...... 13 1.3.2 Well Design...... 13 1.3.2.1 Completion...... 13 1.3.2.2 Well Configuration ...... 14 1.3.2.3 Well Pair Spacing ...... 14 1.3.2.4 Horizontal Well Length ...... 14 1.3.3 Operational Parameters ...... 14 1.3.3.1 Pressure...... 14 1.3.3.2 Temperature ...... 15 1.3.3.3 Pressure Difference between Injector and Producer...... 15 1.3.3.4 Subcool (Steam-trap control)...... 15 1.3.3.5 Steam Additives...... 16 1.3.3.6 Non-Condensable Gas ...... 16 1.3.3.6 Wind Down...... 16 1.4 Objectives...... 17 1.4 Dissertation Structure ...... 19

CHAPTER 2: LITERATURE REVIEW...... 21 2.1 General Review ...... 22 2.2 Athabasca ...... 33 2.3 Cold Lake ...... 35 2.4 Lloydminster ...... 36

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CHAPTER 3: GEOLOGICAL DESCRIPTION ...... 39 3.1 Introduction ...... 40 3.2 Athabasca ...... 41 3.3 Cold Lake ...... 47 3.4 Lloydminster ...... 53 3.5 Heterogeneity ...... 59

CHAPTER 4: EXPERIMENTAL EQUIPMENT AND PROCEDURE...... 62 4.1 Equipmental Apparatus ...... 63 4.1.1 3-D Physical Model...... 63 4.1.2 Steam Generator ...... 67 4.1.3 Temperature Probes...... 68 4.2 Data Acquisition...... 68 4.3 Rock/Fluid Property Measurements...... 68 4.3.1 Permeability Measurement Apparatus ...... 68 4.3.2 HAAKE Roto Viscometer...... 69 4.3.3 Dean Stark Distillation Apparatus...... 71 4.4 Experimental Procedure ...... 73 4.4.1 Model Preparation ...... 73 4.4.2 SAGD Experiment ...... 75 4.4.3 Analysing Samples...... 77 4.4.4 Cleaning...... 78

CHAPTER 5: NUMERICAL RESERVOIR SIMULATION ...... 79 5.1 Athabasca ...... 80 5.1.1 Reservoir Model ...... 80 5.1.2 Fluid Properties ...... 82 5.1.3 Rock-Fluid Properties...... 83 5.1.4 Initial Condistion/Geomechanics ...... 85 5.1.5 Wellbore Model...... 85 5.1.6 Wellbore Constraint ...... 86 5.1.7 Operating Period...... 87 5.1.8 Well Configurations ...... 87 5.1.8.1 Base Case...... 88 5.1.8.2 Vertical Inter-well Distance Optimization...... 94 5.1.8.3 Vertical Injector ...... 98 5.1.8.4 Reversed Horizontal Injector ...... 101 5.1.8.5 Inclined Injector Optimization...... 104 5.1.8.6 Parallel Inclined Injector...... 108 5.1.8.7 Multi-Lateral Producer...... 111 5.2 Cold Lake ...... 113 5.2.1 Reservoir Model ...... 113 5.2.2 Fluid Properties ...... 114 5.2.3 Rock-Fluid Properties...... 115

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5.2.4 Initial Condistion/Geomechanics ...... 116 5.2.5 Wellbore Model...... 116 5.2.6 Wellbore Constraint ...... 116 5.2.7 Operating Period...... 116 5.2.8 Well Configurations ...... 117 5.2.8.1 Base Case...... 117 5.2.8.2 Vertical Inter-well Distance Optimization...... 121 5.2.8.3 Offset Horizontal Injector...... 123 5.2.8.4 Vertical Injector ...... 126 5.2.8.5 Reversed Horizontal Injector ...... 129 5.2.8.6 Parallel Inclined Injector...... 132 5.2.8.7 Parallel Reversed Upward Injectors...... 135 5.2.8.8 Multi-Lateral Producer...... 137 5.2.8.9 C-SAGD...... 140 5.3 Lloydminster ...... 144 5.3.1 Reservoir Model ...... 146 5.3.2 Fluid Properties ...... 147 5.3.3 Initial Condistion/Geomechanics ...... 148 5.3.4 Wellbore Constraint ...... 148 5.3.5 Operating Period...... 149 5.3.6 Well Configurations ...... 149 5.3.6.1 Offset Producer ...... 151 5.3.6.2 Vertical Injector ...... 154 5.3.6.3 C-SAGD...... 157 5.3.6.4 ZIGZAG Producer ...... 160 5.3.6.5 Multi-Lateral Producer...... 162

CHAPTER 6: EXPERIMENTAL RESULTS AND DISCUSSIONS...... 166 6.1 Fluid and Rock Properties ...... 168 6.2 First, Second, and Third Experiments ...... 171 6.2.1 Production Results...... 171 6.2.2 Temperature Profiles ...... 177 6.2.3 History Matching the Production Profile with CMG/STARS...... 183 6.3 Fourth Experiment...... 187 6.3.1 Production Results...... 187 6.3.2 Temperature Profiles ...... 188 6.3.3 History Matching the Production Profile with CMG/STARS...... 196 6.4 Fifth Experiment...... 200 6.4.1 Production Results...... 200 6.4.2 Temperature Profiles ...... 201 6.4.3 Residual Oil Saturation ...... 209 6.4.4 History Matching the Production Profile with CMG/STARS...... 211 6.5 Sixth Experiment...... 215 6.5.1 Production Results...... 215 6.5.2 Temperature Profiles ...... 219

6.5.3 Residual Oil Saturation ...... 224 6.5.4 History Matching the Production Profile with CMG/STARS...... 226 6.6 Seventh Experiment ...... 230 6.6.1 Production Results...... 230 6.6.2 Temperature Profiles ...... 234 6.6.3 Residual Oil Saturation ...... 240 6.6.4 History Matching the Production Profile with CMG/STARS...... 241

CHAPTER 7: CONCLUSIONS AND RECOMMENDATIONS...... 246 7.1 Conclusions ...... 247 7.2 Recommendations ...... 250

REFERENCES ...... 252

LIST OF TABLES

Table 1-1 Effective parameters in Scaling Analysis of SAGD process...... 10 Table 4-1 Dimensional analysis parameters: field vs. physical...... 64 Table 4-2 Cylinder Sensor System in HAAKE viscometer...... 70 Table 5-1 Reservoir properties of model representing Athabasca reservoir...... 82 Table 5-2 Fluid roperties representing Athabasca Bitumen ...... 82 Table 5-3 Rock-Fluid properties...... 85 Table 5-4 Analaytical solution paramters...... 93 Table 5-5 Inclined Injector case...... 104 Table 5-6 Reservoir and fluid properties for Cold Lake reservoir model...... 115 Table 5-7 Values of dilation-compaction properties for Cold Lake reservoir model...... 141 Table 5-8 Reservoir and fluid properties for Lloydminster reservoir model...... 148 Table 6-1 Summary of the physical model experiments ...... 168 Table 6-2 Summary water/gas/oil relative permeability end points of 5th, 6th , and 7th experiments...... 241

LIST OF FIGURES

Figure 1-1 μ −T relationship ...... 2 Figure 1-2 Schematic of SAGD...... 3 Figure 1-3 Vertical cross section of drainage interface ...... 5 Figure 1-4 Steam chamber interface positions ...... 7 Figure 1-5 Interface Curve with TANDRAIN Theory ...... 8 Figure 1-6 Various well configurations...... 19 Figure 2-1 Chung and Butler Well Schemes...... 26 Figure 2-2A Well Placement Schematic by Chan ...... 27 Figure 2-2B Joshi’s well pattern...... 27 Figure 2-3 Nasr’s Proposed Well Patterns...... 28 Figure 2-4 SW-SAGD well configuration ...... 29 Figure 2-5 SAGD and FAST-SAGD well configuration...... 29 Figure 2-6 Well Pattern Schematic by Ehlig-Economides ...... 30 Figure 2-7 The Cross-SAGD (XSAGD) Pattern ...... 30 Figure 2-8 The JAGD Pattern ...... 31 Figure 2-9 U-Shaped horizontal wells pattern...... 32 Figure 2-10 The Schematic of well patterns proposed by Bashbush and Pina ...... 32 Figure 2-11 Athabasca Oil Sand’s Projects ...... 33 Figure 3-1 Alberta’s bitumen resources estimate volume as of December 31, 2011...... 40 Figure 3-2 Bitumen and Heavy Oil deposit of Canada ...... 41 Figure 3-3 Distribution of pay zone on eastern margin of Athabasca...... 42 Figure 3-4 Pay thickness of McMurray-Wabiskaw in the Athabasca Area...... 43 Figure 3-5 Athabasca cross section...... 44 Figure 3-6 Correlation chart of Lower Cretaceous bitumen deposits at Athabasca Oil Sand...... 45 Figure 3-7 Oil Sands at Cold Lake area...... 48 Figure 3-8 Correlation chart of Lower Cretaceous at Cold Lake area ...... 48 Figure 3-9 Clearwater Formation at Cold Lake area...... 49 Figure 3-10 Lower Grand Rapids Formation at Cold Lake area ...... 50

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Figure 3-11 Upper Grand Rapids Formation at Cold Lake area ...... 51 Figure 3-12 McMurray Formation at Cold Lake area...... 52 Figure 3-13 Location of Lloydminster area ...... 54 Figure 3-14 Correlation chart of Lower Cretaceous at Lloydminster area...... 55 Figure 3-15 Distribution of Ribbon-Shaped Manville Group at Lloydminster area...... 57 Figure 3-16 Lloydminster area oil field...... 59 Figure 4-1 Schematic of Experimental Set-up ...... 63 Figure 4-2 Physical model Schematic ...... 65 Figure 4-3 Physical Model...... 66 Figure 4-4 Thermocouple location in Physical Model ...... 67 Figure 4-5 Pressure cooker ...... 68 Figure 4-6 Temperature Probe design ...... 68 Figure 4-7 Permeability measurement apparatus...... 69 Figure 4-8 HAAKE viscometer ...... 70 Figure 4-9 Dean-Stark distillation apparatus ...... 72 Figure 4-10 Sand extraction apparatus...... 72 Figure 4-11 Bitumen saturation step...... 75 Figure 4-12 Injection/Production and sampling stage ...... 76 Figure 4-13 Bottom layer of the model after SAGD experiment and the sampling points for sand analysis...... 77 Figure 5-1 3-D schematic of Athabasca reservoir model ...... 81 Figure 5-2 Cross view of Athabasca reservoir model ...... 81 Figure 5-3 Temperature dependency of bitumen model’s Viscosity for Athabasca ...... 83 Figure 5-4 Water-oil relative permeability ...... 84 Figure 5-5 Relative permeability sets for DW well pairs ...... 85 Figure 5-6 Schematic representation of various well configurations for Athabasca Reservoir ...87 Figure 5-7 Oil Production Rate: Base Case ...... 89 Figure 5-8 Oil Recovery Factor: Base Case ...... 89 Figure 5-9 Cumulative Steam Oil Ratio (cSOR): Base Case...... 90

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Figure 5-10 Steam Chamber Volume: Base Case ...... 90 Figure 5-11 Cross view of chamber development at 4 specified time frames: Base Case ...... 91 Figure 5-12 Steam Quality of DW vs SS during the SAGD life period: Base Case ...... 91 Figure 5-13 Pressure Profile between Injector and Producer at the heel and toe: Base Case...... 93 Figure 5-14 Comparison of numerical and analytical solutions: Base Case ...... 94 Figure 5-15 Oil Production Rate: Vertical Inter-well Distance Optimization ...... 96 Figure 5-16 Oil Recovery Factor: Vertical Inter-well Distance Optimization...... 96 Figure 5-17 Steam Oil Ratio: Vertical Inter-well Distance Optimization ...... 97 Figure 5-18 Steam Chamber Volume: Vertical Inter-well Distance Optimization ...... 97 Figure 5-19 Oil Production Rate: Vertical Injectors...... 99 Figure 5-20 Oil Recovery Factor: Vertical Injectors ...... 99 Figure 5-21 Steam Oil Ratio: Vertical Injectors ...... 100 Figure 5-22 Steam Chamber Volume: Vertical Injectors...... 100 Figure 5-23 Oil Production Rate: Reverse Horizontal Injector...... 102 Figure 5-24 Oil Recovery Factor: Reverse Horizontal Injector...... 102 Figure 5-25 Steam Oil Ratio: Reverse Horizontal Injector ...... 103 Figure 5-26 Steam Chamber Volume: Reverse Horizontal Injector...... 103 Figure 5-27 3-D View of Chamber Growth: Reverse Horizontal Injector...... 104 Figure 5-28 Oil Recovery Factor: Inclined Injector ...... 105 Figure 5-29 Steam Oil Ratio: Inclined Injector...... 105 Figure 5-30 Oil Production Rate: Inclined Injector: Case 07...... 106 Figure 5-31 Oil Recovery Factor: Inclined Injector: Case 07 ...... 106 Figure 5-32 Steam Oil Ratio: Inclined Injector: Case 07...... 107 Figure 5-33 Steam Chamber Volume: Inclined Injector: Case 07 ...... 107 Figure 5-34 Oil Production Rate: Parallel Inclined Injector ...... 109 Figure 5-35 Oil Recovery Factor: Parallel Inclined Injector ...... 109 Figure 5-36 Steam Oil Ratio: Parallel Inclined Injector...... 110 Figure 5-37 Steam Chamber Volume: Parallel Inclined Injector ...... 110 Figure 5-38 Oil Production Rate: Multi-Lateral Producer...... 111

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Figure 5-39 Oil Recovery Factor: Multi-Lateral Producer ...... 112 Figure 5-40 Steam Oil Ratio: Multi-Lateral Producer ...... 112 Figure 5-41 Steam Chamber Volume: Multi-Lateral Producer...... 113 Figure 5-42 3-D schematic of Cold Lake reservoir model ...... 114 Figure 5-43 Viscosity vs. Temperature for Cold Lake bitumen ...... 115 Figure 5-44 Schematic representation of various well configurations for Cold Lake ...... 117 Figure 5-45 Oil Production Rate: Base Case ...... 119 Figure 5-46 Oil Recovery Factor: Base Case ...... 119 Figure 5-47 Steam Oil Ratio: Base Case...... 120 Figure 5-48 Steam Chamber Volume: Base Case ...... 120 Figure 5-49 Oil Production Rate: Vertical Inter-well Distance Optimization ...... 121 Figure 5-50 Oil Recovery Factor: Vertical Inter-well Distance Optimization...... 122 Figure 5-51 Steam Oil Ratio: Vertical Inter-well Distance Optimization ...... 122 Figure 5-52 Steam Chamber Volume: Vertical Inter-well Distance Optimization ...... 123 Figure 5-53 Oil Production Rate: Offset Horizontal Injector ...... 124 Figure 5-54 Oil Recovery Factor: Offset Horizontal Injector...... 125 Figure 5-55 Steam Oil Ratio: Offset Horizontal Injector ...... 125 Figure 5-56 Steam Chamber Volume: Offset Horizontal Injector ...... 126 Figure 5-57 Oil Production Rate: Vertical Injectors...... 127 Figure 5-58 Oil Recovery Factor: Vertical Injectors ...... 128 Figure 5-59 Steam Oil Ratio: Vertical Injectors ...... 128 Figure 5-60 Steam Chamber Volume: Vertical Injectors...... 129 Figure 5-61 Oil Production Rate: Reverse Horizontal Injector...... 130 Figure 5-62 Oil Recovery Factor: Reverse Horizontal Injector...... 131 Figure 5-63 Steam Oil Ratio: Reverse Horizontal Injector ...... 131 Figure 5-64 Steam Chamber Volume: Reverse Horizontal Injector...... 132 Figure 5-65 Oil Production Rate: Parallel Inclined Injector ...... 133 Figure 5-66 Oil Recovery Factor: Parallel Inclined Injector ...... 133 Figure 5-67 Steam Oil Ratio: Parallel Inclined Injector...... 134

Figure 5-68 Steam Chamber Volume: Parallel Inclined Injector ...... 134 Figure 5-69 Oil Production Rate: Parallel Reverse Upward Injector ...... 135 Figure 5-70 Oil Recovery Factor: Parallel Reverse Upward Injector...... 136 Figure 5-71 Steam Oil Ratio: Parallel Reverse Upward Injector ...... 136 Figure 5-72 Steam Chamber Volume: Parallel Reverse Upward Injector...... 137 Figure 5-73 Oil Production Rate: Multi-Lateral Producer...... 138 Figure 5-74 Oil Recovery Factor: Multi-Lateral Producer ...... 139 Figure 5-75 Steam Oil Ratio: Multi-Lateral Producer ...... 139 Figure 5-76 Steam Chamber Volume: Multi-Lateral Producer...... 140 Figure 5-77 Reservoir deformation model...... 141 Figure 5-78 Oil Production Rate: C-SAGD ...... 142 Figure 5-79 Oil Recovery Factor: C-SAGD...... 143 Figure 5-80 Steam Oil Ratio: C-SAGD ...... 143 Figure 5-81 Steam Chamber Volume: C-SAGD...... 144 Figure 5-82 Schematic of SAGD and Steamflood...... 145 Figure 5-83 3-D schematic of reservoir model for Lloydminster reservoir...... 147 Figure 5-84 Temperature dependency of heavy oil model’s Viscosity ...... 149 Figure 5-85 Schematic of various well configurations for Lloydminster reservoir...... 150 Figure 5-86 Oil Procution Rate: Offset Producer...... 152 Figure 5-87 Oil Recovery Factor: Offset Producer...... 152 Figure 5-88 Steam Oil Ratio: Offset Producer...... 153 Figure 5-89 Steam Chamber Volume: Offset Producer ...... 153 Figure 5-90 Oil Production Rate: Vertical Injector ...... 155 Figure 5-91 Oil Recovery Factor: Vertical Injector ...... 155 Figure 5-92 Steam Oil Ratio: Vertical Injector...... 156 Figure 5-93 Steam Chamber Volume: Vertical Injector ...... 156 Figure 5-94 Oil Production Rate: C-SAGD ...... 158 Figure 5-95 Oil Recovery Factor: C-SAGD ...... 158

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Figure 5-96 Steam Oil Ratio: C-SAGD ...... 159 Figure 5-97 Steam Chamber Volume: C-SAGD...... 159 Figure 5-98 Oil Production Rate: ZIGZAG...... 160 Figure 5-99 Oil Recovery Factor: ZIGZAG...... 161 Figure 5-100 Steam Oil Ratio: ZIGZAG ...... 161 Figure 5-101 Steam Chamber Volume: ZIGZAG...... 162 Figure 5-102 Oil Production Rate: Comparison ...... 163 Figure 5-103 Oil Recovery Factor: Comparison ...... 163 Figure 5-104 Steam Oil Ratio: Comparison ...... 164 Figure 5-105 Steam Chamber Volume: Comparison ...... 164 Figure 6-1 Permeability measurement with AGSCO Sand ...... 169 Figure 6-2 Elk-Point viscosity profile ...... 170 Figure 6-3 JACOS Bitumen viscosity profile ...... 170 Figure 6-4 Oil Rate: First and Second Experiment...... 173 Figure 6-5 cSOR: First and Second Experiment ...... 173 Figure 6-6 WCUT: First and Second Experiment ...... 174 Figure 6-7 RF: First and Second Experiment...... 174 Figure 6-8 Oil Rate: Second and Third Experiment ...... 175 Figure 6-9 cSOR: Second and Third Experiment ...... 176 Figure 6-10 WCUT: Second and Third Experiment...... 176 Figure 6-11 RF: Second and Third Experiment ...... 177 Figure 6-12 Temperature profile along the injector at 5 and 20 hours: First Experiment...... 178 Figure 6-13 Layers and Cross sections schematic of the physical model ...... 179 Figure 6-14 Chamber Expansion along the well-pair at 0.1 PVinj...... 180 Figure 6-15 Chamber Expansion along the well-pair at 0.2 PVinj...... 181 Figure 6-16 Chamber Expansion along the well-pair at 0.5 PVinj...... 181 Figure 6-17 Chamber Expansion along the well-pair at 0.6 PVinj...... 182 Figure 6-18 Chamber Expansion along the well-pair at 0.78 PVinj...... 182 Figure 6-19 Chamber Expansion Cross View at 0.78 PVinj: Cross-Section 1 ...... 183

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Figure 6-20 Water /Oil/Gas Relative Permeability: First Experiment History Match...... 184 Figure 6-21 Match to Oil Production Profile: First Experiment ...... 185 Figure 6-22 Match to Water Production Profile: First Experiment ...... 185 Figure 6-23 Match to Steam (CWE) Injection Profile: First Experiment ...... 186 Figure 6-24 Match to Steam Chamber Volume: First Experiment...... 186 Figure 6-25 Oil Rate: First and Fourth Experiment...... 189 Figure 6-26 cSOR: First and Fourth Experiment ...... 189 Figure 6-27 WCUT: First and Fourth Experiment ...... 190 Figure 6-28 RF: First and Fourth Experiment...... 190 Figure 6-29 Temperature profile along the injector at 3 and 16 hours: Fourth Experiment...... 191 Figure 6-30 Chamber Expansion along the well-pair at 0.1 PVinj...... 192 Figure 6-31 Chamber Expansion along the well-pair at 0.2 PVinj...... 193 Figure 6-32 Chamber Expansion along the well-pair at 0.3 PVinj...... 193 Figure 6-33 Chamber Expansion along the well-pair at 0.4 PVinj...... 194 Figure 6-34 Chamber Expansion along the well-pair at 0.5 PVinj...... 194 Figure 6-35 Chamber Expansion Cross View at 0.5 PVinj: Cross Section 1 ...... 195 Figure 6-36 Water /Oil/Gas Relative Permeability: Fourth Experiment History Match...... 197 Figure 6-37 Match to Oil Production Profile: Fourth Experiment ...... 198 Figure 6-38 Match to Water Production Profile: Fourth Experiment ...... 198 Figure 6-39 Match to Steam (CWE) Injection Profile: Fourth Experiment ...... 199 Figure 6-40 Match to Steam Chamber Volume: Fourth Experiment...... 199 Figure 6-41 Oil Rate: Fifth Experiment ...... 202 Figure 6-42 3-D cSOR: Fifth Experiment ...... 202 Figure 6-43 WCUT: Fifth Experiment...... 203 Figure 6-44 RF: Fifth Experiment ...... 203 Figure 6-45 Temperature profile along the injector at 5 and 20 hours: Fifth Experiment ...... 204 Figure 6-46 Chamber Expansion along the well-pair at 0.1 PVinj...... 205 Figure 6-47 Chamber Expansion along the well-pair at 0.2 PVinj...... 206 Figure 6-48 Chamber Expansion along the well-pair at 0.3 PVinj...... 206

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Figure 6-49 Chamber Expansion along the well-pair at 0.4 PVinj...... 207 Figure 6-50 Chamber Expansion along the well-pair at 0.5 PVinj...... 207 Figure 6-51 Chamber Expansion along the well-pair at 0.65 PVinj...... 208 Figure 6-52 Chamber Expansion Cross View at 0.65 PVinj: Cross Section1 ...... 208 Figure 6-53 Sampling distributions per each layer of model...... 209 Figure 6-54 φΔSo across the middle layer: fifth experiment...... 210 Figure 6-55 φΔSo across the top layer: fifth experiment...... 211 Figure 6-56 Water /Oil/Gas Relative Permeability: Fifth Experiment History Match ...... 212 Figure 6-57 Match to Oil Production Profile: Fifth Experiment ...... 213 Figure 6-58 Match to Water Production Profile: Fifth Experiment...... 213 Figure 6-59 Match to Steam (CWE) Injection Profile: Fifth Experiment ...... 214 Figure 6-60 Match to Steam Chamber Volume: Fifth Experiment ...... 214 Figure 6-61 Oil Rate: Fifth and Sixth Experiment ...... 216 Figure 6-62 cSOR: Fifth and Sixth Experiment ...... 216 Figure 6-63 WCUT: Fifth and Sixth Experiment ...... 217 Figure 6-64 RF: Fifth and Sixth Experiment ...... 217 Figure 6-65 Temperature profile along the injector at 4 and 14 hours: Sixth Experiment...... 220 Figure 6-66 Chamber Expansion along the well-pair at 0.1 PVinj...... 221 Figure 6-67 Chamber Expansion along the well-pair at 0.2 PVinj...... 221 Figure 6-68 Chamber Expansion along the well-pair at 0.3 PVinj...... 222 Figure 6-69 Chamber Expansion along the well-pair at 0.4 PVinj...... 222 Figure 6-70 Chamber Expansion along the well-pair at 0.5 PVinj...... 223 Figure 6-71 Chamber Expansion along the well-pair at 0.6 PVinj...... 223 Figure 6-72 Chamber Expansion Cross View at 0.5 PVinj ...... 224 Figure 6-73 φΔSo across the middle layer: sixth experiment...... 225 Figure 6-74 φΔSo across the top layer: sixth experiment...... 226 Figure 6-75 Water /Oil/Gas Relative Permeability: Sixth Experiment History Match...... 227 Figure 6-76 Match to Oil Production Profile: Sixth Experiment ...... 228 Figure 6-77 Match to Water Production Profile: Sixth Experiment ...... 228

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Figure 6-78 Match to Steam (CWE) Injection Profile: Sixth Experiment ...... 229 Figure 6-79 Match to Steam Chamber Volume: Sixth Experiment...... 229 Figure 6-80 Schematic representation of inclined injector pattern...... 230 Figure 6-81 Oil Rate: Fifth and Sixth Experiment ...... 232 Figure 6-82 cSOR: Fifth and Sixth Experiment ...... 232 Figure 6-83 WCUT: Fifth and Sixth Experiment ...... 233 Figure 6-84 RF: Fifth and Sixth Experiment ...... 233 Figure 6-85 Schematic of D5 Location in inclined injector pattern ...... 234 Figure 6-86 Temperature profile in middle of the model at 4 and 10 hours: Seventh Exp ...... 235 Figure 6-87 Chamber Expansion along the well-pair at 0.1 PVinj...... 237 Figure 6-88 Chamber Expansion along the well-pair at 0.2 PVinj...... 237 Figure 6-89 Chamber Expansion along the well-pair at 0.3 PVinj...... 238 Figure 6-90 Chamber Expansion along the well-pair at 0.4 PVinj...... 238 Figure 6-91 Chamber Expansion along the well-pair at 0.5 PVinj...... 239 Figure 6-92 Chamber Expansion Cross View at 0.5 PVinj: Cross Section 1 ...... 239 Figure 6-93 φΔSo across the top layer: seventh experiment ...... 240 Figure 6-94 Water /Oil/Gas Relative Permeability: Seventh Experiment History Match...... 242 Figure 6-95 Match to Oil Production Profile: Seventh Experiment ...... 243 Figure 6-96 Match to Water Production Profile: Seventh Experiment ...... 243 Figure 6-97 Match to Steam (CWE) Injection Profile: Seventh Experiment ...... 244 Figure 6-98 Match to Steam Chamber Volume: Seventh Experiment...... 244

LIST OF SYMBOLS, ABBREVIATIONS, AND NOMENCLATURE

Symbol Definition

C Heat capacity Cp Centipoises cSOR Cumulative Steam Oil Ratio ERCB Energy Recourses and Conservation Board Fo Fourier Number g Acceleration due to gravity h height k Effective permeability to the flow of oil K Thermal conductivity of reservoir krw Water relative permeability krow Oil relative permeability in the Oil-Water System krg Gas relative permeability krog Oil relative permeability in the Gas-Oil System Kv1 First coefficient for Gas-Liquid K-Value correlation Kv4 Fourth coefficient for Gas-Liquid K-Value correlation Kv5 Fifth coefficient for Gas-Liquid K-Value correlation L Length of horizontal well m Viscosity-Temperature relation coefficient nw Exponent for calculating krw now Exponent for calculating krow nog Exponent for calculating krog ng Exponent for calculation krg RF Recovery Factor Sl Liquid Saturation Soi Initial Oil Saturation Soirw Irreducible oil saturation with respect to water Sgr Residual gas saturation Soirg Irreducible oil saturation with respect to gas Sw Water saturation Swcon Connate water saturation TR Reservoir temperature Ts Steam temperature U Interface velocity UTF Underground Test Facility x Horizontal distance from draining point X Dimensionless horizontal distance y Vertical distance from draining point Y Dimensionless vertical distance ΔSo Oil s aturation change

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Greek Symbols

µ Dynamic viscosity νs Kinematic viscosity of bitumen at steam temperature α Thermal diffusivity φ Porosity ρ Density of oil θ Angle of Inclination of interface ζ Normal distance from the interface

CHAPTER 1 INTRODUCTION

1.1 Background Canada’s oil sands and heavy oil resources are among the largest known hydrocarbon deposits in the world. Alberta deposits contain more than 80% of the world’s recoverable reserves of bitumen. However, the amount of conventional oil reserves in Canada is limited and these reserves are declining. As a result of advances in the Steam Assisted Gravity Drainage (SAGD), which was introduced by Butler in 1978; some of the bitumen resources have turned into reserves. These resources include the vast oil sands of Northern Alberta (Athabasca, Cold Lake, and Peace River), and the more heavy oil that sits on the border between Alberta and Saskatchewan (Lloydminster). Currently due to the oil price and SAGD’s efficiency, the oil sands and heavy oils are attracting a lot of attentions. Most of the bitumen contains high fraction of asphaltenes, which makes it highly viscous and immobile at reservoir condition (11-15 ºC). It is their high natural viscosity that makes the recovery of heavy oils and bitumen difficult. However, the viscosity is very sensitive to temperatures, as shown in Fig. 1-1.

10000000 Athabasca Cold Lake 1000000

100000

10000

1000 Viscosity, cp Viscosity,

100

1 0 50 100 150 200 250 Temperature, C

Figure 1-1 μ −T relationship. 3

Currently there are two methods to extract the bitumen out of their deposits: a) Open pit mining, b) In-Situ Recovery. Using strip mining is economical for the deposit close to surface but only about 8% of oil sands can be exploited by this method. The rest of the deposits are too deep for the shovel and truck access. Currently only thermal oil recovery methods can be used to recover bitumen from oil sands, although several non-thermal technologies are under investigation. Thermal oil recovery, either by heat injection or internally generated heat through combustion, introduces heat into the reservoir to reduce the flow resistance by reduction of the bitumen viscosity with increased temperature. Thermal methods include steam flooding, cyclic steam stimulation, in-situ combustion, electric heating, and steam assisted gravity drainage. Among these processes, steam assisted gravity drainage (SAGD) is an effective method of producing heavy oil and bitumen. It unlocks billions barrels of oil that otherwise would have been inaccessible. Figure 1-2 displays a vertical cross-section of the basic SAGD mechanism.

Overburden

Steam Chamber

Net Pay

Underburden

Figure 1-2 Schematic of SAGD In the SAGD process, in order to enhance the contact area between the reservoir and the wellbore, two parallel horizontal wellbores are drilled and completed at the base of the formation. The horizontal well offers several advantages, such as; improved sweep efficiency, increased reserves, increased steam injectivity, and reduced number of wells needed for reservoir development. In the SAGD well-pair, the top well is the steam injector and the bottom well is the oil producer. The vertical distance between the injector 4 and the producer is typically 5 m. The producer is generally located a couple of meters above the base of formation. The SAGD process consists of three phases: 1) Preheating (Start-up) 2) Steam Injection & Oil Production 3) Wind down The purpose of preheating period is to establish fluid communication between injector and producer. The steam is circulated in both wellbores for typically 3-4 months in order to heat the region between the wells. The intervening high viscosity bitumen is mobilized and starts flowing from the injector to the producer as a result of both gravity drainage and the small pressure gradient between wellbores. Once the fluid communication between injector and producer is established, the normal SAGD operation can start. High quality steam is introduced continuously into the formation through the injection well and the oil is produced through the producer. The injected steam tends to rise and expand; it forms a steam saturated zone (steam chamber) above the injection well. The steam flows through the chamber where it contacts cold bitumen surrounding the chamber. At the chamber boundary the steam condenses and liberates its latent heat of vaporization, which serves to heat the bitumen. This heat exchange occurs by conduction as well as by convection. The heated bitumen becomes mobile, drains by gravity together with the steam condensate to the production well along the steam chamber boundary. Within the chamber the pressure remains constant and a counter current flow between the steam and draining fluids occurs. As the bitumen is being produced, the vacated space is left behind for the steam to fill in. The chamber grows upward, longitudinally and laterally before it touches the overburden. Eventually it reaches the cap rock and then spreads only laterally. During the normal SAGD phase two sub-stages can be defined: Ramp-up and Plateau. It is well understood that the initial upward growth of the steam chamber is much faster than the lateral growth. Meanwhile the injection and production rates appear to increase. This stage is called Ramp-Up. As the chamber reaches the formation top, the lateral growth becomes dominant. This period of production in which the oil production rate reaches a maximum (and then slowly declines) while the water cut goes through a minimum is called Plateau. 5

As time proceeds, the chamber spreads laterally and the interface becomes more inclined. The oil has to travel longer distance to reach the production well and larger area of the steam chamber is exposed to the cap-rock. Consequently the oil rate decreases and the SOR increases. The ultimate recovery factor in SAGD is typically higher than 50%. Eventually the SOR becomes unacceptably high and the steam chamber is called “mature.” The Wind-Down stage begins at this point. Butler, McNab and Lo derived the amount of oil flow parallel to the interface and via drainage force through Equation (1.1) by assuming that the steam pressure remains constant in the steam chamber [2], only steam flows in the chamber, oil saturation in the chamber is residual [3], drainage is parallel to the interface, the effective permeability is constant, and heat transfer ahead of the steam chamber to cold part of the reservoir is only by conduction. The steam zone interface was assumed to move uniformly at a constant velocity U. Based on these assumptions, the temperature ahead of the interface is given by Equation (1. 2).

⎛ ∂x ⎞ ⎜ ⎟ dt T=Ts ⎝ ∂t ⎠ y

T=T R

Figure 1-3 Vertical cross section of drainage interface [2]. 2φΔSkgα h q = 2L o (1.1) mν s

TT− S ⎛ Uξ ⎞ = exp ⎜ − ⎟ (1.2) TS −T R ⎝α ⎠ where q : rate of drainage of oil along the interface L : Length of horizontal well φ : porosity

ΔSo : Oil saturation change 6

k : Effective permeability to the flow of oil g : Gravitational acceleration α : Thermal diffusivity h : Reservoir net pay m : Viscosity-Temperature relation coefficient

υ s : Kinematic viscosity of bitumen at steam temperature

Ts : Steam temperature

TR : Reservoir temperature U : Interface velocity ξ : Normal distance from the interface The major assumption for flow relation derivation was that the steam chamber was initially a vertical plane above the production well and the horizontal displacement was given as a function of time t and height y by:

kgα xt= (1.3a) 2φΔSmo ν s (h− y)

2 kgα ⎛⎞t yh=− ⎜⎟ (1.3b) 2φΔSmo ν s ⎝⎠x The position of the interface in dimensionless form can be written as:

2 1 ⎛tD ⎞ Y =−1 ⎜ ⎟ (1.4) 2 ⎝⎠X X = xh/ (1.5) Y = yh/ (1.6)

t kgα t D = (1.7) hφΔ Smho ν s where x : Horizontal distance from draining point y : Vertical distance from draining point X : Dimensionless horizontal distance Y : Dimensionless vertical distance

Interface positions described by equation (1.4) are shown in Figure 1-4 7

1 0.9

0.8 0.2 0.7 0.6 0.4 0.6 0.8 1 0.5 1.2 1.4 0.4 1.6 1.8 0.3 2 Vertical Distance y/h 0.2 0.1 0 0 0.5 1 1.5 2 Horizontal Distance x/h

Figure 1-4 Steam chamber interface positions. The m value is introduced in Equation (1.8) to account for the effect of temperature on viscosity. It is defined as a function of the viscosity-temperature characteristics of the oil, the steam and the reservoir temperature.

−1 ⎡ TS ⎛ 1 1 ⎞ dT ⎤ m = ν − (1.8) ⎢ s ∫T ⎜ ⎟ ⎥ R ⎣ ⎝ ν ν R ⎠ TT− R ⎦ The drainage rate dictated by equation (1.1) is exaggerated compared with experiment data. Butler and Stephens modified this theory and came up with the TANDRAIN theory in which the drainage rate is given by Equation 1.9 [4]. This rate is 87% of that calculated by equation (1.1) and is closer to the experiment data. 1.5φΔSkgα h q = 2L o (1.9) mν s The interface in Figure 1.4 was modified so that the interface will not spread horizontally to infinity. In TANDRAIN theory the interface is connected to the horizontal well, as in Figure 1-5. 8

Figure 1-5 Interface Curve with TANDRAIN Theory Butler analyzed the dimensional similarity of the process in the field and laboratory scale physical models and found that not only tD must be the same for the model and the field, but also a dimensionless number B3 as given by equation (1.10) must be the same [3].

kgh B3 = (1.10) αφΔ Smo ν s

B3 is obtained by combining the dimensionless time (tD) and Fourier number. Fourier number is a dimensionless number that is the ratio of heat conduction rate and thermal energy storage rate. Butler expressed the extent of the temperature in a solid that is heated by conduction can be demonstrated by Fourier number as provided in equation (1.11) [1]. αt F = (1.11) o h 2

For dimensional similarity between a laboratory model and field, in addition to tD,

Fo needs to be the same for both models. Since Butler defined B3 as

t D B3 = (1.13) Fo

Therefore, for dimensional similarity between filed and lab model, the B3 of both models has to be equal.

1.2 Dimensional Analysis Dimensional analysis is a practical technique in all experimentally based areas of engineering research. It can be considered as a simplified type of scaling argument for learning about the dependence of a phenomenon on the dimensions and properties of the system that exhibits the phenomenon. Dimensional analysis is a method for reducing the number and complexity of experimental variables that affect a given physical phenomena. If it is possible to identify the factors involved in a physical situation, dimensional analysis can form a relationship between them. Dimensional analysis provides some advantages such as: reducing number of variables, defining dimensionless equations, and establishing dimensional similarity (Scaling law). Out of the listed advantages, the scaling law allows evaluating the full process using a small and simple model instead of constructing expensive large full scale prototypes. Particular type of similarities is geometric, kinematic, and dynamic similarity. To establish “Similar systems”, one should choose identical values of dimensionless combinations between two systems, even though the dimensional quantities may be quite different. Usually the dimensionless combinations are expressed as dimensionless number such as Re, Fr, and etc. Similarity analyses can proceed without knowledge of the governing equations. However, when the governing equations are known, then the “scale analysis,” term is more suitable. Since this research is dealing with thermal methods therefore the scaling requirements for thermal models need to be considered. These requirements can be generalized as follows: 1. Geometric Similarity: field and model must be geometrically similar. This implies the same width-to-length ratio, height-to-length ratio, dip angle, and reservoir heterogeneities. 2. The values of several parameters containing fluid and rock properties, as well as terms related to the transport of heat and mass, must be equal in the field and model. 3. Field and model must have the same initial conditions and boundary conditions. Scaled model experiments are one of the more useful tools for study and further development of the SAGD process. Before SAGD is applied in a new field, laboratory physical model experiments and field pilots may investigate its performance under 10 various reservoir conditions and geological characteristics. Physical model studies can investigate the effects of related factors by evaluating various scenarios. Such models can be used to optimize the pattern type, size, well configurations, injection and production mode, and effects of additives. By careful scaling, the physical model can produce data to forecast the performance of reservoirs under realistic conditions. It provides a helpful guide for prediction of field applications and for economic evaluation. In order to obtain the scaled analysis in a SAGD process, it is essential to set equal values of B3 in Equation 1.10 for both the physical model and the field properties. The properties of the scaled model are selected such a way that the dimensionless number B3 is the same for the model as for the field. A list of the parameters included in scaling analysis is provided in Table 1.1. Table 1-1 Effective parameters in Scaling Analysis of SAGD process

Parameter Net Pay, m Permeability, mD φΔSo, %

µR, cp

µs, cp

1.3 Factors Affecting SAGD Performance The parameters that control the SAGD performance can be categorized as reservoir properties, well design, and operating parameters. The following provides a brief discussion of the effects of important parameters.

1.3.1 Reservoir Properties

1.3.1.1 Reservoir Depth One of the important parameters affecting SAGD performance is the reservoir depth. Deep reservoirs have higher operating pressure which means higher steam temperature. Higher pressure steam (to some extend) carries higher enthalpy (but lower latent heat) 11 and has lower specific volume. This increases the energy stored in the vapor chamber. Also the heat losses in the well bore and to the overburden increase due to higher temperature and increased tubing length. On the positive side, increased temperature provides lower oil viscosity. The net effect of reservoir depth on SOR and RF needs to be examined in order to determine the optimum range of reservoir depth.

1.3.1.2 Pay Thickness, Oil Saturation, Grain Size, and Porosity Net pay thickness, oil saturation and porosity determine the amount of oil in the reservoir; and higher values yield better oil rate, lower steam oil ratio and higher recovery factor. The minimum pay thickness needed for economically viable SAGD operations appears to be about 15 meters but this needs to be further examined.

1.3.1.3 Permeability (kv, kh) Permeability determines how easily the fluids flow in the reservoir, thus it directly affects the production rate. Low vertical permeability, especially between injector and producer will hinder steam chamber development. High horizontal permeability helps the lateral spreading of steam chamber. In most laboratory experiments, the physical models are packed with glass beads or sand that give isotropic permeability (kv/kh = 1)

1.3.1.4 Bitumen viscosity Heavy oils and bitumen contain a higher fraction of asphaltenes; are highly viscous and sometimes immobile at reservoir condition. It is their high natural viscosity that makes the recovery of heavy oils and bitumen difficult. The oil drainage rate in SAGD under pseudo-steady-state conditions depends on the heated oil viscosity. However, the time required for establishing the communication between the injector and the producer depends largely on the original oil viscosity. When the original oil viscosity is lower and the oil is sufficiently mobile, the communication between the wells is no longer a hurdle. This opens up the possibility of increasing the distance between the two wells and introducing elements of steam flooding into the process.

1.3.1.5 Heterogeneity A significant concern in the development of the SAGD process is that of the possible effects of barriers to vertical flow within the reservoir. These may consist of significant sized shale layers or may be grain-sized barriers whose effect is reflected by a lower 12 vertical than horizontal permeability. In some situations, continuous and extensive shale barriers divide the reservoir and each sub-reservoir has to be drained separately. However, it is common to find layers of shale a few centimeters thick but of relatively limited horizontal length which do not divide the reservoir but make it necessary for fluids to meander around them if they are to flow vertically. It is important to note that the direction of flow is oblique, not vertical. It is the permeability in the direction of flow that determines the rate, not the vertical permeability [3]. Overall it appears that partial shale barriers can be tolerated by the process. In addition to the effect of limited extent shale barriers, it would be desirable to evaluate the effect of heterogeneity due to permeability difference in layers. In some cases the reservoir contains horizontal layers of different permeability, so there will be two cases: ¾ Low permeability on top of high permeability ¾ High permeability on top of low permeability

Beside the effect of shale barriers on vertical flow, their presence results in higher cSOR. Due to their presence in forms of non productive rock within the oil bearing zone, they will be heated as well as the oil sand. This extra heat which does not yield to any additional oil production will cause the cSOR to increase.

1.3.1.6 Wettability Wettability controls the distribution and flow of immiscible fluids in an oil reservoir and thus plays a key role in any oil-recovery process. Once thought to be a fixed property of each individual reservoir, it is now recognized that wettability can vary on both microscopic and macroscopic scales. The potential for asphaltenes to adsorb onto high energy mineral surfaces and thus to affect reservoir wettability has long been recognized. The effect of wettability on SAGD performance has not been adequately evaluated. However, it is apparent that the wettability will affect oil-water relative permeability and residual oil saturation which in turn would affect the gravity drainage of oil and ultimate recovery.

1.3.1.7 Water Leg Many heavy oil and oil sand reservoirs are in communication with water sand(s). Depending on the density (oAPI gravity) of oil, the water sand could lie above or below the oil zone. The presence of a bottom water layer has less an impact on recovery than the case where an overlying water layer is present. Steam flooding a heavy oil or oil sand reservoir with confined/unconfined water sand (water which may lie below or above the oil-bearing zone) is risky due to the possibility of short circuiting the oil-bearing zone. There is a major concern that the existence of thief zones such as top water will have detrimental effects on the oil recovery in (SAGD) process [3]. For underlying aquifers, if the steam chamber pressure is high enough and stand-off distance of the producer is selected correctly then intrusion of water may be prevented.

1.3.1.8 Gas Cap Some of the heavy oil reservoirs have overlying gas caps. Some SAGD studies have suggested that gas-cap production might “sterilize” the underlying bitumen [2]. Many such studies however, assumed rather thick continuous pays with high permeability, and considered a large gas-cap. So considering the case of a small gas-cap on top of the oil sand formation with different well configurations (including vertical injectors) would clarify the feasibility of SAGD projects in such reservoirs.

1.3.2 Well Design

1.3.2.1 Completion SAGD wells are completed with a sand control device in the horizontal section. Trials have been run with wire-wrapped screens, but most operators use slotted liners. Slotted liners are manufactured by cutting a series of longitudinal slots. The slot width is selected, based on the formation’s grain-size distribution, to restrict sand production and allow fluid inflow. Liner design requirements must balance sand retention, open fluid flow area and structural capacity. Larger liner which means larger intermediate casing and larger holes will reduce pressure drop, especially near the heel of injector. It must be decided which liner size would be optimum for the well.

1.3.2.2 Well configuration The most common well configuration for SAGD operation is to place a single horizontal injector directly above a single horizontal producer. The total number of wells in such a pattern is two with an injector-to-producer ratio of 1:1. Based on heavy oil reservoir oil viscosity (either mobile oil or bitumen) at reservoir condition, kv/kh, heterogeneity and other factors, it might be advantageous to place the injector and producer in other configurations than the base case of 5 m apart horizontal wells in the same vertical plane.

1.3.2.3 Well Pairs Spacing In the initial stage of SAGD, the upward rate of growth of the steam chamber would be larger than the rate of sideways growth. Eventually the upward growth is limited by the top of the reservoir, and the sideward growth then becomes critical. After a period of time the interfaces of different chambers intermingle and form a single steam layer above the oil. It would be beneficial to optimize the distance between well pairs, since smaller spacing would yield better SOR and recovery factor but the oil production would decline faster and more wells would be required.

1.3.2.4 Horizontal well length The main advantage of long horizontal well in thermal oil recovery is to improve sweep efficiency, enhance producible reserves, increase steam injectivity, and reduce number of wells needed for reservoir development. The longer well length would yield higher rates but causes higher pressure drop and it may require larger pipes and holes to accumulate the higher flow rates and to reduce the pressure drop. A sensitivity analysis must be done to determine the optimum length.

1.3.3 Operational Parameters

1.3.3.1 Pressure Operating pressure plays a significant role in the rate of recovery. Lower operating pressure reduces the SOR, reduces H2S production, may reduce the silica dissolution, and thereby, reduce the water treatment issues [5]. However, lower pressure operation increases the challenges in lifting the fluid to the surface. A low pressure SAGD operation may end up with a low recovery factor during the economic life of the project; 15 the remaining reserve may be lost forever, as it will be extremely unlikely that an additional SAGD project would be undertaken in the future to “rework” the property. On the other hand, a bitumen deposit which is below the current economic threshold may well become an attractive prospect in the future with advances in technology, simply because it remains intact. Higher steam pressure will cause greater dilation of sandstone, thereby increasing effective reservoir porosity which, in turn it is predicted, will have the result of significantly improving projected SAGD recoveries. It may be beneficial to accelerate the start-up and initial steam chamber development and provide sufficient pressure to lift production fluid to surface.

1.3.3.2 Temperature At the lower steam temperature, which is related to the pressure, the sand matrix is heated to a lower temperature and the energy requirement for heating the reservoir goes down. Conceptually this should lead to a lower steam oil ratio. However, the lower temperature would increase the heated oil viscosity and reduce the oil drainage rate, thereby increasing the project time span. This will increase the time available for heat loss to the overburden and may partially or totally negate the reduced heat requirements. Although the steam temperature is often determined by the prevailing reservoir pressure, in situations where operating flexibility exists, the optimum temperature needs to be determined. When a non-condensable gas is injected with the steam, the pressure can be increased above the saturation pressure of steam by adding more gas.

1.3.3.3 Pressure Difference between Injector and Producer Once the reservoir between the two wells is sufficiently heated and bitumen mobility is evident, a pressure differential is applied between the wells. The risk in applying this pressure differential is creating a preferential flow path between wells which results in the inefficient utilization of energy and may damage the production linear. Determining when to induce this pressure differential and how much pressure differential to apply is critical to overall optimization of the process.

1.3.3.4 Subcool (Steam-trap control) The steam circulation is aimed at establishment of the connectivity between injector and producer. Once the communication between the wells is achieved the SAGD process 16 is switched into the normal injection-production process. Over this period, the steam may break into the producer and by-pass the heated bitumen. In order to decrease the risk of such steam breakthrough, a back pressure is imposed on the production well which creates level of liquid above the production well which is called subcool. The subcool can be either high or low pressure. In the high pressure subcool, the liquid level decreases while in the low pressure one it increases. In a field project the sucool varies between high and low pressures at different time periods. Optimization of the subcool amount and implementation time frame requires intensive investigations.

1.3.3.5 Steam Additives In SAGD process addition of hydrocarbon solvents for mobility control may play an important role. Components of hydrocarbon solvents based on their PVT behavior may penetrate into immobile bitumen beyond the thermal boundary layer. This provides additional decrease in viscosity due to dilution with lighter hydrocarbons in that zone. Different solvent mixtures with varying compositions can be employed for achieving enhancement in SAGD recovery.

1.3.3.6 Non-Condensable Gas In the practical application of SAGD process, the steam within the steam chamber can be expected to contain non-condensable gases; methane and carbon dioxide. Carbon dioxide is often found in the produced gas from thermal-recovery projects and its source is thought to be largely from the rocks within the chamber. The small amounts of non- condensable gas can be beneficial because the gases accumulate at the top edges of the steam chamber and restrict the rate of the heat loss to the overburden [3]. The non- condensable gases may not increase the ultimate recovery but will decrease the SOR. However, presence of too much non-condensable gas can reduce the steam chamber temperature and interfere in the heat transfer process at the edge of the chamber.

1.3.3.7 Wind down The last stage for SAGD operation is wind down. It can be done by either low quality steam or some non condensable gases. Based on field experiences it was proposed to use low quality steam. In order to find the level of this low quality some sensitivity analysis 17 must be done to find the best time for applying the wind down and also the possibility of adding some non condensable gases.

1.4 Objectives Since mid 1980’s, SAGD process feasibility has been field tested in many successful pilots and subsequently through several commercial projects in various bitumen and heavy oil reservoirs. Although SAGD has been demonstrated to be technically successful and economically viable, it still remains very energy intensive, extremely sensitive to geological and operational conditions, and an expensive oil recovery mechanism. A comprehensive qualitative understanding of the parameters affecting SAGD performance was provided in the previous section. Well configuration is one of the major factors which require greater consideration for process optimization. Over the 20 years of SAGD experience, the only well configuration that has been extensively field tested is the standard 1:1 configuration, which has a horizontal injector lying approximately 5 meters above a horizontal producer. The main objective of this study is to evaluate the effect of well configuration on SAGD performance and develop a methodology for optimizing the well configurations for different reservoir characteristics. The role of well configuration in determining the performance of SAGD operations was investigated with help of numerical and physical models. Numerical modeling was carried out using a commercial fully implicit thermal reservoir simulator; Computer Modeling Group (CMG) STARS. The wellbore modeling was utilized to account for frictional pressure drop and heat losses along the wellbore. A 3-D physical model was designed based on the available dimensional analysis for a SAGD type of recovery mechanism. Physical model experiments were carried out in the 3-D model. With this new model, novel well configurations were tested. 1. The most common well configuration for SAGD operation is 1:1 ratio pattern in which a single horizontal injector is drilled directly above a single horizontal producer. However, depending on the reservoir and oil properties it might be advantageous to drill several horizontal/vertical wells at different levels of the reservoir i.e. employ other configurations than the base case one to enhance the drainage efficiency. In this study, three types of bitumen and heavy oil reservoirs 18

in Alberta; Athabasca, Cold Lake, and Lloydminster were considered for evaluating the effects of well configuration. For example, in heavy oil reservoirs containing mobile oil at the reservoir condition, it may be advantageous to use an offset between injector and producer. Figure 1-5 presents some of the modified well configurations that can be used in SAGD operations. These well configurations need to be matched with specific reservoir characteristics for the optimum performance. None of them would be applicable to all reservoirs. The aim of this research was to investigate the conditions under which one or more of these well configurations would give improved performance. When two parallel horizontal wells are employed in SAGD, the relevant configuration parameters are: (a) height of the producer above the base of the reservoir; (b) the vertical distance between the producer and the injector; and (c) the horizontal separation between the two wells, which is zero in the base case configuration; (d) well length of well-pairs. The effects of these parameters in different types of reservoirs were evaluated with numerical simulation and some of the optimized configurations were tested in the 3-D physical model. 2. Hybrids of vertical and horizontal well pairs were also evaluated to see the potentials of bringing down the cost by using existing vertical wells. 3. The most promising well patterns would be experimentally evaluated in the 3-D physical model. 4. The results of physical model experiments will be history matched with reservoir simulators to validate the simulations and to extend the simulations to the field scale for performance predictions.

Injector Injector Injectors Produce

Producer Producer

Basic Well Configuration Reversed Horizontal Injector

Injectors Multi Lateral Producer, Top View

Injector

Injector Producer Producer Producer

C-SAGD Vertical Injector Inclined Injector

Figure 1-6 Various well configurations

1.5 Dissertation Structure This study comprised seven chapters of which Chapter 1 describes the basic concepts of SAGD process, a review on dimensional analysis for SAGD, explanation of effective parameters on SAGD, and eventually the research objectives. Chapter two provides a general review on previous researches on SAGD. This includes both numerical and experimental studies achieved to evaluate SAGD. In addition, extensive literature reviews of proposed well configuration in SAGD process are provided. Most of commercial SAGD projects in three reservoirs of Athabasca, Cold Lake, and Lloydminster are described in chapter two as well. In Chapter three, a simple geological description of Athabasca, Cold Lake, and Lloydminster reservoirs is provided. The sequence and description of different formation for each reservoir is explained and their properties such as porosity, permeability, and oil saturation are provided. The target formations of most commercial projects are referred. In Chapter four, the experimental apparatus which comprised several components such as steam generator, data acquisition, temperature probes, and physical model is well described. The pre/post experimental analysis was achieved in series of equipments such as permeability measurement apparatus, viscometer, and dean stark distillation. Each equipment was described briefly. The experimental methods and procedures are explained in this chapter as well. Chapter five discusses the numerical simulation studies conducted to optimize the well configuration for Athabasca, Cold Lake, and Lloydminster reservoirs. The well 20 constraints, operating condition, and input data such as description of the geological models and PVT data for each reservoir are presented. This chapter outlines the comparison of different well patterns results with the base case results for each reservoir. Based on the RF and cSOR results, some new well patterns are recommended for each reservoir. Chapter six comprises the presentation and discussion of the experimental results. Three sets of well patterns are examined for Athabasca and Cold Lake type of reservoir. Each well pattern is compared against the basic SAGD pattern. The results of each experiment are analysed and described in detail. Eventually each test was history matched using CMG-STARS. Chapter seven summarizes the contribution and conclusions of this research in optimizing the SAGD process under new well configuration both numerically and experimentally. Some future recommendations and research areas are provided in this chapter as well.

CHAPTER 2 LITERATURE REVIEW

2.1 General Review Thermal recovery processes involves several mechanisms such as: a) reduction of the fluid viscosity, resistance against the flow, via introducing heat in the reservoir; b) distillation/cracking of heavy components into lighter fractions. Since distillation and cracking requires specific conditions such as high temperature at low pressures or super high temperature at high pressures, therefore the dominant mechanism in thermal recovery methods is viscosity reduction. In thermal techniques, steam, fire or electricity are employed to heat the oil and reservoir. Among all fluids, water is abundant and has exceptionally high latent heat of vaporization which makes it the best heat carrier for thermal purposes. Therefore, within all thermal methods, steam based recovery methods have become the most efficient for exploiting bitumen and heavy oil. At the same time, steam mobility is also very high. Consequently, combining the gravitational force and mobility difference of bitumen and steam, would cause the steam to easily penetrate, rise into, and override within the reservoir. These characteristics are taken advantage of in the SAGD process. In fact, using horizontal well-pairs in SAGD causes the steam chamber to expand gradually and drain the heated oil and steam condensate from a very large area, even though the well- pairs are drilled in the vicinity of each other and the chance of steam breakthrough in the production well is high. SAGD’s efficiency has been compared to the prior field-tested thermal methods such as steam flood or CSS. In steam flooding, as a result of steam and crude oil density difference, the lighter steam tends to override and it can breakthrough too early in the process. However, being a gravity drainage process, SAGD overcomes this limitation of steam flooding. SAGD offers specific advantages over the rest of thermal methods: a) Smooth and gradual fluid flow: Unlike the steam flood and CSS less oil will be left behind, b) No steam override or fingering, c) Moderate heat loss which yields higher energy efficiency, d) Possibility of production at shallow depths, e) Stable gravitational flow f) Production of heated oil at high rates resulting in faster payout time.

Since the 1980‘s the use of shovels and trucks have dominated tar sands mining operations [2]. Using strip mining is still economical for the deposits that are close to surface but the major part of the oil sand deposits is too deep to strip mine. As the depth of deposit increases, using thermal and non-thermal in situ recovery methods becomes vital. SAGD was first developed by Butler et al [2]. A mathematical model was proposed to predict the production of SAGD based on a steady state assumption. Through years of experiments and field pilot applications the understanding of SAGD process has been greatly broadened and deepened. Butler further estimated the shape of the steam chamber. During the early stage of steam chamber growth, the upward motion of the interface is in the form of steam fingers with oil draining around them while subsequently the lateral and downward movement of the interface takes a more stable form [6]. Alberta Oil Sands have seen over 30 years of SAGD applications and numerous numerical and experimental studies have been conducted to evaluate the performance of SAGD process under different conditions. The experimental models used in laboratory studies were mostly 2-D models. Chung and Butler examined geometrical effect of steam injection on SAGD; two scenarios (spreading steam chamber and rising steam chamber) were established to elucidate the geometrical effect of steam injection on water/oil emulsion formation in the SAGD process [7]. Zhou et al. conducted different experiments on evaluation of horizontal/vertical well configuration in a scaled model of two vertical wells and four horizontal well for a high viscosity oil (11,000 cp). The main objective was to compare the feasibility of steam flood and SAGD in a high mobility reservoir. The results showed that a horizontal well- pair steam flood is more suitable than a classic SAGD [8]. Experiments and simulation were also carried out by Nasr and his colleagues [9]. A two-dimensional scaled gravity drainage experiment model was used to calibrate the simulator. The results obtained from simulation promoted insight into the effect of major parameters such as permeability, pressure difference between well pair, capillary pressure and heat losses on the performance of the process [9].

Chan [10] numerically modeled SAGD performance in presence of an overlying gas cap and an underlying aquifer. It was pointed out that the recovery in these situations may be reduced by up to 20-25% depending on the reservoir setting. Nasr and his colleagues ran different high pressure tests with and without naphtha as an additive. Steam circulation was eliminated and two methods to enhance recovery were proposed as they believed steam circulation causes delay in oil production [11]. Sasaki [12, 13] reported an improved strategy to initialize the communication between the injector and producer. An optical-fiber scope with high resolution was used together with thermocouples to better observe the temperature distribution of the model. It was found that oil production rate increased with increasing vertical spacing, however, the initiation time of the start of production was postponed. A modified process was proposed to tackle this problem. Yuan et al. [14] investigated the impact of initial gas-to-oil ratio on SAGD performance. A numerical model was validated through history matching experimental tests and thereafter the numerical model was utilized for further study. Based on the results they could not conclude the exact impact of the gas presence. They stated that it mostly depends on reservoir conditions and operations. Different aspects of improving SAGD performance were discussed by Das. He

showed that low pressure has two advantages of lower H2S generation and less silica production but has a tendency to require artificial lift [5]. The start-up phase of the SAGD process was optimized using a fully coupled wellbore/reservoir simulator by Vanegas Prada et al. [15]. They conducted a series of sensitivity runs for evaluating the effects of steam circulation rate, tubing diameter, tubing insulation and bottom hole pressure for three different bitumen reservoirs; Athabasca, Cold Lake, and Peace River. The production profile in SAGD process consists of different steps such as: Circulation, Ramp-up, Plateau, and Wind-down. Li et al. [16] studied and attempted to optimize the ramp-up stage. The effect of steam injection pressure on ramp-up time and the associated geo-mechanical effect were investigated as well. The results demonstrated that the higher injection pressure would reduce the ramp-up period and consequently the contribution of the geo-mechanical effect in the ramp-up period would be greater [16].

Barillas et al. [17] studied the performance of the SAGD for a reservoir containing a zone of bottom water (aquifer). The effect of permeability barriers and vertical permeability on the cumulative oil was investigated. Their result was a bit unusual since they concluded that the lower kv/kh would increase the oil recovery factor [17]. Albahlani and Babadagli [18] provided an extensive literature review of the major studies including experimental and numerical as well as field experience of the SAGD process. They reviewed the SAGD steps and explained the role of geo-mechanical and operational effects [18]. The effects of various operational parameters on SAGD performance were discussed in the previous chapter. However, the geological (reservoir) characteristics and heterogeneities play the most significant role in recovery process performance. While every single reservoir property has a specific impact on SAGD process, heterogeneity is the most critical aspect of the reservoir which has a direct effect on both injection and production behavior. Heterogeneity may consist of significant sized shale layers or may be grain-sized barriers whose effect is reflected by a lower vertical than horizontal permeability. A significant concern in the development of the SAGD process is that of the possible effects of barriers to vertical flow within the reservoir. Yang and Butler [19] conducted several experiments using heterogeneity in their physical model. Various scenarios such as: two layered reservoir; high permeability above low permeability and low permeability above high permeability, long horizontal barrier, short horizontal barrier and tilted barrier. The results demonstrated that in the two layered reservoir a faster production rate would be achieved when the high permeability layer is located above the low permeability zone. In addition they showed that the short horizontal barrier does not affect the process [19]. Chen and Kovscek [20] numerically studied the effect of heterogeneity on SAGD. A stochastic model in which the reservoir heterogeneity in the form of thin shale lenses was randomly distributed throughout the reservoir. Besides shale heterogeneity, effect of natural and hydraulic fractures was studied as well [20]. Several studies were conducted to evaluate the contribution of various parameters in the SAGD process. One of the parameters that control the SAGD performance is the well configurations. Over the life of SAGD, the only well configuration that has been field

tested is the standard 1:1 configuration, which has a horizontal injector lying approximately 5 meters above a horizontal producer in the same vertical plane. On the course of well configuration, some 2-D experimental and 3-D numerical simulations were conducted which mostly compared the efficiency of vertical vs. horizontal injectors. It seems that well configuration is an area that has not received enough attention. Chung and Butler tested two different well configurations; the first scheme used parallel wellbores while the second one used a vertical injector which was perforated near the top of the model. Figure 2-1 displays both schemes [6].

Figure 2-1 Chung and Butler Well Schemes [6].

Chan conducted a set of numerical simulations including the standard SAGD well configuration as displayed in Figure 2-2A. He captured additional recovery up to 10-15% in offsetting the producer from injector. The staggered well pattern provided the best results within all the proposed configurations in terms of RF. Increasing drawdown or fluid withdrawal rate could also enhance oil recovery of SAGD process under those conditions [9]. Joshi studied the thermally aided gravity drainage process by laboratory experiments. He investigated SAGD performance for three different well configurations: 1) a horizontal well pair, 2) a vertical injector and a horizontal producer, and 3) a vertical well pair. Figure 2-2B presents the schematic of the well patterns. The maximum oil recovery

27 was observed in the horizontal well pair. It was also shown that certain vertical fracture may help the gravity drainage process, especially at the initial stage, as the fracture gave a higher OSR than the uniform pack [21].

Top of Formation Conventional Offset Staggered

Injector

Producer

Base of Formation

Figure 2-2A Well Placement Schematic by Chan [9].

Figure 2-2B Joshi’s well pattern [20]. Leibe and Butler applied vertical injectors for three types of production wells; vertical, horizontal and planar horizontal. Effect of well type, steam pressure and oil properties were studied [22]. Nasr et al [10] conducted a series of experimental well configuration optimization. Figure 2-3 displays a summary of their studied patterns. Their objective was to combine an existing/newly drilled vertical well with the new SAGD well-pairs. The experiments were conducted in a 2-D scaled visual model and total of 5 tests were achieved. The combined paired horizontal plus vertical well was able to sweep the entire model, in fact chamber was growing vertically and horizontally. The vertical injector accelerated the communication between injector and producer. The RF was improved from 40% up to

60%. In addition, they showed that for a fixed length of horizontal injector, the longer producer would show better performance. [10].

Figure 2-3 Nasr’s Proposed Well Patterns [10].

The main goal of the industry has been to reduce the cost of SAGD operations which drives the need to create and test new well patterns. The Single well SAGD was introduced to use a single horizontal well for both injection and production. Figure 2-4 display the SW-SAGD well pattern. It was field tested primarily at Cold Lake area. Later on several studies were conducted to investigate and optimize SW-SAGD [23]. Luft et al [24] improved the process by introducing insulated concentric coiled tubing (ICCT) inside the well which would reduce the heat losses and was able to deliver high quality steam at the toe of the well. Falk et al [25] reviewed the success and feasibility of SW- SAGD and confirmed ICCT development. They reported the key pilot parameters and reviewed the early production data. Polikar et al [26] proposed a new theoretical configuration called Fast-SAGD. An offset well with the depth and length as the producer was horizontally drilled 50 meters away from the producer. The offset single well is operated under Cyclic Steam Stimulation mode. They found that the offset well would precipitate the chamber growth and increases the ultimate recovery factor. Shin and Polikar [27] focused on FAST-SAGD process and examined several more patterns as displayed in Figure 2-5. They confirmed the enhancement of SAGD via FAST-SAGD process. In addition they demonstrated that addition of two offset wells on

29 either sides of a SAGD well-pair would enhance the total performance by increasing the RF and decreasing the cSOR.

Figure 2-4 SW-SAGD well configuration [23].

Figure 2-5 SAGD and FAST-SAGD well configuration [27].

Further investigation of the effects of well pattern was done by Ehlig-Economides [28]. Inverted, multilevel, and sandwiched SAGD were simulated for the Bachaquero field in Venezuela (Figure 2-6). She included an extra producer in the new well schemes of multilevel and sandwiched. The idea was to utilize and optimize the heat transfer to the reservoir. The results showed that a large spacing between injector and producer is beneficial and the available excess heat in the reservoir can be captured through extra producer.

Figure 2-6 Well Pattern Schematic by Ehlig-Economides [28].

Stalder introduced a well configuration called Cross-SAGD (XSAGD) for low pressure SAGD. The proposed pattern is displayed in Figure 2-7. The main idea is to solve the limitation in oil drawdown due to steam trap control which originates from the small spacing between injector and producer. The injectors are located several meters above the producers but they are perpendicular to each other. The main concept behind this well configuration is to move the injection and production point laterally once the communication between injector and producer has been established. In order to improve the oil rate and obtain thermal efficiency, the section of the wells close to the crossing points requires to be either restricted from the beginning or needs to be plugged later on. The XSAGD results were much more promising at lower pressures [29].

Figure 2-7 The Cross-SAGD (XSAGD) Pattern [29].

Gates et al. [30] proposed JAGD scheme for the reservoirs with vertical viscosity variation. The injector is a simple horizontal wellbore located at the top of the formation, but the producer is designed to be J-shaped to access all the reservoir heterogeneity. They proposed that the heel of the producer needs to be in vicinity of the base of the net pay while the toe has to be several meters below the injector’s toe. Figure 2-8 displays the JAGD well configuration schematic. Initially, the injector would be used for just cold production, thereafter it is converted to the thermal process while the cold production has no more economical benefits. Gates et al. conducted a series of numerical simulations and believed that the thermal efficiency of JAGD is beneficially higher than the normal SAGD for the selected reservoirs.

Figure 2-8 The JAGD Pattern [30].

In 2006, a SAGD pilot was started in Russia introducing a new well configuration called U-shaped horizontal wells which is displayed in Figure 2-9. The pilot contained three well pairs with the length of 200-400m. The well pairs were drilled into the formation primarily vertically down to the heel, then followed the horizontal section, and eventually drilled up to the surface at the toe. The vertical distance between the well pairs is 5m. It was shown that the U-Shaped wellbores will effectively displace the oil for the complex reservoir with the SOR of 3.2 t/t [31].

Figure 2-9 U-Shaped horizontal wells pattern [31]. Bashbush and Pina [32] designed Non-Parallel SAGD well pairs for the warm heavy oil reservoirs. Two cases with azimuth variation were compared against the basic SAGD well configuration. The first case named as Farthest Azimuthal, in which the injector was drilled upward from heel to toe. The second case was called as Cross Azimuth, in which the heels of producer and injector are 6’ apart in one direction and the toes are 14’ apart in the other direction. Both cases are presented in Figure 2-10. Based on the presented results none of the new patterns were able to improve the SAGD performance and the recovery of basic SAGD was more impressive and successful.

Figure 2-10 The Schematic of well patterns proposed by Bashbush and Pina [32].

Since the main objective of this study is to evaluate the effect of well configuration on SAGD performance for three bitumen and heavy oil reserved of Alberta; Athabasca, Cold Lake, and Lloydminster, it would be beneficial to review the existing pilot and commercial SAGD projects in these reservoirs.

2.2 Athabasca SAGD has been field tested in many successful pilots and subsequently through several commercial projects in Athabasca-McMurray Formation. Currently the number of active SAGD pilot and commercial projects in Athabasca is quite large. Figure 2-11 presents an overview of SAGD projects in Athabasca. The Underground Test Facility (UTF) was the first successful SAGD field test project which was initiated by AOSTRA at 40 km northwest of Fort Mc-Murray [34, 35]. The test consisted of multiple phases; “Phase A” was meant to be just a case study to validate the SAGD physical process, “Phase B” was aimed at the commercial feasibility of SAGD process, “Phase D” tested horizontal drilling from surface which was not completely successful. The pilot was operated until 2004 with the ultimate recovery of approximately 65% and cSOR of 2.4 m3/m3. Since then SAGD has been applied in various pilot and commercial projects in Athabasca. CENOVUS (Encana) is currently running the largest commercial SAGD project in Canada. The Foster Creek project started as a pilot with 4 well pairs in 1997, and then expanded to 28 well-pairs in 2001. Currently it consists of more than 160 well pairs and is producing over 100,000 bbl/d. The pay zone is located at 450 m depth and the target formation is Wabiskaw-McMurray. [36]. JACOS started its own SAGD project in Hangingstone using 2 well pairs in 1999 [37, 38]. Due to the success of primary pilot, the project was expanded to 17 well pairs in 2008. Currently they are producing 10,000 bbl/d. The project is producing from Wabiskaw-MacMurray which has 280-310 m depth [39]. One of the best existing SAGD project with respect to its cSOR appears to be the MacKay River (currently owned by Suncor) with the average cumulative SOR of 2.5 m3/m3. This project was started with 25 well pairs in 2002, steam circulation started in September 2002, thereafter the production commenced in November 2002. Later, 16 additional well pairs were added in 2005/2006. This project is also producing from Wabiskaw-McMurray formation which is located 150m below the surface [40, 41]. Encana (now CENOVUS) started a 6 well-pairs pilot SAGD at Phase-1 Christina Lake in 2002/2003. Christina Lake has the lowest cSOR which is equal to 2.1 m3/m3.

Currently, MEG Energy is also running SAGD at Christina Lake. The net pay which is Wabiskaw-McMurray is located at ~ 400m depth [42, 43, and 44]. ConocoPhilips started their SAGD operation with a 3-well-pairs pilot project at Surmont in 2004. Two of these well pairs contain 350 m long slotted liners while the third well contains a 700 m long slotted liner. The commercial SAGD at Surmont started steam injection in June 2007 and oil production later on in Ocotber. Currently Surmont is operated by ConcoPhilips Canada on behalf of its 50% partner Total E&P Canada. The reservoir depth is ~400 m and the formation is Wabiskaw-McMurray [45, 46, and 47].

Figure 2-11 Athabasca Oil Sand’s Projects. [33] Suncor is also a leader in SAGD operations, currently running the Firebag with 40 well-pairs and the MacKay River project mentioned earlier. The first steam injection in the Firebag project commenced in September 2003 and the first oil production was in January 2004 [48]. The average daily bitumen production rate is 48,400 bbl/day with the cSOR of 3.14 m3/m3. However the current capacity is 95,000 bbl/d. The shallowest SAGD operation started in North Athabasca which had 90-100m depth. The Joslyn pilot project started with a well-pair and steam circulation in April 2004. While the Phase II of the project was ongoing, a well blowout occurred in May 2006. Currently there is no injection-production in that area [49].

A 65/35 joint venture of Nexen and OPTI Canada (now CNOOC Canada), phase 1 of the Long Lake Project, is the most unique SAGD project in Athabasca area. The Long Lake project is connected to an on-site upgrader. The project involved three horizontal well pairs at varied length from 800-1000 m, 150 m well spacing. Phase 1 of the project is currently operational with a full capacity of 70,000 b/d operation that will extract crude oil from 81 SAGD well-pairs and covert it into premium synthetic crude oil [50, 51]. Devon started its Jackfish SAGD project in Athabasca drilling 24 well-pairs in 4 pads in 2006 at a depth of 350m. The target formation was Wabiskaw-McMurray. First steam injection commenced in 2007. The project capacity was designed for 35,000 bbl/d. Currenlty the average cSOR is 2.4 m3/m3. The second phase of Jackfish project construction was started in 2008 and it is identical to the first phase of Jackfish 1 [52, 53].

2.3 Cold Lake Cyclic Steam Stimulation (CSS) is the main commercial thermal recovery method employed in the Cold Lake area. Currently the largest thermal project across Canada is the CSS operated by Imperial Oil. However, CSS has its own limitations, which point to application of SAGD at Cold Lake. More recently, Steam-Assisted Gravity Drainage (SAGD) has been field tested in number of pilot projects at Cold Lake. The first SAGD pilot at Cold Lake area was Wolf Lake project. Amoco started the project in 1993 by introducing one 825 m horizontal well-pair in Clearwater Formation. The high cSOR and low RF of first three years operation forced Amoco to change the project into a CSS process [54, 55]. Suncor proposed Burnt Lake SAGD project with the target zone of Clearwater Formation in 1990 and the operation was started in 1996. Later, Canadian Natural Resources Limited (CNRL) acquired the operation of Burnt Lake in 2000. It consists of three well-pairs of 700 -1000m well length. The reported cSOR and RF till end of 2009 were 3.9 m3/m3 and 47.9% respectively [55, 56]. The Hilda Lake pilot SAGD project was commenced by BlackRock in 1997. Two 1000 m well-pairs were drilled in the Clearwater Formation. The operation was acquired by Shell in 2007. The cSOR and RF at the end of 2009 were 3.5 m3/m3 and 35% [57].

Amoco started its second SAGD pilot project in 1998 in Cold Lake area. The pilot included just one well pair of 600 m length which was drilled in Clearwater Formation. The Pilot was on operation for two years and due to high cSOR and low RF of the project was turned into a CSS process [54]. Orion is a commercial project located in Cold Lake area producing from Clearwater Formations. Shell has drilled total of 22 well pairs with the average well length of 750m. However, only 21 of them are on steam. The first steam injection commenced in 2008. The cSOR is high due to early time of the project, and the reported RF is 6-7% [54]. Husky established its own commercial SAGD at Cold Lake, where the drilling of 32 well-pairs was completed in second half of 2006. The well-pairs have approximately 700m length. The Tucker project aimed at producing from Clearwater formation with a depth of ~400m. First steam injection was initiated in November 2006. Eight more well- pairs were appended to the project in 2010. The cSOR to end of May 2010 was above 10 m3/m3 while the RF is below 5% [58]. Although SAGD has been demonstrated to be technically successful and economically viable, questions remain regarding SAGD performance compared to CSS. A more comprehensive understanding of the parameters affecting SAGD performance in the Cold Lake area is required. Well configuration is one of the major factors which require greater consideration for process optimization. Nevertheless, the only well configuration that has been field tested is the standard 1:1 configuration.

2.4 Lloydminster The Lloydminster area, which is located in east-central Alberta and west-central Saskatchewan, contains huge quantities of heavy oil. The reservoirs are mostly complex and thin and comprise vast viscosity range. The peculiar characteristics of the Lloydminster deposits containing heavy oil make almost every single production techniques such as primary, waterflood, CSS and steam-flood uneconomic and inefficient. In fact the highly viscous oil, coupled with the fine-grained, unconsolidated sandstone reservoirs, result in huge rates of sand production with oil. Although these techniques may work to some extend, the recovery factors remain low (5% to 15%) and large volumes of oil are left unrecovered when these methods have been exhausted.

Because of the large quantities of sand production, many of these reservoirs end up with a network of wormholes that makes most of the displacement type enhanced oil recovery techniques unsuitable. Among the applicable methods in Lloydminster area, SAGD has not received adequate attention. Husky's Aberfeldy steam drive pilot started in February 1981 with 43 well drills, out of which 7 wells were for steam injection. The pilot was on primary production for a couple of years and the target zone was the Sparky Sands at 520m depth [59]. CSS thermal recovery at Lloydminster began in 1981, when Husky started the Pikes Peak project. It developed the Waseka sand at the depth of 500 meters which is a fairly thick sand of higher than 10m pay. The project initially consisted of 11 producing wells. In 1984 the project was altered into steamflood since the inter-well communication was established. Later on, up to 2007 the project was expanded to 239 wells including 5 SAGD well-pairs. The project has become mature with the recovery factor of around 70 percent [59, 60]. The North Tangleflags reservoir contains fairly thick Lloydminster channel sand (about 30 meters thick). The reservoir quality, including porosity, permeability, and oil saturation, can be considered as superior. Despite the encouraging initial oil rate, primary production failed due to the high viscosity oil of 10,000 cp and water encroachment from the underlying bottom water. While the aquifer is only 5 metres compared to the oil zone thickness of 30 metres, the aquifer is quite strong and dominates primary production performance limiting primary recovery to only a few percent. In 1987, the operator, Sceptre Resources, constructed a SAGD pilot which included four vertical injectors and a horizontal producer. The steam injection inhibits water encroachment as well as reducing oil viscosity and this resulted in high recovery factor and low steam oil ratio. In 1990, a new horizontal well was added and performed the same manner as the existing one. The production well-pairs established an oil rate of as high as 200 m3/d [61]. The Senlac SAGD project was initiated in 1996 with Phase A. which consisted of three 500m well pairs. It is located 100 kilometers south of Lloydminster, Alberta, Canada. The target zone is the highly permeable channel sand of Dina/Cummings formation buried 750 m deep. Like other formations in the Lloydminster area, the pay zone is located above a layer of water. In 1997 an extra 450 m well-pair was added to the

38 pilot. Phase B was started in 1999 using three 500m well-pairs. The vertical and horizontal distance of the well-pairs is 5m and 135m respectively. Later on Phase C. including two 750m of well-pairs, was started up [62].

CHAPTER 3 GEOLOGICAL DESCRIPTION

3.1 Introduction Canada has the third largest hydrocarbon reserves after Venezuela and Saudi Arabia, containing 175 billion barrels of bitumen/heavy oil/crude oil. Currently, the industry extracts around 1.49 million barrels of bitumen per day [63]. Figure 3-1 displays a review of the bitumen resources and their basic reservoir properties.

Figure 3-1 Alberta’s bitumen resources estimate volume as of December 31, 2011 [64]. The huge reserves of bitumen and heavy oil in Alberta are found in variety of complex reservoirs. The proper selection of an in-situ recovery method, which would be suitable for a specific reservoir, requires an accurate reservoir description and understanding of the geological setting of the reservoir. In fact a good understanding of the geology is essential for overcoming the challenges and technological difficulties associated with in-situ oil sands development. Alberta has several types of hydrocarbon reserves but the major bitumen and heavy oil deposits are Athabasca, Cold Lake, Peace River, and Lloydminster. Figure 3-2 displays the location of the extensive bitumen and heavy oil reservoirs across Alberta and

Saskatchewan. The main deposits are in the Lower Cretaceous Mannville Group which is found running from Northeastern Alberta to Southwest Saskatchewan.

Figure 3-2 Bitumen and Heavy Oil deposit of Canada [65]. In this chapter, a brief review of the geological description associated with the three major oil sand and heavy oil reservoirs of Athabasca, Cold Lake and Lloydminster is presented.

3.2 Athabasca This section of the geology study covers the Athabasca Wabiskaw-McMurray oil sands deposit. Athabasca oil sands deposit is the largest petroleum accumulation in the world, covering an area of about 46,000 km2 [66]. In the Athabasca oil sand, most of the bitumen deposits are found within a single contiguous reservoir, the lower cretaceous McMurray-Wabiskaw interval. Alberta’s oil sands are early Cretaceous in age, which means that the sands that contain the bitumen were originally laid down about 100 million years ago [67]. The McMurray-Wabiskaw stratigraphic interval contains a significant quantity (up to 55%) of the province’s oil sands resources. Extensively drilled, studied and undergoing multi-billion dollar development, the geology of this reservoir is well understood in general, but still delivers geological surprises.

Both stratigraphic and structural elements are engaged in the trapping mechanisms of Athabasca deposit. The McMurray formation was deposited on the Devonian limestone surface in a north-south depression trend, along the eastern margin of the Athabasca oil- sands area. There is a structural dome in the Athabasca area which resulted from the regional dip of the formation to the west and the salt collapse in the east [68]. As displayed in Figure 3-3, most of the reserves in Athabasca area are located east of this anticline feature.

Figure 3-3 Distribution of pay zone on eastern margin of Athabasca [69].

The thickest bitumen within the Athabasca McMurray-Wabiskaw deposit is generally located in a north–south trending channel complex along the eastern portion of the Athabasca area. Figure 3-4 displays the pay thickness of McMurray-Wabiskaw in Athabasca area. This bitumen trend contains all existing and proposed SAGD projects in the Athabasca Oil Sands Area. Outside the area, the McMurray-Wabiskaw deposit

43 typically becomes thinner, channel sequences are less predominant, and the bitumen is generally not believed to be exploitable using SAGD or reasonably predictable thermal technologies. Within the area of concern, there is approximately 500 billion barrels of bitumen in-place in the McMurray-Wabiskaw.

Figure 3-4 Pay thickness of McMurray-Wabiskaw in the Athabasca Area [64].

As mentioned earlier, currently there are two available commercial production methods for the exploitation of bitumen out of McMurray-Wabiskaw Formations: either open-pit mining or in-situ methods. The surface mining is able to extract approximately 10 percent of the reserves and mostly from the reserves situated along the valley of the Athabasca River north of Fort McMurray. The Cretaceous Formation in Athabasca River has been eroded in a way that the oil sands are exposed in vicinity of the surface and provide access for the shovel and trucks. Figure 3-5 displays the cross view of the Cretaceous Formation in Athabasca River. The rest of the reserves are situated too deep

44 to provide access for the surface mining facilities and their recovery requires in-situ methods. However there are some deposits, with a buried depth of 80-150m, that are too deep for surface mining and too shallow for steam injection.

Figure 3-5 Athabasca cross section [69].

There is no official and formal classification for the stratigraphic nomenclature of the Athabasca deposit; however it has been developed based on experience. Generally the geologists divide the McMurray formation into three categories of Lower, Middle and Upper members. This simple scheme may be valid on a small scale, but when extended to a broader scale may no longer apply [70]. This historical nomenclature fails in some part of the McMurray Formation. In some areas, McMurray Formation just includes lower and upper members while in other parts of McMurray only middle and upper members exist. The McMurray Formation is overlain by the Wabiskaw member of the Clearwater Formation which is dominantly marine shale and sandstone. The Clearwater itself is located underneath the Grand Rapids Formation which is dominated by sandstone. Clearwater Formation acts as the cap rock for the McMurray reservoirs, which prevents

any fluid flow from McMurray formation to its overlaying formation or ground surface. The thickness of Clearwater formation varies between 15 to 150m [71]. The thickness and integrity of Clearwater formation is essential since it must be able to hold the steam pressure during the in-situ recovery operations. However for the part of Athabasca where the oil sand is shallow or the cap rock has low thickness special operating design such as pressure and steam temperature is required. Figure 3-3 displays a summarized description of the facies characteristics through the McMurray-Wabiskaw interval. The McMurray Formation is located on top of the Devonian Formation which is mostly shale and limestone.

Age Group Wabasca Athabasca

Grand Grand Rapids

Mannville Rapids

Upper Lower Cretaceous Clearwater Clearwater

Wabiskaw Wabiskaw

Mannville

Lower McMurray McMurray

Mainly Sand Bitumen Saturated Sand

Figure 3-6 Correlation chart of Lower Cretaceous bitumen deposits at Athabasca Oil Sand. The Lower McMurray has good petro-physical properties; it has high porosity and permeability. It mostly contains the bottom water in Athabasca area but in some specific regions it comprises sand-dominated channel-and-bar complexes [69]. The maximum thickness of this member is up to 75m which is composed of mostly water-bearing sand and is located above a layer of shale and coal. The grain size in the lower member is coarser than the other two members [68, 72].

The Middle Member may have 15-30 m of rich oil-bearing sand and in some specific areas it can even be up to 35 m. Thin shale breaks are present while coal zone is absent in the Middle McMurray. The interface of Lower and Middle member is somewhere sharp but it can be gradual as well. In some specific areas of Athabasca the Middle member channels penetrated into the Lower McMurray sediments deeply. The upward-fining in the Middle Member is typical [68, 72]. The richest bitumen reserve among Athabasca deposit belongs to the Upper McMurray member. The Upper McMurray’s channel sand thickness may be as high as 60 m with no lateral widespread shale discontinuity [69]. This member is overlain by Wabiskaw member of the Clearwater Formation. Thin coal, bioturbated sediments, very fine-grained, and small upward coarsening sequences are typical in the Upper Member [68]. The Upper McMurray has somewhat lower porosity, reduced permeability compared to Lower McMurray. The successful pilot and commercial schemes within the Upper McMurray include: the Dover UTF, MacKay River, Hangingstone, and Christina Lake. The Athabasca sands is comprise of approximately 95% quartz grains, 2 to 3% feldspar grains, and the rest is mostly clay and other minerals [67]. The Athabasca sands are very fine to fine-grained and moderately well sorted. Shale beds within the oil sands consist of silt and clay-sized material and only rarely contain significant amounts of oil. Less than 10 percent of the fines fraction is clay minerals [69]. Low clay content and lack of swelling clays, differentiates it from other deposits in Alberta [68]. The McMurray Formation mostly occurs at the depths of 0 to 500 m. The Athabasca oil sands deposit is extremely heterogeneous with respect to physical reservoir characteristics such as geometry, component distribution, porosity, permeability, etc. Several factors affect the petro-physical properties in Athabasca area and are attributed to high porosity and permeability of McMurray Formation compared to the other sandstones deposits: minimum sediment burial, early oil migration, lack of mineral cement in the oil sands which occupies the void space in porous media. The petro-physical properties of Athabasca are thought to have resulted from the depositional history of the sediments. However, the bitumen properties are strongly affected by post depositional factors [71]. The reservoir and bitumen properties have a distinctive lateral and vertical variation. It is

47 believed that the microbial degradations had a major effect on bitumen heterogeneity across the Athabasca which resulted in heavier petroleum with accompanying methane as a side product. At reservoir temperature (11 °C), bitumen is highly viscous and immobile. The bitumen density varies from 6 to 11º API with a viscosity higher than 1,000,000 cP. Viscosity can vary by an order of magnitude over 50 m vertical span and 1 km lateral distance. The single most fortunate characteristic feature of the Alberta oil sands is that the grains are strongly water-wet. However, lack of this characteristic would not allow the hot water/steam extraction process to work well. There are areas where basal aquifer with thickness of greater than 1 m are expected, however due to existence of an impermeable layer the oil-bearing zone is not always in direct contact with bottom water [69].

3.3 Cold Lake The Cold Lake oil-sands deposit has been recognized as a highly petroliferous region, covering approximately 23,800 km2 in east-central Alberta and containing over 250 billion barrels of bitumen in place; it has the second highest rank for volume of reserves in-place among the major oil sand areas in Canada [64]. The bitumen and heavy oil reserves at the Cold Lake area are contained in various sands of the Mannville Group of Lower Cretaceous age. Figure 3-7 and 3-8 present the correlation chart for Lower Cretaceous bitumen and heavy oil deposits at Cold Lake area. As displayed on Figure 3-7, Cold Lake is inimitable in comparison with Athabasca deposit; all the formations in Mannville Group are oil bearing zones. For this reason the Cold Lake area provides an ideal condition for various recovery method applications. At Cold Lake the Mannville Group comprises the Grand Rapids, Clearwater and McMurray Formations. Unlike the Athabasca Oil Sands, more reserves belong to the Grand Rapids and Clearwater Formations than the McMurray. Currently the main target of industry at Cold Lake area is Clearwater Formation. Although the Grand Rapids has higher saturation, it is considered a future prospective target zone. The Mannville Group is overlain by the marine shale of the Colorado Group [73]. At Cold Lake area the

Mannville sands are unconsolidated and the reservoir properties vary significantly over the areal extension.

Figure 3-7 Oil Sands at Cold Lake area [73].

Age Group Cold Lake Athabasca

Upper Mannville Grand Grand Rapids Rapids

Lower Cretaceous

Clearwater

Wabiskaw

Lower Mannville

McMurray McMurray

Mainly Sand Bitumen Saturated Sand Shale

Figure 3-8 Correlation chart of Lower Cretaceous at Cold Lake area.

The Clearwater is an unconsolidated and oil-bearing formation. It is located on top of the McMurray section. The Clearwater is overlain by the Lower and Upper Grand Rapids Formation, which extends to the top of the Manville Group. The Formation quality is moderate and the thickness can be as high as 50 m [73]. At Clearwater Formation, only about 20% of the sand is quatz. The rest is feldspar (~28%), volcanics (23%), chert (~20%), and the rest is other minerologies [74, 75, and 76]. The reservoir continuity in horizontal direction is considered excellent but on the other hand there is vertical discontinuity in the forms of shale and tight cemented sands and siltstones which occurs irregularly. There are also many calcite concretions present. The petro-physical properties are considered excellent, with the average porosity being 30 to 35 %, and the average permeability in the order of multiple Darcies [75, 77]. Figure 3-9 displays the cross section of Clearwater Formation at Cold Lake area and the extension trend of the reserves in Alberta. In contrast to the massive sands of the Clearwater Formation, the oil bearing zone in the upper and lower members of the Grand Rapids Formation are thin and poorly developed [75]. In the Grand Rapids, heavy oil can be associated with both gas and water. The gas can exist in forms of solution gas and gas cap. Mostly the Upper Grand Rapids has high gas saturations and acts as the overlaying gas cap formation.

Fig 3-9 Clearwater Formation at Cold Lake area [75].

In the lower member of the Grand Rapids Formation, reservoirs contain thin sands with the interbedded shale; the sands thickness ranges from 4-7 m but at some specific zones the formation can be as thick as 15m. The bed continuity is in sheet form and considered as good but existence of occasional shale leads to poor reservoir continuity. The Lower Grand Rapid Formation has a fairly good continuity in both vertical and horizontal directions. Reservoir sands are fine to medium-grained and well sorted. Porosity can be as high as 35% while the permeability is in multi-Darcy range. [78]. Figure 3-10 demonstrates the extension and cross plot of Lower Grand Rapids Formation in Cold Lake area. The lower Grand Rapids Formation is saturated with higher viscosity bitumen and the solution gas is much lower than the Clearwater Formation [76]. This makes the Lower Grand Rapids a less desirable target zone for thermal applications. Another critical issue is that the formation is in contact with the water bearing sands. The Lower Grand Rapids formation has had a history of sand production problems due to its highly unconsolidated nature.

Fig 3-10 Lower Grand Rapids Formation at Cold Lake area [74].

In the upper member of the Grand Rapids Formation, reservoirs consist of mostly gas but in some regions the formation has oil bearing zone with the interbedded shale layers. The reservoirs are discontinuous with the average thickness of 6m. Shale layer interbeds are typical. The sands are poorly to well sorted with a fine to medium grain size. Porosity

51 is less than 35% and permeability is generally poor, due to high silt and clay content. [75]. Figure 3-11 displays the cross section of the Upper Grand Rapids Formation. The McMurray Formation at Cold Lake area has basal sand section, upper zone of thinner sand, and interbedded shale layers. The upper zone is generally oil-bearing sands while the basal sand is mostly water saturated zone [74]. Therefore the formation is formed of couple of single pay zones which offers the possibility of multi-zone completion. The McMurray Formation at Cold Lake area is over a layer of aquifer. The deposit is fairly thin with the maximum thickness of 9m. The lateral continuity of the formation is fairly good but the vertical communication suffers from interbedded shale layers. The sands are fine to medium grain size and moderately well sorted. The average porosity is 35%, which implies good permeability. [75]. Figure 3-12 presents the cross view of the McMurray Formation at Cold Lake area.

Fig 3-11 Upper Grand Rapids Formation at Cold Lake area [75].

Fig 3-12 McMurray Formation at Cold Lake area [75]. Most of Cold Lake thermal commercial operational target is Clearwater Formation which is mostly at the depth of about 450 m. The minimum depth to the first oil sand in Cold Lake area is ~300m. Grand Rapids Formation is a secondary thermal reservoir. At Clearwater the sands are thick, often greater than 40m, with a high net/gross thickness ratio. Porosity ranges from 30 to 35%, with oil saturations that average 70% PV. At the initial reservoir temperature of 13 °C, the oil viscosity is about 100,000 cp. It is ordinary to find layers of mud interbeds, shale, and clasts in Clearwater Formation. Existence of any clays or mud interbeds tends to significantly reduce the porosity of sediments, and consequently reducing permeability [77]. The major issue in SAGD application in Cold Lake area is the presence of heterogeneities of various forms. Generally the net pay at Cold Lake area is higher than the one in Athabasca. On the other hand, Cold Lake reservoirs contain lower viscosity, lower permeability, higher shale percentage, lower oil saturation and extensive gas over bitumen layers. The main production mechanism in Cold Lake area is Cyclic Steam Stimulation which has been the proven commercial recovery method since 1980’s. Steam is injected above formation fracture pressure and fractures are normally vertical oriented in a north east to southwest direction. However the CSS process has various geological and operational limitations which make its applications so limited. Unlike the CSS process this area is in its in infancy for the SAGD applications. Due to specific Cold Lake

53 reservoir properties, SAGD method was less attractive here than in Athabasca. A limited number of SAGD projects have been field tested in the Lower Grand Rapids and Clearwater Formations at Cold Lake area. The Burnt Lake (Shell) and Hilda Lake (Husky) were designed to produce bitumen from the Clearwater formation via the SAGD process. Later on, since CSS had discouraging results at Lower Grand Rapids in the Wolf Lake area due to extensive sand production, BP and CNRL replaced CSS with the SAGD. The results demonstrated promising behaviour.

3.4 Lloydminster Large quantity of heavy oil resources are present in variety of complex thin reservoirs in Lloydminster area which are situated in east-central Alberta and west-central Saskatchewan. The area has long been the focal point of heavy oil development. Figure 3-13 displays the latitude of Lloydminster area. The whole area covers about 324 townships or 29, 860 km2 [80]. The Lloydminster heavy oil sands are contained in the Mannville Group sediments which are early Cretaceous in age. The Lower Cretaceous contains both bitumen and heavy oil and has a discontinuous north-south trend which starts from Athabasca in the north passes through Cold Lake and ends up in the Lloydminster area [81]. At Lloydminster the entire Mannville Group is considered a target zone. Which is completely different from that which was characterized in Central Alberta. In the Lloydminster area, interbedded sandstones with layers of shale and mudstones are overlain by coals which occur repeatedly throughout the entire Mannvile Group [82, 83]. Thus the Mannville Group is a complex amalgamation sandstone, siltstone, shale and coal which are overlain by the marine shale sands of Colorado Group [80]. The sandstones are mostly unconsolidated with porous cross-beddings. The shale is generally bioturbated with a gray color which has acted as a hydrocarbon source rock [83]. In the Lloydminster area, the Mannville Group can be subdivided into groups of the Lower, Middle and Upper members. Each member informally comprises a number of formations. Different stratigraphic nomenclatures have been used in the Lloydminster heavy oil area. A summary of different subdivisions for the Mannville Group is presented in Figure 3-14.

Figure 3-13 Location of Lloydminster area [80].

There are some discrepancies in subdivision of the Mannville Group members because of drastic lateral changes in facies. Some geologists assign only Dina formation to the lower Mannville while others include Lloydminster and Cummings Formations as well. In this research the stratigraphic nomenclature which is presented on Figure 3-14 has been considered. As displayed on Figure 3-14 the Mannville group at Lloydminster area is subdivided into nine stratigraphic units. The Lower Mannville contains Dina Formation which is formed of thick and blocky sandstone. Its thickness can reach as high as 67 m. A layer of thick coal is located on top of Dina. This is the thickest coal in Manville Group at Lloydminster area which can be up to 4m thick.

Age Group Cold Lake Lloydminster

Colony Upper McLaren Grand Rapids Waseca

Lower Cretaceous Mannville Group Sparky GP Middle RL-Rex Clearwater Lloydminster

Cummings

Lower

McMurray Dina

Mainly Sand Heavy Oil Saturated Sand Shale

Figure 3-14 Correlation chart of Lower Cretaceous at Lloydminster area. The Dina Formation is corresponding to the McMurray Formation in the Lower Mannville Group of the Northern and Central Alberta basin [81]. It is both oil and a gas bearing zone but due to small reserve is not considered as a productive zone [84]. The sandstones are fine to medium-grained size and mainly well-sorted with some layers of coal and shale. The Middle Mannville consists of five distinct members; Cummings, Lloydminster, RL-Rex, General Petroleum (GP), and the Sparky. This member is comprised of narrow, Ribbon-Shaped sandstone, and shale layers [80]. The associated thickness for each single formation is approximately 6-9m and their range in width is about 1.6-6.4 km and in length is 15-32 km [85]. The Sparky sandstone is very fine to fine-grained, well sorted, coarsening upward with cycles of interbedded shale. A thin coaly unit or highly carbonaceous mudstone is usually present right at the top of Sparky unit [82]. The Sparky Member might have a thickness of up to 30m and usually with a 1m to 2m of mudstone. The length of the

56 channel sand could extend in order of tens of kilometers while its width would be in range of 0.3-2 km. The water saturation in higher part of the Sparky is about 20 percent whilst due to a transition zone in the lower part of Sparky the water saturation increases as high as 60 percent [85]. The permeability of the Sparky formation ranges between 500 to 2000 mD. GP Member with the maximum thickness of up to 18m thick (Average net pay of 6m) is located beneath the Sparky member and has a fairly constant recognizable thickness [86]. The sands of GP are mostly oil saturated, very fine-grained and well sorted. A layer of shale is situated beneath the oil stained sands of GP. The clean sand porosity of the GP usually exceeds 30 %. GP is less productive than Sparky. Rex Member can not be counted as a good pay among the Middle Mannvile Group. It included series of shale layers near the base of the formation and coal at the top. Its thickness may vary from 15-24m [87]. The Lloydminster is the most similar to the GP in terms of thickness and distribution. It consists of shale layers which are mostly gray with the very fine to fine grained sands. Thin layer of coal exists near the top of Lloydminster Formation. The sands are mostly oil stained but have high water saturation as well. The Cummings Member has a thickness of 12-48m containing highly interbedded light gray shale. Like the other members at Middle Mannville, the sandstone is ribbon shaped and mostly sheet sand stone (several tens of km2) [80]. It has both oil and gas saturations but it is not considered as commercially productive. Figure 3-15 clearly presents the distribution of Ribbon-Shaped Mannville group.

Figure 3-15 Distribution of Ribbon-Shaped Manville Group at Lloydminster area [80].

The Upper Mannville comprises Colony, McLaren, and Waseca Formation. This zone has the same sandstone distribution as in the Middle Mannville. The sandstones are discontinuous and sheet-like which have variable thickness and width but mostly in the range of 35 m and 300 m respectively [80]. Variable successions of coal layers are present throughout the Upper Member. The Upper Mannville has both oil and gas zones but the gas zone is situated in Alberta while the oil bearing horizons are mostly in the Saskatchewan side [87]. The Colony and McLaren are usually difficult to differentiate. Both are comprised of fine to very fine grained sandstone with the interbedded light gray shale and variable coal sequences [86, 88]. Their thickness can be as high as 61m while 6 m of that could be shale or coal. The oil and gas saturations are not commonly distributed over the entire area but these formations are mostly gas stained. However some local oil or gas stained deposits can be found as well. Waseca Formation follows the same trend as the members of Middle Mannville Group. It consists of two pays with the thickness of 3-6m which is separated by 1m thick

interbedded shale layer [87]. The lower part of Waseca Formation is oil saturated zone and has high quality with porosity of ranging from 30-35% and permeability of 5-10 Darcy’s. In the Lloydminster area the target formations have quite a range and unlike the Athabasca and Cold Lake area there is no specific and single pay for the current and future developments. However, most of the Mannville Group formations are situated at depth of about 450-500 m. The conventional oil ranges from heavy (<15° API) to medium gravity (up to 38° API) at reservoir temperature. The Mannville Group sands in general have quite a large range of the viscosity; the crude oil viscosity ranges from 500 to 20,000 cp at reservoir temperature of 22 °C. Water saturation varies between 10 to 20 percent. The porosity and permeability of most formations in Mannville Groups are 22-32 percent and 500-5000 mD respectively. The rocks are mostly water wet but in some specific areas they can be oil wet as well. The recovery mechanism in the study area is mostly primary depletion, which is principally by solution gas drive and gas cap expansion. The primary recovery has a low efficiency of about 8% due to high crude oil viscosity, low solution GOR, and low initial reservoir pressure. At the same time due to bottom water encroaching, high water cuts can be observed as well. However, numerous primary and secondary (mostly waterflood) projects are being implemented in the area. Figure 3-16 presents various active projects in the Lloydminster area. The reservoirs are mostly complex and thin with a wide range of oil viscosity. These characteristics of the Lloydminster reservoirs make most production techniques such as primary depletion, waterflood, CSS and steamflood relatively inefficient. The highly viscous oil, coupled with the fine-grained, unconsolidated sandstone reservoir, often result in huge rates of sand production with oil during primary depletion. Although these techniques may work to some extent, the recovery factors remain low (5% to 15%) and large volumes of oil are left unrecovered when these methods have been exhausted. Because of the large quantities of sand production, many of these reservoirs end up with a network of wormholes which make most of the displacement type enhanced oil recovery techniques inapplicable.

For heavy oil reservoirs containing oil with the viscosity smaller than 5000 cp, both SAGD and steam-flooding can be considered applicable for extraction of the heavy oil. Minimum reservoir thickness of at least 15 meters is likely required for SAGD to be applicable. In fact this type of reservoir provides more flexibility in designing the thermal recovery techniques as a result of their higher mobility and steam injectivity. Steam can be pushed and forced into the reservoir displacing the heavy oil and creating more space for the chamber to grow. There is considerable field experience available for developing such techniques: Aberfeldy steam drive pilot, CSS thermal recovery at Pikes Peak, North Tangleflags SAGD pilot project, and Senlac SAGD project.

Figure 3-16 Lloydminster area oil field [89]

3.5 Heterogeneity The Alberta’s oil sands deposits are extremely heterogeneous with respect to physical reservoir characteristics and fluid properties. Therefore, the recovery methods which depend on inter-well communication will suffer in Alberta deposits since the horizontal continuity is commonly poor. The reservoir heterogeneities have a deep impact in steam chamber development and the ultimate recovery of SAGD. In high quality reservoirs

60 which encounter no shale barrier or thief zones, the classic SAGD chamber would be in the form of inverted triangle pointing to the producer while for the poor quality reservoirs the form of steam chamber is more elliptical than triangle and will be driven by heterogeneities.

The feasibility of SAGD field implementation depends on various reservoir parameters such as reservoir geometry, horizontal and vertical permeability, depth, net- pay thickness, bottom water, overlaying gas cap, existence of shale barriers, component distribution, cap rock thickness, viscosity of bitumen, etc. Detailed characterization of above aspects is required to better understand the reservoir behaviour and reactivity at production conditions. SAGD performance depends directly on the presence or absence of these factors. In controlling SAGD performance, the following factors play critical roles; ¾ Horizontal continuity of cap rock ¾ Ease of establishing an efficient communication between Injector and Producer. ¾ Presence of any heterogeneity across the net pay and their lateral/longitudinal extension. ¾ Extent of shale along the wellbore ¾ Existence of bottom water or gas cap ¾ Presence of lean zones (thief zones) Both Lloydminster and Cold lake area have quite a thick and continuous cap rock laid over the pay zones. The horizontal continuity of cap rock within the McMurray Formation is relatively poor and in some regions there is no cap rock at all and if shallow enough the bitumen is extracted by surface mining. The shale heterogeneity is a minor issue at Athabasca while it creates serious concerns at Cold Lake and Lloydminster area. McMurray formation almost exhibits analogous characteristics over the Athabasca region, but some local heterogeneity also exists. There is no specific way to determine the extension of shale barriers in the oil sands deposits. The effect of shale presence on SAGD performance needs to be evaluated through numerical simulations. In addition to the shale barriers and cap rock continuity, water and gas zones have a deep impact in steam chamber development and the ultimate recovery. The bottom water

61 and gas cap thickness varies over few meters over the entire area of Alberta. Their impact on SAGD is variable and really depends on their thickness and extension over the entire net pay. In the McMurray, less gas cap and bottom water exists while at Cold Lake and Lloydminster and specifically at Lloydminster, there are few formations which are not in contact with gas or water zones.

CHAPTER 4 EXPERIMENTAL EQUIPMENT AND PROCEDURE

This chapter describes first the experimental equipment and second the experimental procedures used to collect and analyse the data presented. A consistent experimental procedure was kept throughout the tests. The equipment description is presented in three sections: a) viscosity and permeability measurement equipment, b) the equipment which comprised the physical model setup and c) sample analysis apparatus.

4.1 Experimental Apparatus The schematic of the SAGD physical model is presented in Figure 4-1.

Model Temperature

Steam

Water

Load Cell

Figure 4-1 Schematic of Experimental Set-up The model comprised several components including: a) Steam Generator, b) Data Acquisition System, c) Temperature Probes, and d) Physical Model.

4.1.1 3-D Physical Model Physical models have been assisting the development of improved understanding of complex processes, where analytical and numerical solutions require numerous simplifications. During the past decades, physical models have become a well-established

aid for improving the thermal recovery methods. The physical models for studying thermal recovery can be either in the form of partial (elemental) or fully scaled models. Due to the issues with respect to the handling, operating, and sampling of the thermal projects, usually elemental models have been incorporated to study the thermal processes. For the SAGD process, the scaling criteria proposed by Butler were used in this study to scale down the target reservoirs to the physical model size. Butler analysed the

dimensional similarity problem in SAGD and found that a dimensionless number B3 as given by the equation below must be the same in the field and the physical model [1].

k.g.h B3 = α.φ.ΔSo.m.υs The dimensional analysis includes some approximations and simplifications as well. Some parameters were excluded from the above dimensional analysis and consequently would be un-scaled between reservoir and physical model. These parameters are: rock- fluid properties such as relative permeability and capillary pressure and thermal expansion-compression, emulsification effect, and wellbore completion properties such as skin and perforation zones. There are several additional discrepancies such as operating condition, initial bitumen viscosity, and rock properties, between the physical model and the field. Therefore to conduct a reasonable dimensional analysis a few assumptions concerning the properties of the reservoir were considered, which are listed in Table 4-1. Table 4-1 Dimensional analysis parameters: field vs. physical. Parameter Physical Model Athabasca Cold Lake m 1.9 3.9 3.9 Permeability, D 300 3-5 3-5 Net pay, m 0.25 20 20 µs, cp 70 30 40 ρ, kg/m3 987 1000 1000 φΔSo 0.4 0.2 0.2 Wellbore length, m 0.5 500 500 Well-pair spacing, m 0.5 200 200

According to economical/simulation study conducted by Edmunds, the minimum net pay which can make a SAGD project feasible is 15m [90]. So a thickness of 20m was selected for both Cold Lake and Athabasca reservoirs. The viscosity of saturating

bitumen at injecting steam temperature is different between the physical model and field condition. The thermal diffusivity, α, was assumed to be equal in physical model and the field. The permeability of the packing sand for the physical model is selected to make the physical model dimensionally similar to the field. As per Table 4-1, in order to establish the dimensional similarity, it is necessary to select high permeable packing sand for the physical model comparing to the packing medium in field.

The well length and well-pair spacing has no effect on B3 value but they impact the physical model dimensions. The physical model designed for this study was a rectangular model which was fabricated from a fiber reinforced phenolic resin with dimensions of 50¯50¯25 cm in i, j, k directions. The physical model is schematically shown in Figure 4-2. 50 cm Physical Model Cavity

25 cm

50 cm

Figure 4-2 Physical model Schematic As a role of thumb, the minimum well spacing is twice the net pay. In designing the current physical model, the same rule was employed and the model width was selected as 50 cm. The 50 cm well length is a minimal arbitrary value that was selected so that the effect of well length on SAGD performance can be observed and at the same time the total weight of model (the box, 110 kg of sand, and 25 liter of oil) would be reasonable. As shown in Figure 4-3, the model was mounted on a 1.5 m stand to facilitate its handling. Two mounting shafts were incorporated at the side of the model to enable rotating the model by full 360 degrees. Most SAGD physical models described in the literature use one transparent side, which is usually made of Plexiglas. Since this model is designed to account for the longitudinal and lateral extension of chamber along a horizontal wellbore, no visual side

was incorporated. A total of 31 multi-point thermocouple probes, each providing 5 point measurements, were installed to track the steam chamber within the model. Figure 4-4 displays the location of the thermocouple probes in the model. Thermocouples were entered into the model from its back side and in 8 rows (A to G rows in Figure 4-4). Their location was selected in a staggered pattern to cover the entire model. The odd rows (A, C, E, and G) comprised 4 columns of thermocouples while the even rows (B, D, and F) have 5 columns of thermocouples. The thermocouples were connected to the Data Acquisition instrument, which provided the inputs for the LabView program to record and display the temperature profile within the model. The pressure of the model is somewhat arbitrary. It has an effect on the fluid viscosity, via its effect on the steam temperature, but the scaling does not dictate any pressure on the production side. The model used in this work was designed for low pressure operation and its rated maximum operating pressure was 100 kPa (gauge). The maximum steam injection pressure used in the experiments was about 40 kPag.

Figure 4-3 Physical Model.

G F E D C B 3" A 4"

Figure 4-4 Thermocouple location in Physical Model There are numerous reported studies of SAGD process using physical models but most of them use two-dimensional models, which ignore the effect of wellbore length in the chamber development. However, since this model can be considered a semi-scaled 3 D model, it is expected to provide more realistic and field representative results on the effects of well configuration.

4.1.2 Steam Generator A large pressure cooker was modified to serve as the steam generator. The pressure cooker was made of heavy cast aluminum with the internal capacity of approximately 28 litres. The vessel's inside diameter was 12.6 inches, the inside height was 14 inches and its empty weight was 29 lbs. A ½ inch line was connected to the opening for automatic pressure control, which eliminated the weight based pressure control. During the experiments, this outlet line was connected to the injector well of the physical model. Electrical heaters were installed in the pressure cooker to heat the water and convert it to steam. These electrical heaters were controlled by a temperature controller that maintained the desired steam temperature in the vessel. In addition, a pressure switch was installed in the power line that would cut off the power to the heaters if the pressure became higher than the safe limit. Finally the pressure cooker also contained a rupture disc that would have relieved the pressure if the internal pressure had become unsafe. The selective pressure regulator was designed to release excess steam at 18 lb of pressure. The steam generator was placed on top of a load cell to record the weight of the vessel and its contents. The decline in the weight provided a direct measure of the amount of steam injected into the physical model.

Figure 4-5 Pressure cooker 4.1.3 Temperature Probes The temperature measurements inside the physical model were made with 31 multi point (5 points per probe), 1/8 inch diameter, 23 inch length, type-T thermocouples. Figure 4-5 presents the specification of the multi-point thermocouples. PT.A PT.B PT.C PT.D PT.E 4.0” 8.5” 13.0”

17.5” 21.5” 23” Figure 4-6 Temperature Probe design

4.2 Data Acquisition A National Instruments data acquisition system was used to monitor and record the experimental data. These data included the temperatures sensed by a large number of thermocouples in the experimental set-up as well as the weight of the steam generator. A LabVIEW program was used to coordinate the timing and recording of the data.

4.3 Rock/Fluid Property Measurements

4.3.1 Permeability measurement apparatus A simple sand-pack apparatus was assembled to measure the permeability of the sand used in the physical model experiments. The apparatus comprised a low rate pump, a

69 differential pressure transducer, and a Plexiglass sand-pack holder (for high rates a stainless steel holder was used). The schematic of the apparatus is displayed in Figure 4 7. The main objective was to inject water at specific rates and measure the corresponding pressure difference across the sand pack. The permeability was determined using Darcy’s law, since the length and diameter of the sand pack was known.

24 cm 2.5 cm Figure 4-7 Permeability measurement apparatus

4.3.2 HAAKE Roto Viscometer The HAAKE RotoVisco 1 is a controlled rate (rotational) viscometer / rheometer, which is specifically, designed for quality control and viscosity measurements of fluids such as liquid hydrocarbons. It measures viscosity at defined shear rate or shear stress. The possible range of temperature that the HAAKE viscometer can handle is 5-85 ºC. Figure 4-8 displays the front view of the HAAKE viscometer. The viscometer used in this work offered a choice of 3 sensor rotors: Z31, Z38, and Z41 which are designed for high, middle and low viscosity fluids respectively. The amount of sample required for each sensor is different and the choice of sensor depends primarily on the viscosity of the fluid. The table 4-2 presents the specification for each sensor

Figure 4-8 HAAKE viscometer .Table 4-2 Cylinder Sensor System in HAAKE viscometer. Senor Z31 Z38 Z41 Rotor Material Titanium Titanium Titanium Radius, Ri, mm 15.72 19.01 20.71 +/- ΔRi, mm 0.002 0.004 0.004 Length, mm 55 55 55 +/- L, mm 0.03 0.03 0.03 Cup Material Steel Steel Steel Radius, Ra, mm 21.7 21.7 21.7 +/- ΔRa, mm 0.004 0.004 0.004 Sample Volume, cm3 52.0 33.0 14.0

4.3.3 Dean-Stark distillation apparatus Two types of samples were obtained from each experiment; 1) the samples which were in the form of water in oil emulsions and 2) the water-oil-sand samples in the form of core sample from the model. For separation of water from oil and water and oil from sand, the extraction method which uses the Dean-Stark distillation method was incorporated. The Dean-Stark apparatus consists of a heating mantle, round bottom flask, trap, and condenser as shown in Figure 4.9. The sample was mixed with toluene with the proportion of 2:1 and was poured in the flask. The sample was heated with the heating mantle for 24 hours. During the heating, vapors containing the water and toluene rise into the condenser where they condense on the walls of the condenser. Thereafter, the liquid droplets drip into the distilling trap. Since toluene and water are immiscible, they separate into two phases. When the top layer (which is toluene, being less dense than water) reaches the level of the side-arm it can flow back to the flask, while the bottom layer (which is water) remains in the trap. After 24 hours no more water exists in the form of emulsion in oil. It is important to drain the water layer from the Dean-Stark apparatus as needed to maintain room for trapping additional water. Since during each test, up to 60 samples were collected, a rack containing six units of Dean-Stark distillation set-ups were employed to speed up the analysis. These units were located in a fume hood. Extraction of water and oil from oil-water-sand mixture was conducted in the same Dean-Stark distillation apparatus with implementation of some minor changes. A Soxhlet was inserted on top of the flask. The mixture of water-oil-sand was placed inside a thimble which itself is placed inside the Soxhlet chamber. The rest of process is the same as the one expressed on Dean-Stark distillation process. The sand extraction apparatus is displayed on Figure 4-10.

Figure 4-9 Dean-Stark distillation apparatus

Figure 4-10 Sand extraction apparatus

4.4 Experimental procedure Each experiment consisted of four major steps: model preparation, running the experiment, analysis of the produced samples, cleaning. Prior to each experiment the load cell was calibrated to decrease the errors with respect to weight measurement of the steam generator.

4.4.1 Model Preparation The model preparation was achieved in a step-wise manner as follows: • Cleaning the physical model • Pressure testing the model • Packing the model • Evacuating the pore space of packed model • Saturating the model with water • Displacing the water with bitumen Prior to each experiment, the physical model was opened, the thermocouples were taken out and the whole set was cleaned. Thereafter, the model was assembled, the thermocouples were placed back into the model and the pressure test was conducted to make sure there was no leak in the model. Usually the model was left pressurized with gas for 12 hrs to make sure there was no pressure leak. Various fittings were incorporated in the model for the purpose of packing, bitumen saturation and future well placement. The ones for bitumen saturation had mesh on them while the other ones were fully open. At the next stage, the physical model was packed using clean silica sand. During packing the model was vibrated using a pneumatic shaker. During the vibration the model was held at several different angles to make sure that the packing was successful and no gap would be left behind and a homogenous packing was created. The packing and shaking process typically took 48 hours of work and about 120 kg of sand was required to fill the model. The next step was to evacuate the model to remove air from the pore space. The model was connected to a vacuum pump and evacuated for 12 hours. The model was disconnected from the vacuum pump and kept on vacuum for couple of hours to make

74 sure that it held the vacuum. If high vacuum was maintained, it was ready for saturating with water. The model was saturated with de-ionized water using a transfer vessel. The water vessel was filled with water, placed on a balance and was connected to the bottom of the model. Since the transfer vessel was placed at a higher level than the model, both pressure difference and gravity head forced the water to imbibe into the packed model. Approximately 21-22 kg water was required to fully saturate the model with water which was equal to the total pore volume of the model. The last stage is the drainage displacement of water with the bitumen. Two different bitumen samples were available and both of them were practically immobile at room temperature. The oil was placed in a transfer vessel which was wrapped with the heating tapes and was connected to a nitrogen vessel. The oil was warmed up to 50-60 ºC and was pushed into the model by gravity and pressurized nitrogen. The selected temperature was high enough that made the bitumen mobile and was low enough to prevent evaporation of the residual water Figure 4-11 displays bitumen saturation arrangement. A three point injection scheme was used with injection points at the top of the model. During the oil flood, the injection points started at the far end and were moved to the middle of the model after about 60 % of the expected water production had occurred and finally were directly on top of the production ports near the end of drainage. The displaced water was produced via three different valves and the relative amount of water produced from the two outer valves was monitored and kept close to each other by manipulating the openings of these TWO valves. This ensured uniform bitumen saturation throughout the model and specifically at the corners of the model. The displaced water was collected and the connate water and initial oil saturation were calculated. Approximately 18 kg of bitumen was placed in the model which took between two to three weeks of bitumen injection.

1: Pressure vessel wrapped 1 with heating tapes

2 2: Isolated transfer line

3 3: Connection valves

Bitumen flow direction

Figure 4-11 Bitumen saturation step 4.4.2 SAGD Experiment Each experiment was initiated by calibration of the load cell. A few hours before steam injection, the steam generator was filled with de-ionized water step by step (by adding weighed quantities of water) and the load cell reading was recorded. The steam generator was set to a desired temperature between 107-110 ºC. The steam transfer line which connected the steam generator to the model was wrapped with heating tape. The purpose was to ensure that high quality steam would be injected into the model and eliminate any steam condensation prior to the inlet point of the injector. The weight of the steam generator was recorded every minute. After the steam generator had reached the set point temperature, the injection valve was opened to let the steam flow into the model. The production valve was opened simultaneously. The produced oil and water samples were collected in glass jars.

Figure 4-12 Injection/Production and sampling stage The temperatures above the injection and production wells in the model were continuously monitored via LabView program. Once steam break-through occurred in the production well, steam trap control was achieved using back pressure via the production valve. This was confirmed by monitoring the temperature of the zone between producer and injector and ensuring that an adequate sub-cool (approximately 10 ºC) was present.

The produced fluid sampling bottle was changed every 20-30 minutes and each experiment took between 12 to 30 continuous hours to complete. Figure 4-12 shows the injection/production and sampling stage. At end of the test, the steam injection was stopped but the production was continued to get the amount of oil which could be produced from the stored heat energy in the model. Then the steam generator was shut off and the physical model was cooled down. After the model had completely cooled down, the thermocouples were taken out in 3 steps and 27 samples of sands were taken from the model from three different layers in the model. Figure 4-13 displays the bottom view of the mature SAGD model and the location of the sand samples in that layer.

7 8 9

4 5 6

1 2 3

Figure 4-13 Bottom layer of the model after SAGD experiment and the sampling points for sand analysis

4.4.3 Analysing samples Each sample bottle was weighed to obtain the weight of the produced sample. The sample analysis started with separation of water from oil in the Dean Stark set up. Each jar’s content was mixed with toluene and the whole mixture was placed in one single flask. 6 samples were analysed simultaneously using the six available Dean-Stark set ups. Each analysis took at least 12 hours. During the extraction, the collected water in the trap part of the set up was drained as needed to allow more water to be collected in the trap. Once the separation was completed the total amount of water produced from the sample was weighed and recorded. The amount of oil produced was determined from the difference between the total sample weight and the weight of water. This procedure was repeated for the all samples and eventually the cumulative oil and water production profile could be determined. This water-oil separation took about 10-15 days for each experiment. The next step was separation of water and oil from the collected sand samples. Since only 4 Soxhlet units were available, only four sets of separation could be run

78 simultaneously. The mixture was placed in the thimble and weighed. The thimble containing the sand sample was placed in the Soxhlet chamber. The evaporation and condensation of toluene washes the water and oil from the sand and eventually they will be condensed and the water collected in the trap. Once the thimble and sand were clean, it was taken out and dried. The amount of collected water was recorded and consequently the residual oil and water saturations could be determined.

4.4.4 Cleaning At the end of each run the entire set up including the physical model, the injector and producer, all fittings and valves, and connection lines were disassembled. The valves and fittings were soaked in a bucket of toluene while the wells and the physical model were washed with toluene.

CHAPTER 5

NUMERICAL RESERVOIR SIMULATION

This chapter discusses the numerical simulation studies conducted to optimize the well configuration in a SAGD process. These numerical studies were focused on three major reservoirs in Alberta as: Athabasca, Cold Lake, and Lloydminster. The description of the simplified geological models associated with each reservoir is presented first followed by the PVT data for each reservoir. The results of simulation studies are then presented and discussed.

5.1 Athabasca

The McMurray formation mostly occurs at the depths of 0 to 500 m. The total McMurray formation gross thickness varies between 30-100 meters with an average of 30 m total pay. The important petro-physical properties of McMurray formation are porosity of 25–35% and 6-12 D permeability. The bitumen density varies from 8 to 11º API with a viscosity of larger than 1,000,000 cp at reservoir temperature of 11 °C.

5.1.1 Reservoir Model

Numerical modeling was carried out using a commercial fully implicit thermal reservoir simulator, Computer Modeling Group (CMG) STARS 2009.13. A simplified single well pair 3-D model was created for this study. The model was set to be homogenous with average reservoir and fluid properties of the McMurray formation sands in Athabasca deposit. Since the model is homogenous and the SAGD mechanism is a symmetrical process, only half of the SAGD pattern was simulated. The model size was 30¯500¯20 m and it was represented with the Cartesian grid blocks of size 1¯50¯1 m in i¯j¯k directions, respectively. The total number of grid blocks equals 6,000. Figure 5-1 displays a 3-D view of the reservoir model. Figure 5-2 shows that across the well pairs the size of the grid blocks are minimized which allows capturing a reasonable shape of steam chamber across the well pairs. In addition since most of the sudden changes in reservoir and fluid temperature, saturation, and pressure occurs in vicinity of the well-pairs, using homogenized grid blocks across the well-pairs allows the model to better simulate them.

30 500 Figure 5-1 3-D schematic of Athabasca reservoir model

Injector

Producer

Figure 5-2 Cross view of the Athabasca reservoir model

The horizontal permeability and porosity was 5 D and 34% respectively, and the

Kv/Kh was set equal to 0.8 for all grid blocks. The selected reservoir properties for the representative Athabasca model are tabulated in table 5-1. The initial oil saturation was assumed to be 85% with no gas cap above the oil bearing zone. The thermal properties of rock are provided in table 5-1 as well [91]. The heat losses to over-burden and underburden are taken into account. CMG-STARS calculate the heat losses to the cap rock and base rock analytically. The capillary pressure was set to zero since at reservoir temperature the fluids are immobile due to high viscosity and at steam temperature; the interfacial tension between

82 oil and water becomes small. Moreover, the capillary pressure is expected to be very small in high permeability sand. Table 5-1 Reservoir properties of model representing Athabasca reservoir Net Pay 20 m Depth 250 m Permeability, Kh 5,000 md Kv/Kh 0.8 Porosity 34 % Initial Pressure, PR 2,000 kPa Initial Temperature, TR 11 °C Oil Saturation, So 85 % mole fraction Gas in Oil 6 % Oil Viscosity @ TR 1.6E+6 cp Formation Compressibility 1.4E-5 1/kPa Rock Heat Capacity 2.6E+6 J/m3.°C Thermal Rock Conductivity 6.6E+5 J/m.d.°C Overburden/Underburden Heat Capacity 2.6E+6 J/m3.°C

5.1.2 Fluid Properties

Only three fluid components were included in the reservoir model as: Bitumen, water, and methane. Three phases of oleic, aqueous, and gas exist in the model. The oleic phase can contain both bitumen and methane, the aqueous phase contains only water while the gas phase may consists of both steam and methane. The thermal properties of the fluid and rock were obtained from the published literature. The properties of the water in both aqueous and gas phase were set as the default values of the CMG-STARS. The properties of the fluid (Bitumen and methane) model are provided in Table 5-2. Table 5-2 Fluid properties representing Athabasca Bitumen

Oil Viscosity @ TR 1.6E+6 cp 3 Bitumen Density @ TR 999.3 Kg/m Bitumen Molecular Mass 570.0 g/mole Kv1 5.45 E+5 kPa Kv4 -879.84 °C Kv5 -265.99 °C To represent the phase behavior of methane, a compatible K-Value relationship was implemented with the CMG software [92]. The corresponding K-value for methane is provided in table 5-2 [91]. It is assumed that no evaporation occurs for the bitumen component.

Kv4 Kv K − Value = 1 exp T + Kv5 P To estimate a full range of viscosity vs. temperature, the Mehrotra and Svercek viscosity correlation was used [93]. ln ln(μ) = A + B ln(T) Figure 5-3, shows the viscosity-temperature variation for bitumen model.

10000000.0

1000000.0

100000.0

10000.0

1000.0 Viscosity, cp cp Viscosity, 100.0

10.0

1.0 0.0 50.0 100.0 150.0 200.0 250.0 300.0 Temperature, C

Figure 5-3 Temperature dependency of bitumen model’s Viscosity for Athabasca

5.1.3 Rock-Fluid Properties

Since there was no available experimental data for the rock fluid properties, the three phase relative permeability defined by Stone’s Model was used to combine water-oil and liquid-gas relative permeability curves. Two types of rock were defined in most of the numerical models: rock type 1 which applied to entire reservoir, and rock type 2 which was imposed on the wellbore but in both rock types, the rock was considered water-wet. Straight line relative permeability was defined for the rock fluid interaction in the well pairs. Some typical values of residual saturates were selected [91, 47] and since this part of study does not include any history matching procedure, therefore all the end points are

equal to one. Table 5-3 summarizes the rock-fluid properties. The water-oil and gas-oil relative permeability curves are displayed on Figure 5-4. Figure 5-5 presents the relative permeability sets for the grid blocks containing the well pairs.

Figure 5-4 Water-oil relative permeability.

Figure 5-5 Relative permeability sets for DW well pairs Table 5-3 Rock-fluid properties SWCON: Connate Water 0.15 SWCRIT: Critical Water 0.15 SOIRW: Irreducible Oil for Water-Oil Table 0.2 SORW: Residual Oil for Water-Oil Table 0.2 SGCON: Connate Gas 0.05 SGCRIT: Critical Gas 0.05 KROCW - Kro at Connate Water 1 KRWIRO - Krw at Irreducible Oil 1 KRGCL - Krg at Connate Liquid 1 nw 3 now 3 nog 3 ng 2

5.1.4 Initial Condition/Geo-mechanics

The reservoir model top layer is located at a depth of 250 m and at initial temperature of 11 ºC. The water saturation is at its critical value of 15% and the initial mole fraction of gas in bitumen is 6%. The total pore volume and oil phase volume are 1.28 and 1.09 E+5m3. Geo-mechanical effect was ignored in the entire study.

5.1.5 Wellbore Model

CMG-STARS 2009.13 provides two different formulations for horizontal wellbore modeling; Source/Sink (SS) approach and Discretized Wellbore (DW) model. SS modeling has some limitations such as: a) the friction and heat loss along the horizontal section is not taken into account; b) it does not allow modeling of fluid circulation in wellbores; c) liquid hold-up in wellbore is neglected [94]. In fact, to heat up the intervening bitumen between the well pairs during the preheating period of SAGD process, a line heater with specific constraint has to be assigned for the wellbore. This

86 would affect the cumulative SOR. The DW model provides the means to simulate the circulation period and it considers both heat and friction loss along the horizontal section of the wellbore. CMG-STARS models a DW the same as the reservoir. Hence, each wellbore segment is treated as a grid block in which the fluid flow and heat transfer equations are solved at each time step. The flow in tubing and annulus is assumed as laminar. The flow equations through tubing and annulus are based on Hagen-Poiseuille equation. If the flow became turbulent, then the permeability of tubing and annulus would be modified. However, DW has its own limitations as well. One of the most significant restrictions of DW is that it does not model non-horizontal (deviated) wellbores. For this study a combination of both SS and DW models were used. Most of the rock fluid properties were also used for the grid blocks containing the DW except the thermal conductivities and relative permeability. The thermal conductivity of stainless steel and cement were set for tubing and casing respectively. Straight line relative permeability presented in Figure 5-5 was imposed for the grid blocks containing DW. All of the wells were modeled as DW except the non-horizontal ones. The non- horizontal injectors are modeled as line source/sink combined with a line heater. The line heaters were shut in after the circulation period ended. The DW consists of a tubing and annulus which were defined as injector and producer respectively. This would provide the possibility of steam circulation during the preheating period.

5.1.6 Wellbore Constraint

The injection well is constrained to operate at a maximum bottom hole pressure. It operates at 500 kPa above the reservoir pressure. The steam quality is equal to 0.9 at the sand-face. The corresponding steam saturation temperature at the bottom-hole pressure is 224 °C. The production well is assumed to produce under two major constraints: minimum bottom-hole pressure of 2,000 kPa and steam trap of 10 °C. The specified steam trap constraints for producer will not allow any live steam to be produced via the producer.

5.1.7 Operating Period

SAGD process consists of three phases of a) Preheating (Start-up), b) Steam Injection & Oil Production, and c) Wind down. Each numerical case was run for total of 6 years. The preheating is variable between 1-4 months depending on the well configuration. For the base case, the circulation period is 4 months which is similar to the current industrial operations. The main production periods is approximately 5 years while the wind down takes only 1 year. The SAGD process stops when the oil rate declines below 10 m3/d.

5.1.8 Well Configurations

Numerous simulations were conducted for well configuration cases in search for an improved well configuration for the McMurray formation in Athabasca type of reservoir. To start with, a base case which has the classic well pattern (1:1 ratio with 5 m vertical inter-well spacing) was modeled. The base case was compared with available analytical solutions and performance criteria. Furthermore, the performance of the examined well patterns was compared against the base case results. Figure 5.6 presents some of the modified well configurations that can be used in SAGD operations. These well configurations need to be matched with specific reservoir characteristics for the optimum performance. None of them would be applicable to all reservoirs.

Injectors Injector Injector

5m 5m Producer Producer Producer Basic Well Configuration Vertical Injectors Reversed Horizontal Injector Injectors Injector

Producer Producer Inclined Injector Parallel Inclined Injectors Multi Lateral Producer

Figure 5-6 Schematic representation of various well configurations for Athabasca Reservoir

5.1.8.1 Base Case This configuration is the classic configuration as recommended by Butler. It follows the same schedule of preheating, normal SAGD, and wind down. The vertical inter-well distance was 5 m and the producer was placed 1.5 m above the base of the pay zone. Two distinct base cases were defined for comparison; a) both injector and producer wellbores were modeled based on DW approach, b) the injector was modeled with SS wellbore approach and the producer was simulated with DW. Since in some of the future well patterns, the injectors is modeled as a Source well, then for the sake of comparison case b can be used as the base case. The circulation period is 4 month and the total production period is approximately 6 years. The results of both cases are reasonable and close to each other. Figures 5-7 and 5 8 present the oil rate and recovery factor vs. time for both cases. Figure 5-9 and 5-10 display the cSOR and chamber volume vs. time. Both cases provided similar results except for the cSOR. The recovery factor for both DW and SS models are close to each other, being 66.2% and 65.0% respectively. As per Figure 5-9, there is a small difference in cSOR values for the two base cases. The final cSOR for the Base Case-DW and Base Case-SS are 2.54 and 2.23 m3/m3 respectively. On Figure 5-7, the total production period is divided into four distinct regions as: 1) circulation period, 2) ramp-up, 3) plateau, and 4) wind down. Figure 5-11 displays the cross section of the chamber development across the well pairs during the four regions. By the time the ramp-up period is completed the chamber reaches the top of reservoir. The maximum oil rate occurs at the end of ramp-up period. During this period the chamber has the largest bitumen head and smallest chamber inclination. In the Base Case-SS model, a line heater was introduced above the injector. The heater with the modified constraint injected sufficient heat into the zone between the injector and producer. This supplied amount of energy is not included in cSOR calculations. Also, the SS wellbore does not include the frictional pressure drop along the wellbore. These conditions make the base case with the line source to operate at a lower cSOR.

100 Base Case-DW Base Case-SS SCTR stands for Sector 80

Oil Prod RateProd Oil SCTR (m3/day)

20 1 2 3 4

0 2009 2010 2011 2012 2013 2014 Time (Date)

Figure 5-7 Oil Production Rate: Base Case

80 Base Case-DW Base Case-SS 70

30 Oil Recovery Factor SCTR SCTR Recovery Factor Oil

0 2009 2010 2011 2012 2013 2014 Time (Date)

Figure 5-8 Oil Recovery Factor: Base Case

5.0 Base Case-DW Base Case-SS 4.5

4.0

3.5

3.0

2.5

2.0

1.5 Steam Oil Ratio Cum SCTR (m3/m3) 1.0

0.5

0.0 2009 2010 2011 2012 2013 2014 Time (Date)

Figure 5-9 Cumulative Steam Oil Ratio (cSOR): Base Case

60,000 Base Case-DW Base Case-SS

50,000

40,000

30,000

20,000 Steam Chamber Volume SCTR (m3) SCTR (m3) Volume Chamber Steam

10,000

0 2009 2010 2011 2012 2013 2014 Time (Date)

Figure 5-10 Steam Chamber Volume: Base Case

1 2

3 4

Figure 5-11 Cross view of chamber development at 4 specified time frames: Base Case

1.0

0.9

0.8

0.7

0.6

0.5

0.4 Steam Quality Downhole Downhole Quality Steam 0.3

0.2

0.1 Base Case-DW Base Case-SS 0.0 2009 2010 2011 2012 2013 2014 Time (Date)

Figure 5-12 Steam Quality of DW vs SS during the SAGD life period: Base Case

Figure 5-12 displays the steam quality of DW vs SS injector for the base cases. In the model containing discretized wellbore there is some loss in steam quality due to the heat loss and friction, while in the Source/Sink model, the steam quality profile is completely flat; no change along the injector Figure 5-13 displays the pressure profile along the vertical distance between the toe of injector and producer and also the pressure profile at the heel of injector and producer. There is a small pressure drop along the injector and/or producer. It seems that the way STARS treats producers and injectors is somewhat idealistic. The producer drawdown does not change from heel to the toe which in real field operation is not true. Most of the SAGD operators have problems in conveying the live steam to the toe of the injector to form a uniform steam chamber. Das reported that a disproportionate amount of steam, over 80%, is injected near the heel of the injector and the remaining goes to the toe if live steam conquers the heat loss and friction along the tubing [14]. As a result, the steam chamber grows primarily at the heel and has a dome shape along the well pairs. This situation may lead to steam breakthrough around the heel area and reduce the final recovery factor. Since these effects are not captured in the model, the simulated base-case performance is better than what can be achieved in the field. Therefore, when the new well configurations are compared against the base cases and show even marginally better performance, they are considered promising configurations. The base case model was validated against Butler’s analytical model. The analytical model includes the solution for oil rates during the rising chamber and depletion period [1]. The parameters of the numerical model were incorporated into the analytical solution and the obtained oil production rate was compared against the numerical base case result. Table 5-4 presents the list of parameters incorporated in the analytical solution of Base Case results. The oil production rate for numerical and analytical results is presented in Figure 5-14. There is a reasonable consistency between both results. Both models forecast quite similar ramp up and maximum oil rate. However, after two years of production the results deviate from each other which is due to the boundary effects and the simplifying assumptions (single phase flow, ignoring formation compressibility, constant viscosity, etc.) in the analytical solution. In fact, the numerical model is able to

93 simulate the wind down step as well while the analytical solution only predicts the depletion period. Table 5-4 Analytical solution parameters

Typical Athabasca Base Case Reservoir Temperature 11 °C

Oil Kinematic Viscosity @ TR 1587284.57 cS Bitumen Kinematic Viscosity @ 100°C 203.9 cS Reservoir Thickness 20 m Thermal Diffusivity 0.07 m2/D Porosity 0.34 Initial Oil Saturation 0.85 Residual Oil Saturation 0.25 Effective Permeability for Oil Flow 1.6 D Well Spacing 60 m Vertical Space From Bottom 1.5 m Steam Pressure 2.5 Mpa Parameter m 3

Bitumen Kinematic Viscosity @ Ts 7.10E-06 cS

2,500

2,498

2,496

2,494

2,492

2,490

Pressure (kPa) (kPa) Pressure 2,488

2,486

2,484 Injector: Heel 2,482 Injector: Toe Producer: Heel Producer:Toe 2,480 2009 2010 2011 2012 2013 2014 Time (Date)

Figure 5-13 Pressure Profile between Injector and Producer at the heel and toe: Base Case

160 Butler's Analytical Method 140 CMG Simulation Results: Base Case

120 /d 3 100

40 Oil ProductionOil Rate, m

0 0 1 2 3 4 5 6 Time, Year

Figure 5-14 Comparison of numerical and analytical solutions: Base Case Aherne and Maini introduced the Total Fluid to Steam Ratio (TFSR) which is an indicator for evaluation of the balance between fluid withdrawal and steam injection pressure [35]. In fact the TFSR indicates the water leak off from the steam chamber. The TFSR was expressed as: H O Prd + Oil Prd - Steam in Chamber TFSR = 2 Steam Inj They stated that if the TFSR is less than 1.38 m3/m3 then the pressure of the reservoir will increase or there will be some leak off from the chamber. The current numerical base case model has a TFSR of 1.4 m3/m3 which demonstrates that the injection and production is balanced. The base case was evaluated using these validation criteria. Since its performance is acceptable, the performance of future well patterns will be compared against the base case.

5.1.8.2 Vertical Inter-well Distance Optimization The optimum vertical inter-well distance between the injector and producer depends on reservoir permeability, bitumen viscosity, and preheating period. Locating the injector

95 close enough to the producer would shorten the circulation period, but on the other hand the steam trap control becomes an issue. To obtain the best RF and cSOR, the vertical distance needs to be optimized. To study the effect of vertical inter-well distance on SAGD performance, five distances were considered: 3, 4, 6, 7, and 8m. The idea was to investigate if changing the vertical distance will improve the recovery factor and cSOR. The oil rate, RF, cSOR, and the chamber volume are presented on Figures 5-15, 5-16, 5-17 and 5-18 respectively. It is observed that the performance decreases as the vertical distance increases above 6m. Increasing the inter-well spacing between injector and producer delays the thermal communication between producer and injector which imposes longer circulation period and consequently higher cSOR. Since for the large vertical distance between the well pairs, the injector is placed close to the overburden, the steam is exposed to the cap rock for a longer period of time and therefore the heat loss increases which results to higher cSOR and less recovery factor. When the inter-well distance is smaller than the base case, the preheating period is shortened but the effect on subsequent performance is not dramatic. The optimum vertical distance between the injector and producer is assumed to be 5m in most of reservoir simulations and field projects. Figures 5-16 and 5-17 show that the vertical distance can be varied from 3 to 6m and 4m appears to be the optimal distance. The 4m vertical spacing has the highest recovery factor and same cSOR as 3, 5, and 6m vertical spacing cases.

100 Base Case-DW Vertical Space=3m Vertical Space=4m Vertical Space=6m Vertical Space=7m 80 Vertical Space=8m

40 Oil Prod Rate Prod Oil SCTR (m3/day)

0 2009 2010 2011 2012 2013 2014 Time (Date)

Figure 5-15 Oil Production Rate: Vertical Inter-well Distance Optimization

70 Base Case-DW Vertical Space=3m Vertical Space=4m 60 Vertical Space=6m Vertical Space=7m Vertical Space=8m

30 Oil Recovery SCTR Factor Oil 20

0 2009 2010 2011 2012 2013 2014 Time (Date)

Figure 5-16 Oil Recovery Factor: Vertical Inter-well Distance Optimization

5.0 Base Case-DW Vertical Space=3m 4.5 Vertical Space=4m Vertical Space=6m Vertical Space=7m 4.0 Vertical Space=8m

3.5

3.0

2.5

2.0

1.5 Steam Oil Ratio Cum SCTR (m3/m3) (m3/m3) SCTR Cum Ratio Oil Steam 1.0

0.5

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Figure 5-17 Steam Oil Ratio: Vertical Inter-well Distance Optimization

60,000 Base Case-DW Vertical Space=3m Vertical Space=4m Vertical Space=6m 50,000 Vertical Space=7m Vertical Space=8m

40,000

30,000

20,000 Steam Chamber Volume SCTR (m3)

10,000

0 2009 2010 2011 2012 2013 2014 Time (Date)

Figure 5-18 Steam Chamber Volume: Vertical Inter-well Distance Optimization

5.1.8.3 Vertical Injector Vertical wellbores are cheaper and simpler to drill than the horizontal wellbores. An advantage of vertical wells with respect to horizontal well is that it is possible to change the injection point as the SAGD project becomes mature. Their disadvantage is that to cover a horizontal wellbore, several vertical wells are required. Typically for every 150 200 m of horizontal well length a vertical well is needed. Therefore, for this study with 500 m long horizontal wells, a well configuration with three/two vertical injectors and a horizontal producer was evaluated. The possibility of replacing the horizontal injector with sets of vertical injectors was studied and the results are presented in this section. Comparisons with the base case are presented in Figures 5-19, 5-20, 5-21, and 5-22. The circulation of the vertical injectors was achieved by introducing line heater on the injectors. The heating period was the same as base case preheating period. Once the heating stage was terminated, the injectors were set on injection. The model encountered some numerical instability during the first few month of production but it stabled down for the rest of production period. The results demonstrate that using only two vertical injectors is not sufficient to deplete the reservoir in 6 years of production window. Its recovery factor is only 50% after 6 years of production while its cSOR is close to 3.0 m3/m3. However 3 vertical injectors case has comparable RF results with the base case model, which is about 65% after 6 years of production, but it requires larger amount of steam. The steam chamber volume of the 3 vertical injectors is larger than the base case which demonstrates that the steam is delivered more efficient than the base case. Vertical injectors cause some instability in numerical modeling once the steam zone of each vertical well merges to the adjacent steam zone. This issue was resolved using more refined grid blocks along the producer.

150 Base Case-SS 2 Vertical Injectors 3 Vertical Injectors

120

60 Oil Rate SC (m3/day) SC Rate Oil

0 2009 2010 2011 2012 2013 2014 2015 2016 2017 Time (Date)

Figure 5-19 Oil Production Rate: Vertical Injectors

70 Base Case-SS 2 Vertical Injectors 3 Vertical Injectors 60

30 Oil Recovery Factor SCTR SCTR Factor Recovery Oil 20

0 2009 2010 2011 2012 2013 2014 2015 2016 2017 Time (Date)

Figure 5-20 Oil Recovery Factor: Vertical Injectors

100

10.0 Base Case-SS 2 Vertical Injectors 9.0 3 Vertical Injectors

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3.0 Steam Oil Ratio Cum SCTR (m3/m3) (m3/m3) SCTR Cum Ratio Oil Steam

2.0

1.0

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Figure 5-21 Steam Oil Ratio: Vertical Injectors

70,000 Base Case-SS 2 Vertical Injectors 3 Vertical Injectors 60,000

50,000

40,000

30,000

20,000 Steam Chamber Volume SCTR (m3) (m3) SCTR Volume Chamber Steam

10,000

0 2009 2010 2011 2012 2013 2014 2015 2016 2017 Time (Date)

Figure 5-22 Steam Chamber Volume: Vertical Injectors

101

5.1.8.4 Reversed Horizontal Injector It has been suggested that most of the injected steam in a basic SAGD pattern is injected near the heel of the injector, where the pressure difference between the injector and producer is high. Thus basic SAGD would yield an uneven and slanted chamber along the well pair. The Reversed Injector is introduced to solve the no uniformity of steam chamber growth via a uniform pressure difference along the well pair. This well configuration is able to provide live steam along almost the whole length of the injector and producer. The vertical distance between the injector and producer is 5 m. The injector’s heel is placed above the producer’s toe and its toe right above the producer’s heel. This well configuration, creates an even pressure drop between the injector and producer. The steam chamber growth would be more uniform in all directions. This configuration uses the concept of countercurrent heat transfer and fluid flow. Figures 5-23, 5-24, 5-25 and 5-26 compare the technical performance of Reverse Horizontal Injector and Base Case-SS. In both Base Case-SS and Reversed Horizontal Injector models, a source-sink wellbore type was used as Injector. A line heater was introduced above the injector. The oil recovery factor increased by 4% with reversed injector while, cSOR remained the same as in the Base Case-SS, while chamber volume increased by 8.9%. As discussed in the base case section, currently the numerical simulators does not effectively model the steam distribution (including pressure drop and injectivity) along the injectors, and therefore the results of Reversed Horizontal injector is close to the base case. Figure 5-26 displays a 3-D view of depleted reservoir using the Reversed Horizontal Injector. The chamber grows laterally, longitudinally and vertically in a uniform manner. The results suggest that there is potential benefit for reversing the injector. This pattern provides the possibility of higher and uniform pressure operation. This strongly suggests that this pattern should be examined through a pilot project in Athabasca type of reservoir.

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100 Base Case-SS Reversed Horizontal Injector

40 Oil Prod Oil Rate SCTR (m3/day)

0 2009 2010 2011 2012 2013 2014 Time (Date)

Figure 5-23 Oil Production Rate: Reverse Horizontal Injector

70 Base Case-SS Reverse Horizontal Injector

30 Oil Recovery FactorSCTR Oil 20

0 2009 2010 2011 2012 2013 2014 Time (Date)

Figure 5-24 Oil Recovery Factor: Reverse Horizontal Injector

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Figure 5-25 Steam Oil Ratio: Reverse Horizontal Injector

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Figure 5-26 Steam Chamber Volume: Reverse Horizontal Injector

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One Year Five Years

Figure 5-27 3-D View of Chamber Growth: Reverse Horizontal Injector

5.1.8.5 Inclined Injector Optimization Mojarab et al. introduced a dipping injector above the producer. It was shown that the well configuration will provide a small improvement in the SAGD performance [95]. For simulating the inclined well, the size of grid blocks in vertical direction was reduced to appropriately capture the interferences at different angles. The optimum distance at the heel and toe was explored. Table 5-5 presents the eight different cases that were investigated. Table 5-5 Inclined Injector Case Distance to Producer Heel, m Distance to Producer Toe, m Case 1 7.5 2.5 Case 2 8 3 Case 3 8.5 3.5 Case 4 9 4 Case 5 9.5 4.5 Case 6 10 5 Case 7 8.5 2.5 Case 8 9.5 2.5

The angle of injector inclination was varied to determine the optimum angle. The production results are compared against the basic pattern. RF and cSOR results for all inclined injector cases are presented in Figure 5-28 and 5-29. The injector was modeled based on the SS wellbore modeling, so the base case is the Base Case-SS model. Figure 5-28 and 5-29 demonstrate that the Inclined Injector Case#7 provides promising performance. It has increased the recovery factor by 3.1% while the cSOR was about the same as in the Base Case-SS. This configuration requires less than 3 months of steam circulation.

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70 Base Case-SS Inclined Inj Case 01 Inclined Inj Case 02 60 Inclined Inj Case 03 Inclined Inj Case 04 Inclined Inj Case 05 Inclined Inj Case 06 50 Inclined Inj Case 07 Inclined Inj Case 08

30 Oil Recovery Factor SCTR Factor Recovery Oil 20

0 2009 2010 2011 2012 2013 2014 Time (Date)

Figure 5-28 Oil Recovery Factor: Inclined Injector

5.0 Base Case-SS Inclined Inj Case 01 4.5 Inclined Inj Case 02 Inclined Inj Case 03 Inclined Inj Case 04 4.0 Inclined Inj Case 05 Inclined Inj Case 06 Inclined Inj Case 07 3.5 Inclined Inj Case 08

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Figure 5-29 Steam Oil Ratio: Inclined Injector

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100 Base Case-SS Inclined Inj Case 07

40 Oil Rate SC (m3/day) Rate SC (m3/day) Oil

0 2009 2010 2011 2012 2013 2014 Time (Date)

Figure 5-30 Oil Production Rate: Inclined Injector: Case 07

70 Base Case-SS Inclined Inj Case 07

30 Oil Recovery FactorSCTR Oil 20

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Figure 5-31 Oil Recovery Factor: Inclined Injector: Case 07

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Figure 5-32 Steam Oil Ratio: Inclined Injector: Case 07

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Figure 5-33 Steam Chamber Volume: Inclined Injector: Case 07

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The results show that optimum distance at the heel and the toe can varies from 7-9 m and 2-3 m respectively. Figures 5-30 through 5-33 compare the results for optimum Inclined Injector and the base case.

5.1.8.6 Parallel Inclined Injectors In this pattern, two 250 m long inclined injectors were placed above the producer. This well configuration is aimed at solving the nonuniformity of steam chamber along the producer for long horizontal wellbores. Nowadays, the commercial projects are running SAGD with well lengths of 1000 m or higher. Consequently, the degree of inclination in the Inclined Injector pattern becomes small through 1000 meters of wellbore. Since in the current study the base case is defaulted as 500m, therefore for this pattern two sets of inclined injector are suggested. Each injector has about 250 m length and their heels are connected to the surface. The heel to toe direction of both injectors is the same as producer. Both injectors are source/sink type of wellbore and two line heaters were introduced on the injectors to warm up the bitumen around them. The heating period was less than 3 months. The results obtained with dual inclined injectors above the producer are compared with the Base Case-SS pattern in Figures 5-34, 5-35, 5-36 and 5-37. The parallel inclined injector pattern provides higher RF but at the expense of larger cSOR. The RF is increased by 4.6%, but on the other hand the cSOR increases by 4.4% as well. As the economic evaluation was not part of this project, the conclusions are based on the production performance only. However, it is obvious that an economic analysis would be necessary for the final decision. The main advantage of this well configuration is that it has the flexibility of the vertical injector and deliverability of horizontal wellbores.

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100 Base Case-SS Parallel Inclined Injectors

40 Oil Prod Rate SCTR (m3/day) SCTR Rate Prod Oil

0 2009 2010 2011 2012 2013 2014 Time (Date)

Figure 5-34 Oil Production Rate: Parallel Inclined Injector

70 Base Case-SS Parallel Inclined Injectors

30 Oil Recovery Factor SCTR SCTR Factor Recovery Oil 20

0 2009 2010 2011 2012 2013 2014 Time (Date)

Figure 5-35 Oil Recovery Factor: Parallel Inclined Injector

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Figure 5-36 Steam Oil Ratio: Parallel Inclined Injector

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Figure 5-37 Steam Chamber Volume: Parallel Inclined Injector

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5.1.8.7 Multi-Lateral Producer Unnecessary steam production is often associated with mature SAGD. Large amount of bitumen would be left behind in the area between the adjoining chambers. It is believed that a multi-lateral well could maximize overall oil production in a mature SAGD. Multi lateral wells are expected to provide better horizontal coverage than horizontal wells and could extend the life of projects. In order to increase the productivity of a well, the productive interval of the wellbore can be increased via well completion in the form of multi-lateral wells. A case study on the evaluation of multilateral well performance is presented. Multiple 30 m legs are connected to the producer. Figures 5-38, 5-39, 5-40 and 5-41 display the results for the Mutli-Lateral pattern against the Base Case-SS. The results are not dramatic. The Multi-Lateral provides a small benefit in recovery factor but not in cSOR. Considering the cost involved in drilling multilaterals, this configuration does not appear promising. This pattern may be a good candidate for thin reservoirs which vertical access is limited and it would be more beneficial to enlarge the horizontal distance between wellpairs

100 Base Case-SS Multi-Lateral Producer

40 Oil Prod Rate (m3/day) SCTR

0 2009 2010 2011 2012 2013 2014 Time (Date)

Figure 5-38 Oil Production Rate: Multi-Lateral Producer

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70 Base Case-SS Multi-Lateral Producer

Oil Recovery Factor SCTR

0 2009 2010 2011 2012 2013 2014 Time (Date)

Figure 5-39 Oil Recovery Factor: Multi-Lateral Producer

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Figure 5-40 Steam Oil Ratio: Multi-Lateral Producer

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Figure 5-41 Steam Chamber Volume: Multi-Lateral Producer

5.2 Cold Lake

The minimum depth to the first oil sand in Cold Lake area is ~300m while most commercial thermal projects have occurred at the depth of about 450 m. In Clearwater formation the sands are often greater than 40m thick, with a net/gross ratio of greater than 0.5. Porosity ranges from 30 to 35%, with oil saturations that average 70% PV. At the initial reservoir temperature of 13 °C, the oil viscosity is about 100,000 cp.

5.2.1 Reservoir Model

Same as the numerical step in Athabasca reservoir section, the (CMG) STARS 2009.13 software was used to numerically model the most optimum well configuration. A 3-D symmetrical Cartesian model was created for this study. The model is set to be homogenous with averaged reservoir and fluid property to honor the properties in Cold Lake area. The model corresponds to a reservoir with the size of 30m×500m×20 m. It was covered with the Cartesian grid block size of 1×50×1 m in i×j×k directions, respectively. Figure 5-42 displays a 3-D view of the reservoir model.

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500

Figure 5-42 3-D schematic of Cold Lake reservoir model The absolute permeability in horizontal direction is 5 D and the Kv/Kh is set equal to be 0.8. The porosity of sand is 34%. The model is assumed to contain three phases with bitumen, water, and methane as solution gas in bitumen. The initial oil saturation was assumed to be 85% with no gas cap above the oil bearing zone. The thermal properties of rock are provided in table 5-6. The heat losses to over-burden and under-burden are taken into account as well. CMG-STARS calculate the heat losses to the cap rock and base rock analytically. The capillary pressure is set to zero as in the case of Athabasca reservoir.

5.2.2 Fluid Properties

The fluid definition for Cold Lake reservoir (including K-Value definition and values) followed the same steps as the one described in section 5.1.2, except the fact that Cold Lake viscosity is different.

To estimate a full range of viscosity vs temperature, the Mehrotra and Svercek viscosity correlation was used [93].

ln ln(μ) = A + B ln(T) Figure 5-43, shows the viscosity-temperature variation for bitumen at cold lake area.

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1000000

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1000 Viscosity, cp 100

1 0 50 100 150 200 250 300 Temperature, C

Figure 5-43 Viscosity vs. Temperature for Cold Lake bitumen

5.2.3 Rock-Fluid Properties The relative permeability data set is exactly the same as in the Athabasca model. Table 5-3 summarizes the rock-fluid properties. The thermal properties of reservoir and cap rock are the same as the ones were presented in Table 5-1. The water-oil and gas-oil relative permeability curves are displayed in Figure 5-4. Figure 5-5 presents the relative permeability sets for the grid blocks containing the well pairs.

Table 5-6 Reservoir and fluid properties for Cold Lake reservoir model. Net Pay 20 m Depth 475 m Permeability, Kh 5,000 md Kv/Kh 0.8 Porosity 34 % Initial Pressure, PR 2,670 kPa Initial Temperature, TR 15 °C Oil Saturation, So 85 % mole fraction Gas in Oil 6 % 3 Bitumen Density @ TR 949 Kg/m

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5.2.4 Initial Condition/Geomechanics

The reservoir model top layer is located at a depth of 475 m and at initial temperature of 15 ºC. The water saturation is at its critical value of 15% and the initial mole fraction of gas in bitumen is 6%. The total pore volume and oil phase volume are 1.28 and 1.09 E+5m3 respectively. Geo-mechanical effects were ignored in the entire study except in the C-SAGD well configuration.

5.2.5 Wellbore Model

All the wells were modeled as DW except the non horizontal ones. The non horizontal injectors are modeled as line source/sink combined with a line heater. The line heaters were shut in after the circulation period ended. The DW consists of a tubing and annulus which were defined as injector and producer respectively. This would provide the possibility of steam circulation during the preheating period.

5.2.6 Wellbore Constraint

The injection well is constrained to operate at a maximum bottom hole pressure. It operates at 500 kPa above the reservoir pressure. The steam quality is equal to 0.9 at the sand-face. The corresponding steam saturation temperature at the bottom-hole pressure is 237 °C. The production well is assumed to produce under two major constraints: minimum bottom-hole pressure of 2,670 kPa and steam trap of 10 °C. The specified steam trap constraints for producer will not allow any live steam to be produced via the producer.

5.2.7 Operating Period

Each numerical case was run for total of 4 years. The preheating is variable between 1-4 months depending on the well configuration. For the base case, the circulation period is 50 days which is approximately similar to the current industrial operations. The main production periods is approximately 3 years while the wind down takes only 1 year. The SAGD process stops when the oil rate declines below 10 m3/d.

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5.2.8 Well Configurations

A series of comprehensive simulations were completed to explore the most promising well configuration for the Clearwater formation in Cold Lake area. First a base case which has the classic well pattern (1:1 ratio with 5 m vertical inter-well spacing) was modeled. Then the performance of the other well patterns was compared against the base case results. The horizontal well length for both injector and producer was set at 500 m. Figure 5-44 displays the schematics of different well configurations. These well configurations need to be matched with specific reservoir characteristics for the optimum performance. None of them would be applicable to all reservoirs.

Injectors Injector Injector

5m Y X Producer Producer Producer Basic Well Configuration Vertical Injector Offset Horizontal Injector

Injectors Injector Injectors

5m Producer Producer Producer Reversed Horizontal Injector Parallel Inclined Injectors Parallel Reversed Upward Injectors

Injector Producer X

Multi Lateral Producer C-SAGD

Figure 5-44 Schematic representation of various well configurations for Cold Lake

5.2.8.1 Base Case This configuration introduces a wellpair consisting of injector and producer with the vertical interwell distance of 5 m. The producer is placed 1.5 m above the base of the net pay. Two distinct base cases were defined for future comparison; a) both injector and producer wellbores are modeled based on DW approach, b) the injector is modeled with SS wellbore approach and the producer is simulated with DW. The circulation period is 50 days and the reservoir is depleted in 4 years. A close examination of the chamber growth in both DW and SS models will show that that STARS treats wellbores too idealistically. The temperature profile along the wellpairs is

118 completely uniform during circulation as well as during the main SAGD stage. However in most of the field cases, operators have difficulties in conveying the live steam to the toe of injector for creating uniform steam chamber. As a result, the steam chamber will have its maximum height at the heel of wellpairs and would become slanted along length of the wellpairs. This situation may create a potential for steam to breakthrough into the producer, resulting in difficulties in steam trap control and ultimately reduces the final recovery factor. Therefore, the new well configurations that have significantly higher chances of activating the full well length will be considered successful configurations even when their simulated performance is only slightly better than the base case. Figure 5-45, 5-46, 5-47, and 5-48 display the progression of the production for both base cases during depletion of the reservoir. Both cases provided consistent results except for the cSOR. The recovery factor for both DW and SS models are pretty close to each other. As per Figure 5-47, there is a small difference in cSOR of DW and SS models with the respective values of 2.47 and 2.17 m3/m3. In the Base Case-SS model, a line heater was introduced above the injector. The heater with the modified constraint would provide sufficient heat into the intervening zone between the injector and producer. This supplied amount of energy is not included in cSOR calculations which results in lower cSOR. Therefore the difference in cSOR can be ignored as well and both cases can be assumed to behave similarly.

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Figure 5-45 Oil Production Rate: Base Case

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Figure 5-46 Oil Recovery Factor: Base Case

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Figure 5-47 Steam Oil Ratio: Base Case

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Figure 5-48 Steam Chamber Volume: Base Case

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5.2.8.2 Vertical Inter-well Distance Optimization As discussed previously, the optimum vertical inter-well distance between the injector and producer depends on reservoir permeability, bitumen viscosity, and preheating period. To obtain the best RF and cSOR, the vertical distance needs to be optimized. To study the effect of vertical inter-well distance on SAGD performance, five distances were considered: 3, 4, 6, 7, and 8m. The idea was to investigate if changing the vertical distance will improve the recovery factor and cSOR. The oil rate, RF, cSOR, and the chamber volume are presented on Figures 5-49, 5-50, 5-51 and 5-52. It is observed that the performance decreases with increasing the vertical distance. When the distance is smaller than the base case, the preheating period is shortened but the effect on subsequent performance is not dramatic. The optimum vertical distance between the injector and producer is assumed to be 5m in most of reservoir simulations and field projects. Figures 5-50 and 5-51 show that the vertical distance can be varied from 3 to 6m and 4m appears to be the optimal distance.

160 Base Case-DW Vertical Space=3m Vertical Space=4m 140 Vertical Space=6m Vertical Space=7m Vertical Space=8m

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60 Oil ProdRate (m3/day) SCTR

0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-49 Oil Production Rate: Vertical Inter-well Distance Optimization

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70 Base Case-DW Vertical Space=3m Vertical Space=4m 60 Vertical Space=6m Vertical Space=7m Vertical Space=8m

30 Oil Recovery Factor SCTR

0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-50 Oil Recovery Factor: Vertical Inter-well Distance Optimization

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Figure 5-51 Steam Oil Ratio: Vertical Inter-well Distance Optimization

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Figure 5-52 Steam Chamber Volume: Vertical Inter-well Distance Optimization

5.2.8.3 Offset Horizontal Injector The interwell distance between the injector and producer depends on reservoir permeability, bitumen viscosity, and preheating period. Cold Lake contains bitumen with the average viscosity of about 100,000 cp which can be ranked as a lower viscosity reservoir among the bitumen saturated sands. Cold Lake bitumen offers a tempting option of offsetting injector from producer. The idea behind offsetting the injector is to increase the drainage area available for the SAGD draw-down despite the fact that both recovery factor and cSOR would be comparable to the Base Case pattern. Therefore it is appealing to consider a configuration when the injector is positioned at an offset of certain distance from the producer. In order to operate a SAGD project with offset injector, the vertical interwell distance needs to be small. The vertical distance is assumed to be either 2m or 3m while the offset distances are set to be 5m and 10m. Four cases were simulated to investigate the possibility of offsetting the injector for a SAGD process; a) Vertical distance of 2m with the horizontal offset of 5m, b) Vertical

124 distance of 2m with the horizontal offset of 10m, c) Vertical distance of 3m with the horizontal offset of 5m, and d) Vertical distance of 3m with the horizontal offset of 10m. Figures 5-53, 5-54, 5-55, and 5-56 show that there is some benefit in providing extra horizontal spacing. According to the oil production profile and recovery factor, 10m offset does not offer any advantage to a SAGD process in Cold Lake, it decreases the RF and dramatically increases the cSOR. The 10m horizontal offset requires long preheating period which results in high cSOR. Once the communication between injector and producer established, due to high viscosity of the bitumen and large horizontal spacing between injector and producer, the steam chamber does not get stable and the oil rate fluctuates during the course of production. The steam chamber does not grow uniformly along the injector and major amount of bitumen is left unheated. When the horizontal offset is around 5m, there is some improvement in RF but at the expense of higher cSOR.

160 Base Case-DW Offset Horizontal Injector: VD=2m-Off=5m Offset Horizontal Injector: VD=2m-Off=10m 140 Offset Horizontal Injector: VD=3m-Off=5m Offset Horizontal Injector: VD=3m-Off=10m

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60 Oil ProdRate (m3/day) SCTR

0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-53 Oil Production Rate: Offset Horizontal Injector

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70 Base Case-DW Offset Horizontal Injector: VD=2m-Off=5m Offset Horizontal Injector: VD=2m-Off=10m 60 Offset Horizontal Injector: VD=3m-Off=5m Offset Horizontal Injector: VD=3m-Off=10m

30 Oil Recovery Factor SCTR

0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-54 Oil Recovery Factor: Offset Horizontal Injector

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3.0 Steam Oil Ratio Cum SCTR (m3/m3)

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Figure 5-55 Steam Oil Ratio: Offset Horizontal Injector

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60,000 Base Case-DW Offset Horizontal Injector: VD=2m-Off=5m Offset Horizontal Injector: VD=2m-Off=10m Offset Horizontal Injector: VD=3m-Off=5m 50,000 Offset Horizontal Injector: VD=3m-Off=10m

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0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-56 Steam Chamber Volume: Offset Horizontal Injector

5.2.8.4 Vertical Injector As discussed previously, the vertical wellbores are included in each part of the current study because of their advantages over the horizontal ones such as drilling price, ease of operation, flexibility of operation. Typically for every 150-200 m of horizontal well length a vertical well is needed. Therefore, for this study with 500 m long horizontal wells, a well configuration with three/two vertical injectors and a horizontal producer was evaluated. The possibility of replacing the horizontal injector with sets of vertical injectors was studied and the results are presented in this section. Comparisons with the base case are presented in Figures 5-57, 5-58, 5-59, and 5-60. As was seen in Athabasca section, the results demonstrate that two vertical injectors are not sufficient to deplete a 500m long reservoir since its recovery factor reaches 55% after four years of production with a steam oil ratio of 3.0 m3/m3. On the other hand, the three vertical injectors case provides comparable RF with respect to base case RF but at larger amount of injected steam. The RF and cSOR of three vertical injectors is 63% and

127

3.2 m3/m3 respectively. . The steam chamber volume of the 3 vertical injectors is larger than the base case which demonstrates that the steam is delivered more efficient than the base case. The line heater was used to establish the thermal communication between the vertical injectors and producer. The heating period was the same as base case preheating period. Once the intervening bitumen between injector and producer is warmed up, the injectors were set on injection Vertical injectors caused some instability in numerical modeling once the steam zone of each vertical well merges to the adjacent steam zone. This issue was resolved using more refined grid blocks along the producer.

180 Base Case-SS 2 Vertical Injectors 160 3 Vertical Injectors

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60 Oil Prod Rate (m3/day) SCTR

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Figure 5-57 Oil Production Rate: Vertical Injectors

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70 Base Case-SS 2 Vertical Injectors 3 Vertical Injectors 60

Oil Recovery Factor SCTR

0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-58 Oil Recovery Factor: Vertical Injectors

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Figure 5-59 Steam Oil Ratio: Vertical Injectors

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0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-60 Steam Chamber Volume: Vertical Injectors

5.2.8.5 Reversed Horizontal Injector This pattern was well described previously and its aim was defined to establish a uniform steam chamber along the well-pairs by imposing a uniform pressure difference along the injector/producer vertical interwell distance. This well configuration is able to provide live steam almost along the whole length of the injector and producer. The vertical distance between the injector and producer is 5 m. The injector’s heel is placed above the producer’s toe and its toe right above the producer’s heel. The steam chamber growth is uniform in three main directions: vertically, laterally, and longitudinally. The oil rate, RF, cSOR, and the chamber volume are plotted on Figures 5-61, 5-62, 5 63, and 5-64. The technical performance of Reverse Horizontal Injector and Base Case- DW are compared. In both Base Case-DW and Reversed Horizontal Injector models, a discretized wellbore formulation was used as Injector. Oil recovery factor increased by 2%, but the cSOR was the same as Basic Case-DW. The results suggest that there is a potential benefit for reversing the injector in Cold Lake type of reservoir. This pattern provides the possibility of higher and uniform

130 pressure operation. This strongly suggests that this pattern be examined through a pilot project in Cold Lake type of reservoir.

140 Base Case-DW Reversed Horizontal Injector

120

100

60 Oil Prod Rate SCTR (m3/day) SCTR Rate Prod Oil 40

0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-61 Oil Production Rate: Reverse Horizontal Injector

131

70 Base Case-DW Reverse Horizontal Injector

30 Oil Recovery Factor SCTR SCTR Factor Recovery Oil 20

0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-62 Oil Recovery Factor: Reverse Horizontal Injector

5.0 Base Case-DW Reverse Horizontal Injector 4.5

4.0

3.5

3.0

2.5

2.0

1.5 Steam Oil Ratio Cum SCTR (m3/m3) (m3/m3) SCTR Cum Ratio Oil Steam

1.0

0.5

0.0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-63 Steam Oil Ratio: Reverse Horizontal Injector

132

60,000 Base Case-DW Reverse Horizontal Injector

50,000

40,000

30,000

20,000 Steam Chamber Volume SCTR (m3) (m3) SCTR Volume Chamber Steam

10,000

0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-64 Steam Chamber Volume: Reverse Horizontal Injector

5.2.8.6 Parallel Inclined Injectors Vertical, horizontal, and inclined injectors provide some advantages for the SAGD process, namely: flexibility of injection point, extensive access to the reservoir, and short circulation period. The parallel Inclined Injector was designed to combine all these benefits together. In this pattern, two 250 m inclined injectors were located above the producer. The pattern is shown in Figure 5-44. The injectors were defined using the SS wellbore formulation; therefore the results are compared against the Base Case-SS pattern. Figures 5-65, 5-66, 5-67, and 5-68 present the ultimate production results for the Parallel Inclined Injectors. The recovery factor increased by 3.6%, but the cSOR also increased by 13.8%.

133

140 Base Case-SS Parallel Inclined Injectors

120

100

60 Oil Prod Rate (m3/day) SCTR 40

0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-65 Oil Production Rate: Parallel Inclined Injector

70 Base Case-SS Parallel Inclined Injectors

Oil Recovery Factor SCTR

0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-66 Oil Recovery Factor: Parallel Inclined Injector

134

5.0 Base Case-SS Parallel Inlcined Injectors 4.5

4.0

3.5

3.0

2.5

2.0

1.5 Steam Oil Ratio Cum SCTR (m3/m3) Steam Oil SCTR Ratio Cum

1.0

0.5

0.0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-67 Steam Oil Ratio: Parallel Inclined Injector

60,000 Base Case-SS Parallel Inclined Injectors

50,000

40,000

30,000

20,000 Steam Chamber Volume(m3) SCTR

10,000

0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-68 Steam Chamber Volume: Parallel Inclined Injector

135

5.2.8.7 Parallel Reversed Upward Injectors Parallel inclined injector and reversed horizontal showed encouraging performance in comparison with the Base case. Combining the advantages gained via these two well configurations, the Parallel Reversed Upward Injectors was proposed. Two upward inclined injectors were introduced above the producer. The main thought behind this special design, is to provide a uniform pressure profile along the injector and producer and resolve the unconformity of steam chamber associated with the Base Case pattern. Each injector has about 250 m length and their heels are connected to the surface. The first injector has its heel above the toe of producer. Figure 5-69, 5-70, 5-71, and 5-72 compare the technical performance of Parallel Reversed Inclined Injectors and Base Case-SS. The recovery factor and cSOR increased by 5.5%.

140 Base Case-SS Parallel Reverse Upward Injectors

120

100

60 Oil ProdRate (m3/day) SCTR 40

0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-69 Oil Production Rate: Parallel Reverse Upward Injector

136

70 Base Case-SS Parallel Reverse Upward Injectors

30 Oil Recovery Factor SCTR

0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-70 Oil Recovery Factor: Parallel Reverse Upward Injector

5.0 Base Case-SS Parallel Reverse Upward Injectors 4.5

4.0

3.5

3.0

2.5

2.0

1.5 Steam Oil Ratio Cum SCTR (m3/m3)

1.0

0.5

0.0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-71 Steam Oil Ratio: Parallel Reverse Upward Injector

137

60,000 Base Case-SS Parallel Reverse Upward Injectors

50,000

40,000

30,000

20,000 Steam Chamber Volume (m3) SCTR

10,000

0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-72 Steam Chamber Volume: Parallel Reverse Upward Injector

5.2.8.8 Multi-Lateral Producer Economic studies show that SAGD mechanism is not feasible in thin reservoirs due to enormous heat loss and consequently high cSOR [90]. Therefore the low RF production mechanisms such as cold production will continue to be used for extraction of heavy oil. On the other hand in Cold Lake type of reservoir, unnecessary steam production is often associated with mature SAGD and large amount of bitumen would be left behind in the area between the chambers. In order to access more of the heated mobilized bitumen and increase the productivity of a well, the productive interval of the wellbore can be increased via well completion in the form of multi-lateral wells. Multi lateral wells are expected to provide better horizontal coverage than horizontal wells and they can extend the life of projects. A simulation study on the evaluation of multilateral well performance is presented. Multiple 30 m legs are connected to the producer. Figure 5-73, 5-74, 5-75, and 5-76 show the results for Mutli-Lateral pattern against the Base Case-SS. The Multi-Lateral depletes the reservoir significantly faster than the

138 basic pattern. The plotted results demonstrate that the Multi-Lateral is not able to provide any other significant benefits over the performance of base case SAGD

140 Base Case-SS Multi-Lateral Producer

120

100

60 Oil Prod Rate SCTR (m3/day) (m3/day) SCTR Rate Oil Prod 40

0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-73 Oil Production Rate: Multi-Lateral Producer

139

70 Base Case-SS Multi-Lateral Producer

30 Oil Recovery Factor SCTR

0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-74 Oil Recovery Factor: Multi-Lateral Producer

5.0 Base Case-SS Multi-Lateral Producer 4.5

4.0

3.5

3.0

2.5

2.0

1.5 Steam Oil Ratio Cum SCTR (m3/m3)

1.0

0.5

0.0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-75 Steam Oil Ratio: Multi-Lateral Producer

140

70,000 Base Case-SS Multi-Lateral Producer

60,000

50,000

40,000

30,000

Steam Chamber Volume (m3) SCTR 20,000

10,000

0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-76 Steam Chamber Volume: Multi-Lateral Producer

5.2.8.9 C-SAGD At Cold Lake, Cyclic Steam Stimulation has been successfully used as the main recovery mechanism because there are often heterogeneities in form of shale barriers that are believed to limit the vertical growth of steam chamber and consequently decrease the efficiency of thermal methods. In CSS process, the steam is injected at high pressure (usually higher than the fracture pressure) into the reservoir; its high pressure creates some fractures in the reservoir, and its high temperature causes a significant drop in bitumen viscosity. As a result a high mobility zone will be created around the wellbore which the fluids (melted bitumen and condensate) can flow back into the wellbore. The fracturing stage is known as deformation which includes dilation and re-compaction. Beatle et al defined a deformation model which is presented in Figure 5-77 [96]. During the steam injection into the reservoir, the reservoir pressure increases and the rock behaves elastically. The rock pore volume at the new pressure will be obtained based on the rock compressibility, initial reservoir pressure, and initial porosity. If the reservoir pressure increases above the so called pdila, then the reservoir pore volume

141 follows the dilation curve which is irreversible. It may reach the maximum porosity. If the pressure decreases from any point on the dilation curve, then the reservoir pore volume follows the elastic compaction curve. If the pressure drops below the re- compaction pressure ppact, re-compaction occurs and the slop of the curve is calculated by the residual dilation fraction fr.

Figure 5-77 Reservoir deformation model [96].

Every single cycle of a CSS process follows the entire deformation envelope. The deformation properties of the cold lake reservoir are provided in Table 5-7 [97]. Table 5-7 Values of dilation-compaction properties for Cold Lake reservoir model. pdila 7,300 kPa ppact 5,000 kPa φmax 1.25 φi Residual Dilation Fraction, fr 0.45 Dilation Compressibility 1.0 E-4 1/kPa

The C-SAGD pattern is aimed at combining the benefits of CSS and SAGD together. This configuration starts with one cycle of CSS at both injector and producer locations to create sufficient mobility in vicinity of both wellbores. The one cycle comprises the steam injection, soaking, and production stage. The CSS cycle starts with 20 days of steam injection at a maximum pressure of 10,000 kPa on both injector and producer, 7

142 days of soaking, and approximately two months of production. Thereafter it switches into normal SAGD process by injection of steam from injector and producing via producer. The constraints of injector and producer are the same as values are presented in section 5.2.6. The objective of the C-SAGD well pattern is to decrease the preheating period without affecting the ultimate recovery factor and cumulative steam oil ratio. The injector and producer are placed at the same depth with two set of offsets: 10m and 15m. Their results are compared against the Base Case. It has to be noted that both injector and producer in the C-SAGD patter are modeled using the SS wellbore. As a result some marginal value (due to higher pressure and injection rate approximately larger than 0.2 0.3 m3/m3) has to be added to their ultimate cSOR value. Figure 5-78, 5-79, 5-60, and 5 61 presents the oil rate, RF, cSOR, and the chamber volume of the two C-SAGD cases in comparison with the base case results.

300 Base Case-DW C-SAGD-Offset=10m 270 C-SAGD-Offset=15m

240

210

180

150

120 Oil ProdRate (m3/day) SCTR 90

0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-78 Oil Production Rate: C-SAGD

143

80 Base Case-DW C-SAGD-Offset=10m C-SAGD-Offset=15m 70

30 Oil Recovery Factor SCTR

0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-79 Oil Recovery Factor: C-SAGD

10.0 Base Case-DW C-SAGD-Offset=10m 9.0 C-SAGD-Offset=15m

8.0

7.0

6.0

5.0

4.0

3.0 Steam Oil Ratio Cum SCTR (m3/m3)

2.0

1.0

0.0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-80 Steam Oil Ratio: C-SAGD

144

90,000 Base Case-DW C-SAGD-Offset=10m 80,000 C-SAGD-Offset=15m

70,000

60,000

50,000

40,000

30,000 Steam Chamber Volume (m3) SCTR

20,000

10,000

0 2008-7 2009-1 2009-7 2010-1 2010-7 2011-1 2011-7 2012-1 Time (Date)

Figure 5-81 Steam Chamber Volume: C-SAGD

The C-SAGD pattern with the offset of 10m is able to deplete the reservoir in 3 years at ~70% RF and cSOR of 2.2 m3/m3 (needs to add ~0.2-0.3 m3/m3 due to SS injector and producer). The pattern enhances the RF of SAGD process significantly. The only limitation with this pattern, for the current research scope, is the requirement for super high injection pressure for a short period of time.

5.3 Lloydminster

Steam-flooding has been practiced extensively in North America. Generally speaking, steam is introduced into the reservoir via a horizontal/vertical injector while the heated oil is being pushed towards the producer. Several types of repeated patterns are known to provide the most efficient recovery factor. The major issues with the steam flooding process are: (1) steam tends to override the heavy oil and breaks through to the production well; and (2) the steam has to displace the cold heavy oil into the production well. These concerns make steam flooding inefficient in reservoirs containing heavy oil with reservoir condition viscosities higher than 1000 cp. However, in SAGD type of

145 process the heated oil remains hot as it flows into the production well. Figure 5-82 shows both steam flooding and SAGD processes. At Lloydminster area, the reservoirs are mostly complex and thin with a wide range oil viscosity. These characteristics of the Lloydminster reservoirs make most production techniques such as primary depletion, waterflood, CSS and steamflood relatively inefficient. The highly viscous oil, coupled with the fine-grained, unconsolidated sandstone reservoir, often result in huge rates of sand production with oil during primary depletion. Although these techniques may work to some extent, the recovery factor remains low (5% to 15%) and large volumes of oil are left unrecovered when these methods have been exhausted. Because of the large quantities of sand production, many of these reservoirs end up with a network of wormholes which make most of the displacement type enhanced oil recovery techniques inapplicable. Steam Oil & Water

Overburden Overburden Steam Chamber Net

Underburden Underburden

Vertical Cross Section of SAGD Vertical Cross Section of Steamflood

Figure 5-82 Schematic of SAGD and Steamflood For heavy oil reservoirs containing oil with the viscosity smaller than 5000 cp, both SAGD and steamflooding can be considered applicable for extraction of the heavy oil. In fact this type of reservoir provides more flexibility in designing the thermal recovery techniques as a result of their higher mobility and steam injectivity. Steam can be pushed and forced into the reservoir displacing the heavy oil and creating more space for the chamber to grow. On the other hand due to small thickness of the net pay, the heat loss could make the process uneconomical for both methods. However, steamflood faces its own additional problems as well, no matter where it is applied. For the SAGD case,

146 although drainage by the SAGD mechanism from the steam chamber to the production well is conceivable, due to the small pay thickness, the gravity forces may not be large enough to provide economical drainage rates. Unfortunately, SAGD has not received adequate attention in Lloydminster area, mostly due to the notion that lower drainage rate and higher heat loss in thin reservoirs would make the process uneconomical. While this may be true, the limiting reservoir thickness and inter-well horizontal distance for SAGD under varying conditions has not been established. These reservoirs contain oil with sufficient mobility. Therefore the communication between the SAGD well pairs is no longer a hurdle. This opens up the possibility of increasing the distance between the two wells and introducing elements of steamflooding into the process in order to compensate for the small thickness of the reservoir. In fact a new application of SAGD mechanism for the reservoir with the conventional heavy oil could be the combination of an early lateral steam drive with SAGD afterwards. In this scheme, steam would be injected from an offset horizontal injector, pushing the oil towards the producer. Once the communication between injector and producer is established the recovery mechanism will be changed to a SAGD process by applying steam trap control to the production well. Among the whole Mannville group, the formations that have potential to be considered as oil bearing zone are Waseca, Sparky, GP and Lloydminster. These sandstone channels thicknesses may rarely go up to 20m and the oil saturation up to 80%. Their porosity ranges from 30-35 percent and permeability from 5 to 10 Darcy’s. Mannville group contains both conventional and heavy oil with the API ranging from 15 38 °API and viscosity of 800-20,000 cp at 15 °C.

5.3.1 Reservoir Model

The optimization of the well configuration study was carried out via a series of numerical simulations using CMG’s STARS 2010. A 3-D symmetrical-Cartesian homogenous reservoir model was used to conduct the comparison analysis between different well configurations. The reservoir and fluid properties were simply averaged to present the best representative of Lloydminster deposit. The model corresponds to a reservoir with the size of 90m×500m×10 m using the Cartesian grid block sizes of

147

1×50×1 in i×j×k directions, respectively. Figure 5-83 displays a 3-D view of the reservoir model.

500

90 Figure 5-83 3-D schematic of reservoir model for Lloydminster reservoir The reservoir and fluid properties are summarized in Table 5-8. The rock properties are the same as Athabasca and Cold Lake.

5.3.2 Fluid Properties

As in simulations of Athabasca and Cold Lake reservoirs, three components were included in the reservoir model as: Oil, water, and methane. The thermal properties of the fluid and rock were obtained from the published literature. The properties of the water in both aqueous and gas phase were set as the default values of the CMG-STARS. The properties of the fluid (oil and methane) model are provided in Table 5-8. The K-Values of methane are the same as the numbers presented for Athabasca and Cold Lake reservoirs. To estimate a full range of viscosity vs. temperature, the Mehrotra and Svercek viscosity correlation was used [93]. ln ln(μ) = A + B ln(T) Figure 5-84, shows the viscosity-temperature variation for the heavy oil model. Rock fluid properties are the same as the relative permeability sets presented for Athabasca and Cold Lake reservoirs.

148

Table 5-8 Reservoir and Fluid Properties for Lloydminster reservoir model Net Pay 10 m Depth 450 m Permeability, Kh 5,000 md Kv/Kh 0.8 Porosity 34 % Initial Pressure, PR 4,100 kPa Initial Temperature, TR 20 °C Oil Saturation, So 80 % mFrac Gas in Oil 10 % Oil Viscosity @ TR 5,000 cp

5.3.3 Initial Conditions/Geomechanics The reservoir model top layer is located at a depth of 450 m and at initial temperature of 20 ºC. The water saturation is at its critical value of 20% and the initial mole fraction of gas in heavy oil is 10%. The total pore volume and oil phase volume are 1.92 and 1.54 E+5m3. Geo-mechanical effects were ignored in the entire study except the C-SAGD pattern.

5.3.4 Wellbore Constraint The well length was kept constant at a value of 500m. The injection well was constrained to operate at a maximum bottom hole pressure. It operated at 500 kPa above the reservoir pressure. The steam quality was equal to 0.9 at the sand-face. The corresponding steam saturation temperature at the bottom-hole pressure is 258.8 °C. The production well is assumed to produce under two major constraints: minimum bottom-hole pressure of 1,000-2,000 kPa and steam trap of 10 °C (The 1,000 kPa is for the offset of larger than 30 m). The specified steam trap constraints for producer will not allow any live steam to be produced via the producer.

149

10000

1000

100 Viscosity, cp Viscosity,

1 0 50 100 150 200 250 300 Temperature,C

Figure 5-84 Temperature dependency of heavy oil model’s Viscosity

5.3.5 Operating Period

Each numerical case was run for total of 7 years. The preheating is variable for Lloydminster area and it really depends on the well configuration and wellbore offset.

5.3.6 Well Configurations

The basic well pattern is practical for the reservoirs with the thickness of higher than 20 m as the vertical inter-well distance is 5 m and the producer is placed at least 1.5 m above the base of the pay zone. However, depending on the reservoir thickness and oil properties it might be advantageous to drill several horizontal/vertical wells at different levels of the reservoir i.e. employ other configurations than the classic one to enhance the drainage and heat loss efficiency. These well configurations need to be matched with specific reservoir characteristics for the optimum performance. When two parallel horizontal wells are employed in SAGD, the relevant configuration parameters are: (a) height of the producer above the base of the reservoir; (b) the vertical distance between the producer and the injector; and (c) the horizontal

150 separation between the two wells, which is zero in the base case configuration. Although the assumed net pay for the Lloydminster reservoir is 10 m, but just for sake of comparison, the base case is the same pattern was defined before, i.e. an injector located 5m above the producer which is the case under the name of VD=5m_Offset=0m. Figure 5-85 displays the schematics of different well configurations. These well configurations need to be matched with specific reservoir characteristics for the optimum performance. None of them would be applicable to all reservoirs.

Injectors Produce Injectors Injector

5m Producer Producer Basic Well Configuration Offset Producer, Top View Vertical Injector

Injectors Produce Injectors Produce

Injector Producer X

C-SAGD ZIGZAG Producer, Top View Multi Lateral Producer, Top View

Figure 5-85 Schematic of various well configurations for Lloydminster reservoir The SS wellbore type is used in all the defined well configurations for Lloydminster. In fact due to some of the special patterns such as C-SAGD, some high differential pressure and consequently high fluid rates are required which the DW modeling is not able to model properly. As a result, some marginal value has to be added to their ultimate cSOR value in order to compensate for replacing DW by SS wellbore. Two types of start-up are used in initializing the proposed patterns in Figure 5-85: a) routine SAGD steam circulation, b) one CSS cycle. Due to the nature of fluid and reservoir in Lloydminster area, initial oil viscosity of 5,000 cp at reservoir temperature, the initial mobility is high but not sufficient for a cold production start. The primary production leads to a small recovery factor and would create worm holes in the net pay. Therefore some heat is required to be injected into the reservoir to mobilize the heavy oil. Among the six proposed well patterns, only C-SAGD initializes the production by one cycle of CSS. In C-SAGD pattern, the steam at high pressure of 10,000 kPa is

151 injected in both injector and producer; thereafter both wells were shut-in for a week (soaking period). The heated mobilized heavy oil around the injector and producer were produced for approximately 4 months. Eventually the steam was injected via injector and pushed the heavy oil towards the producer which was set at a minimum bottom-hole pressure of 1,000 kPa. The start-up stage in the rest of the patterns follows the same routing steps of a regular SAGD process; steam circulation which followed by injection/production via injector and producer. The steam circulation is achieved by defining a line heater above the injector and producer. The period of steam circulation really depends on the well pair horizontal spacing and is variable among each pattern.

5.3.6.1 Offset Producer The lower viscosity of the Lloydminster deposit comparing to Cold Lake and Athabasca reservoirs opens up the possibility of increasing the distance between the two wells and introducing elements of steam flooding into the process in order to compensate for the small thickness of the reservoir. Due to the low viscosity and sufficient mobility, the communication between the SAGD well pairs may be no longer a hurdle. Therefore the horizontal separation between the two well is more flexible in Lloydminster type of reservoir and due to the small thickness of the net pay the vertical distance needs to be as small as possible. The objective of the offset producer pattern is to increase the horizontal spacing between wells as much as possible. To establish the chamber on top of the well pairs which are separated horizontally, the fact that any increase in the well spacing may require more circulation period needs to be considered. Horizontal well spacing of 6, 12, 24, 30, 36, and 42 m were tested to obtain the optimum performance. The circulation period was varied between 20 and 80 days which occurred at 6m and 42m offset producer. Figure 5-86, 5-87, 5-88, and 5-89 shows the results for the offset injector against the Base Case-DW.

152

200 VD=5m-Offset=0m VD=0m-Offset=6m 180 VD=0m-Offset=12m VD=0m-Offset=18m VD=0m-Offset=24m 160 VD=0m-Offset=30m VD=0m-Offset=36m VD=0m-Offset=42m 140

120

100

80 Oil Rate SC (m3/day) SC Rate Oil

0 2009 2010 2011 2012 2013 2014 2015 2016 Time (Date)

Figure 5-86 Oil Production Rate: Offset Producer

75 VD=5m-Offset=0m VD=0m-Offset=6m VD=0m-Offset=12m VD=0m-Offset=18m VD=0m-Offset=24m 60 VD=0m-Offset=30m VD=0m-Offset=36m VD=0m-Offset=42m

30 Oil Recovery Factor SCTR SCTR Factor Recovery Oil

0 2009 2010 2011 2012 2013 2014 2015 2016 Time (Date)

Figure 5-87 Oil Recovery Factor: Offset Producer

153

6.0 VD=5m-Offset=0m VD=0m-Offset=6m VD=0m-Offset=12m VD=0m-Offset=18m 5.0 VD=0m-Offset=24m VD=0m-Offset=30m VD=0m-Offset=36m VD=0m-Offset=42m

4.0

3.0

2.0 Cum Steam Oil Ratio (m3/m3)

1.0

0.0 2009 2010 2011 2012 2013 2014 2015 2016 Time (Date)

Figure 5-88 Steam Oil Ratio: Offset Producer

1.0e+5 VD=5m-Offset=0m VD=0m-Offset=6m VD=0m-Offset=12m VD=0m-Offset=18m VD=0m-Offset=24m 8.0e+4 VD=0m-Offset=30m VD=0m-Offset=36m VD=0m-Offset=42m

6.0e+4

4.0e+4 Steam Chamber Volume SCTR (m3) (m3) SCTR Volume Chamber Steam

2.0e+4

0.0e+0 2009 2010 2011 2012 2013 2014 2015 2016 Time (Date)

Figure 5-89 Steam Chamber Volume: Offset Producer

154

The minimum RF is 66% which belongs to the base case, 42m offset producer pattern and the maximum obtained RF is 71% which obtained by the 30m offset. On the other hand the 42m and 36m offset producer provide the minimum steam oil ratio of 4.6 m3/m3. Among all the offset patterns the 30m offset producer provides the most optimum performance. Therefore, it can be concluded that if any offset horizontal well is decided to be drilled in Lloydminster type of reservoir, the horizontal inter-well distance can not be larger than 30m.

5.3.6.2 Vertical Injector According to early experience of SAGD in Lloydminster area, vertical wells were considered as successful with the steam oil ratio of 3-6 m3/m3 [98]. Generally 3-4 vertical injection wells with an offset of 50m have been used for a 500m long horizontal producer. There is an unanswered question of how much of horizontal offset should be considered between vertical injectors and horizontal producers so that the SAGD would achieve optimum performance. Vertical injector well configuration was tested using 3 vertical wells combined with a horizontal producer using the offsetting values of 0, 6, 12, 18, 24, 30, 36, and 42 horizontal wells. The zero offset case locates the three vertical injectors above the producer imposing 4 m of vertical inter-well distance. In the rest of offset cases, the injector’s completed down to the producer’s depth. The comparison between the base case results and the vertical well scenarios are presented in Figure 5-90, 5-91, 5-92, and 5-93.

The pattern which has 3 vertical injectors 5m above the producer exhibits the best performance regarding the RF and cSOR. It RF equals to 70% while its cSOR is 5.2 m3/m3. However the 42m offset vertical injectors pattern has a promising performance with an extra benefit. This pattern allows to enlarge the drainage area by 42m which will affect the number of required well to develop a full section much less than the no offset vertical injectors.

155

210 VD=5m-Offset=0m 3VW-VD=5m-Offset=0m 3VW-VD=0m-Offset=6m 3VW-VD=0m-Offset=12m 180 3VW-VD=0m-Offset=18m 3VW-VD=0m-Offset=24m 3VW-VD=0m-Offset=30m 3VW-VD=0m-Offset=36m 150 3VW-VD=0m-Offset=42m

120

90 Oil Rate SC (m3/day) SC Rate Oil

0 2009 2010 2011 2012 2013 2014 2015 2016 Time (Date)

Figure 5-90 Oil Production Rate: Vertical Injector

Oil Recovery Factor SCTR SCTR Factor Recovery Oil 24

VD=5m-Offset=0m 3VW-VD=5m-Offset=0m 3VW-VD=0m-Offset=6m 3VW-VD=0m-Offset=12m 12 3VW-VD=0m-Offset=18m 3VW-VD=0m-Offset=24m 3VW-VD=0m-Offset=30m 3VW-VD=0m-Offset=36m 3VW-VD=0m-Offset=42m 0 2009 2010 2011 2012 2013 2014 2015 2016 Time (Date)

Figure 5-91 Oil Recovery Factor: Vertical Injector

156

6.0 VD=5m-Offset=0m 3VW-VD=5m-Offset=0m 3VW-VD=0m-Offset=6m 3VW-VD=0m-Offset=12m 5.0 3VW-VD=0m-Offset=18m 3VW-VD=0m-Offset=24m 3VW-VD=0m-Offset=30m 3VW-VD=0m-Offset=36m 3VW-VD=0m-Offset=42m 4.0

3.0

2.0 Steam Oil Ratio Cum SCTR (m3/m3) (m3/m3) SCTR Cum Ratio Oil Steam

1.0

0.0 2009 2010 2011 2012 2013 2014 2015 2016 Time (Date)

Figure 5-92 Steam Oil Ratio: Vertical Injector

1.0e+5 VD=5m-Offset=0m 3VW-VD=5m-Offset=0m 3VW-VD=0m-Offset=6m 3VW-VD=0m-Offset=12m 3VW-VD=0m-Offset=18m 8.0e+4 3VW-VD=0m-Offset=24m 3VW-VD=0m-Offset=30m 3VW-VD=0m-Offset=36m 3VW-VD=0m-Offset=42m

6.0e+4

4.0e+4 Steam Chamber Volume SCTR (m3) (m3) SCTR Volume Chamber Steam

2.0e+4

0.0e+0 2009 2010 2011 2012 2013 2014 2015 2016 Time (Date)

Figure 5-93 Steam Chamber Volume: Vertical Injector

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5.3.6.3 C-SAGD The C-SAGD pattern was simulated in Cold Lake reservoir and its results were promising. Due to low oil viscosity and thickness at Lloydminster reservoir, it is desired to shorten the circulation period as much as possible. The C-SAGD provides the possibility to establish the communication between injector and producer in minimal time period. As explained earlier in Cold Lake section, this pattern comprises of one CSS cycle at both injector and producer locations and thereafter it switches to regular SAGD process. The CSS cycle starts with 15 days of steam injection at a maximum pressure of 10,000 kPa on both injector and producer, 7 days of soaking, and approximately three months of production. Thereafter it switches into normal SAGD process by injection of steam from injector and producing via producer. During the normal SAGD, the constraints of injector and producer are the same as values are presented in section 5.4.4. The injector and producer are placed at the same depth with the offsetting spacing of 6, 12, 18, 24, 30, 36, and 42 m. Figures 5-94, 5-95, 5-96, 5-97 present the C-SAGD results. According to RF results, the offset of 6 and 12m is small for a C-SAGD process. But since the horizontal inter-well distance between the injector and producer gets larger, the RF will be somewhere around 80% which sounds quite efficient. The patterns with an offset value of larger than 12m are able to deplete the reservoir with a cSOR in the range of 6-6.5 m3/m3. According to the results, the most optimum horizontal inter-well spacing is 42m since it has the highest RF, the lowest cSOR, and provides the opportunity to enlarge the drainage area.

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210 VD=5m-Offset=0m C-SAGD-Offset=6m C-SAGD-Offset=12m C-SAGD-Offset=18m 180 C-SAGD-Offset=24m C-SAGD-Offset=30m C-SAGD-Offset=36m C-SAGD-Offset=42m 150

120

90 Oil Rate SC (m3/day) SC Rate Oil

0 2009 2010 2011 2012 2013 2014 2015 2016 Time (Date)

Figure 5-94 Oil Production Rate: C-SAGD

90 VD=5m-Offset=0m C-SAGD-Offset=6m 80 C-SAGD-Offset=12m C-SAGD-Offset=18m C-SAGD-Offset=24m C-SAGD-Offset=30m 70 C-SAGD-Offset=36m C-SAGD-Offset=42m

Oil Recovery Factor SCTR SCTR Factor Recovery Oil 30

0 2009 2010 2011 2012 2013 2014 2015 2016 Time (Date)

Figure 5-95 Oil Recovery Factor: C-SAGD

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7.0

6.0

5.0

4.0

3.0

2.0 Steam Oil Ratio Cum SCTR (m3/m3) (m3/m3) SCTR Cum Ratio Oil Steam VD=5m-Offset=0m C-SAGD-Offset=6m C-SAGD-Offset=12m C-SAGD-Offset=18m 1.0 C-SAGD-Offset=24m C-SAGD-Offset=30m C-SAGD-Offset=36m C-SAGD-Offset=42m 0.0 2009 2010 2011 2012 2013 2014 2015 2016 Time (Date)

Figure 5-96 Steam Oil Ratio: C-SAGD

1.2e+5 VD=5m-Offset=0m C-SAGD-Offset=6m C-SAGD-Offset=12m C-SAGD-Offset=18m 1.0e+5 C-SAGD-Offset=24m C-SAGD-Offset=30m C-SAGD-Offset=36m C-SAGD-Offset=42m

8.0e+4

6.0e+4

4.0e+4 Steam Chamber Volume SCTR (m3) (m3) SCTR Volume Chamber Steam

2.0e+4

0.0e+0 2009 2010 2011 2012 2013 2014 2015 2016 Time (Date)

Figure 5-97 Steam Chamber Volume: C-SAGD

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5.3.6.4 ZIGZAG Producer A new pattern called “ZIGZAG” was designed and compared against the horizontal offsets. The objective for this well pattern was to shorten the circulation period without affecting the ultimate performance. The horizontal inter-well distance between the injector and producer are assumed as 12, 18, 24, 30, 36, and 42 m. The producer enters into the formation at X meters offset of the injector but it approaches toward the injector up to X/2 meters away from injector and it bounce back to its primary location of X meters from injector. This move repeatedly occurs throughout the length of injector. The results of ZIGZAG pattern are provided in Figures 5-98, 5-99, 5-100, and 5-101. Increasing the offset between injector and producer enhance the performance which has the same trend in other configurations. The 42m offset depletes the reservoir much faster while it exhibits the highest RF of 78% and lowest cSOR of 5 m3/m3.

180 VD=5m-Offset=0m ZIGZAG-Offset=12m 160 ZIGZAG-Offset=18m ZIGZAG-Offset=24m ZIGZAG-Offset=30m ZIGZAG-Offset=36m 140 ZIGZAG-Offset=42m

120

100

80 Oil Rate SC (m3/day) SC Rate Oil 60

0 2009 2010 2011 2012 2013 2014 2015 2016 Time (Date)

Figure 5-98 Oil Production Rate: ZIGZAG

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80 VD=5m-Offset=0m ZIGZAG-Offset=12m ZIGZAG-Offset=18m 70 ZIGZAG-Offset=24m ZIGZAG-Offset=30m ZIGZAG-Offset=36m ZIGZAG-Offset=42m 60

30 Oil Recovery Factor SCTR SCTR Factor Recovery Oil

0 2009 2010 2011 2012 2013 2014 2015 2016 Time (Date)

Figure 5-99 Oil Recovery Factor: ZIGZAG

6.0 VD=5m-Offset=0m ZIGZAG-Offset=12m ZIGZAG-Offset=18m ZIGZAG-Offset=24m 5.0 ZIGZAG-Offset=30m ZIGZAG-Offset=36m ZIGZAG-Offset=42m

4.0

3.0

2.0 Steam Oil Ratio Cum SCTR (m3/m3) (m3/m3) SCTR Cum Ratio Oil Steam

1.0

0.0 2009 2010 2011 2012 2013 2014 2015 2016 Time (Date)

Figure 5-100 Steam Oil Ratio: ZIGZAG

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1.0e+5 VD=5m-Offset=0m ZIGZAG-Offset=12m ZIGZAG-Offset=18m ZIGZAG-Offset=24m ZIGZAG-Offset=30m 8.0e+4 ZIGZAG-Offset=36m ZIGZAG-Offset=42m

6.0e+4

4.0e+4 Steam Chamber Volume SCTR (m3) (m3) SCTR Volume Chamber Steam

2.0e+4

0.0e+0 2009 2010 2011 2012 2013 2014 2015 2016 Time (Date)

Figure 5-101 Steam Chamber Volume: ZIGZAG

5.3.6.5 Multi-Lateral Producer For the thin reservoirs of Lloydminster type, due to its potential for much higher heat loss and consequently high cSOR, the conventional SAGD is considered uneconomical. In order to access more of the heated mobilized bitumen and increase the productivity of a well, the productive interval of the wellbore can be increased via well completion in the form of multi-lateral wells. Multi lateral wells are expected to provide better reservoir coverage than horizontal wells and they can extend the life of projects. The multi-lateral producer was numerically simulated and compared against the base case. The multi lateral producer has 10 legs each has 50m length. The producer is located at the same depth of the injector and with an offset of 6m. The results of the Multi-Lateral producer are presented in Figure 5-102, 5-103, 5-104, and 5-105. It’s performance is compared against the most promising well pattern that was explored in earlier sections.

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180 Multi-Lateral-Offset=6m VD=0m-Offset=30m 160 3VW-VD=0m-Offset=42m C-SAGD-Offset=42m ZIGZAG-Offset=42m

140

120

100

80 Oil Rate SC (m3/day) SC Rate Oil 60

0 2009 2010 2011 2012 2013 2014 2015 2016 Time (Date)

Figure 5-102 Oil Production Rate: Comparison

90 Multi-Lateral-Offset=6m VD=0m-Offset=30m 3VW-VD=0m-Offset=42m C-SAGD-Offset=42m 75 ZIGZAG-Offset=42m

Oil Recovery Factor SCTR SCTR Factor Recovery Oil 30

0 2009 2010 2011 2012 2013 2014 2015 2016 Time (Date)

Figure 5-103 Oil Recovery Factor: Comparison

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7.0 Multi-Lateral-Offset=6m VD=0m-Offset=30m 3VW-VD=0m-Offset=42m 6.0 C-SAGD-Offset=42m ZIGZAG-Offset=42m

5.0

4.0

3.0

2.0 Steam Oil Ratio Cum SCTR (m3/m3) (m3/m3) SCTR Cum Ratio Oil Steam

1.0

0.0 2009 2010 2011 2012 2013 2014 2015 2016 Time (Date)

Figure 5-104 Steam Oil Ratio: Comparison

1.2e+5 Multi-Lateral-Offset=6m VD=0m-Offset=30m 3VW-VD=0m-Offset=42m C-SAGD-Offset=42m 1.0e+5 ZIGZAG-Offset=42m

8.0e+4

6.0e+4

4.0e+4 Steam Chamber Volume SCTR (m3) (m3) SCTR Volume Chamber Steam

2.0e+4

0.0e+0 2009 2010 2011 2012 2013 2014 2015 2016 Time (Date)

Figure 5-105 Steam Chamber Volume: Comparison

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The Multi-Lateral producer is able to sweep off the heavy oil in 4 years at a RF of 67% and cSOR of 5.6 m3/m3. Its performance with respect to ultimate recovery factor and steam oil ratio is weaker than the rest of optimum patterns. The C-SAGD pattern exhibits the highest RF (81%) and at the same time highest cSOR (6.4 m3/m3). Among these patterns, the vertical injectors seems to provide reasonable performance since its recovery factor is 70% but at a low cSOR value of 5.2. In addition to the vertical injector performance, the drilling and operation benefits of vertical injector over the horizontal injector, this 3-vertical injector is recommended for future development in Lloydminster reservoirs.

CHAPTER 6 EXPERIMENTAL RESULTS AND DISUCSSIONS

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This chapter presents the results and discussions of the physical model experiments conducted for evaluating SAGD performance in two of Alberta’s bitumen reservoirs: a) Cold Lake, b) Athabasca. The objective of these experiments was to confirm the results of numerical simulations for the optimum well configuration in a 3-D physical model. Two type of bitumen were used in experiments: 1) Elk-Point oil which represents the Cold Lake reservoir, and 2) JACOS bitumen which represents the Athabasca reservoir. Three different well configurations were tested using the two oils: I) Classic SAGD Pattern, II) Reverse Horizontal Injector and III) Inclined Injector. Each experiment was history matched using a commercial simulator, CMG-STARS, to further understand the performance and behaviour of each experiment. A total of seven physical model experiments were conducted. Four experiments used the classic two parallel horizontal wells configuration, which were considered base case tests. The first experiment was used as the base case for the Cold Lake reservoir. When the physical model was designed, there were some concerns regarding the initially assumed reservoir parameters, which were applied in the dimensional analysis. In the second experiment, the assumed permeability of the model was increased while the same fluids were used for saturating the model. In fact the second experiment was conducted to examine the scaling criteria discussed in chapter 4. Since a large volume of sand was required in each experiment and re-packing the model was time consuming, there was a thought that perhaps the model can be re- saturated after each run by oil flooding the depleted model, without any cleaning and opening of the model. Therefore the third experiment was run aiming at reducing the turn-around time for experiments by re-saturating the model. The last classic SAGD pattern was the fifth experiment which uses the same sand as the first experiment but was saturated using the Athabasca bitumen. Two sets of experiments used the Reverse Horizontal Injector pattern. Each test used a different bitumen while they both were packed with the same AGSCO silica sand. Finally the last experiment used the Inclined Injector pattern using the Athabasca bitumen and AGSCO sand.

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Table 6-1 presents a summary of all experiments and their relevant initial properties. Table 6-1 Summary of the physical model experiments.

Experiment Permeability Porosity Soi Swi Viso @ Ti Well Spacing D % % % cp cm First 270 36.00 86.02 13.98 29,800 5 Second 650 36.25 96.80 3.20 29,800 5 Third 650 36.25 96.80 3.20 29,800 5 Fourth 265 31.60 87.30 12.70 29,800 10 Fifth 260 34.60 86.90 13.10 440,668 10 Sixth 260 31.00 87.50 12.50 440,668 10 Seventh 260 32.90 87.00 13.00 440,668 5-18 The performance of each experiment was examined based on the injection, production, and temperature (steam chamber) data. Performance analysis included oil rate, water cut, steam injection rate (CWE), cumulative Steam Oil Ratio (cSOR), recovery factor, Water Cut (WCUT), and steam chamber contour maps. The contour maps were plotted to observe the shape and size of steam chamber at various times of each test. The chamber volume profile for each experiment was calculated using SURFER 9.0 software which is powerful software for contouring and 3D surface mapping. To obtain a representative chamber volume, every single temperature reading of the thermocouples was imported into the SURFER at specific pore volumes injected (PVinj) time; thereafter the chamber volume which was enclosed by steam temperature was calculated. The final step in the analysis was matching the production profile of each experiment using a numerical simulation model, CMG-STARS.

6.1 Fluid and Rock Properties Two types of packing material; either glass beads or sand, were used to create a porous medium inside the model. The glass beads were of A-130 size and provided a permeability of 600-650 D. The sand was the AGSCO 12-20 mesh sand with a permeability of 250-290 D and a porosity of 31-34%. The porosity and permeability of AGSCO 12-20 was measured in the apparatus displayed in Figure 4-2. The sand-pack was prepared in a 68 cm long stainless steel tube to conduct the permeability measurements at higher rates. The measured points are shown in Figure 6-1 in forms of the flow rate versus pressure drop, and the slope of the fitted straight line is the permeability. According to the slope of the best fit line to the experimental data, the

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permeability of the AGSCO 12-20 was 262 D with the associated porosity of 33%. The AGSCO 12-20 was used in the last five experiments. The porosity associated with the AGSCO 12-20 sand was measured at the start of each run in the 3-D physical model and it varied between 31-34 %. Table 6-1 lists the measured values of porosities for each physical model run. It is assumed that the permeability would be similar when the same sand is packed into the physical model and the resulting porosity in the model is not too different from that in the linear sand-pack. The objective of this study was aimed at experimental evaluation of the optimum well configurations on Cold Lake and Athabasca type of reservoirs. Hence two heavy oils were obtained; Elk Point heavy oil provided by Husky Energy and the Athabasca bitumen provided by JACOS. The viscosity of both heavy oils was measured using the HAAKE viscometer described in chapter 4. The viscosity was measured at temperatures of 25-70 ºC. To estimate a full range of viscosity vs. temperature, the Mehrotra and Svercek viscosity correlation [93] was used to honor the measured viscosities of both oils. Figure 6-2 and 6-3 show the viscosity-temperature variation for Elk-Point and Athabasca bitumen respectively. The oil density at room temperature of 21 ºC was 987 and 1000 kg/m3 for Elk Point and JACOS oil respectively.

80 Measured y = 262.22x 70 Linear Regression R2 = 0.9891

2 50

40 cc/min/cm

30 Q/A,

0 0 0.05 0.1 0.15 0.2 0.25 0.3 ∆P/L, psi/cm

Figure 6-1 Permeability measurement with AGSCO Sand

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100000 Measured Data Mehrotra's Corelation

10000

1000 cp

100 Viscosity,

1 0 50 100 150 200 250 300 Temperature, °C

Figure 6-2 Elk-Point viscosity profile 1000000 Measured Date Mehrotra Correlation 100000

10000 cp

1000 Visco,

100

1 0 50 100 150 200 250 300 Temperature, C

Figure 6-3 JACOS Bitumen viscosity profile

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6.2 First, Second, and Third Experiments 6.2.1 Production Results The first experiment was conducted to attest the base case performance in Cold Lake type of reservoir. Its well configuration was the classic 1:1 ratio which is a horizontal injector located above a horizontal producer. The vertical distance between the horizontal well-pair was 5 cm. This vertical distance was an arbitrary number but it is geometrically similar to the 5 m inter-well distance in 25 m thick formation. The model was packed using AGSCO 12-20 mesh sand and saturated with the Elk-Point oil (at irreducible water saturation) using the procedure described in Chapter 4. In order to fully saturate the model, ~19.5 kg of heavy oil was consumed which lead to initial oil saturation of ~86%. The saturation step took 12 days to complete. The second experiment used the same configuration and vertical inter-well distance. However instead of AGSCO 12-20 mesh sand, A-130 size glass beads were used to pack the model. These glass beads provided a permeability of 600-650 D. The third experiment was a repeat of second one and it was intended to test the feasibility of re-saturating the model using the Elk-Point oil. Unfortunately the re- saturating idea was not successful and the results were rather discouraging. The third experiment’s results were compared against the second experiment. The first and second experiments are compared using the oil production rate, cSOR, WCUT, and recovery factor in Figures 6-4, 6-5, 6-6 and 6-7. The oil rate in the first experiment remains mostly in a plateau between 3 to 5 cc/min following a short-lived peak of 11 cc/min. It shows another peak near the end that is related to blow-down. Compared to this, the maximum oil rate in the second experiment is much higher and the rate stays in vicinity of 15 cc/min for most of the run. As shown in Figure 6-4 the oil rate in the second experiment is about 3 times the rate in the first experiment. The first experiment was run continuously for 27 hours. The oil rate reached a peak at ~1 hr which was due to accumulation of heated oil above the producer as a result of initial attempt for steam trap control. The first steam breakthrough happened after 10 min of steam injection. During the run, we attempted to keep 10 ºC of steam trap over the production well by tracking the temperature profile of the closest thermocouple. However

172

controlling the steam trap by manually adjusting the production line valve was a tricky process which contributed to production rate fluctuations. The water-cut (WCUT) in first experiment stabilized at 65-70% during the first 10 hours of the test. The chamber at this time was expanding in the lateral directions and along the wells, but it had already reached to the top of the model. In fact at 0.2 PVinj (5 hours) the steam had touched the top of the model and it had started transferring heat to the environment through the top wall which increased the heat loss and caused more steam condensation. At 0.2 PVinj, the WCUT displays a small increase but the major change occurs at 10 hours when the chamber is fully developed at the top and the heat loss increases. It caused the WCUT to stabilize at a higher level of ~80%. After 25 hours of steam injection, first experiment was stopped and the production well was fully opened. The objective was to utilize the amount of heat that was transferred to the model and the rock. The comparison of the cSOR for both experiments is shown in Figure 6-5. The cSOR of the second experiment increased up to 1.5 cc/cc at about 0.1 PVinj and dropped sharply down to 0.5 at 0.2 PVinj while the oil rate increases during this period. The cSOR remained then remained at ~0.7 cc/cc up to end of second experiment. The explanation for the sharp increase in oil rate is the production of collected oil above the production well as the back pressure on the production well was reduced in controlling the sub-cool temperature. The cSOR in the first experiment is roughly three times higher than the cSOR in the second experiment. Figure 6-7 shows a comparison of the recovery factor for both experiments. Again the second experiment shows vastly superior performance. Figure 6-4, 6-5, 6-6 and 6-7 show that the formation permeability is a critically important parameter. In fact the only difference between the two results is the impact of the higher permeability which was about 2.50 times higher in the second run.

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25 First Experiment Second Experiment

n 15

10 Oil Rate, cc/mi Rate, Oil

0 0 5 10 15 20 25 30 Time, hr

Figure 6-4 Oil Rate: First and Second Experiment 8 First Experiment Second Experiment 7

cSOR, cc/cc 3

0 0 5 10 15 20 25 30 Time, hr

Figure 6-5 cSOR: First and Second Experiment

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100 First Experiment Second Experiment 90

40 WCUT, %

0 0 5 10 15 20 25 30 Time, hr

Figure 6-6 WCUT: First and Second Experiment 45 First Experiment Second Experiment 40

20 RF, %

0 0 5 10 15 20 25 30 Time, hr

Figure 6-7 RF: First and Second Experiment

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The second and third experiments are compared using oil rate, cSOR, WCUT, and recovery factor in Figures 6-8, 6-9, 6-10 and 6-11. The production profile of second and third experiments is totally different. The maximum oil rate, oil rate plateau, cSOR, WCUT, and RF of both experiments are not equal and do not even follow the same trend. These results lead to the conclusion that it is not possible to re-generate the initial conditions by oil-flooding the post SAGD run model. It is possible that due to the heating and cooling steps in SAGD and the blow-down period, in which some of the water flashes to steam, the wettability of sand may have changed and it caused a totally different production profile. The first experiment is considered as the base case for the well configuration study.

50 Second Experiment Third Experiment 45

n 30

20 Oil Rate, cc/mi Rate, Oil 15

0 0 2 4 6 8 10 1214 1618 20 Time, hr

Figure 6-8 Oil Rate: Second and Third Experiment

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3.5 Second Experiment Third Experiment 3.0

2.5

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1.5 cSOR, cc/cc cc/cc cSOR,

1.0

0.5

0.0 0 2 4 6 8 10 12 14 16 18 20 Time, hr

Figure 6-9 cSOR: Second and Third Experiment

80 Second Experiment Third Experiment 70

WCUT, % 30

0 0 2 4 6 8 10 12 14 16 18 20 Time, hr

Figure 6-10 WCUT: Second and Third Experiment

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45 Second Experiment Third Experiment 40

20 RF, %

0 0 2 4 6 8 10 12 14 16 18 20 Time, hr

Figure 6-11 RF: Second and Third Experiment

6.2.2 Temperature Profiles Figure 6-12 displays the temperature change with time at different locations along the injector during the first run. D15-D55 thermocouples (See Figure 4-5 for temperature probe design) are located on top of the injector in a row starting from the heel up to toe of the injector. The chamber grows along the length of the injector but D55, the thermocouples closet to the toe, never reaches the steam temperature. D45, which is 6 inches upstream of the toe, initially reaches the steam temperature but subsequently cools down. At ~40 min of the injection, the increased drainage of cold heavy oil from the heel zone suppresses the passage of steam to the toe of the injector. As a result, a sharp decrease in temperature at D55 is observed, which resulted in a drop in the oil production rate. During the entire run, the shape of chamber remains inclined towards the toe of the injector.

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100

Temperature, C Temperature, 40 D15 D25 20 D35 D45 D55 0 0 1 2 3 4 5 Time, hr

120

100

Temperature, C Temperature, 40 D15 D25 20 D35 D45 D55 0 0 4 8 12 16 20 Time, hr

Figure 6-12 Temperature profile along the injector at 5 and 20 hours: First Experiment

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The shape of steam chamber within the model using the recorded temperatures in the first experiment was determined at 0.1, 0.2, 0.5, 0.6, and 0.78 PVinj. The model was examined in 5 vertical cross-sections perpendicular the wellbore and in 7 horizontal layers parallel to the wellbore(A, B, D, D, E, F, and G, where G and A layers are located at the top and bottom of model respectively). The 7th layer (Layer A) is located somewhere below the production well; it does not contribute any interesting result and therefore is not shown in the plots. Figure 6-13 presents the schematic of the 7 layers and 5 cross sections of the physical model.

Cross Section 5 Cross Section 4 Cross Section 3 Cross Section 2 Cross Section 1 Layer G Layer F Layer E Layer D

Layer C Layer B Layer A Figure 6-13 Layers and Cross sections schematic of the physical model The cartoons in Figures 6-14, 15, 16, 17, and 18 represent the chamber extension across the top six layers. Figure 6-19 represents the vertical cross-section which is located at the inlet of the injector (cross section 1) at 0.78 PVinj. As the injection starts, the injector attempts to deliver high quality steam into the entire length of the wellbore. According to Figure 6-14, the injector fails to provide live steam at the toe. At 2 hours of steam injection, which is 0.1 PVinj, the chamber tends to rise vertically and grow laterally and along the well pairs. At 0.2 PVinj, the chamber above the injector heel has reached the top of the model but it is non-uniform along the length of well pair. After 16 hours of steam injection, the chamber is in slanted shape and the injectors tip has still not warmed up to steam temperature. When the steam injection is about to be stopped (0.78 PVinj), the chamber growth is continuing in all directions but it keeps its slanted shape and the injector fails in delivering the steam to the toe. Thus the classic well pattern was not able to provide high quality steam uniformly along the well

180 pair length and consequently created a slanted chamber along the length of the wells with maximum growth near the heel of the injector. Large amount of oil was left behind and the SAGD process ran at high cSOR. Continuing steam injection up to 0.78 PV did not make the chamber grow more along the wells. This configuration has been practiced in the industry since SAGD was introduced; however, it resulted in high cSOR and a slanted steam chamber with very little reservoir heating near the toe. The question then is whether this problem can be mitigated by using a modified well configuration.

Injector Producer

Figure 6-14 Chamber Expansion along the well-pair at 0.1 PVinj.

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Injector Producer

Figure 6-15 Chamber Expansion along the well-pair at 0.2 PVinj.

Injector Producer

Figure 6-16 Chamber Expansion along the well-pair at 0.5 PVinj.

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Injector Producer

Figure 6-17 Chamber Expansion along the well-pair at 0.6 PVinj.

Injector Producer

Figure 6-18 Chamber Expansion along the well-pair at 0.78 PVinj.

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Injector

Producer

Figure 6-19 Chamber Expansion Cross View at 0.78 PVinj: Cross-Section 1

6.2.3 History Matching the Production Profile with CMG/STARS The performance of the first experiment was history matched using the CMG STARS. It was attempted to honor the production profile just by changing few reasonable parameters. The thermal conductivity and heat capacity of the model frame (made of Phenolic resin) for the heat loss purpose was taken as wood thermal properties which was 4.65E-1 J/(cm*min*oC) and 7.65 J/(cm3*oC) respectively. These thermal properties control the heat loss from overburden and under-burden. The permeability and porosity of the model were 240 D and 0.34 respectively. The viscosity profile was the same as the one presented on Figure 6-2. The relative permeability to oil, gas, and water which lead to final history match are provided in Figure 6-20. The end points to water, gas, and oil were assumed to be 1. The results of match to oil, water, and steam injection profile are presented in Figure 6-21, 22, and 23 respectively. It should be noted that the initial constraint on the producer was the oil rate while the second constraint was steam trap. The Injector constraint was set as injection temperature with the associated saturation pressure.

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It is evident that the numerical model match of the experimental data is reasonable. However, another result that needs to be looked into is the chamber volume. As discussed earlier the chamber volume was calculated using thermocouple readings. The results were compared against the chamber volume reported by STARS in Figure 6-24. The match is reasonable during most the experiment except the last point of water production profile at 0.78 PVinj. At 22 hours, when the oil rate has a sharp increase, the numerical model is not able to honor the production profile which leads to a mismatch in chamber volume as well.

Figure 6-20 Water /Oil/Gas Relative Permeability: First Experiment History Match.

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14.0 6,000 Experimental Result-Oil Rate History Match-Oil Rate Experimental Result-Cum Oil History Match-Cum Oil 12.0 5,000

10.0

4,000

8.0

3,000

6.0 Oil (cm3/min) Rate SC CumulativeOil SC (cm3) 2,000

4.0

1,000 2.0

0.0 0 0 4 8 12 16 20 24 28 Time (hr) Figure 6-21 Match to Oil Production Profile: First Experiment

28 14,000 Experimental Result-Water Rate History Match-Water Rate Experimental Result-Cum Water History Match-Cum Water 24 12,000

20 10,000

16 8,000

12 6,000 WaterRate SC (cm3/min) Cumulative Water SC (cm3)

8 4,000

4 2,000

0 0 0 4 8 12 16 20 24 28 Time (hr)

Figure 6-22 Match to Water Production Profile: First Experiment

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30 18,000 Experimental Result-Steam (CWE) Rate History Match-Steam (CWE) Rate Experimental Result-Cum Steam (CWE) History Match-Cum Steam (CWE)

25 15,000

20 12,000

15 9,000

WaterRate SC (cm3/min) Cumulative Water SC (cm3) 10 6,000

5 3,000

0 0 0 4 8 12 16 20 24 28 Time (hr) Figure 6-23 Match to Steam (CWE) Injection Profile: First Experiment

4,000 Experimental Result History Match

3,500

3,000

2,500

2,000

1,500 Steam Chamber Volume SCTR (cm3)

1,000

500

0 0 4 8 12 16 20 24 28 Time (hr) Figure 6-24 Match to Steam Chamber Volume: First Experiment

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6.3 Fourth Experiment 6.3.1 Production Results The classic SAGD pattern in previous experiments was not able to provide high quality steam at the toe of the injector and create a uniform chamber. Therefore, the test ended up with low RF and high cSOR. Numerical simulations of Cold-Lake reservoir in chapter 5 showed that using the Reversed Horizontal Injector may improve the SAGD process performance. As a result the fourth experiment was designed to test the Reversed Horizontal Injector pattern using the same sand and bitumen as in the first experiment. The vertical distance between the horizontal well-pair was set at 10 cm. This vertical distance was chosen to improve the manual steam trap control by choking the production with a valve. The model was packed using AGSCO 12-20 mesh sand and a total of ~120 kg sand was carefully packed into the model which was gently vibrated during the packing process. The permeability of the packed model was ~260 D. The model was then evacuated and water was imbibed into the model using both pressure difference and gravity head. The water was then displaced by injecting the Elk-Point heavy oil. Approximately, 18.0 kg of heavy oil was consumed which lead to initial oil saturation of ~90%. Using the new well pattern, the model was depleted in 17 hours with low cSOR. The results of fourth experiments are compared against the first experiment and presented on Figure 6-25, 26, 27, and 28. The oil rate fluctuated during the first 3 hours (0.1 PVinj) of production but then it started to steadily increase and peaked at 15 cc/min. The oil rate then fell to a high plateau at 11 cc/min which lasted for almost 5 hours. Subsequently, the oil rate dropped down to 6 cc/min at 11 hours (0.3 PVinj) which is nearing the wind down stage. The fluctuation of oil rate before 0.1 PVinj is mostly due to the upward chamber growth which creates counter current steam vapor and condensate-heated oil flow. After 0.2 PVinj, the chamber is almost stable and it has reached the top and is growing sideways. This results in increasing and stable oil rate. As shown in Figure 6-25, changing the well configuration increases the oil rate almost 3 times higher than the base case (first experiment) oil rate. In addition the fourth experiment depletes the reservoir at higher cumulative oil volumes much faster (18 hours comparing to 27 hours) than the first

188 experiment. It should be kept in mind that this improvement is due to the well configuration only; the permeability and oil viscosity were kept constant in both experiments. The first steam breakthrough happened after 20 min of steam injection. During the run time, we tried to keep 10 ºC of steam trap over the production well by tracking the temperature profile of the closest thermocouple. The steam trap control was a difficult task during the chamber’s upward growth, however, once the chamber reach to the top of the model it was really smooth and easy. The cSOR in the fourth experiment stabilized at ~1 cc/cc after a sharp rise at early time of production. Comparing the cSOR profile of the first and fourth experiments, it can be concluded that not only the oil rate is 3 times higher in fourth experiment but also the cSOR is nearly 3 times lower, which makes the Reversed Horizontal Injector pattern doubly successful and a very promising option for future SAGD projects. In the fourth experiment, only half of the total produced liquid was water. The WCUT of fourth experiment remained at 40-60% during the entire test period. Figure 6-28 compares the RF of the first and fourth experiments. Fourth experiment was able to produce slightly higher than 50% of OOIP in 17 hours which demonstrate that the Reversed Horizontal Injector is able to deplete the reservoir much faster than the classic SAGD pattern and its final RF at the same time is much higher.

6.3.2 Temperature Profiles The temperature profile along the injector well is presented in Figure 6-29. Five thermocouple points of D31-D35, which are located on the injector, were chosen to validate the steam injection homogeneity along the injector. It can be seen that steam has been successfully delivered throughout the entire length of injector; after 6 hours, all thermocouples show temperatures at or above 100 oC. At 0.5 hrs a sharp temperature decrease occurred at the toe of the injector which resulted from the steam trap control procedure and imposing some extra back pressure on the production well. Figure 6-29 brings out a clear message: Reverse Horizontal Injector successfully delivers live steam throughout the entire length of injector.

189

16 First Experiment Fourth Experiment 14

10 n

6 Oil Rate, cc/mi Rate, Oil

0 0 5 10 15 20 25 30 Time, hr

Figure 6-25 Oil Rate: First and Fourth Experiment

8 First Experiment Fourth Experiment 7

cSOR, cc/cc 3

0 0 5 10 15 20 25 30 Time, hr

Figure 6-26 cSOR: First and Fourth Experiment

190

100 First Experiment 90 Fourth Experiment

40 WCUT, % WCUT,

0 0 5 10 15 20 25 30 Time, hr

Figure 6-27 WCUT: First and Fourth Experiment

60 First Experiment Fourth Experiment

30 RF, %

0 0 5 10 15 20 25 30 Time, hr

Figure 6-28 RF: First and Fourth Experiment

191

120

100

Temperature, C Temperature, 40

D31 D33 20 D35 D37 D39 0 0 1 2 3 Time, hr

120

100

60 Temperature, C Temperature, 40

D31 D33 20 D35 D37 D39 0 0 2 4 6 8 10 1214 16 Time, hr

Figure 6-29 Temperature profile along the injector at 3 and 16 hours: Fourth Experiment

192

In order to analyse the 3-D growth of the chamber along and across the well-pair, the chamber expansions along the well-pair were determined at 0.1, 0.2, 0.3, 0.4, and 0.5 PVinj in different layers. As before, the model was partitioned into 5 vertical cross- sections along the wellbore and 7 horizontal layers (A, B, D, D, E, F, and G, where G and A layers are located at the top and bottom of model respectively). Figures 6-30, 31, 32, 33, and 34 present the chamber extension across each layer. Figure 6-35 presents the vertical cross-section which is located at the inlet of the injector at 0.5 PVinj.

Injector Producer

Figure 6-30 Chamber Expansion along the well-pair at 0.1 PVinj.

193

Injector Producer

Figure 6-31 Chamber Expansion along the well-pair at 0.2 PVinj.

Injector Producer

Figure 6-32 Chamber Expansion along the well-pair at 0.3 PVinj.

194

Injector Producer

Figure 6-33 Chamber Expansion along the well-pair at 0.4 PVinj.

Injector Producer

Figure 6-34 Chamber Expansion along the well-pair at 0.5 PVinj.

195

According to Figures 6-30-34, the Reversed Horizontal Injector is able to introduce steam along the entire well length. Even at early steam injection period (0.1 PVinj) the entire injector length is warmed up close to the injection temperature. At this point, the steam chamber just needs to grow laterally and vertically. After 0.2 PVinj, the steam chamber almost approached the side walls, leading to the maximum oil rate and minimum WCUT. Sometimes after 0.3 PVinj when the chamber hits the side walls, the oil rate started to decrease, which leads to higher WCUT. As per Figures 6-31 and 6-32, the chamber grows somewhat faster at the heel of producer where the steam broke through initially but it was controlled by steam trap later on. In chapter 5 it was mentioned that the new pattern is able to create homogenous steam chamber along the well pairs. The plotted temperature contours using the recorded temperatures confirm that a uniform chamber was created on top of the well pairs. This fact also confirms that a uniform pressure drop existed between the injector and producer throughout the experiment period, which improves the SAGD process efficiency and leads to higher RF and lower cSOR, as shown earlier.

Injector

Producer

Figure 6-35 Chamber Expansion Cross View at 0.5 PVinj: Cross Section 1

196

6.3.3 History Matching the Production Profile with CMG/STARS The performance of the fourth experiment was history matched using the CMG STARS. As in the first experiment, few parameters were changed to get the best match of the experimental results. The thermal conductivity and volume capacity of the model frame (made of Phenolic resin) was the same as in the first experiment. The permeability and porosity of the model were 260 mD and 0.31 respectively. The viscosity profile is the same as the one presented on Figure 6-2. The relative permeability to oil, gas, and water which lead to final history match are provided on Figure 6-36. The end point to water, gas, and oil were 0.75, 0.35, and 1 respectively. The results of match to oil, water, and steam injection profile are presented on Figure 6-37, 38, and 39. It has to be noted that the initial constraint on producer was the oil rate while the second constraint was steam trap. The Injector constraint was set as injection temperature with the associated saturation pressure. It seems that the numerical model matches the experimental data reasonably well. The last result that needs to be looked into is the chamber volume. As discussed earlier the chamber volume was calculated using thermocouple readings. The results were compared against the chamber volume reported by STARS in Figure 6-40. The match is reasonable during the entire experiment except for the last point which is 0.5 PVinj. The difference can be due to possible error in simulation of the heat loss from the side walls of the model, which becomes a larger factor near the end.

197

Figure 6-36 Water /Oil/Gas Relative Permeability: Fourth Experiment History Match.

198

20 10,000 Experimental Result-Oil Rate History Match-Oil Rate Experimental Result-Cum Oil History Match-Cum Oil

16 8,000

12 6,000

8 4,000 Oil Rate SC (cm3/min)Oil Cumulative SC (cm3) Oil

4 2,000

0 0 0 4 8 12 16 20 Time (hr)

Figure 6-37 Match to Oil Production Profile: Fourth Experiment

15 10,000 Experimental Result-Water Rate History Match-Water Rate Experimental Result-Cum Water History Match-Cum Water

12 8,000

9 6,000

6 4,000 Water (cm3/min) Rate SC Cumulative Water SC (cm3)

3 2,000

0 0 0 4 8 12 16 20 Time (hr)

Figure 6-38 Match to Water Production Profile: Fourth Experiment

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18 12,000 Experimental Result-Steam (CWE) Rate History Match-Steam (CWE) Rate Experimental Result-Cum Steam (CWE) History Match-Cum Steam (CWE) 15 10,000

12 8,000

9 6,000

Water Rate SC (cm3/min) RateWater SC 6 4,000 Cumulative (cm3) Water SC

3 2,000

0 0 0 4 8 12 16 20 Time (hr)

Figure 6-39 Match to Steam (CWE) Injection Profile: Fourth Experiment

8,000 Experimental Result History Match

7,000

6,000

5,000

4,000

3,000

Steam Chamber Volume SCTR (cm3) (cm3) SCTR Volume Chamber Steam 2,000

1,000

0 0 4 8 12 16 20 Time (hr)

Figure 6-40 Match to Steam Chamber Volume: Fourth Experiment

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6.4 Fifth Experiment 6.4.1 Production Results Part of current study was aimed at optimizing the well configuration for Athabasca reservoir. Numerical simulations were conducted and promising well configurations were identified. It was considered desirable to test some of those configurations in the 3-D physical model. To start with a simple 1:1 pattern was needed to establish an experimental base case for the Athabasca study. Hence the fifth experiment was conducted to build the base case for further comparisons. The pattern includes only 2 horizontal wells; one located near the bottom of the physical model and the second well, which operates as an injector, was located 10 cm above the producer. The larger inter-well distance of 10 cm was used to overcome difficulties encountered in the manual steam trap control by manipulating the production line valve. The model was packed and saturated using the procedure described earlier. A total of ~120 kg sand was packed into the model and the permeability of the porous packed model was ~260 D. The bitumen used for saturating the model was provided by JACOS from Athabasca reservoir. In order to fully saturate the model, ~21.6 kg of bitumen was consumed, which gave the initial oil saturation of ~87%. The saturation step took 20 days to be completed. The fifth experiment was completed by injection of steam into the model via injector for 20 hrs. The oil rate, cSOR, WCUT, and RF are presented in Figures 6-41, 42, 43, and 44. The first steam break-through occurred approximately after one hour of steam injection. Controlling the steam break-through was really difficult throughout the entire experiment, once the back pressure on the production valve was reduced in order to let more oil come out, the steam jumped into the production well. As a result the back pressure had to be increased which caused the liquid level to raise in vicinity of the production well. The steam trap control never became fully stable throughout the experiment and was one of the biggest challenges during the test. Most of the fluctuations in oil production rate were due to steam trap control process. The cSOR in this experiment had a sharp rise, similar to the previous SAGD tests, and thereafter it stabilized at ~2 cc/cc. The sharp rise is due to vertical chamber growth.

201

At 0.5 PVinj (~15 hours) when the entire injector starts getting live steam, the cSOR drops sharply which explains the sharp increase in oil rate and high slope WCUT reduction. At 0.55 PVinj (16.3 hours) the steam broke through and to control the live steam production higher back pressure was imposed on the producer, which caused a sharp decrease in oil rate and a pulse in cSOR and WCUT profile. However after a while it was stabilized and the oil rate went back on the track again and the cSOR became stable. Water production in the fifth experiment was similar to the first test. According to Figure 6-43 almost 60% of the total produced liquid was water which is the expected behavior in SAGD. The RF profile is presented in Figure 6-44. Almost 50% of the bitumen was produced after 20 hours.

6.4.2 Temperature Profile Figure 6-45 displays the temperature profile along the injector. D15-D55 thermocouples (Figure 4-5) are located in a row starting from the heel up to toe of injector. At about 20 min of production, the chamber was collapsing down and the temperature was decreasing due to low injectivity, the steam was not able to penetrate into the bitumen saturated model. Consequently a sharp drop in the temperature profile was created, which resulted in reduced oil production rate as well. The back pressure was removed completely to facilitate steam flow and this allowed the steam to move again. However, the chamber along the producer and injector was unstable for the first 3 hours of production. The Chamber formed at the heel (about 2/5 of the injector length) in one hour and the temperature near the heel was stable to the end of this test, but the rest of the wellbore had difficulties in delivering steam into the model. After 10 hours the middle of the injector reached the steam temperatures while the rest of the wellbore (the 2/5th of injector length covering D45 and D55) got warmed up to steam temperature only after 16 hours had passed from the beginning the test. It can be seen that these temperature and chamber volume fluctuations result in oil production scatter.

202

20 Fifth Experiment 18

n 12

8 Oil Rate, cc/mi Rate, Oil

0 04 8 1 216 20 Time, hr Figure 6-41 Oil Rate: Fifth Experiment

3.0 Fifth Experiment

2.5

2.0

1.5 cSOR, cc/cc

1.0

0.5

0.0 0 4 8 121 62 0 Time, hr

Figure 6-42 cSOR: Fifth Experiment

203

90 Fifth Experiment 80

40 WCUT, %

0 0 4 8 12 16 20 Time, hr

Figure 6-43 WCUT: Fifth Experiment

60 Fifth Experiment

30 RF, %

0 0 4 8 12 16 20 Time, hr Figure 6-44 RF: Fifth Experiment

204

120

100

Temperature, C Temperature, 40

D15 D25 20 D35 D45 D55 0 0 1 2 3 4 5 Time, hr

120

100

Temperature, C Temperature, 40 D15 D25 20 D35 D45 D55 0 0 4 8 12 16 20 Time, hr

Figure 6-45 Temperature profile along the injector at 5 and 20 hours: Fifth Experiment

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In order to analyse the 3-D growth of the chamber along and across the well-pair, the chamber expanse along the well-pair were determined at 0.1, 0.2, 0.3, 0.4, 0.5, and 0.65 PVinj for different layers. As in the previous experiments, the model was partitioned into 5 vertical cross-sections along the well-pairs and 7 horizontal layers (A, B, D, D, E, F, and G, where G and A layers are located at the top and bottom of model respectively). Figures 6-46, 47, 48, 49, 50, and 51 present the chamber extension across each layer (only 6 layers are shown). Figure 6-51 represents the cross-section which is located at the heel of the injector at 0.5 PVinj.

Injector Producer

Figure 6-46 Chamber Expansion along the well-pair at 0.1 PVinj.

206

Injector Producer

Figure 6-47 Chamber Expansion along the well-pair at 0.2 PVinj.

Injector Producer

Figure 6-48 Chamber Expansion along the well-pair at 0.3 PVinj.

207

Injector Producer

Figure 6-49 Chamber Expansion along the well-pair at 0.4 PVinj.

Injector Producer

Figure 6-50 Chamber Expansion along the well-pair at 0.5 PVinj.

208

Injector Producer

Figure 6-51 Chamber Expansion along the well-pair at 0.65 PVinj.

Injector

Producer

Figure 6-52 Chamber Expansion Cross View at 0.65 PVinj: Cross Section1

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Figures 6-46 to 6-51 show that a major shortcoming of the classic pattern is uneven injection of steam along the injector length, which results in a slanted steam chamber. The injector is not able to supply live steam at the toe; most of the steam gets injected near the heel which causes an issue in steam trap control and lower productivity because the zone near the toe does not get heated. At the end of the physical model experiment, the process produced a slanted chamber which gave a reasonable RF but at higher cSOR.

6.4.3 Residual Oil Saturation The model was partitioned into three layers each had a thickness of approximately 8 cm and each layer comprised 9 sample locations. Figure 6-53 presents the schematic of the sample locations on each layer. 50 cm

7 8 9 50 cm 8cm 4 5 6

1 2 3

Figure 6-53 Sampling distributions per each layer of model The sand samples taken from these locations were analyzed in the Dean Stark apparatus. The volumetric balance on the taken samples, extracted oil and water, and the cleaned dried sand was used to calculate the residual oil and water saturations. Using the porosity, initial oil saturation, and residual oil saturation the φΔSo parameter can be calculated. In section 4.4.4, a range of 0.2-0.3 was assumed for the model while in a real reservoir, this number would typically be 0.15-0.2. Figure 6-54 presents the φΔSo of the middle layer, where the injector is located and the chamber has grown throughout the entire layer. The injector is located at X=25.5 cm and enters into the model at Y=0 cm. At X=25.5 cm, the maximum value of φΔSo is 23.3 which is located at the heel of the injector where most of steam was injected and resulted in the minimum residual oil saturation. Along the length of the injector the residual oil saturation increases which cause a decreasing trend in φΔSo value.

210

Mid Layer 28 26.7 26 23.3 22.2 23.9 24 25.1 22.0 22.3 22 21.7 % 20

So, 20.0

φΔ 18

14 8.5 12 25.5 10 Y, cm 8.5 42.5 25.5 X, cm 42.5

Figure 6-54 φΔSo across the middle layer: fifth experiment. The average φΔSo of the middle layer stays in the range of 0.2-0.3 which was assumed in the dimensional analysis section. The variations in the values of φΔSo are partly due to the process performance and partly due to the experimental errors. There can be some unevenness in the porosity due to the packing inhomogeneity and the calculation of residual saturation by extraction has some associated error. There are two higher values of residual oil saturations on the two corners close to the heel of injector which may be interpreted as the error associated with the measurement technique. The same plot was generated for the top layer in Figure 6-55. In figure 6-55 the residual oil saturation keeps the expected trend parallel to the injector at 8.5 and 25.5 cm on X-axis, however the trend fails on 42.5 cm location on X-axis. Again in one corner close to the injector’s heel the residual oil saturation is unexpectedly high. The average residual saturation of the top layer still falls in the expected range listed the dimensional analysis section.

211

Top Layer

22.0 22.4 24 22.8 24.4 21.0 22 21.1 21.2

20 % 19.7 20.0

So, 18 φΔ 16

14 8.5 12 25.5 10 Y, cm 8.5 42.5 25.5 X, cm 42.5

Figure 6-55 φΔSo across the top layer: fifth experiment.

6.4.4 History Matching the Production Profile with CMG/STARS In order to analyze and study the performance of the fifth experiment under numerical simulation, its production profile was history matched using the CMG-STARS. Only the relative permeability curves, porosity, permeability and the production constraint were changed to get the best match of the experimental results. The thermal conductivity and heat capacity of the model frame (made of Phenolic resin) was the same as in the previous experiment. The permeability and porosity of the model were 260 mD and 0.34 respectively. The viscosity profile was the same as the one presented on Figure 6-3 which is the measured and modeled viscosity profile for Athabasca bitumen. The relative permeability to oil, gas, and water which gave the final history match is provided in Figure 6-56. The end points to water, gas, and oil were assumed to be 0.3, 0.14, and 1 respectively. The results of the match to oil, water, and steam production profile are presented in Figure 6-57, 58, and 59. It should be noted that the initial constraint on producer was the oil rate while the second constraint was steam trap. The Injector constraint was set as injection temperature with the associated saturation pressure.

212

It seems that the numerical model matches the experimental data quite well. However one last result that needs to be looked into is the chamber volume. As discussed earlier the chamber volume was calculated using thermocouple readings. The results were compared against the chamber volume reported by STARS in Figure 6-60. This match is a bit off during the entire experiment. Since there were too many issues in steam trap control and the chamber was expanding erratically during the experiment, it was not surprising that the chamber volume history was not well-matched.

Figure 6-56 Water /Oil/Gas Relative Permeability: Fifth Experiment History Match.

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20.0 10,000 Experimental Result: Oil Rate History Match: Oil Rate Experimental Result: Cum Oil History Match: Cum Oil

8,000 15.0

6,000

10.0

4,000 Oil Rate SC (cm3/min)Oil Cumulative SC (cm3) Oil

5.0 2,000

0.0 0 0 200 400 600 800 1,000 1,200 Time (min)

Figure 6-57 Match to Oil Production Profile: Fifth Experiment

30 15,000 Experimental Result: Water Rate History Match: Water Rate Experimental Result: Cum Water History Match: Cum Water

24 12,000

18 9,000

12 6,000 Water (cm3/min) Rate SC Cumulative Water SC (cm3)

6 3,000

0 0 0 200 400 600 800 1,000 1,200 Time (min)

Figure 6-58 Match to Water Production Profile: Fifth Experiment

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42 18,000 Experimental Result: Steam (CWE) Rate History Match: Steam (CWE) Rate Experimental Result: Cum Steam (CWE) History Match: Cum Steam (CWE) 35 15,000

28 12,000

21 9,000

Water Rate SC (cm3/min) RateWater SC 14 6,000 Cumulative (cm3) Water SC

7 3,000

0 0 0 200 400 600 800 1,000 1,200 Time (min)

Figure 6-59 Match to Steam (CWE) Injection Profile: Fifth Experiment

8,000 History Match Experimental Result

6,000

4,000

Steam Chamber Volume SCTR (cm3) (cm3) SCTR Volume Chamber Steam 2,000

0 0 200 400 600 800 1,000 1,200 Time (min)

Figure 6-60 Match to Steam Chamber Volume: Fifth Experiment

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6.5 Sixth Experiment 6.5.1 Production Results The classic SAGD pattern in fifth experiment showed the expected performance of a 1:1 ratio SAGD well pattern. Although it provides commercially viable performance in the field, some of the issues with it are: low oil rate, not very high RF, high WCUT, high cSOR. In the physical model experiments, it gives very long run time due to slow drainage rate. In addition to these difficulties, if the temperature contour maps were studied carefully, the steam chamber is not homogenous and it is slanted along the well pairs. Several numerical simulations that were run on Athabasca reservoir and were presented in Chapter 5 showed the Reversed Horizontal Injector pattern to be superior to the classic pattern. It was shown that the new pattern is able to improve the performance of the SAGD process. The new well configuration was tested in Cold Lake type of reservoir in the fourth experiment, and it showed large improvement, that was considerably more pronounced than the numerical simulation result. Therefore it would be desirable to test the new well configuration under the Athabasca type of reservoir conditions as well. Hence, the sixth experiment was designed to test the Reversed Horizontal Injector pattern under Athabasca conditions. As in the preceding base case experiment, 10 cm vertical inter-well distance was used. The same AGSCO 12-20 mesh sand used to create the porous medium in the model. The permeability and porosity of the porous packed model were ~260 D and 0.31 respectively. In order to fully saturate the model, ~18.0 kg of JACOS bitumen was consumed which lead to initial oil saturation of ~90%. Using the new well pattern, the model was depleted in 13 hours with relatively low cSOR. The results of this experiment is compared against the fifth experiment and presented in Figures 6-61, 62, 63, and 64.

216

25 Fifth Experiment Sixth Experiment

10 Oil Rate,cc/min

0 0 4 8 12 16 20 Time, hr

Figure 6-61 Oil Rate: Fifth and Sixth Experiment 3.5 Fifth Experiment Sixth Experiment 3.0

2.5

2.0

1.5 cSOR, cc/cc

1.0

0.5

0.0 0 4 8 12 16 20 Time, hr Figure 6-62 cSOR: Fifth and Sixth Experiment

217

90 Fifth Experiment Sixth Experiment 80

40 WCUT, %

0 0 4 8 12 16 20 Time, hr Figure 6-63 WCUT: Fifth and Sixth Experiment

60 Fifth Experiment Sixth Experiment

30 RF, %

0 0 4 8 121 62 0 Time, hr Figure 6-64 RF: Fifth and Sixth Experiment

218

The oil production profile of the sixth experiment is compared against the fifth experiment in Figure 6-61. The oil rate profile has some fluctuations throughout the experiment. Before 0.1 PVinj (~3 hours), the steam chamber is growing upward and laterally which makes the chamber to be somewhat unstable due to the counter current flow. Consequently the liquid production shows fluctuations which can be observed in Figure 6-61. The oil rate fluctuates between 5 and 10 cc/min. The steam chamber reaches to top of the model somewhere between 0.1 and 0.2 PVinj (~4.5 hours) which leads to a sharp increase in the oil rate. Then the average oil rate somewhat stabilized at 15 cc/min with a maximum and minimum of 20 and 10 cc/min respectively. At 0.4 PVinj where the chamber hits the adjacent sides, the oil rate gets another jump but since the chamber cannot spread anymore and extra heat loss occurs from the sidewalls, the oil rate drops down at 0.5 PVinj (11 hours). A part of the oil rate fluctuation originated from the manual control of the steam trap using the valve adjustments. The Reverse Horizontal Injector displays a dramatic improvement, where the oil rate of this experiment is nearly twice that of the fifth experiment (which used the classic pattern). The first steam breakthrough happened after 50 min of steam injection. During the run, we tried to keep 10 ºC of steam trap over the production well by tracking the temperature profile of the closest thermocouple. Since the pressure drop along the well- pair was almost uniform, the steam trap control was relatively simple. In this experiment the cSOR increased sharply during the rising chamber phase of the process. It then decreases smoothly to ~1.5 cc/cc. A comparison of the cSOR profiles of the fifth and the sixth experiments is provided in Figure 6-62. The sixth experiment displays lower cSOR, almost half of the fifth experiment. The WCUT in sixth experiment is 50-60% and is compared against the fifth experiment in Figure 6-63. It can be seen that the well configuration in sixth experiment yields less heat loss which caused the WCUT to be lower compared to the fifth experiment. Figure 6-64 demonstrates the RF of these two experiments. According to Figure 6-64, the Reversed Horizontal Injector can provide higher RF in shorter period compared to the classic well pattern. In the sixth experiment, after 13 hours, 55% of the OOIP had been produced while at the same time only 25% of OOIP had been produced by the classic pattern in the fifth experiment. The combination of oil rate, cSOR, WCUT, and RF profile makes the Reversed Horizontal Injector a very

219

promising replacement for the classic pattern in SAGD process in Athabasca type of reservoir.

6.5.2 Temperature Profiles Figure 6-65 displays the temperature profiles at the injector for the first 4 and first 14 hours of steam injection. D31-D39 thermocouples (Figure 4-5) are located in a row starting from the heel up to toe of the injector. The first four points get to steam temperature in less than one hour. The last point which is located at the toe of the injector warmed up to steam temperature after 2 hours. This made the steam trap control very easy since the steam broke through to the production well at the producer’s toe instead of its heel. The chamber growth in the model was studied by determining the chamber expansions in different layers at 0.1, 0.2, 0.3, 0.4, 0.5 and 0.6 PVinj. Out of the 7 layers (A, B, D, D, E, F, and G where G and A layers are located at the top and bottom of model respectively) only 6 layers are included in the plots since the 7th layer (Layer A) is located somewhere below the production well, and does not show any interesting result. Figures 6-66, 67, 68, 69, 70, and 71 represent the chamber extension across each layer. Figure 6-72 represent the cross-section which is located at the inlet of the injector at 0.6 PVinj. At 0.1 PVinj, the chamber has just formed around the injector in the E layer which is located above the injector. At 0.2 PVinj, the chamber hit the top of the model and it started growing only laterally. At 0.3 PVinj, it approached the vicinity of the side walls but it is at 0.4 PVinj when the steam chamber reaches the side walls. From 0.4 PVinj till 0.6 PVinj, the steam chamber grows downward on the side walls, which is reflected in the chamber development on C and B layers. According to Figures 6-66 to 6-71, the Reversed Horizontal Injector pattern delivers high quality steam throughout the injector soon after the steam injection starts. It successfully develops a uniform chamber laterally while it continuously supplies the live steam at the toe of the injector. This results in low cSOR and WCUT while the oil rate and RF are dramatically higher.

220

120

100

Temperature, C Temperature, 40

D31 D33 20 D35 D37 D39 0 0 1 2 3 4 Time, hr

120

100

60 Temperature, C Temperature, 40

D31 D33 20 D35 D37 D39 0 0 2 4 6 8 10 12 14 Time, hr Figure 6-65 Temperature profile along the injector at 4 and 14 hours: Sixth Experiment

221

Injector Producer

Figure 6-66 Chamber Expansion along the well-pair at 0.1 PVinj.

Injector Producer

Figure 6-67 Chamber Expansion along the well-pair at 0.2 PVinj.

222

Injector Producer

Figure 6-68 Chamber Expansion along the well-pair at 0.3 PVinj.

Injector Producer

Figure 6-69 Chamber Expansion along the well-pair at 0.4 PVinj.

223

Injector Producer

Figure 6-70 Chamber Expansion along the well-pair at 0.5 PVinj.

Injector Producer

Figure 6-71 Chamber Expansion along the well-pair at 0.6 PVinj.

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Injector

Producer

Figure 6-72 Chamber Expansion Cross View at 0.5 PVinj

6.5.3 Residual Oil Saturation As in the fifth experiment, the model was partitioned into three layers each has a thickness of approximately 8 cm and each layer comprised 9 sample locations. Figure 6 52 presents the schematic of the sample locations on each layer. The same methodology presented in section 6.4.3 was followed to calculate φΔSo over each layer of the model. Figure 6-73 presents the φΔSo of the middle layer, where the injector is located and the chamber has grown throughout the entire layer. The injector is located at Y=25.5 cm and enters into the model at X=50 cm. The average φΔSo over the middle layer is in the range of 12-14 %. The run time of sixth experiment was short and compared to the rest of tests and it lead to higher residual oil saturation over the middle layer. At Y=25.5 cm, which is along the length of the injector, the residual oil saturation has a fairly constant values showing a flat trend in φΔSo value. The maximum oil saturation is located on top of the injector’s heel which is right above the producer’s toe in the reversed horizontal injector pattern. There are two high values of residual oil saturations on the two corners close to the toe of injector which may be due to less depletion near the two corners. The same plot was generated for the top layer in

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Figure 6-74. The distribution of the residual oil saturation over the top layer is more uniform than the middle layer which means steam was able to sweep out more oil and the chamber was spread uniformly throughout the entire layer. The average residual saturation of the top layer still falls in the expected range of the dimensional analysis section.

Mid Layer 13.6 14 13.2

13 13.1 12.9 12.6 12.7 %

12.3 12.1 So, 12 12.2 φΔ

11 8.5

25.5 10 Y, cm 8.5 42.5 25.5 X, cm 42.5

Figure 6-73 φΔSo across the middle layer: sixth experiment.

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Top Layer

26 22.9 25.3 22.3 24 23.5 23.7 23.5 22.5 22 22.5 22.2 20 %

So, 18 φΔ 16

14 8.5 12 25.5 10 Y, cm 8.5 42.5 25.5 X, cm 42.5

Figure 6-74 φΔSo across the top layer: sixth experiment.

6.5.4 History Matching the Production Profile with CMG/STARS The results of sixth experiment were history matched using CMG-STARS. It was tried to keep the consistency between the sixth and previous numerical models. Therefore, the thermal conductivity and heat capacity of the model frame (made of Phenolic resin) were kept the same as in first, fourth, and fifth experiments. The permeability and porosity of the model were 260 mD and 0.31 respectively. The viscosity profile was the same as the one presented on Figure 6-3. The relative permeability to oil, gas, and water which lead to final history match are shown in Figure 6-75. The end point to water, gas, and oil were assumed to be 0.17, 0.08, and 1 respectively. The results of match to oil, water, and steam production profile are presented on Figure 6-76 to 6-78. As in the previous simulations, the initial constraint on producer was the oil rate while the second constraint was steam trap. The Injector constraint was set as injection temperature with the associated saturation pressure. In this case also, the numerical model matched the experimental data reasonably well. The match of the chamber volume, whose

227 experimental values were calculated using thermocouple readings while the simulated values were as reported by STARS, is shown in Figure 6-79. The match turned out to be nearly perfect.

Figure 6-75 Water /Oil/Gas Relative Permeability: Sixth Experiment History Match.

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24 12,000 Experimental Result: Oil Rate History Match: Oil Rate Experimental Result: Cum Oil History Match: Cum Oil 20 10,000

16 8,000

12 6,000 Oil Rate SC (cm3/min)Oil

8 4,000 Cumulative SC (cm3) Oil

4 2,000

0 0 0 2 4 6 8 10 12 14 Time (hr)

Figure 6-76 Match to Oil Production Profile: Sixth Experiment

30 12,000 Experimental Result: Water Rate History Match: Water Rate Experimental Result: Cum Water History Match: Cum Water 25 10,000

20 8,000

15 6,000

Water (cm3/min) Rate SC 10 4,000 Cumulative Water SC (cm3)

5 2,000

0 0 0 2 4 6 8 10 12 14 Time (hr)

Figure 6-77 Match to Water Production Profile: Sixth Experiment

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28 14,000 Experimental Result: Steam (CWE) Rate History Match: Steam (CWE) Rate Experimental Result: Cum Steam (CWE) History Match: Cum Steam (CWE) 24 12,000

20 10,000

16 8,000

12 6,000 Water Rate SC (cm3/min) RateWater SC Cumulative (cm3) Water SC 8 4,000

4 2,000

0 0 0 2 4 6 8 10 12 14 Time (hr)

Figure 6-78 Match to Steam (CWE) Injection Profile: Sixth Experiment

8,000 Experimental Result History match 7,000

6,000

5,000

4,000

3,000

Steam Chamber Volume SCTR (cm3) (cm3) SCTR Volume Chamber Steam 2,000

1,000

0 0 2 4 6 8 10 12 14 Time (hr)

Figure 6-79 Match to Steam Chamber Volume: Sixth Experiment

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6.6 Seventh Experiment 6.6.1 Production Results The simulation study, presented in Chapter 5, showed that the inclined injector may provide some advantages over the classic pattern. This pattern was able to supply high quality steam to the toes of injector and producer, because it has higher pressure gradient near the toes. Note that the producer was horizontal while the injector was dipping down with smaller vertical inter well distance at the toe of injector and producer than the vertical distance between the well pairs at the heel. The chamber was developed initially near the toe and grew backward towards the injector’s heel. This pattern demonstrated some improvement in SAGD process which was persuasive enough to warrant its testing in the physical model. The inclined injector pattern was tested in Athabasca type of reservoir in the seventh experiment. The performance of the inclined injector well was compared against the results of the fifth and the sixth experiments, both of which also represented Athabasca reservoir. The schematic of the inclined injector pattern is displayed in figure 6-80. The vertical inter well distance at the heel and toe of injector were 18 and 5 cm respectively.

Injector

18 cm 5 cm Producer Figure 6-80 Schematic representation of inclined injector pattern

The model was packed using the same AGSCO 12-20 mesh sand which was used in the previous experiments. The initial porosity of the porous packed model was 0.33. The model was initially evacuated and thereafter was saturated with water. Unfortunately, although a pressure leak test was conducted before water imbibition, the water penetrated into the edges of the model and started leaking. The model was drained out of water. However fixing this leak took 6 months while the model was still full of sand. The water saturation was repeated four times after the model leak was fixed and gave consistent results. Eventually the water was displaced out of porous media using injection of JACOS bitumen from Athabasca reservoir. Approximately 19.8 kg of bitumen was

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consumed which lead to initial oil saturation of ~96%. This number was higher than previous tests. The saturation step took 7 days to be completed. The performance of the inclined injector is compared against the classic pattern and reversed horizontal injector in Figures 6-81, 82, 83, and 84. Similar to the previous experiments the oil rate profile has some fluctuations throughout the experiment, it goes as high as 35 cc/min and as low as 7 cc/min with the average of 20-25 cc/min. After 8 hours (0.4 PVinj) the oil rate dropped down to 15 cc/min and thereafter to 10 cc/min at 0.5 PVinj. The oil rate produced by the inclined injector is higher than the classic pattern and surprisingly even higher than the Reversed Horizontal Injector. The improved performance can also be observed in the cSOR profile in Figure 6-82, where its cSOR stabilizes at 1.0 cc/cc. Figure 6-83 compares the WCUT of the three well patterns. The portion of oil in total fluid in inclined injector has a small improvement with respect to the Reversed Horizontal Injector but it shows quite impressive improvement in comparison with the classic pattern. The final RF, shown in Figure 6-84 was similar to that in the sixth experiment but in considerably shorter period, which makes its performance even better. It depleted 53% of the OOIP in 10 hours. During the seventh experiment run time, it was observed that the chamber growth was not the same as was seen in numerical modeling. Based on the simulation results, the chamber was supposed to start from the injector and producer toes and grow back towards the injector and producer heels. However it grew from middle of injector and was expanding laterally and towards the toe and heel of injector. To further analyse the performance, the temperature contours in different layers of the model and the temperature profile between the injector and producer need to be examined. There was a row of thermocouples parallel to the producer but 5 cm above it. The temperatures recorded at these points (their location is displayed in Figure 6-85) are presented in Figure 6-86.

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40 Fifth Experiment Sixth Experiment 35 Seventh Experiment

15 Oil Rate,cc/min

0 0 4 8 12 16 20 Time, hr

Figure 6-81 Oil Rate: Fifth and Sixth Experiment 3.5 Fifth Experiment Sixth Experiment 3.0 Seventh Experiment

2.5

2.0

1.5 cSOR, cc/cc

1.0

0.5

0.0 0 4 8 12 16 20 Time, hr

Figure 6-82 cSOR: Fifth and Sixth Experiment

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90 Fifth Experiment Sixth Experiment 80 Seventh Experiment

40 WCUT, %

0 0 4 8 12 16 20 Time, hr

Figure 6-83 WCUT: Fifth and Sixth Experiment 60 Fifth Experiment Sixth Experiment Seventh Experiment 50

30 RF, %

0 0 4 8 121 62 0 Time, hr

Figure 6-84 RF: Fifth and Sixth Experiment

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6.6.2 Temperature Profile Figure 6-85 displays the location of D15-55 thermocouples with respect to injector and producer locations. D15-D55 thermocouples (Figure 4-5) are located in a row starting from the location 5 cm above the heel of producer up to toe of the injector (which is 5 cm above the toe of producer).

Injector

18 cm D25 D45 D15 D35 D55 5 cm Producer

Figure 6-85 Schematic of D5 Location in inclined injector pattern.

As per numerical simulation results, it was expected that the chamber grows from the injectors toe. The minimum resistance against the steam flow is at the injector and producer toes where the distance is shortest between the well pairs. Hence it should lead to chamber growth at the injector's toe which was confirmed by the simulation study. Therefore, within the five thermocouples, the D55 should show an early rise in its temperature profile and while as the chamber grows backward, the rest of thermocouples on the chamber path, i.e., D45, D35, D25, and D15 will subsequently warm up to steam temperature. Figure 6-86, shows that the order of temperature increase at D55 thermocouple is not consistent with the numerical results and the pattern concept. The green and blue lines represent D35 and D45 respectively. The D35 shows the earliest increase on temperature profile followed by the D45 which had the second highest temperature at early time of injection period. It seems that the chamber growth started near the middle of the physical model. One of the contributing reasons for this discrepancy appears to be the high heat loss near the toe of the injector, since it was very close to the wall of the model.

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120

100

60 Temperature, C Temperature, 40

D15 D25 20 D35 D45 D55 0 0 2 46 81 0 Time, hr

120

100

Temperature, C Temperature, 40

D15 D25 20 D35 D45 D55 0 0 1 2 3 4 Time, hr Figure 6-86 Temperature profile in middle of the model at 4 and 10 hours: Seventh Experiment

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In order to better understand the chamber shape and growth within the model, the temperature contours were generated in different layers at 0.1, 0.2, 0.3, 0.4, 0.5 and 0.6 PVinj. Figures 6-87, 88, 89, 90, and 91 represent the chamber extensions in six different layers. Figure 6-86 represents the vertical cross-section which is located at the inlet of the injector at 0.5 PVinj. The unusual chamber growth, mentioned earlier occurred before 2 hours of injection, i.e. at PVinj of less than 0.1. However the unusual chamber growth left its mark on the temperature contours at 0.1, 0.2, and 0.3 PVinj. At 0.1 PVinj, the chamber is above the heel of the injector in the top layer (Layer-G) but near the toe of the producer in the layer containing the producer (Layer-B). The temperature contours representing the chamber in G, F and E layers are a bit unusual and appear to follow the inclination of the inclined injector. At this early time in the run, the chamber already covers nearly the full length of the model in D layer. The D layer represents the D55 thermocouple presented in Figure 6-85. In the classic well configuration, the injector would be located in this layer. At 0.2 PVinj, the chamber is well developed at the top of the model and it covers half of the top layer (Layer-G). The temperature contours in Figure 6-88 shows that the hottest spot in all layers is located on the heel side of the wells which is at mark 10 on the y-axis scale. The temperature contours in G, F, and E layers in Figures 6-89 and 6-90 show that the chamber growth is from the heel towards the toe. In fact some unheated spots can be noticed on the toe side in some layers while the heel side is heated up to steam temperature in all layers. It is also apparent that at this point in the run the chamber covers a large fraction of the total volume. Compared to the volume of chamber in the classic pattern at 0.2 PVinj, shown in Figure 6-47, the chamber is substantially larger. The production profile confirmed that the inclined injector may have significant advantage over the classic pattern but the experimental temperature profiles leave some unanswered question concerning why the chamber grows in the manner observed in this experiment. The expected result from the numerical simulation model was a systematic growth starting from the toe region and progressing toward the heels of the wells. The experiment showed a more uniform development of the chamber. Actually, the experiment showed better than expected performance and if this can be confirmed in a field trial, the inclined injector would become the well configuration of choice.

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Figure 6-87 Chamber Expansion along the well-pair at 0.1 PVinj.

Figure 6-88 Chamber Expansion along the well-pair at 0.2 PVinj.

238

Figure 6-89 Chamber Expansion along the well-pair at 0.3 PVinj.

Figure 6-90 Chamber Expansion along the well-pair at 0.4 PVinj.

239

Figure 6-91 Chamber Expansion along the well-pair at 0.5 PVinj.

Injector

Producer

Figure 6-92 Chamber Expansion Cross View at 0.5 PVinj: Cross Section 1

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6.6.3 Residual Oil Saturation As in the previous experiment, the model was partitioned into three layers, each having a thickness of approximately 8 cm, and each layer comprised 9 sampling locations. Figure 6-53 presents the schematic of the sample locations on each layer. The same methodology presented in section 6.4.3 was followed to calculate φΔSo over each layer of the model. Figure 6-93 presents the φΔSo of the top layer, where the chamber has grown throughout the entire layer. The injector is located at X=25.5 cm and enters into the model at Y=0 cm. The average φΔSo in the top layer is in the range of 21-26 %. At Y=25.5 and 42.5 cm, where the injector approaches the producer, the residual oil saturation is low. However at the heel of injector, Y=8.5 cm, due to large spacing between injector and producer, higher residual oil saturation was observed. According to Figure 6-93 chamber was fairly homogenous throughout the top layer. The average residual saturation of the top layer falls in the expected range of the dimensional analysis section.

Top Layer 25.7 28 26.7 25.9 26.2 26 26.5 22.8 21.6 25.4 24 25.1

22 % 20 So,

φΔ 18

14 8.5 12 25.5 10 Y, cm 8.5 42.5 25.5 X, cm 42.5

Figure 6-93 φΔSo across the top layer: seventh experiment.

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6.6.3 History Matching the Production Profile with CMG/STARS The production and chamber volume profile of the seventh experiment was history matched using CMG-STARS. Since the sand type and the model was the same as in the previous tests, the thermal conductivity and heat capacity of the model frame (made of Phenolic resin) was kept the same as in previous tests. The permeability and porosity of the model were 260 mD and 0.33 respectively. The viscosity profile was the same as the one presented on Figure 6-3. The relative permeability to oil, gas, and water which lead to final history match are presented in Figure 6-94. The end point to water, gas, and oil were assumed to be 0.15, 0.005, and 1 respectively. The relative permeability to the gas was really low, without which matching the steam injection and water production rate was impossible. Table 6-2 compares the end point of water, gas, and oil which have been used in history matching of fifth, sixth, and seventh experiments. According to this table the end point to the gas relative permeability in seventh experiment is artificially low. It was attempted to match the production profile with higher gas relative permeability, but it was simply not possible. Eventually it was decided to keep the end point value of the gas relative permeability as low as 0.005 and add this to the surprising behavior of the seventh experiment. Physically, there is no valid reason why the gas relative permeability should be so low. Table 6-2 Summary water/gas/oil relative permeability end points of 5th, 6th, and 7th experiments. Experiment End Point gas Rel. End Point water End Point Oil Rel. Perm. Rel. Perm. Perm. Fifth 0.30 0.14 1.00 Sixth 0.075 0.17 1.00 Seventh 0.005 0.15 1.00 The results of history match to oil, water, and steam production profile are presented in Figure 6-95, 96, and 97. As in previous tests, the initial constraint on the producer was the oil rate while the second constraint was steam trap. The Injector constraint was set as injection temperature with the associated saturation pressure. It is apparent that the numerical model’s match to experimental results is reasonable but it is based on using unrealistically low gas relative permeability. As discussed earlier for previous experiments, the chamber volume was calculated using the thermocouple

242 readings. The results were compared against the chamber volume reported by STARS in Figure 6-98. The match was not very good in spite of the low gas relative permeability. Table 6-2 also shows that the gas relative permeability was considerably smaller in history match of the sixth experiment compared to the fifth experiment. This too is an artificial adjustment, since the gas relative permeability would be expected to be similar in experiments using the same rock-fluid system. It is partly due to the weakness of the simulator in modeling two-phase flow in the wellbore.

Figure 6-94 Water /Oil/Gas Relative Permeability: Seventh Experiment History Match.

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42 12,000 Experimental Result: Oil Rate History Match: Oil Rate Experimental Result: Cum Oil History Match: Cum Oil 35 10,000

28 8,000

21 6,000 Oil Rate SC (cm3/min)Oil

14 4,000 Cumulative SC (cm3) Oil

7 2,000

0 0 0 2 4 6 8 10 12 Time (hr)

Figure 6-95 Match to Oil Production Profile: Seventh Experiment

25 10,000

20 8,000

15 6,000

10 4,000 Water (cm3/min) Rate SC Cumulative Water SC (cm3)

5 2,000

Experimental Result: Water Rate History Match: Water Rate Experimental Result: Cum Water History Match: Cum Water 0 0 0.0 2.0 4.0 6.0 8.0 10.0 12.0 Time (hr)

Figure 6-96 Match to Water Production Profile: Seventh Experiment

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30 12,000 Experimental Result: Steam (CWE) Rate History Match: Steam (CWE) Rate Experimental Result: Cum Steam (CWE) History Match: Cum Steam (CWE) 25 10,000

20 8,000

15 6,000

Water Rate SC (cm3/min) RateWater SC 10 4,000 Cumulative (cm3) Water SC

5 2,000

0 0 0 2 4 6 8 10 12 Time (hr)

Figure 6-97 Match to Steam (CWE) Injection Profile: Seventh Experiment

10,000 Experimental Result History Match

8,000

6,000

4,000 Steam Chamber Volume SCTR (cm3) (cm3) SCTR Volume Chamber Steam

2,000

0 0 2 4 6 8 10 12 Time (hr)

Figure 6-96 Match to Steam Chamber Volume: Seventh Experiment

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The last two physical model tests show that both new well configurations (Reversed Horizontal Injector and Inclined Injector) are very promising for Athabasca reservoir. Their performance in the physical model tests is vastly superior to that of the classic pattern. The field scale numerical simulation presented in Chapter 5 was not able to capture this dramatic improvement in the performance. It is difficult to say with certainty whether the physical model results or the numerical simulation results would be closer to the field performance of these well configurations. This question can be answered directly by a field trial of the modified well configurations. Therefore, it is strongly recommended that both of these well configurations should be evaluated in field pilots.

CHAPTER 7 COCLUSIONS AND RECOMMENDATIONS

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7.1 Conclusions

In this research homogenous reservoir models with averaged properties typical of Athabasca, Cold Lake, and Lloydminster reservoirs were constructed for each reservoir to investigate the impact of well configuration on the ultimate recovery obtained by the SAGD process. The following conclusions are based on the results of the numerical simulation study: • Six well patterns were studied for Athabasca reservoir including: Basic Pattern, Vertical Injectors, Reversed Horizontal Injector, Inclined Injector, Parallel Inclined Injector, and Multi-Lateral Producer. The Vertical Injectors pattern performed poorly in Athabasca reservoir since the pattern with 3 vertical injectors provided the same recovery factor as the base case but its steam oil ratio was much higher. The Reversed Horizontal Injector pattern and the inclined injector provided higher recovery factor but same steam oil ratio in comparison with the base case pattern. Their results suggest that there is potential benefit for reversing or inclining the injector. These two cases were considered candidates for further evaluations in the physical model set-up. The Parallel Inclined Injectors configuration provided higher recovery factor, but the cSOR was increased. The Multi-Lateral provided a small benefit in recovery factor but not in cSOR. Therefore out of the six patterns only the Reserved Horizontal Injector and Inclined Injector were selected for further study in Athabasca reservoir. • In the Cold Lake reservoir, eight patterns were examined: Basic Pattern, Offset Horizontal Injector, Vertical Injectors, Reversed Horizontal Injector, Parallel Inclined Injector, Parallel Reversed Upward Injector, Multi-Lateral Producer, and C-SAGD. Offsetting the injector provided some benefit in improving the RF but at the expense of higher cSOR. The results of vertical injectors were the same as in Athabasca. The three vertical injectors pattern was able to deplete the reservoir as fast and as much as the base case but at higher cSOR values. Reversed Horizontal Injector somewhat improved the RF while its cSOR was the same as base case pattern. This well configuration was included in the list of patterns to be examined in the 3-D physical model. The Parallel Inclined Injector and the Parallel Reversed Upward Injector patterns were not able to improve the

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performance of SAGD. The Multi-Lateral Producer was able to deplete the reservoir much faster than the base case but at the expense of higher cSOR. The C-SAGD pattern with the offset of 10m was able to deplete the reservoir much faster than the base case pattern. It’s cSOR was larger than the base case cSOR (including addition of ~0.2-0.3 m3/m3 to the final cSOR value of 2.5 m3/m3 due to Source/Sink injector and producer). The pattern enhanced the RF of SAGD process significantly. As a result the Reverse Horizontal Injector and C-SAGD are assumed the most optimal well patterns at Cold Lake. The only limitation with C- SAGD pattern is the requirement of very high injection pressure for a short period of time which was not possible in our low pressure physical model. Therefore only the Reversed Horizontal Injector was selected for testing in the 3-D physical model. • At Lloydminster, due to the particular reservoir and fluid properties, such as low initial viscosity and net pay, it’s more practical to offset the injector from producer and introduce the elements of steam flooding into the process in order to compensate for the small thickness of the reservoir. Total of six main well configurations were tested for Lloydminster: Basic Pattern, Offset Producer, Vertical Injector, C-SAGD, ZIZAG Producer, and Multi-Lateral Producer. For each pattern except the Multi-lateral pattern, several horizontal inter-well spacing values, such as 6, 12, 18, 24, 30, 36, and 42m were examined. Among all the patterns, the 30m Offset producer, 42m offset vertical injectors, 42m Offset C- SAGD, and 42m Offset ZIGZAG provided the most promising performance. Among these best patterns, the 42m offset vertical injectors provided the most reasonable performance since their recovery factor was 70% but at a minimum cSOR value of 5.2. In addition to the vertical injector performance, the drilling and operational benefits of vertical injectors over the horizontal injector, this 3- vertical injector is recommended for future development in Lloydminster reservoirs.

Further on, to confirm the results of numerical simulations for the optimum well configuration, a 3-D physical model was designed based on the dimensional analysis proposed by Butler. Two types of bitumen were used in experiments: 1) Elk-Point oil

249 which represents the Cold Lake reservoir, and 2) JACOS bitumen which represents the Athabasca reservoir. Three different well configurations were tested using the two oils: I) Classic SAGD Pattern, II) Reverse Horizontal Injector and III) Inclined Injector. A total of seven physical model experiments were conducted. Four experiments (using Athabasca and Cold Lake bitumen) used the classic pattern which was considered as base case tests. Two experiments used the Reverse Horizontal Injector pattern for Cold Lake and Athabasca bitumen and the last experiment used the Inclined Injector pattern with the Athabasca bitumen. The Main conclusions from the experimental study conducted in this research are as follows: • Out of four basic pattern experiments, two tests were conducted using two different permeabilities of 600 and 260 mD. The results were consistent and their rate and cSOR were nearly proportional to the permeability. • The classic SAGD well configuration was tested for both Athabasca and Cold Lake reservoirs. This pattern is not able to sweep the entire model due to non- homogeneity of the chamber growth along the well-pair. A slanted chamber was formed above the producer and it was necessary to increase the steam injection rate to keep the chamber growing. • The Reversed Horizontal Injector well configuration that was identified as promising by the numerical simulation study was examined in the 3-D physical model and its results were compared against the classic pattern. This pattern was tested for both Athabasca and Cold Lake reservoirs. The Reversed Horizontal Injector provided significantly improved performance with respect to RF, cSOR and chamber volume. The associated chamber growth was uniform in all directions. • The Inclined Injector pattern was examined experimentally for Athabasca type bitumen. Its results were compared with basic pattern and Reverse Horizontal Injector and it provided very promising performance with respect to RF, cSOR and chamber volume. • The results of each experiment were history matched using CMG-STARS. All the numerical models were able to honor the experimental results reasonably well. However, different relative permeability curves were needed to history match the

250

performance of different well patterns. This was attributed to problems in accurately modeling the wellbore hydraulics in the simulator. • The results of the Reverse Horizontal Injector and the Inclined Injector patterns strongly suggest that these patterns should be examined through a pilot project in Athabasca/Cold Lake type of reservoir.

7.2 Recommendations

The performance of Reversed Horizontal Injector and Inclined Injector in the physical model tests is vastly superior to that of the classic pattern. The field scale numerical simulation presented in Chapter 5 was not able to capture this dramatic improvement in the performance. It is difficult to say with certainty whether the physical model results or the numerical simulation results would be closer to the field performance of these well configurations. This question can be answered directly by a field trial of the modified well configurations. Therefore, it is strongly recommended that both of these well configurations should be evaluated in field pilots. In this research a homogenous reservoir with averaged properties was constructed for Athabasca, Cold Lake, and Lloydminster reservoirs to investigate the impact of well configuration on the ultimate recovery obtained by SAGD process. However, reservoir characterization plays an important role in all thermal recovery mechanisms. Therefore, it is essential to numerically examine the robustness of the new patterns in a more realistic geological model in order to validate the optimized well patterns in a heterogeneous reservoir. In this study the high pressure patterns such as C-SAGD were not examined through the experimental study. Therefore the laboratory verification of the high pressure patterns in a 3-D physical model will be beneficial. Most experimental studies, including this thesis, study SAGD process using single well pair models. Therefore once the chamber reaches to the sides of the model, it encounters no flow boundaries during the depletion period. In the commercial SAGD projects, the chambers will eventually merge with each other and create a series of instabilities. Modeling the chamber to chamber process at the time that oil rate starts to decline will be an interesting area of research.

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This research was more focused on the recovery performance of SAGD; therefore the process was terminated at the end of each test by stopping steam injection and producing the mobilized heated bitumen around the producer. Most of the experimental studies ignore the last SAGD step which is Wind-Down. Once a high pressure model is designed, some study can be conducted on optimizing the best approach for shutting the injector down. Optimization of wind-down strategy at the time when one chamber merges into another can improve SAGD performance and create more stability for a commercial project operation. The impact of solvent injection can be evaluated for the new well configurations. However, the solvent recovery needs to be optimized for each well pattern so that the economics of the project may be optimized. An economical study including the cost of surface and subsurface facilities is required for each recommended well pattern so that a logical decision can be made in selecting the best pattern.

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