The Pennsylvania State University. The Graduate School. College of Earth and Mineral Sciences

Transcription

1 The Pennsylvania State University The Graduate School College of Earth and Mineral Sciences ANALYSIS OF FIELD DATA FROM BAKKEN WELLS FOR STIMULATION EFFECTIVENESS USING DATA MINING TECHNIQUES A Thesis in Energy and Mineral Engineering by John Akenhead Plas Otwe 214 John Akenhead Plas Otwe Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science May 214

2 ii The thesis of John Akenhead Plas Otwe was reviewed and approved* by the following: John Yillin Wang Assistant Professor of Petroleum and Natural Gas Engineering Thesis Co-Advisor Andrew Kleit Professor of Energy and Environmental Economics Thesis Co-Advisor Mku Thaddeus Ityokumbul Associate Professor of Mineral Processing and Geoenvironmental Engineering Luis F. Ayala Associate Professor of Petroleum and Natural Gas Engineering Graduate Program Officer of Energy and Mineral Engineering *Signatures are on file in the Graduate School

3 iii ABSTRACT North Dakota has since 212 become the second largest oil producing state in the USA due to its successful development of the Bakken with improved drilling and stimulation technologies. However, hydraulic fracture stimulation and completion strategies adopted by operators to create massive reservoir contact and conductive pathways for oil and gas flow vary a lot giving a broad spectrum of production results even in the proximity of location in the same field or play. It is critical to continuously evaluate effectiveness of the stimulation treatments with respect to production performances in order to improve on treatment parameters, completion variables and to know the extent to which they could be limited by good geological effects of the acreage under consideration. For this work thousands of well data were screened and about 44 wells with sufficient completion and treatment information were selected for analysis. Production performances in relation to stimulation and completion variables were studied using, engineering and statistical methods as well as analysis for best economic practices. New insights gained through this work will benefit the industry in offering better completion and stimulation strategies across the Bakken.

4 iv TABLE OF CONTENTS LIST OF FIGURES. LIST OF TABLES... ACKNOWLEDGEMENTS.. v xiii xvi CHAPTER 1: INTRODUCTION.. 1 CHAPTER 2: LITERATURE REVIEW Bakken Formation Bakken Production Trends, Geological and Engineering Factors controlling Production : Data Mining Techniques 18 CHAPTER 3: PROBLEM STATEMENT AND METHODOLOGY. 22 CHAPTER 4: DATA ANALYSIS Data Gathering Engineering Analysis and Field Review Geological and Structural Influences on Production Statistical Analysis Summary of Best Practices 183 CHAPTER 5: ECONOMIC ANALYSIS Net Present Value (NPV) and Discounted Profitability Index (DPI) Economic case study for wells using the NPV and DPI metric. 191 CHAPTER 6: CONCLUSIONS AND RECOMMENDATIONS 199 REFERENCES.. 21

5 v LIST OF FIGURES Figure 1.1: North Dakota daily oil production from (from North Dakota Department of Mineral Resources, 21) 3 Figure 2.1: Map of Williston Basin showing the Bakken Formation (sourced from )... 5 Figure 2.2: Strategraphic members of the Bakken (sourced from Bakken Decision Support System, ) 6 Figure 2.3: Multi-staged fracture using completion tools (sourced from Gheselin (28) after Schlumberger) 12 Figure 2.4: Proppant size comparisons. (Vincent (28) 16 Figure 3.1: 3-month oil production with time for Parshall field in Mountrail County, North Dakota 23 Figure 4.1: Histogram of wells under study in fields and Counties in North Dakota 27 Figure 4.2: Fluid system selection based on brittleness of shale reservoir rock (Mullen et al 21.).. 3 Figure a: 3-month cumulative oil with time for 88 wells in Parshall and Vanhook fields in Mountrail County, North Dakota. 33 Figure b: Fracture fluid with time for 88 wells in Parshall and Vanhook fields in Mountrail County, North Dakota. 33 Figure c: Fracture fluid usage with time for 88 wells in Parshall and Vanhook fields in Mountrail County. 34 Figure d: Proppant usage with time for 88 wells in Parshall and Vanhook fields in Mountrail County. 34 Figure e: Proppant to fluid ratio with time for 88 wells in Parshall and Vanhook fields in Mountrail County. 35 Figure f: 3-month oil production with proppant to fluid ratio (PPG) for Parshall and Vanhook fields. 35 Figure g: 3-month oil per foot of lateral with time for Parshall and Vanhook fields. 36 Figure : 3-month oil with time for Operator AE in Parshall field. 37 Figure a: 3-month oil production with time for region A 39 Figure b: Proppant usage with time for region A 39 Figure c: Frac fluid with time for region A 4

6 vi Figure d: 3-month oil with for region B 4 Figure e: Proppant usage with time for region B 41 Figure f: Frac fluid usage with time for region B 41 Figure g: 3-month with time for region C. 41 Figure h: Proppant usage with time for region C 42 Figure i: Frac fluid usage with time for region C 42 Figure : 3-month oil with time for Vanhook 43 Figure : Average oil production with stage-count for Operator AE in Parshall field 44 Figure a: 3-month oil vs. lateral length for 88 wells in Parshall and Vanhook fields Figure b: 3-month oil vs. frac fluid for 88 wells in Parshall and Vanhook fields 46 Figure c: 3-month oil vs. proppant for 88 wells in Parshall and Vanhook fields..46 Figure d: 3-month oil vs. PPG for 88 wells in Parshall and Vanhook fields 47 Figure : Cumulative oil production for Parshall and Vanhook fields. 48 Figure : 3-month oil production for 9 wells in the Sanish field, Mountrail County 49 Figure : Lateral length over time for 9 wells in the Sanish field, Mountrail County 5 Figure : Proppant usage with time for 9 wells in the Sanish field, Mountrail County... 5 Figure : Fracture fluid volume over time in the Sanish field, Mountrail County 51 Figure : Proppant to fluid concentration over time in the Sanish field, Mountrail County Figure : 3-month oil production vs. proppant concentration (PPG) in the Sanish field 52 Figure : 3-month oil production vs. number of stages in the Sanish field 53 Figure : 3-month oil production vs. treatment pressure in the Sanish field.. 53 Figure : 3-month oil production vs. treatment rate in the Sanish field 54 Figure : 3-month oil per foot vs. proppant per foot for wells in the Sanish field.. 55 Figure : Average cumulative oil production by stages for Operator AW in Sanish field.. 55 Figure a: 3-month oil vs. lateral length for 9 wells in the Sanish field 57 Figure b: 3-month oil vs. proppant for 9 wells in the Sanish field 58

7 vii Figure c: 3-month oil vs. frac fluid for 9 wells in the Sanish field 58 Figure : Lateral length with time for 7 wells in the Stanley, Ross, Robinson lake and Alger (SRRA) fields in Mountrail County 59 Figure : 3-month oil production with time, for 7 wells in the Stanley, Ross, Robinson Lake and Alger (SRRA) fields 59 Figure : Proppant usage with time for 7 wells in SRRA fields 6 Figure : Frac fluid with time for 7 wells in the SRRA fields 6 Figure : Proppant to fluid ratio (PPG) with time for 7 wells in SRRA fields 61 Figure : Treatment rate with time for wells in SRRA fields 62 Figure : Treatment pressure with time for wells in SRRA fields 62 Figure : Oil production with time for wells in Stanley field 63 Figure : Proppant usage with time for wells in Stanley field 63 Figure : Frac fluid usage with time for wells in Stanley field 64 Figure : Proppant to frac fluid ratio (PPG) with time for wells in Stanley 64 Figure : PPG vs. lateral length of wells in the Stanley field 65 Figure : Treatment rate with time in the Stanley field 65 Figure : 3-month Oil production with time for wells in Ross field 67 Figure : Proppant usage with time for wells in Ross field 68 Figure : Frac fluid used with time for wells in Ross field 68 Figure : Proppant concentration with time for wells in Ross field 69 Figure : Treatment rate with time for wells in Ross field 69 Figure : Average cumulative oil by stages for Stanley wells 7 Figure : Average cumulative oil by stages for Alger wells 7 Figure : Average cumulative oil by stages for Ross wells 71 Figure a: 3-month oil vs. lateral length for 7 SRRA wells.. 72 Figure b: 3-month oil vs. proppant for 7 SRRA wells 72 Figure c: 3-month oil vs. frac fluid for 7 SRRA wells 73 Figure d: 3-month oil vs. PPG for 7 SRRA wells 73

8 viii Figure e: 3-month oil vs. number of stages for wells in SRRA. 74 Figure : Average cumulative oil for Stanley, Ross, Robinson Lake and Alger.. 75 Figure : 3-month oil with time for 5 wells in McKenzie County. 76 Figure : Frac fluid with time for 5 wells in McKenzie County.. 76 Figure : Proppant use with time for 5 wells in McKenzie County 77 Figure : Proppant to fluid ratio (PPG) with time for McKenzie County 77 Figure : Treatment pressure over time for wells in McKenzie County.. 78 Figure : Treatment rate with time for wells in McKenzie County. 78 Figure : Lateral length of 5 wells in the McKenzie County 79 Figure a: Treatment rate vs. lateral length 79 Figure b: Treatment pressure vs. lateral length. 8 Figure c: PPG vs. lateral length. 8 Figure a: Lateral vs. 3-month oil 81 Figure b: PPG vs. 3-month oil.. 81 Figure c: number of stages with time for 5 wells in McKenzie County 81 Figure : Average oil by stage with time for region C in McKenzie County.. 83 Figure a: 3-month oil vs. lateral length for 5 wells in McKenzie 84 Figure b: 3-month oil vs. proppant for 5 wells in McKenzie County 84 Figure c: 3-month oil vs. frac fluid for 5 wells in McKenzie County 84 Figure d: 3-month oil vs. proppant concentration (PPG) for 5 wells in McKenzie 85 Figure e: 3-month oil vs. number of stages for wells in McKenzie 85 Figure f: 3-month oil vs. treatment pressure for wells in McKenzie 85 Figure g: 3-month vs. treatment rate for wells in McKenzie County 86 Figure : 3-month cumulative oil with time for 9 wells in Dunn County 87 Figure : Proppant weight over time for 9 wells in Dunn County. 88 Figure : Frac fluid volume over time for 9 wells in Dunn County 88 Figure : Proppant to fluid ratio (PPG) for 9 wells in Dunn County. 89

9 ix Figure : Treatment rate over time for 9 wells in Dunn County 89 Figure : 3-month oil vs. treatment rate for wells in Dunn County 9 Figure : Treatment rate vs. lateral length for wells in Dunn County 9 Figure : Treatment pressure with time for wells in Dunn County 91 Figure : Lateral length over time for 9 wells in Dunn County 91 Figure : 3-month oil vs. lateral length for 9 wells in Dunn County 92 Figure : 3-month oil vs. PPG for 9 wells in the Dunn County 92 Figure a: 3-month oil vs. lateral length for 9 wells in Dunn County 94 Figure b: 3-month oil vs. proppant for 9 wells in Dunn County 94 Figure c: 3-month oil vs. frac fluid for 9 wells in Dunn County 95 Figure d: 3-month oil vs. with PPG for 9 wells in Dunn County 95 Figure e: 3-month oil vs. treatment pressure for Dunn County 95 Figure : 3-month oil with time for 5 wells in Divide, William and Burke (DWB) Counties 97 Figure : Proppant usage with time for 5 wells in Divide, William and Burke (DWB) Counties 97 Figure : Frac fluid usage with time for 5 wells in Divide, William and Burke (DWB) Counties 98 Figure : Proppant to fluid ratio (PPG) over time for 5 wells in Divide, William and Burke (DWB) Counties 98 Figure : Treatment rate over time for 5 wells in Divide, William and Burke Counties 99 Figure : Treatment pressure with time for 5 wells in Divide, William and Burke (DWB) Counties 99 Figure : Lateral length for 5 wells in DWB Counties 1 Figure : Lateral length vs. PPG for wells in DWB Counties 1 Figure : 3-month oil vs. PPG for 5 wells in DWB Counties 1 Figure : 3-month oil vs. lateral length for 5 wells in DWB Counties 11 Figure a: 3-month oil vs. lateral lengths for 5 wells in DWB Counties 12 Figure b: 3-month oil vs. proppant for 5 wells in DWB Counties 13

10 x Figure c: 3-month oil vs. frac fluid for 5 wells in DWB Counties 13 Figure d: 3-month oil vs. number of stages for DWB Counties Figure e: 3-month oil vs. treatment rate for wells in DWB Counties. 14 Figure f: 3-month oil vs. treatment pressure for wells in DWB Counties 14 Figure 4.3.1: Map of Hydrogen Index for North Dakota (Nordeng, LeFever, 29).. 17 Figure 4.3.2: Isopach of Bakken showing increase in thickness (NDGS GI-9321).. 18 Figure 4.3.3: Resistivity contour map of the Middle Bakken (Hester, Schmoker, 1985) 19 Figure 4.3.4: Thickness map of the Bakken (Hester and Schmoker, 1985) 19 Figure 4.3.5: Snapshot of the Lineament system in the Parshall field (NDGS-GI 153, Anderson F.J., 212) 11 Figure 4.3.6: Well thickness with time for Parshall-Mountrail County 111 Figure 4.3.7: 3-month oil with well thickness for Parshall- Mountrail County 111 Figure 4.3.8: Hydrogen Index map of the Bakken in North Dakota 115 Figure 4.3.9: 3-month oil with thickness of reservoir for McKenzie 116 Figure 4.3.1: 3-month oil with normalized resistivity per thickness for McKenzie Figure : 3-month oil with thickness for SRRA wells 118 Figure : 3-month oil with normalized resistivity for SRRA wells 119 Figure : 3-month oil with reservoir thickness for Stanley 12 Figure : 3-month oil with normalized resistivity for Stanley 12 Figure : 3-month oil with reservoir thickness for Alger 121 Figure : 3-month oil with normalized resistivity for Alger 121 Figure : 3-month oil with reservoir thickness for Ross 122 Figure : 3-month oil with normalized resistivity for Ross 122 Figure : 3-month oil with thickness for Divide, William and Burke Counties 125 Figure 4.3.2: 3-month oil with resistivity for Divide, William and Burke Counties 125 Figure : Structures influencing oil and gas production in North Dakota 126 Figure : 3-month oil with thickness for William County 127 Figure : 3-month oil with resistivity for William County 127

11 xi Figure : 3-month oil with normalized resistivity for William County 128 Figure : 3-month oil with thickness for Burke County 129 Figure : Thickness with resistivity for Burke County 129 Figure ; 3-month oil with thickness for Divide County 13 Figure : 3-month oil with resistivity for Divide County 13 Figure : Production from wells close to structural elements in North Dakota Bakken 131 Figure 4.3.3: Map showing well density around structural elements from periods (Nordeng, 21) 132 Figure 4.4.1: Histogram of lateral lengths for the SRRA fields Mountrail County 137 Figure 4.4.2: Histogram of standardized proppant weight for SRRA fields-mountrail County..138 Figure 4.4.3: Histogram of standardized fluid volume for SRRA fields 139 Figure 4.4.4: Histogram of number of stages for SRRA fields 139 Figure 4.4.5: Histogram of treatment rate for SRRA fields 14 Figure 4.4.6: Histogram of treatment pressure for SRRA fields 14 Figure 4.4.7: Histogram of average monthly oil production for SRRA fields 142 Figure 4.4.8: Histogram of log transformed oil production for SRRA 143 Figure 4.4.9: Histogram of average monthly gas production for SRRA fields Figure 4.4.1: Histogram of log transformed average gas production for SRRA fields 144 Figure : Residual plots for oil production model in SRRA fields 149 Figure : Residual plots for gas model in SRRA fields 153 Figure : Residual plots of oil model for Sanish fields 156 Figure : Residual plots for gas model for Sanish fields 159 Figure : Residual plots for oil model for Parshall and Vanhook fields 161 Figure : Residual plots for gas model for Parshall and Vanhook fields 164 Figure : Residual plots of oil model for McKenzie County 167 Figure : Residual plots of gas model for McKenzie County wells 17 Figure : Residual plots of oil model for Dunn County wells 172

12 xii Figure 4.4.2: Residual plots of gas model for Dunn County wells 175 Figure : Residual plots of oil model for Divide, William and Burke Counties 179 Figure : Residual plots of gas model for Divide, William and Burke Counties. 18 Figure : Production decline with time for oil wells 182 Figure 5.1: NPV with time chart for Par-17 well 192 Figure 5.2: NPV with time chart for Par-49 well 193 Figure 5.3: NPV with time chart for San Figure 5.4: NPV with time chart for San Figure 5.5: NPV with time chart for DWB Figure 5.6: NPV with time chart for DWB

13 xiii LIST OF TABLES Table 2.1 Proppant types and sizes (adapted from Udoh A., 213 after Carbo Ceramics) 15 Table 4.2 Young Modulus of various lithologies 29 Table Average field treatment characteristics for regions A, B and C of Parshall. 42 Table Correlation of controlling factors with 3-month oil production for Parshall and Vanhook fields. 47 Table Correlation of controlling factors with 3-month oil production for Sanish 56 Table Average treatment characteristics for Operators AW and B in the Sanish field 57 Table Summary of average treatment parameters for SRRA fields 71 Table Correlation of controlling factors with 3-month oil production for SRRA 74 Table Summary of average treatment parameters for regions A, B and C in McKenzie 82 Table Correlation of controlling factors with 3-month production for McKenzie County wells. 86 Table Summary of average treatment parameters for Dunn County fields 93 Table Correlation of controlling factors with 3-month oil production for Dunn. 96 Table Summary of treatment parameters for Divide, William and Burke Counties 12 Table Correlation of controlling factors with 3-month oil production for Divide, William and Burke Counties.. 15 Table Average field characteristics values for Dunn County wells. 113 Table Average field characteristics values for McKenzie County wells. 115 Table Average field values for Stanley, Robinson Lake, Ross and Alger wells. 118 Table Treatment parameters for 3 wells in Ross field (Lateral) Table Treatment parameters for 3 wells in Ross field (Proppant and Fluid) 123 Table Average field characteristic values for Divide, William and Burke wells..124 Table Treatment parameters for 2 wells in William County.128 Table Descriptive statistics for 7 wells in SRRA- Mountrail County.141 Table Correlation between average monthly oil production for SRRA wells..143 Table Test of Fixed Effects for oil production for SRRA.. 147

14 xiv Table Coefficients and solution for Fixed Effects for oil production-srra 148 Table Test of nonlinearity in Lateral length, Fluid volume and Proppant for oil production in SRRA..149 Table Test for Fixed Effects for gas production for SRRA..152 Table Coefficients and solution of Fixed Effects for gas production-srra 152 Table Test of nonlinearity in Lateral length, Fluid volume and Proppant for gas-srra 153 Table Test of Fixed Effects for oil production for Sanish wells 155 Table Coefficients for the solution of Fixed Effects for oil production-sanish 155 Table Test for nonlinearity in Lateral length, Fluid volume and Proppant for oil production in Sanish field. 156 Table Test of Fixed Effects for gas production in Sanish field Table Coefficient and solution of fixed effects for gas production in Sanish field 158 Table Test of nonlinearity for gas production Sanish. 158 Table Test for Fixed Effects for oil production in Parshall and Vanhook fields.. 16 Table Test for nonlinearity in predictors with oil production for Parshall-Vanhook..16 Table Solution of Fixed Effects with oil production in Parshall and Vanhook. 161 Table Test for Fixed Effect for gas production in Parshall and Vanhook 162 Table Test for nonlinearity in gas production for Parshall and Vanhook. 163 Table Solution of Fixed Effects for gas production in Parshall and Vanhook Table Test for Fixed Effects for oil production McKenzie. 165 Table Test for nonlinearity for oil production McKenzie 166 Table Solution of Fixed Effects with oil production- McKenzie 166 Table Test of Fixed Effects for gas production McKenzie. 168 Table Test for nonlinearity for gas production McKenzie. 168 Table Solution of Fixed Effects with gas production McKenzie 169 Table Test for Fixed Effects for oil production in Dunn County 171 Table Solution of Fixed Effects for oil production Dunn County 171 Table Test for nonlinearity in predictors with oil production Dunn County 172

15 xv Table Test for Fixed Effects for gas production - Dunn County 173 Table Solution of Fixed Effects with gas production- Dunn County..174 Table Test for nonlinearity in predictors for gas production Dunn County 174 Table Test for Fixed Effects for oil production in Divide, William and Burke (DWB) Counties 176 Table Test for nonlinearity in predictors with oil production for DWB Counties 176 Table Solution of Fixed Effects for gas production DWB Counties Table Test for Fixed Effects for gas production DWB Counties Table Test for nonlinearity in predictors with gas DWB Counties 178 Table Solution of Fixed Effects with gas production DWB Counties 179 Table Adjusted R-Squared values for Oil and Gas models 181 Table Summary of Best Practices for Top Producing Wells in North Dakota Bakken 186 Table Summary of Average Characteristics for Fields in North Dakota Bakken 186 Table 5.1 Treatment and Well Data Table 5.2 Actual Treatment Data by Oil Service Company- September17, 212 (Adapted from Udoh A., 213) Table 5.3 Unit Treatment Cost for Bakken in North Dakota (Adapted from Udoh A., 213) 189 Table 5.4 Capital Expenditure on six Wells.. 191

16 xvi ACKNOWLEDGEMENTS Glory is to God for His faithfulness, grace, provision and enablement for this academic pursuit in Petroleum and Natural Gas Engineering. Many special thanks to my advisors Dr. Wang and Dr. Kleit for their direction, critique, input and counsel for this work. My gratitude goes to Dr. Ityokumbul for accepting to be on the committee. I appreciate my colleagues Adityah Chaudhary and Quimei Zhou for the time spent together and the fruitful discourse on Hydraulic Fracture treatment and evaluation for effectiveness in producing oil and gas resource. Thanks to Kwame Kankam for assistance and guidance with the statistics portion of this work.

17 Chapter 1 INTRODUCTION The development of the Bakken play which is an integral part of the Williston Basin has evolved with time since The play which covers an area of 3, square miles across the states of North Dakota, South Dakota, Montana and the Provinces of Manitoba and Saskatchewan in Canada (Baihly et al, 212; Kulkami, 21) has gained prominence due to advances in drilling, completion and hydraulic stimulation practices. Drilling of horizontal wells and fracture stimulating in varied well completion designs has yielded different production results for different operators in the field. The learning process continues with individual operators understanding influencing their strategies for optimum recovery. Different approaches in completions have been tried with best recovery being associated with stimulation with uncemented liners and compartmental techniques in open hole. Lateral length of the horizontal well is also varied across the play, ranging between anything up to 7, feet for shorter ones and up to 11, feet for longer ones. Different sizes and quantities of proppant has been pumped as well as volumes of fluid ranging from freshwater to cross-linked gels to enhance productivity from tight oil reservoirs. The key objective for a given resource in place is to maximize contact area with the reservoir and increase conductivity to aid in recovery. However, average production for the same time span, which reflects the completion and stimulation design preferences, shows a wide spectrum of results. The varied recovery across the play has fuelled an ongoing debate over which completion strategy longer or shorter laterals, stage counts, fluid volumes, choice and quantity of proppant, injection rates and treatment pressures should be employed. Though the Bakken is most extensive in North Dakota, complexity of the unconventional play with a high degree of geologic heterogeneity and

18 2 underlying faults, natural fractures and other structural shifts is believed to influence resource recovery variability even within a small area of the play. Many operators are thought to have brought their experiences from similar fields into the play while others are grappling with less than expected results after massive stimulation treatments (Grau et al, 211). Resource in place is unquestionable, with the 28 USGS assessment of estimated 3. to 4.3 billion barrels of undiscovered technically recoverable oil in the US of the Bakken formation with an average value of 3.65 billion barrels of oil, 1.85 trillion cubic feet of associated dissolved natural gas and 148 million barrels of natural gas liquids in place (Pollastro et al, 28). It is therefore important to evaluate stimulation effectiveness in the field to improve well performance and to understand to what extent oil recovery is (strongly) influenced by geology, completion and stimulation parameters in the formation in North Dakota. The USGS geologic assessment units for North Dakota groups field potential into five continuous zones with the Mountrail County which has Parshall and Sanish Fields being the most prolific due to the uniqueness of middle Bakken reservoir, stratigraphic trap, maturity setting of source rocks, over pressured matrix, high oil saturation, high EURs and rates of production (Grau et al, 211). Reservoir quality assessment is challenging in horizontal wellbores because a greater part of the lateral spanning thousands of feet, is not logged open hole (Shelley et al, 211). Thus reservoir characterization and also the influence of natural fractures will be a wildcard variable, making evaluation of stimulation effectiveness difficult. Other assumptions on reservoir homogeneity, magnitude of maximum and minimum stress for facture orientation (Tabatabaei, 29) may impact well performance. Despite the challenges faced by operators, North Dakota oil and gas production continues to increase and has surpassed Alaska as the second largest oil producer in the US by March 212.

19 3 Evaluation of stimulation parameters will unearth the best practices for producing economic wells, improve future treatments and catapult North Dakota to the number one oil producing state in USA. This work uses publicly available data on well production and hydraulic fracture treatment for evaluating the effectiveness of stimulation in different fields across the play in North Dakota by different operators. Production trends will be studied across the assessment units, field to field and between specific operators. Statistical and economic analysis will be conducted to evaluate fracture treatments while providing answers on longer versus shorter laterals, economic stage counts and other parameters that control well performance. Statistical analysis will measure the level of significance of parameters that control well performance, the relative importance of controlling factors when compared to others and the correlation between factors and the oil production metric. Figure1.1: North Dakota daily oil production from (N.D. Department of Mineral Resources, 21)

20 4 Chapter 2 LITERATURE REVIEW In this chapter, I will first introduce the Bakken shale play in section 2.1, followed by discussion on production trends and pertinent geological and engineering factors in section 2.2, and finally review of literature on data mining techniques in section The Bakken Formation The Upper Devonian and Lower Mississippian Bakken Formation is a widespread continuous oil resource source rock that covers close to 2, square miles of subsurface formation within the Williston Basin. It is a thin but a widespread tight oil reservoir that underlies parts of Montana, North Dakota in the USA as well as Saskatchewan and Manitoba Provinces in Canada. Since its discovery in 1953 (Breit et al,1992) when the first well was drilled in the Antelope Field, progressive activity has made it one of the most active oil basins in the US with significant oil rig count and increasing production volumes (Pollastro et al,28) The Bakken Formation is made of highly organic-rich, siliciclastic rock sequence which is informally divided into three intervals: the Upper Bakken Shale, the Middle Bakken, and the Lower Bakken Shale. All three members have distinct lithology and are recognizable on well logs. The Upper and Lower Shale members are organic-rich marine shales with as much as 35 percent total organic content by weight and are the petroleum source rock for the Middle Bakken and the Three Forks. They are relatively of consistent lithology as compared to the middle member which is heterogeneous and consists of sandstone and dolomites of varied depositional facies and lithology and has measureable porosity (Pollastro, 28).

21 5 The Bakken is overlain by the thick Mississippian Lodgepole, made of nonporous and impermeable carbonates and underlain by the Three Forks Formation. Together the Lodgepole and the Three Forks formation acted as the trap and seals around the Bakken source rock deposition and facilitated thermal conversion of kerogen in the Bakken Shale into petroleum through increased temperature and pressure. In the absence of high- permeability formation to allow migration of petroleum, the pore fluid under sustained pressure within subsequently produced mini-fractures in the shale members. Figure 2.1: Map of Williston- Bakken Formation ( The Lodgepole Formation consists of dense limestone and calcareous shale with minor amounts of chert and anhydrite with a maximum thickness of 9 ft in eastern McKenzie, ND. It consists of three members: the Cottonwood, Paine and Woodhurst members. The North Dakota Industrial Commission (NDIC) defines the limit of the Bakken petroleum system to include only 5 ft of

22 6 the Lodgepole above the Upper Bakken (Nordeng S.H, 29). The stress anisotropy of the Lodgepole makes it is an excellent barrier for fracture height growth. The Upper Bakken serves as contact with the overlying Lodgepole and has high Gamma Ray signature. The Upper Bakken is made up of black, organic rich, pyritic shale with measured total organic content (TOC) up to 4 percent (Wiley et al, 24). It serves as rich marine kerogen source formed under anaerobic conditions and is widespread throughout the Bakken and is a source and overlying seal for oil produced in the oil window. Figure 2.2: Stratigraphic Members of the Bakken ( The Middle Bakken is the main reservoir for oil generated in the oil windows in the Upper and Lower Bakken Shales. This reservoir facies is made up clastic limestone, burrowed silty and sandy dolomite with fair to good porosity. It is laterally homogenous and as much as 9ft thick at the depocenter in North Dakota and up to 15ft. at the shallow limit in Montana. The Middle Bakken is made of 5 distinct mappable subdivisions of the stratigraphic unit. These individual

23 7 subdivisions also known as lithofacies, have distinguished lithologic characteristics from adjacent ones based on conditions of sedimentation, grain size and mineralogy. Of the 5 units only 2 lithofacies with sandstone composition make the best reservoir. The Lower Bakken has high Gamma Ray signatures and is composed of black to brownish-black fissile non-calcareous organic mudstones. TOC is up to 21 percent and overlies the immediate Three Forks except for areas where the discontinuous Sanish Member is present. It has a maximum thickness of 56ft and is of the smallest geographic extent. The Sanish Member is a discontinuous accumulation that lies at the top of the of the Upper Devonian Three Forks formation. It is a coarse-grained siltstone to fine-grained sandstone and dolomite. The Three Forks Formation lies immediately below the Lower Bakken Shale member and is used as a fracture initiation point to maximize height growth in fracture stimulation jobs. It is composed of shales, dolostones, siltstones, sandstones, and minor occurrences of anhydrite and could be up to 25ft thick on the average. The Three Forks is made up of four units with the productive unit made up interbedded siltstone and shale beds. The NDIC defines the Bakken Petroleum System as the interval that contains the Bakken Formation, the upper 5ft of the Devonian Three Forks including the discontinuous Sanish member where present and the lower 5ft of the overlying Lodgepole Formation (Nordeng S. H., 29).

24 8 2.2 Bakken Production Trends The Bakken Formation is currently the largest oil pay in the lower 48 States in the US after a remarkable feat that dates back to 1953 when the first well was drilled in the Antelope Field in McKenzie County, North Dakota. By the end of December-212 it has surpassed both California and Alaska to be the number 2 oil producer after Texas which was averaging 2.22 million bpd. The evolution has been on the strength of technological advances in drilling, completions and hydraulic fracture stimulation technologies coupled with excellent takeaway price by the operators. The long history of production has been in phases with the shift from the era of unstimulated or Hail-Mary Frac wells with shorter laterals (32 spacing)(grau et al, 211) which epitomized the pump and pray period (Dick Ghiselin, 28) to the present time where laterals top 1,ft and are stimulated with millions of sand and fracture fluid. Production was spurred on by tax incentives to produce from uneconomic reservoirs and the need for accelerated production to meet the volatile energy security in the US. From 25 up to 29 marked the discovery and production from the Parshall Field in North Dakota for which staged completion was first introduced into the play by engineers with understanding from other shale plays (Grau et al, 211). Staged completions were in the 5 to 8 range on 64 and 128 acre spacing. Coupled with the USGS assessment of unproduced oil-inplace of the play to be 3.65 billion barrels of oil and introduction of new technologies, the interest and activity (rig count) in the play rocketed. Since 29, longer laterals have been drilled with stage counts averaging about 3 (Baihly et al, 212) accompanied by introduction of special proppants and fluid systems and completion styles

25 9 resulting in higher production. The cumulative increase in production for the play overshadows the variability in individual output from operators in the field for nearly the same stimulation variable input. The trend indicates that more operators are still on the learning horizon and there is the need for research into all the key parameters which will result in economic production of resource from the Bakken and other shale oil plays. Designing of a fracture treatment for the tight oil play like the Bakken depends on so many factors for which economics is paramount. The significant factors that impacts treatment and resulting production response can be summarized as; 1. Oil in-place from the area of thermal maturation and conversion of kerogen into oil from source rocks. 2. Contact of well bore with reservoir matrix to achieve a maximum surface area and rock stimulated volume (SRV). 3. Conductive pathways deep into the reservoir to interconnect induced far-field fractures and natural fractures for effective drainage. Resource in place Oil in place assessment has been estimated by the USGS for the Bakken Total Petroleum System to be 3.65 billion barrels of oil (BBO) is mainly dependent on having the assessed unit reservoir source rocks being thermally mature. From the perspective of oil rents, raising investment capitalization and selling of corporate shares; the assessed oil in place seems to vary. Leigh Price s (1999) unpublished work put it at 413 BBO, Saskatchewan Industry and Resources (25) quotes 1 BBO while a major independent producer suggests 24 BBO.

26 1 Thus oil in place is unquestionable with assessment for individual geologic units influenced by thermal maturity and burial depth of source rocks across the play, local porosity, and permeability. The amount of oil in place is directly related to the total organic content (TOC) of the source rocks. Organic matter in the form of Kerogen is transformed into oil as result of temperature and burial depth. The Bakken shale members are rich in kerogen with the upper member having as much as 4 percent TOC by weight. Reservoir contact The next effect of maximizing reservoir contact has many controlling factors to it, which we discuss below. Wellbore Azimuth - Minimum contact of wellbore with matrix will be achieved by a longitudinal fracture by drilling in the direction of the maximum horizontal stress which will require one stimulation treatment. However for multiple contacts and for diversion, the choice of drilling in the direction of minimum horizontal stress will enable staged completion as a result of transverse vertical fractures. Lateral length For maximum contact, longer laterals have been drilled as opposed to shorter ones. The choice of length could be impacted by acre spacing available. Longer laterals appear to provide greater exposure to wellbore and will drain a larger area for the same reservoir quality. For tight reservoirs that require stimulation to achieve propped conductive pathways, stimulating the entire wellbore for longer laterals will be challenging as compared to shorter intensely fracked lateral. Some operators have been consistent with one approach and changing strategy over time, as others drilled different

27 11 lengths of laterals with some mixed results. There is raging debate about the economic length of lateral. Should it be shorter with moderate contact but with high frac intensity or maximum contact sacrificing fracture density. Drilling and completion The uptick in oil production in the Bakken and other tight shale plays has been on the strength of technological advances in drilling and completion. Horizontal wellbore technique has evolved from the 32 acre to 128 plus spacing which is completed in record times. Directional drilling is also employed while multi-laterals from one primary vertical well bore have been experimented to maximize contact and drainage from the Bakken as well. Completion Methods Evolution of completion methods with time in the Bakken accounts for the successful and economic production of the formation. Open-hole completions are the current trend out of many options available. Early completion methods employed cemented wellbore with perforations through the casing. Though it allowed for control of fracture initiation; formation damage together with pressure losses and isolation of natural fractures limited its application. Current completions allow for successive isolation of horizontal open-hole into compartments for treatment with varied mechanical diversion tools (McMaster, 21). Sliding sleeves activated by graduated balls, external swell packers and the hybrid of these two systems are used for staged treatments. Multi-staged fracturing of laterals in cemented wellbore employed the plug and perf stimulation. Plugging tools are used to isolate the location to be treated, beginning close to the toe followed by perforation. Ball activated sealers are also used for isolating the

28 12 frac interval. The plug and perf treatments had fluid leakage into the earlier fractured zone, requiring additional fluid and pumping. Swell packers and hydraulic ball activated sliding sleeves tools were developed to mitigate the fluid and pressure losses for economic stimulation treatments (Tran, 211). Figure2.3; Multi-Staged fracture using completion tools sourced from Gheselin-28 Conductivity in interconnecting far-field created fractures and natural fractures into an excellent flow path for draining into the wellbore are needed for optimum production from tight oil plays. Hydraulic fracture treatments are designed to create fracture networks and to dilate and prop up existing natural fractures. Fracturing treatments may depend on the essential geomechanical and petrophysical properties of the stimulated rock. These properties of the reservoir rock include the following (Kundert and Mullen, 29; Cipolla et al 28); i. Young s Modulus ii. iii. iv. Poisson Ratio Pore Pressure Effective Porosity and Permeability

29 13 v. Bottom hole temperature (BHT) vi. Minimum in-situ stress. The above properties determine the quality and quantities of hydraulic fracture stimulation parameters ranging from fluid type and volumes, proppant type and weight, treatment pressures and injection rate as well as the staging process to achieve the desired stimulated rock volume. For example, the brittleness of the reservoir shale is regarded as an important factor in the designing a massive fracture job that will help production drawdown during the economic life of the well. Softer shales which are less brittle and have low Young s Modulus will be more difficult to fracture for large propped conductive pathways than a more brittle one that has other elements in their lithology that makes them harder and have higher values on the Brinell hardness scale (Romanson et al, 211). Narrow fractures tend to be created in high Young Modulus and wider fractures result from treating low Young s Modulus rock. Additionally higher Young Modulus creates tall fracs and treatment should be designed to avoid breaking in undesired bedding like a water zone. The Bakken formation has a complex lithology ranging from feldspar, quartz, dolomite, limestone and pyrites (Olsen, 29). Dolomites and quartz elements make a better quality reservoir rock with measureable porosity and permeability while clay, feldspar and limestone have lower reservoir quality. High quality fine grained, small pore size rock with large thickness and areal extent make excellent reservoirs resulting in efficient flow within the reservoir(udoh, 213). Higher quality tight reservoirs are prone to formation damage during drilling and perforation. Long fractures may be required for low to moderate quality reservoir as opposed to designing for higher conductivity for shorter fracture in higher quality reservoir.

30 14 In-situ stresses are the dominant factors in controlling fracture azimuth and orientation, treating pressures, proppant crushing and embedment, fracture geometry and fracture height growth (Gidley, 1989). The overburden stress is the principal stress element and there is not much variation or anisotropy between the two horizontal stress profiles in the Bakken which makes designing of complex fracture networks possible (Udoh, 213). Natural fractures make it possible for economic development of Shale plays. The presence of natural fractures and their intersection with hydraulic fracture enhances flow to the wellbore. However stress may deform or even close natural fractures. Also not all natural fractures contribute meaningfully to production until they are stimulated (Cipolla, 29). The discussed properties and others not listed are guide posts to help with the stimulation treatment design. They are uncontrollable but the choices of controlling factors in our stimulation treatment ranging from proppant selection and weight, fluid type and volume, treatment rate, treatment pressure and number of staging will create the sufficient SRV for effective drainage over the productive life of the reservoir. Hydraulic fracture stimulation in horizontal wells is the dominant technology driving the success in the Bakken. We look at the various elements of the treatment that creates the stimulated reservoir volume essential for economic production. Proppant Type and Weight Proppants are used to keep the fracture open during the productive life of the well. The choice of the propping agent and quantities are essential for creating high conductive pathways to allow fluid flow into the wellbore. The proppant should have adequate strength to prevent crushing and

31 15 to create optimum conductivity. Sand and ceramic proppants have greater application in the Bakken and they come in different sizes from the 1 Mesh, 2/4, 4/7 and other variations. The table below list some of the proppants widely used across the Bakken. Table 2.1 Proppant Types and the Sizes (Carbo-Ceramics) Gravel Size (in.) U.S. Mesh Size Approximate Median Diameter (in.) (µm.).6 x.17 4/ x.17 4/ x.17 4/ x.33 2/ x.47 16/ x.66 12/ x.66 12/ x.79 1/ x.79 1/ x.94 8/ x.132 6/ Generally we have the 16/2 > 2/4 > 4/7 > 1 Mesh. At lower closure stress and moderate to high brittle reservoir rock, higher permeability could be achieved using larger size proppant of appropriate strength. At higher closure stresses, higher strength smaller proppant will be preferred to larger proppants to avoid crushing. For the areas considered for this work the following types of proppant are widely used and reported; 2/4 Sand and their commercial variations 4/7 sand 1 Mesh Sand

32 16 As lateral wellbore length is increased and for other design considerations total pounds of proppant is generally increased. According to Wiley et al (24) more proppants will generally lead to greater chances of staged diversion. We will study the influence of proppant type and the total mass pumped to production response in this work. Figure 2.4: Proppant size comparison (Vincent, 28) Fracture Fluid Fractured fluid is pumped at the desired treatment pressure to create fractures in the reservoir rock and to transport proppants deep into the formation. Again the choice of fluid and quantity is influenced by the set of geomechanical and petrophysical properties of the reservoir rock discussed earlier on. The fracture fluid type has evolved with time with transition from water and its derivatives to special designed fluids. Among the types in use the following have been reported for the Bakken treatment under consideration for this work. 1. Water based fluids 2. Linear Fluids 3. Cross-linked Fluids

33 17 Other fluids for design consideration are Foam based fluids and Energized fluids. For high rate low proppant concentration jobs, large volume of the appropriate fluid is pumped whilst for low rate high proppant concentration jobs, smaller volumes of the desired fluid finds application. The fracture fluid must be easily flowed back and should not damage formation, proppant and components of the well. Treatment Rate and Pressure We will determine the influence of injection rate and pressure on stimulation effectiveness in this work. The fracture fluid is injected at certain determined rates to create staged diversion and create an effective stimulated volume. High treatment rate are used to fracture more ductile formation and to increase fracture density in longer laterals. Higher rates are not appropriate for high quality reservoirs as they easily create near wellbore washouts and leak-off in the formation and unrestrained height growth. Number of Stages Successive isolation of the productive length of the lateral for intense fracture is called staging. The portions of the lateral to isolate are determined by gas shows and oil stains measured while drilling (MWD). The isolated parts using completion tools are fraced with the designed mass of proppant and fluid at the optimum injection rate and pressure. The Bakken has transitioned from the Hail Mary frac period with no stimulation staging to the current era where staging tops the 5 mark with analyst debating on the economic staging. In some respects the increased staging is rather a spread of the same proppant to fluid volumes to target more specific parts of the

34 18 reservoir than any excessive increase in proppant and fluid. We will study the effect of staging on stimulation effectiveness and determine an economic stage limit for the areas under this work. All together the measured controlling variables- the Lateral Length of Horizontal Well, Proppant Weight, Proppant Type, Fracture Fluid Type, Fracture Fluid Volume, Treatment Rate, Treatment Pressure, and the Number of Stages- and their relationship with the Production metric will be studied to verify the stimulation effectiveness and to catalogue the resume of best practices for the study area. 2.3 Data Mining Data mining is the process by which knowledge can searched out or discovered from large data devoid of structure and meaningful patterns. It involves analysis of the data and synthesis of useful information for different end uses. Data mining searches for hidden information, locates patterns hitherto unknown, establishes structure, trends and relationships within the data. It is essentially the method for finding correlations in large relational databases (Palace, 1996). The integrity and quality of the data source must be guaranteed, after which various analytical tools are used for mining information and structure. Statistical analysis, artificial intelligence, graphical analysis and data visualization tools are some of the current tools that are used on large data sources. After establishing correlation and statistical significance in the large data, logical inductive inferences as well as predictive forecasting can be made for different end uses and the results tested. The data mining process begins with a defined problem and continues with the gathering and preparation of the data pool. A model is then created to fit the transformed data. The model is then evaluated for goodness of fit and for of making predictions and knowledge deployment.

35 19 Data mining technique is fast gaining greater application in the petroleum industry especially in unconventional reservoirs and in secondary and tertiary resource recovery. Data mining for evaluation of effectiveness of stimulation on production response and predictive forecasting for petroleum and natural gas projects is receiving attention lately. A US Department of Energy funded project for evaluation of secondary oil recovery in Nebraska was done by Coral Production Corporation and reported on May, 21. The purpose was to identify factors that were likely to impact the performance of a water flood in Nebraska. Data was collected on 14 cases and analyzed to decipher correlations and structure. Initial water flooding had given mixed results due to a common problem traced to geological influences, high free gas saturation at the end of primary recovery, wettability and fractures in the reservoir rock. Coral Production Corporation was able to rapidly use data mining scheme to inexpensively estimate secondary recovery as a function of primary recovery using data mining and neural network software tool (Data Mining at Nebraska Oil and Gas Commission, May 21). They needed some years to ascertain the accuracy of their work through actual production results. Awoleke et al (21) did an analysis of data from approximately 11, completions in the Barnett Shale using data mining schemes. Their work used conventional statistics and virtual intelligence software techniques to identify trends and relationships in production data and to predict future water production in the Barnett. They concluded that the process was cumbersome and required a lot of intuitive reasoning while accuracy of their estimation was between %. Shelly et al (21) presented their work on the evaluation of production potential of hydraulically fractured completions in horizontal wells using data-driven techniques and used predictive neural network software to forecast future production. The predicted model values

36 2 compared closely with actual production volumes. However the numbers of wells evaluated are not enough to draw conclusions for larger production data. Shelly et al (211) used data- driven and engineering modeling to plan and evaluate hydraulic fracture stimulated horizontal Bakken completions. They gained an understanding of well completions in non-homogenous formation. However, the model for evaluation of production resulted in over-prediction by over 1 percent of actual production measurements. Baihly et al (212) also did an analysis on the number of staging for well completions in the Bakken to determine an economic stage limit using data mining techniques. They screened thousands of wells in the North Dakota according to a set criterion and grouped them to determine the staging limit for economic well production. Stage count was not the sole criterion for economic production with other factors like unique reservoir trap and geology impacting on economics of production. Ayers et al (212) employed data mining techniques to determine the correlation between stimulation parameters and their relationship to lifetime production performance. Though their model could match previous data, intuitive reasoning may result in over prediction of future performance. In addition there were significant geologic factors which impacted stimulation effectiveness which needed further study. All the above works reported a data collection process, preparation of the data to observe correlations, used statistical analysis to test significance of variable, fitted a model for the variables and in some instances used software tools to do prediction of future trends-which are all part of the data mining process.

37 21 For the current work, we will use conventional statistics and data mining techniques to decipher patterns in production across the Bakken based on the stimulation parameters reported for areas under consideration; observe the trend and relationship between production response variable and the stimulation and completion controlling factors to determine actionable best practices for economic production; and use a statistical model to fit the controlling factors with production response and understand key geological attributes affecting production performance variability. The advantage here is the use of actual production field data and the use of models that will not over-fit the relationships between our variables as inherent in prediction software tools. The statistical model will test individual groupings and report controlling factors that are significant for optimizing our production response benefit.

38 22 Chapter 3 STATEMENT OF THE PROBLEM The Bakken was originally discovered in 1953 and employed vertical well completions with minimal stimulation. The 199s saw a horizontal drilling boom with laterals targeting the Bakken shale (Mullen et al, 21). The current cycle of production in the Bakken is targeting the middle Bakken, Sanish and the Three Forks using varied lateral lengths and evolving completion and stimulation practices. Completions have been either longitudinal which employs one massive stimulation job or transverse orientation which accommodates multi-stage fracture treatments. Treatment sizes has also evolved with millions of different sand sizes and strength used along with a variety of fluids from fresh water to cross-linked gels pumped at different injection rates and pressures. While some operators have imported their experiences from other shale plays based on similar petrophysical and geomechanical properties of the reservoir rock, others have been consistent with specific designs and updating strategy with time when necessary. There are no observed specific standards across the play. Individual well performances have shown mixed results with greater variation as shown in figure 3.1. Production recovery is varied across the play, with some treatment jobs returning disappointing and less than expected results. This trend is a reflection of the understanding of the play by the numerous operators resulting in different stimulation strategies been adopted although apparent variability in adjacent sections of the same field could be due to lithological heterogeneity and contributions from underlain structural elements like faults and natural fractures. Fracturing and completion parameters that directly control overall production are not well established and there appear to be no industry standards either.

39 3 Month Oil (1 bbl) Month Oil with Time Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time (month- year) Figure 3.1: 3-month cumulative oil production with time for 88 wells in Mountrail County, North Dakota. The objective of this study is to identify the parameters that affect production response and to evaluate stimulation effectiveness using statistical, engineering and economic analysis of actual stimulation and production data from Bakken wells. This will be accomplished as follows: To carry out a comprehensive literature review on the Bakken field and wells To collect data on wells in the North Dakota from public and private sources. Analyze data using conventional statistical tools Study to observe correlations in the data collected and patterns across play Perform economic analysis to evaluate stimulation, drilling and completion designs that gives the best economic wells Investigate controlling factors using statistical tools. Summarize stimulation best practices across the entire North Dakota.

40 24 Document findings in a MSc. Thesis and SPE Paper.

41 25 Chapter 4 DATA ANALYSIS This chapter discusses the data gathering process and analyses using engineering, data exploration and statistical methods. Data gathering concentrated on the wells drilled in the North Dakota portion of the Bakken from year 28 and upwards with minimum cumulative production of three years except for one county where a thirty (3) month metric will be used for assessment due late development. We will explore the engineering decisions behind the quality and quantity of key parametric inputs and their influence on production response and make inferences on design strategy based on model trends from research work across Shale tight oil basins in the US. Another subsection mines the collected production and stimulation data to observe the effect of controlling stimulation parameters on production, observe production trends across the Bakken play, search for optimum and economic limits for individual and combination of controlling factors such as staging, proppant weight, injection rate, fracture fluid volumes etc. Finally a statistical subsection tests the significance of each controlling factor individually and in combination with others in a fitted model.

42 DATA GATHERING Wells were picked from various counties and fields in North Dakota and grouped into six (6) categories based well density and activity, proximity to drastically reduce geological influence on production and to explore production variability due to positional vintage, and most importantly according to the USGS assessment that groups the region into five continuous units based on the area of the oil generation window for the Bakken. Data for the study were collected from the DrillingInfo and the NDIC with total study well count limited by incomplete reportage on stimulation and completion parameters. About 7 wells were screened for reporting on horizontal wellbore length, hydraulic fracturing treatment and completion data. The level of unreported parameters makes the data gathering for the North Dakota wells extremely difficult and time consuming especially when additional information is to be collected from DrillingInfo. It was possible to select an active well from NDIC well-files and have excellent report on stimulation and completion data only to discard it because it is shut- in or has lengthy breaks in production on DrillingInfo portal. A significant number of wells are also on confidential status and the operators restrict reportage on stimulation parameters such as the fluid and proppant used. Names for the relevant fracture fluids could be misleading with nomenclatures like Water, Fresh Water and Clean Fluid possibly meaning the same thing. Lateral length of wellbore, proppant mass, fracture fluid volume were consistently reported whilst proppant types, fluid type, number of stages, treatment rate and pressure were discretionally to a large extent. Missing data or unreported data could possibly affect its relevance unless sample size tests statistically significant.

43 Number of Wells 27 For the general model that will test controlling factors on response production, higher numbers of missing predictor values will disqualify them from consideration. A total of 44 wells were selected from six counties and grouped into six categories as follows; 1. Sanish Field (Mountrail County) 9 Wells. 2. Parshall Field (Mountrail County) 9 Wells. 3. Stanley, Ross, Robinson Lake and Alger [SRRA] Fields (Mountrail County) Dunn County 9 Wells. 5. McKenzie County 5 Wells. 6. Divide, William and Burke [DWB] Counties 5 Wells. The Parshall group has additional wells from the Vanhook area for our assessment on well location (place) on production variability. The well grouping is shown in figure 4.1 below. The Divide, William and Burke group is abbreviated as DWB and the Stanley, Ross, Robinson Lake and Alger as SRRA. 1 Wells per Group SANISH PARSHALL SRRA DUNN McKENZIE DWB Well Grouping (County- Fields) Figure 4.1; Number of Wells in Grouping

44 ENGINEERING ANALYSIS Economic production from the Bakken and other unconventional reservoirs are made possible through the creation of massive conductive surface area in contact with the rock matrix, either by the existence and further dilation of natural fractures or the development of fracture network during hydraulic stimulation treatments (Warpinski et al, 29). The success in creating these reservoir conductive pathways results in a stimulated reservoir volume (SRV) which is critical for successful well performance. Some of the factors that contribute to an effective SRV are based on the following (Romanson et al 211), 1. Presence of reservoir rock heterogeneity such as natural fractures, fissures, faults and cleats. 2. Geomechanical properties such as the reservoir hardness and brittleness. 3. Matrix permeability 4. Treatment fluid viscosity 5. Magnitude of stress anisotropy Another important contributor to SRV is fracture intensity, which studies have shown to be dependent on fracture spacing. For the Bakken Shale which is microfractured, the treatment design is often geared towards creation of complex fracture geometry using shorter fracture spacing. Fracture design also accommodates the composition of the shale reservoir rock. Shales with less clay mineral tend to be more brittle and additional elements of silica render them amenable to fracturing and more productive.

45 29 Brittle rocks are good candidates for the creation of high intensive fracture network system while ductile reservoir rocks have significant closure stress which could heal unpropped hydraulic or natural fractures (Romanson et al 211; after Kundert and Mullen, 29). The Brinell Hardness Number (BHN) is used as a guide for determining formation brittleness and to make decisions for selection of portions of the reservoir to stimulate and choice of various parameters for stimulation design. BHN is essential for the determination of dynamic elastic modulus and yield strength for many rocks. Some correlations exist for determining Young s Modulus and Yield Strength from BHN (see Geertsma, 1985); Young Modulus E (dyn) =77.25* BHN and BHN Yield Stress BHN psi Table 4.2 Young Modulus of Various Lithologies-DOE Hydraulic Fracturing White Paper, 24. LITHOLOGY Soft Sandstone Hard Sandstone Limestone Coal Shale YOUNG MODULUS 2 to 5 *1 6 psi 6 to 1*1 6 psi 8 to 12*1 6 psi.1 to 1*1 6 psi 1 to 1*1 6 psi Young Modulus, defined as the ratio of stress to strain for uniaxial stress loading is a measure of stiffness of the material. When the Young Modulus is large for stiff rock material, narrow fractures are produced in hydraulic stimulation jobs. For low modulus we have wider fractures for hydraulic fracture stimulation. High values of Young Modulus reservoir rock tend to have highly propped formation after stimulation while softer rocks with low Young Modulus and

46 3 lower brittleness could have proppant embedment issues and affect selection of proppant size and strength. For brittle reservoirs, lower treatment pressures, lower injection rates, higher volume and low proppant concentrations usually with smaller size proppants have been used to create far-field fracture intensity. For the ductile or less brittle reservoir rocks, closely spaced fracture treatments using higher proppant concentration usually with higher strength and bigger size proppants, high injection rate, lower volumes of fracture fluids with increased viscosity are excellent for creating fracture intensity (Wang and Zeng, 211; DOE Hydraulic Fracturing White Paper, 24). In this section we explore the understanding behind key engineering decisions on choices of stimulation signatures or treatment methods applied in the fields as well as the possible causes for performance variation. We will examine the evolution of individual stimulation and completion parameters over time, analyze how their combined effect in multi-staged treatments have impacted production performance and attempt to identify the stimulation strategy by matching stimulation characteristics with trends which have been studied and proven by other research work over a number of shale oil basins across US (Mullen et al, 21; Rickman et al 28). Figure 4.2: Fluid system recommendation based on brittleness of shale formation. (Mullen et al 21)

47 31 FIELD REVIEW This section reviews the stimulation work covered in the six areas under study, summarizes its characteristics and makes inferences on engineering decisions behind the treatment signature adopted. We will observe oil and gas production trend with time, analyze various controlling factors with time and their measured correlation with a 3-month cumulative oil and gas production response. The Bakken has been assessed as a prolific continuous reservoir with varied geological attributes of its different plays and fields. Hydraulic fracturing is currently the best option for producing the huge resource in place. Numerous factors go into achieving the optimum stimulated reservoir rock for effective drainage. Stimulation and treatment strategies are as varied as the number of operators posing a challenge to production output and economic return. Choice of shorter or longer lateral wellbore, successful isolation and staged fracturing of lateral compartments, appropriate injection rates and pressures for fracture intensity jobs or to minimize leakoff and near-wellbore washout are some of the design variables for the Engineer. Other decisions to be made include consistency in maintaining the same fracture fluid volume and proppant per lateral foot for targeting specific sections of lateral with the greatest gas shows and oil stains or to overly increase proppant and fluid volume for maximum reach and far-field fracture intensity. For the number of stages reported, we will analyze the data collected to see if an increase in staging corresponded with additional increase in the proppant and fluid usage or average values per lateral foot has been spread to target specific reservoir length. We will explore the trend of increased staging with production and determine the possible economic stage limit.

48 32 For treatment rates and pressures, we will observe their effect on production when associated with a type of fracture fluid, sizes of proppant and proppant concentration for each stimulation job. High injection rates, high pressure signature treatments with low proppant concentration, high volume fluid are possible for stimulating longer laterals to achieve far-field frac intensity. For less brittle and more ductile reservoirs, the use of a low rate, high proppant concentration and low volume cross-linked job signatures have been reported. Finally we will measure the correlation coefficient of each individual controlling factor with the production response variable and state their significance in summarized table PARSHALL FIELD This subsection performs engineering analysis for 88 wells in Parshall and Vanhook fields for an understanding of stimulation strategies applied. We next evaluate individual well performances in Parshall and Vanhook and compare them with the entire group average characteristics. A 3-month cumulative oil production with time for 88 wells in the Parshall-Vanhook fields in Mountrail County, North Dakota is shown in figure a. The oil production shows a decreasing trend with time for the area under study. The first set of stimulation activity occurred between June-8 to December-8 and is labeled as region A. The second batch of wells were stimulated from June-9 to September-9 and is referred as region B, whilst the last batch of wells under study were stimulated from January-1 to August -1 corresponding to region C. Oil production decreased with successive increase in the proppant and fluid volumes used with time. We will observe if similar trend holds for the individual Parshall and Vanhook fields and investigate this anomaly under Section 4.3 of this work.

49 Frac Fluid (1 gal) 3-Month Oil(1 bbl) 33 3-Month Oil over Time -Parshall Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time(month-yea) Figure a:3-month cumulative oil with time for 88 wells in Parshall-Vanhook, Mountrail County. ND. 3, Frac Fluid over Time-Parshall 2,5 2, 1,5 1, 5 Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time(month-year) Figure b: Fracture fluid with time for 88 wells in Parshall-Vanhook Field Proppant and fracture fluid showed increasing usage with time for the Parshall-Vanhook fields.

50 Lateral Length (ft.) Proppant (1 lb.) 34 Proppant over Time-Parshall 4,5 4, 3,5 3, 2,5 2, 1,5 1, 5 Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time(month-year) Figure c: Proppant usage with Time for 88 wells in Parshall-Vanhook Fields Lateral Length over time-parshall Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time(month-year) Figure d: Lateral length of 88 horizontal wells in Parshall-Vanhook Fields. With the exception of few long laterals drilled by fringe operators, lateral lengths for the field averaged 45 feet in both Parshall and Vanhook. Since the 3-month cumulative oil plot with

51 3-Month Oil (1 bbl) PPG (lb/gal) 35 time showed a decreasing trend, we expect to see the same trend for production per foot of lateral. PPG over Time-Parshall Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time(month-year) Figure e: Proppant to fluid ratio over time for Parshall-Vanhook Fields 7 3-Month Oil vs. PPG-Parshall PPG( proppant to fluid ratio in lb/gal) Figure f: 3-month oil production with proppant to fluid ratio (PPG) - Parshall-Vanhook.

52 3-Month Oil/Foot(bbl/ft) 36 The first time segment or region A (Jun-8 to Dec-8) from figure e had high values of PPG as a result of low volume, high proppant concentration job to produce more oil. A quick look at figure e also reveals stimulation treatment for the third time segment or region C (Jan-1 to Aug-1) used high volume of frac fluid than proppant (smaller PPG) to obtain the marginal fracture intensity for oil production volumes. A plot of PPG with time in figure e therefore showed a downward trend with time. 3-month oil with proppant to fluid ratio (PPG) shows an upward trend with positive slope. It indicates lower values of PPG corresponding to higher frac volume and relatively lower proppant treatments; and higher PPG values are consistent with low gelled water treatments. 3-Month Oil/Foot over Time Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time(month-year) Figure g: 3-month oil per foot over time for Parshall-Vanhook fields. 3-month oil per foot shows similar trend as the 3-month oil over time since the laterals are of the same approximate length, there will not be much variation in the oil per foot values.

53 3 Month Cummulative Oil (1bbl) 37 PARSHALL FIELD We now investigate the treatment designs and the production response for the Parshall field only using the dominant operator AE in the Parshall area. A plot using only the parameters for the operator AE in the Parshall area is shown in figure The 3-month oil production follows the same trend as the entire Parshall-Vanhook group, decreasing in production volumes with time. The chart for AE is grouped into three distinct zones, marked by different time intervals circled as A, B and C. For the regions A, B and C, we will plot their production trends with time, proppant and fluid usage with time from figures a-i, to compare the trends to those of the Parshall-Vanhook field plots. Parshall Field Oil Production with Time Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time (month-year) Figure : 3 Month Oil with time for Operator AE in Parshall.

54 38 The period July-8 to December-8 tagged as region A has a consistent increase in production with time. The region B marks the time line June-9 to September-9 also maintains a consistent average parameters. Region C marks the zone for the least production in the group and is identified by April-1 to August-1 timeline. Although combined output shows a downward trend with time, a look at the plots for Regions A, B and C show mixed results. Region A shows a consistent use of the same average amount of fracture fluid and proppant for stimulation. Gelled water and fine proppant size 1 Mesh was used for treatment resulting in the best frac production. The high proppant concentration, low volume water based frac must have been designed for conductivity in the more permeable area than regions Band C. Region B shows increased use of proppant and fluid volume over time but recorded a downward trend in production response. Cross-linked fluid was the main fracture fluid type with some occasional use of water. The bigger 2/4 proppant size was in greater use unlike the 1 mesh sand mostly recorded for A, but there are instances where the 1 mesh was combined with 2/4 for treatment in region B. We see the use of a high proppant concentration and low volume cross-linked job signatures for a possible less permeable and less naturally fractured region B compared to A region, Region C records the least production volume over time. The treatment is characterized by high proppant, high volume and low proppant concentration cross-linked and increased staged job. We infer the treatment was to achieve fracture intensity over the length of the well. Region C may be of lower quality reservoir rock than the other two regions. The average characteristics of

55 Proppant Weight (lb) 3 Month Oil (1 bbl) 39 the three regions are captured in table and detailed investigation of the production variation is covered in Section 4.3 of this chapter. 3 Month Oil with Time - A Jun-8 Jul-8 Sep-8 Oct-8 Dec-8 Time (month-year) Figure a 3 Month oil production with time for region A-Parshall 3.E+6 Proppant Weight with Time- A 2.E+6 2.E+6 1.E+6 5.E+5.E+ Jun-8 Jul-8 Sep-8 Oct-8 Dec-8 Time (month-year) Figure b: Proppant usage with time in region A-Parshall

56 3 Month OIL (1 bbl) Frac Fluid Volume (gal) 4 Frac Volume with Time - A 9.E+5 8.E+5 7.E+5 6.E+5 5.E+5 4.E+5 3.E+5 2.E+5 1.E+5.E+ Jun-8 Jul-8 Sep-8 Oct-8 Dec-8 Time (month-year) Figure c: Frac fluid usage with time for region A-Parshall 3 Month Oil with TIME - B May-9 Jul-9 Aug-9 Oct-9 Dec-9 Jan-1 Time ( month-year) Figure d: 3-month cumulative oil with time for region B-Parshall

57 Frac Fluid Volume (gal) Proppant Weight (lb) 41 Proppant with Time -B 4.E+6 3.E+6 2.E+6 1.E+6.E+ May-9 Jul-9 Aug-9 Oct-9 Dec-9 Jan-1 Time( month-year) Figure e: Proppant usage with time for region B-Parshall Frac Fluid with Time - B 2.E+6 1.E+6 5.E+5.E+ May-9 Jul-9 Aug-9 Oct-9 Dec-9 Jan-1 Time (month-year) Figure f: Frac fluid usage with time for region B-Parshall 3 Month OIL vs Time -C Mar-1 Apr-1 May-1 May-1 Jun-1 Jul-1 Jul-1 Aug-1 Figure g: 3-month cumulative oil with time for region C-Parshall

58 42 4.E+6 Proppant with Time -C 3.E+6 2.E+6 1.E+6.E+ Mar-1 Apr-1 May-1 May-1 Jun-1 Jul-1 Jul-1 Aug-1 Figure h: Proppant usage with time for region C-Parshall 2.E+6 Frac Fluid with Time -C 2.E+6 1.E+6 5.E+5.E+ Mar-1 Apr-1 May-1 May-1 Jun-1 Jul-1 Jul-1 Aug-1 Figure i: Frac fluid usage with time for region C-Parshall Table : Average field characteristics for regions A, B and C for Parshall Region Lateral Proppant Fluid PPG 3Month 3Month Treatment Stages Length Weight Volume Oil Gas Rate # (ft.) (lb.) (gal) (1 3 bbl) (1 3 Mcf) (bpm) A ,75,583 (1mesh) 663, N/A N/A B ,375,1 (mixture) 539, N/A 8 C ,157,115 (2/4) 1,43, N/A 13

59 3 Month Oil (1bbl) 43 VANHOOK The Vanhook controlling factors with time as well as controlling factors with the 3-month cumulative oil are similar to the Parshall plots and they will not be repeated here, but the summary of field characteristics for Vanhook in comparison to the Parshall field is captured. 3 month Oil with Time -Vanhook Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time(month-year) Figure : 3-month oil with time for Vanhook Production decline over time for Vanhook which is similar to Parshall is discussed under Section 4.3. Production versus Number of Stages We next explore the trend involving increased staging treatments and averaged production and attempt to determine the economic stage using figures from the dominant Operator AE in Parshall. The average oil production for wells in the following stage groupings is used for figure Up to 1 Stage Counts (Best Performance)

60 Average Cumulative Oil (bbl) to 15 Stage Counts 16 to 19 Stage Counts 2 to 22 Stage Counts 23 to 25 Stage Counts 26 to 29 Stage Counts and 3 to 3+ Stage Counts 25 Average Oil Production by Stages (Operator AE) to 15 Stages up to 1 Stages 16 to 19 Stages 2 to 22 Stages Cummulative Time (months) Figure Average oil production with stage count Operator AE, Parshall We see higher production associated with lower stage counts up to 1, followed by the groups. The results affirm the trends observed for the regions A, B and C, with the lower stage counts reflecting trends in the high quality reservoir region A and greater staging with increased job size, a requirement for the region C. The anomaly in stimulation response is explained Section 4.3.

61 3-Month Oil (1bbl) 45 Controlling Factors with 3-Month Cumulative Production The relationship between a controlling factor and the 3-month production response is plotted in a chart followed by verification of the statistical significance of each individual controlling factor to the 3 month production metric using the t-test statistic and the r-squared value.the combined effect of controlling factors to production response variant will be examined in a statistical model in latter section of this chapter. 3-Month Oil vs Length-Parshall Lateral Length (1 ft.) Figure a: 3-Month oil production vs. lateral lengths for 84 wells Parshall-Vanhook

62 3-Month Oil (1bbl) 3-Month Oil (1bbl) 46 3-Month Oil vs Fluid-Parshall Frac Fluid (1gal) Figure b: 3-Month oil vs. Fracture fluid for 84 wells in Parshall-Vanhook Month oil vs Proppant-Parshall Proppant (1 lbs.) Figure c: 3-month oil vs. Proppant for Parshall-Vanhook Less fracture fluid and more proppant provide higher proppant concentration for increased production. High volume fluid and low proppant resulting in low proppant concentration gives less oil production. The 3-month oil versus proppant concentration chart provides the limit of

63 3-Month Oil (1 bbl) 47 proppant concentration (PPG) for better production. The 2 to 3 PPG range gives the best production response Month Oil vs. PPG-Parshall PPG( proppant to fluid ratio in lb/gal) Figure d: 3-month oil vs. proppant concentration for Parshall-Vanhook Table Correlation of controlling factors with 3 Month Oil Production Controlling Factor Lateral Length Proppant Mass Frac Fluid Volume Number of Stages Treatment Rate Treatment Pressure Constant Coefficient SE of Coefficient T P R- Squared Significance P % No % No % No No % No % No

64 48 Oil Production with Time 36 MONTH 3 MONTH 12 MONTH Vanhook Parshall 6 MONTH Average Oil Production (1 bbl) Figure : Cumulative oil production for Parshall and Vanhook- Mountrail County

65 3 Month Oil( 1bbl) SANISH FIELD-MOUNTRAIL The plot of 3-month cumulative oil production with time is shown in figure for 9 wells in the Sanish field in the Mountrail County of North Dakota. The plot shows an upward trend with a marginal increase in oil production over time. We explore the contribution of any of the controlling factors to this production trend over the same period of time. The spread of lateral length for the Sanish field is shown in figure Lateral length with time shows a bimodal distribution for two operators for the data collected. The dominant operator AW shows consistency with an average lateral length of 9316ft with the fringe operator averaging 5128 ft. We further examine the impact of these choices along with other controlling influences in the treatment design using cross plots. The plot of 3-month cumulative oil production with time is shown in the chart below for the Sanish field. 3 Month Oil with Time -Sanish Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time(month-year) Figure : 3-month oil production for 9 wells in the Sanish-Field Mountrail County.

66 Proppant (1 lb) Lateral Length (ft) 5 Lateral Length with Time - Sanish Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time(month-year) Figure Lateral length over time in the Sanish field Proppant with Time -Sanish Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time(month-year) Figure : Proppant usage with time in the Sanish Field Proppant usage over time is shown in figure We observe that from June-8 to September-9, million pounds of proppant was used for stimulation treatment. For the

67 Frac Fluid (1 gal) 51 October-9 to August-1 period proppant usage averaged around 2.5 million pounds which resulted in an appreciable oil production Fluid Volume with Time-Sanish Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time(month-year) Figure : Fracture fluid volume over time in the Sanish field. Fracture fluid volume usage trend is depicted in figure for Sanish field. The plot shows consistently, less than one million gallons of fluid was used up to September-9, with the period from October- 9 to August-1 showing a marked increase above 1million to about 2 million gallons of fracture fluid. We can infer that the combined effect of increased proppant and frac fluid volume accounted for the upward trend in production shown in figure We next examine the trend of proppant to frac fluid concentration (PPG) over time and its impact on the 3 month cumulative oil production. In figure , the chart shows an even spread of proppant concentration between 2 to 2.5 pounds per gallon for the period up to September-9 then a slight increase afterwards. The impact of PPG on production is seen in figure where production is clustered around the 2 to 2.5 PPG interval with 2.3 being the optimum PPG.

68 3 Month Oil (1 bbl) Proppant to Fluid Ratio (lb/gal) PPG with Time -Sanish Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time (month- year) Figure : Proppant to fluid concentration over time in the Sanish field. 3 Month Oil with PPG-Sanish PPG Proppant to Fluid ratio (lb/gal) Figure : 3-month oil production vs. proppant concentration (PPG) in the Sanish field. We explore trend of number of stages from the plot with 3-month cumulative oil production.

69 3-month Oil (1 bbl) 3Mon Oil (1 bbl) 53 6 Scatterplot of 3Mon Oil vs Stages Stages Figure : 3-month oil production vs. the number of stages. In figure as the number of stages increased, there was a corresponding increase in oil production up to 18 stages limit then a decline in average production values for wells with higher stage count. 3-Month Oil vs Treatment Pressure Treatment Pressure (psi) Figure : 3-month oil production vs. treatment pressure-sanish Fields.

70 3-month Oil (1bbl) 54 Two trends are observed for the treatment pressure for oil production in the figure One treatment trend employs lower pressures between psi and lower injection rates shown in figure for higher production. The second trend has pressures in the range of 65-9 psi and relatively high injection rates recording slightly lower production than the first Month Oil vs Treatment Rate Treatment Rate (bpm) Figure : 3-month oil with Treatment rate for the Sanish Field Production per foot of lateral is plotted against proppant per lateral foot for further analysis. The 3 month production per foot and the proppant per foot shows a good corellation. As the proppant per foot variable is increased, we observe a an appreciable increase in the production per foot reponse. This explains the upward trend in production for slight increase in proppant and fluid volumes for the relatively shorter laterals in the dominant operator s wells. The longer laterals are stimulated with higher pressure and rate returns a lower response in production.

71 3 Month Oil/foot(bbl/ft) 55 3Month Oil/ft vs. Proppant/ft- Sanish Proppant per foot (lb/ft) Figure : 3-month oil per foot vs. proppant per foot AVERAGE CUMMULATIVE OIL PRODUCTION by STAGES NUMBER OF CUMMULATIVE MONTHS Up to 1 Stages Stages 2-22 Stages 23-25Stages 3-3+ Stages 9 Stages COMPANY B Figure : Average cumulative production by stage by dominant operator AW in Sanish.

72 56 Figure shows the data for operator AW, as the number of stage count was increased, there was a corresponding increase in the proppant and fluid volumes that resulted in greater production up to a limit (16-18), after which any further staging recorded smaller production volumes.the fringe operator B doing 9 stages with shorter laterals is shown as company B on the graph. Controlling Factors with 3-Month Cumulative Production. We summarize the significance of each controlling factor to 3 month production response variant and consider the associted effect with other factors to the oil and gas production response in a statistical model in later section 4.4 of this chapter. The relationship of each controlling factor to the 3-month oil production is shown in the next series of charts and a summary of their statistic significance and degree of correlation is shown in table Table : Correlation of controlling factors with 3 Month Oil Production for Sanish Controlling Factor Lateral Length Proppant Mass Frac Fluid Volume Number of Stages Treatment Rate Treatment Pressure Constant Coefficient SE of Coefficient T P R- Squared Significance P % Yes % Yes % Yes % Yes % No % Yes

73 3-Month Oil (1bbl) 57 Table : Average Treatment Characteristics for operators AW and B in the Sanish Field. Operator Length Proppant Fluid Volume Rate Pressure PPG 3 Month Oil ft lb (gallons) bpm psi lb/gal bbl , ,4, ,779 AW(averaged) AW(High) ,619,957 1,178, ,158 B ,525, , ,572 Table is summary of average characteristics of the two dominant operators in Sanish field for the data set collected. Operator AW(averaged) is the average treatment values of all wells treated by the firm while Operator AW(High) are average values of wells treated at high injection rates and high treatment pressure by operator AW. 3-Month Oil vs Length -Sanish Lateral Length(ft.) Figure a: 3-month oil vs. Lateral length for 9 wells in Sanish Field

74 3-Month Oil (1 bbl) 3-Month Oil (1bbl) 58 3-Month Oil vs Proppant-Sanish Proppant (1 lbs.) Figure b: 3-month oil vs. Proppant for 9 wells in Sanish Field Month Oil vs Fluid-Sanish Frac Fluid (1 gal) Figure c: 3-month oil vs. Fracture Fluid for 9 wells in Sanish Field The three plots (figure a-c ) show that oil production increased with the three controlling factors ( ie. lateral length, mass of proppant and fracture fluid). For the laterals, the 9ft. ones appear to be producing better than the shorter ones on the average. As the quantity of proppant increased, there was significant increase in oil production and similar trend is observed for increase in fluid volume and production output.

75 3 Month Oil (1 bbl) Lateral Length (ft) STANLEY, ROBINSON LAKE, ROSS AND ALGER FIELDS-MOUNTRAIL 12, Lateral Length with Time 1, 8, 6, 4, 2, Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time (month-year) Figure : Lateral length of 7 wells over time. There are three ranges of lateral lengths drilled with time for this region. We have a 4-6ft, 65-85ft and 9ft plus range for different operators in the four fields. 3 3 Month Oil with Time Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time (month- year) Figure : 3-month oil production with time for 7 wells in SRRA-Mountrail County.

76 Frac Fluid (1 gal) Proppant (1lb) 6 The 3-month cumulative oil production with time shows degree of dispersion in the production values which might be an indication of variation in treatment styles by the operators or may be due to other factors which we will examine later in Section 4.3 of this work. 5 Proppant with Time Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time (month-year) Figure : Proppant usage with time for 7 SRRA wells in - Mountrail County Frac Fluid with Time Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time (month-year) Figure : Fracture Fluid with time for 7 SRRA wells in Mountrail County

77 Proppant to Fluid Ratio (lb/gal) 61 We observe a significant contribution of proppant and fracture fluid volumes to oil production from their plots with time. The two controlling factors were increased proprtionately over the same period of oil production increase.proppant to fluid concentration (PPG) with time chart is shown in figure , treatment rate with time in figure and treatment pressure with time in figure for making futher deductions on their contribution to oil production. From the plots, we see lower PPG values at later months corresponding to greater oil production. As we observed from earlier plots for proppant and frac fluid usage supporting production with time, we infer that relatively higher fluid volumes were used than proppant resulting in the low proppant concentration.treatment rates and pressures also increased with time for increased oil production. We have high volume, low proppant concentration, high rate and pressure treatment resulting in higher production with time.the treatment style or strategy could be targeting a farfield fracture intensity, propping a ductile reservoir rock or intersecting a basin structural element to support oil production. We will look at individual fields to find where this will hold true Proppant to Fluid Ratio with Time Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time (month-year) Figure : Proppant to fluid ratio with time for SRRA- Mountrail County

78 Treatment Pressre (psi) Treatment Rate (bpm) 62 Treatment Rate with Time Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time (month-year) Figure : Treatment rate with time for SRRA in Mountrail County 12 Treatment Pressure with Time Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time (month--year) Figure Treatment pressure with time for SRRA- Mountrail Count In summary we observe that high volume, low proppant concentration at higher treatment pressure and treatment rates yields greater oil production. We will explore individual fields to verify if this holds for all areas and also if the strategy is for treating only the longer laterals.

79 Proppant (lb) 3 Month Production(1 bbl) 63 STANLEY The 3-month oil production for Stanley plot shows marginal increase in oil volumes over time Months Oil with Time Stanley Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 time (month-year) Figure : Oil production with time for Stanley Field 3 Proppant with Time-Stanley Jun-8 Sep-8 Dec-8 Mar-9 Jul-9 Oct-9 Jan-1 May-1 Aug-1 Time(month-year) Figure : Proppant with time for Stanley Field

80 PPG (lb/gal) Frac Fluid (gal) 64 Plot of controlling factors with time for Stanley show an upward trending usage of proppant and frac fluid. However, there is a relatively greater amount of proppant to smaller fluid volume that accounts for increased proppant to fluid concentration. 25 Frac Fluid with Time-Stanley Jun-8 Sep-8 Dec-8 Mar-9 Jul-9 Oct-9 Jan-1 May-1 Aug-1 Time (month-year) Figure : Frac Fluid use with time for Stanley Proppant to Fluid Ratio -Stanley Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Time (month Year) Figure : Proppant to Frac fluid ratio over time for Stanley

81 Treatment Rate(bpm) PPG (lb/gal) 65 Treatment pressure and injection rate also increases with time for treating relatively shorter laterals. The plots of the controlling factors are shown in figures PPG vs Length - Stanley , 4, 6, 8, 1, Lateral Length-(ft.) Figure : PPG vs. Lateral length for wells in Stanley Treatment Rate with Time- Stanley Jun-8 Sep-8 Dec-8 Mar-9 Jul-9 Oct-9 Jan-1 May-1 Aug-1 Time (month -year) Figure : Treatment rate with time for Stanley Field

82 66 We can infer that the high volume, low propant concentration may be a strategy for the longer laterals in the region.from figure , the increasing trend of higher proppant concetration with less fluid volumes in shorter laterals at moderate treatment pressure and fluid injection rates is a possible design for higher conductivity to fracture intensity. Avoiding leakoffs and screenouts could also be factor for the low volume,moderate injection and treatment pressure treatment design for the shorter laterals.

83 3 Month Oil (1 bbl) 67 ROSS AND ALGER FIELDS These two fields exbit the same treatment characteristics as observed for the SRRA region.they show higher oil production consistent with high volume, low proppant concentration at higher injection rate and treatment pressure. The treatment signature could be to achieve far-field fracture intensity in the longer laterals or for intersecting a basin geostructural element for better drainage. The time trend of treatment parameters is shown for only one of two fields and the summary of all field characteristics for the SRRA region is captured in a table We also assess the impact of these treatment styles by observing progressive stage count on production as captured in plots for each field Month Oil with Time - Ross Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time (month- year) Figure : 3 Month oil production with time Ross We see the contribution of increased proppant and fracture fluid to the incresing production in figures ,16.

84 Frac Fluid (gal) Proppant (lb) 68 Proppant with Time-Ross Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time (month-year) Figure : Proppant usage with time for Ross 3 Frac Fluid with Time-Ross Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time (month-year) Figure : Frac Fluid with time for Ross

85 Treatment Rate (bpm) PRoppant to Fluid Ratio(lb/gal) Proppant to Fluid Ratio with Time - Ross Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time (month- year) Figure : Proppant concentration with time for Ross-Field 5 Treatment Rate with Time-Ross Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time (month-year) Figure : Treatment Rate with time for Ross Field Figures show the stage count with production in Ross, Stanley and Alger Fields.

86 Average Oil (1bbl) Average Cumulative Oil (1bbl) 7 Production by Stage Count-Stanley Up to 1 Stages Stages Stages 2-22 Stages 3-3+ Stages Time( months) Figure : Average Production by stages for Stanley 3 Production by Stage Count-Alger Up to 1 Stages Stages Stges 2-22 Stages 3-3+ Stages Time (months) Figure : Average Prroduction by stage count for Alger

87 Average Oil (1bbl) 71 Production by Stage Count-Ross Up to 1 Stages Stages 2-22 Stages Stages 3-3+ Stages Time(months) Figure : Average production by stages for Ross The average field characteristics for each of the fields under SRRA is summarized in table Table : Summary of average treatment parameters for SRRA fields. FIELD Length Proppant Fluid Volume Rate Pressure PPG 3 Month Oil ft lb (gallons) bpm psi lb/gal bbl ALGER 6,766 2,525,11 1,761, , ,125 STANLEY 6,165 1,579, , , ,497 ROSS 8,91 2,26,514 1,342, , ,268 ROBINSON LAKE 9,6 2,183,66 1,83, , ,87

88 3-Month Oil-(1 bbl) 3-Month Oil (1 bbl) 72 Controlling Factors with 3-Month Cumulative Production. The relationship of each controlling factor to the 3-month oil production is shown in the next series of charts and a summary of their statistic significance and degree of correlation is captured in Table Month Oil vs Length-SRRA , 4, 5, 6, 7, 8, 9, 1, 11, Lateral Length (Ft.) Figure a: 3-Month oil vs.lateral length for SRRA Fields- Mountrail County Month Oil vs Proppant-SRRA Proppant(1 lbs) Figure b: 3-Month Oil vs Proppant for SRRA in Mountrail

89 3-Month Oil (1bbl) 3-Month Oil (1bbl) 73 3-Month Oil vs Frac Fluid-SRRA Frac Fluid (1 gal) Figure c: 3-Month oil vs. Fracure fluid for SRRA-Mountrail Month Oil vs PPG-SRRA PPG (lb/gal) Figure d: 3-month oil vs. Proppant concentration (PPG) for SRRA- Mountrail

90 3-Month Oil (1bbl) Month Oil vs Stages-SRRA Number of Stages Figure e: 3-month oil vs. Number of Stages for SRRA Mountrail Figures a-e, show increase in the controlling factors, resulted in higher oil production. Finally we summarize the significance of each controlling factor to 3 month production response variant and consider the associted effect with other factors to the oil and gas production response in a statistical model in later section of this chapter. Table Correlation of Controlling factors with 3 Month Oil Production for SRRA Controlling Factor Lateral Length Proppant Mass Frac Fluid Volume Number of Stages Treatment Rate Treatment Pressure Constant Coefficient SE of Coefficient T P R- Squared Significance P % Yes % Yes % Yes % Yes % Yes % Yes

91 Time (month) 75 A chart showing cummuative oil production over time is shown below for the SRRA region. Average Oil Production with Time 36Month 3Month 12Month ROBINSON LAKE ROSS STANLEY ALGER 6Month Average Cumulative Oil (bbl) Figure : Average oil production for Stanley, Robinson Lake, Ross and Alger Fields- Mountrail County, North Dakota

92 Frac Fluid (1gal) 3 Month Oil (1bbl) McKenzie COUNTY 3 Month Oil with Time-McKenzie Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time (month-year) Figure : 3-month oil with time for 5 wells in McKenzie County There is an upward trend of oil production with time and we will explore the contrbution of proppant and frac fluid use toward it. Frac Fluid withtime-mckenzie Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time(month-year) Figure Frac fluid with time for 5 wells in McKenzie County

93 Proppant to Fluid Ratio (lbs/gal) Proppant (1lb) 77 Proppant with Time-McKenzie 4, 3,5 3, 2,5 2, 1,5 1, 5 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time(month-year) Figure : Proppant use with time for 5 wells in Mcenzie County Proppant and frac fluid both increased with time, with relatively more fluid quantities pumped to give a slightly decreasing trend of proppant to fluid ratio with time as shown below PPG with Time-McKenzie Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time(month-year) Figure : Proppant to fluid ratio (PPG) with time for 5 wells in McKenzie County.

94 Treatment Rate (bpm) Treatment Pressure (psi) Treatment Pressure with Time- McKenzie Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time(month-year) Figure : Treatment pressure over time for Mckenzie County Treatment rate is fairly consistent reducing slightly with time whilst treatment pressure increases with time for fracturing longer laterals. Treatment Rate with Time-McKenzie Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time (month-year) Figure : Treatment rate with time for McKenzie County.

95 Treatment Rate(bpm) Lateral Length (ft) 79 Lateral Length with Time-Mckenzie Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 TIME (month-year) Figure : Lateral length of 5 wells with time in McKenzie County The lateral length of wells falls within (39-6) and (8-17) feet range for the data set. From plots of treatment pressure, injection rate and 3 month cumulative oil with lateral length shown in figure a-c, we infer that longer laterals are frac-stimulated at higher pressures and fluid injection rates from 25-6bpm to achieve far-field fracture intensity; and the shorter laterals are fraced at lower to high (36-6 bpm) fluid injection rates and lower pressures Lateral Length(ft) Figure a: Treatment Rate vs. lateral length for wells in McKenzie

96 PPG(bpm) Treatment Pressure(psi) Lateral Length (ft) Figure b: Treatment Pressure vs. Lateral length for wells in McKenzie Lateral(ft) Figure c: Proppant Concentration vs. Lateral length for 5 wells in McKenzie Plots of PPG with lateral length and 3 month oil with PPG in figure a-c, shows that as proppant to fluid concentration increases, there is an increase in production for both shorter and longer laterals. This supports increase in stage count over time trend as well as oil production.

97 Stage Count 3Month Oil (bbl) 3 Month Oil (1bbl) Lateral Length(ft) Figure a: 3-month oil vs. Lateral length for 5 wells in McKenzie PPG(bpm) Figure b: 3-month oil vs. PPG for 5 wells in McKenzie Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time-(month-year) Figure c: Number of Stages with Time for McKenzie Wells

98 82 The McKenzie data set is divided into 3 areas based on geographical location for further analysis. Region A considers well activity for all sections in T (148,149) N and R (92-98) W combinations. Region B looks at wells for all sections in T (15,151) N and R (92-98) W permutation whilst Region C is for wells in the T (152,153) N and R (92-98) W. Table : Summary of average treatment parameters for A, B and C regions in McKenzie County. Region Length Proppant Fluid Volume Rate Pressure PPG 3 Month Oil ft lb (gallons) bpm psi lb/gal bbl A ,719,898 1,396, ,135 B ,77,389 1,35, ,69 C 754 1,415,17 1,166, ,691 Mckenzie ,544,414 1,265, ,713 Region B follows the trend of stimulating of longer laterals at higher pressure, fluid injection rate (25-6 bpm.) and proppant concentration between the 1-2 PPG ranges. This signature records the highest average 3 month cumulative oil for the McKenzie data set followed by Region C which shows a higher fluid injection rate, lower pressure and high proppant concentration treatment. Though region A has the highest proppant and fluid volumes as well as treatment pressure and treatment rate, it has the least oil production for the 3 month period. We will explain the anomaly in Section 4.3 of this chapter. A further look at Region C reveals increased stage count results in increased oil production. The plot of average production for each stage count for Region C is shown in figure

99 Cummulative Oil(1 bbl) Average Oil by Stage Count-C Up to 1 Stages 11 to 15 stages 19 to 21 Stages 24 to 29 Stages Time (months) Figure : Stage-wise average oil with time for region C-McKenzie County Increased staging with increased fluid and proppant resulted in increased oil production over time. The only departure from the trend is noticed with the stage count where are all the controlling factors are low in value compared with the up to 1 Stages values. Also all the stages followed one of the stimulation signatures discussed for Mackenzie with the exception of 11to 15 stages. 3 Month cumulative oil with treatment parameters The plots of the relationship of the treatment parameters with 3-month cumulative oil is shown next followed by table listing the summary of their statistic significance and degree of correlation. The 3 month cumulative oil increased with the inccrease in all treatment factors except treatment rate and treatment pressure.

100 3-Month Oil (1 bbl) 3-Month Oil (1 bbl) 3-Month Oil (1 bbl) 84 3-Month Oil vs Length -McKenzie Lateral Length (ft.) Figure a: 3-month Oil vs. lateral length for 5 wells in McKenzie 3-Month Oil vs Proppant -Mckenzie , 1,5 2, 2,5 3, 3,5 4, Proppant (1 lbs) Figure b: 3-month oil vs. proppant for 5 wells in McKenzie. 3-Month Oil vs. Fluid-McKenzie Frac Fluid (1 gal) Figure c: 3-month oil vs. frac fluid for 5 wells in McKenzie

101 3-Month Oil (1 bbl) 3-Month Oil (1 bbl) 3-Month Oil (1 bbl) 85 3-Month Oil vs PPG-McKenzie Proppant to Fluid-PPG (lb/gal) Figure d: 3-month oil vs. proppant concentration (PPG) for 5 wells in McKenzie 3-Month Oil vs Stages-Mckenzie Stages Figure e: 3-month oil vs. number of stages for McKenzie 3-Month Oil vs Pressure -Mckenzie Treatment Pressure (psi) Figure f: 3-month oil vs. treatment pressure for McKenzie

102 3-Month Oil (1 bbl) Month Oil vs Treatment Rate- Mckenzie Treatment Rate (bpm)- Figure g: 3-month oil with treatment rate for McKenzie Table : Correlation of controlling factors with 3-month oil production -McKenzie County Controlling Factor Lateral Length Proppant Mass Frac Fluid Volume Number of Stages Treatment Rate Treatment Pressure Constant Coefficient SE of Coefficient T P R- Squared Significance P % No % Yes % Yes % Yes % No % No The table above shows proppant, fluid volume, and number of stages are significant in predicting the 3-month response variable.

103 3 Month Oil(1bbl) DUNN COUNTY The cumulative oil response to the controlling predictors of proppant, lateral length, frac fluid volume, treatment rate and pressure, and number of stages is observed over time in this section. The 3-month cumulative oil from start of production for 9 wells is shown below. 3 Month Oil over Time-Dunn County Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time(month-year) Figure : 3-month cumulative oil production for 9 wells in Dunn County. We see from the plot above that oil production increases over time. We explore from the plots of the controlling factors over time if they have a correlation with the oil response trend for the same time period. Proppant usage over time is shown in figure , where we observe a significant increase in total proppant used for the 3-month oil production trend. Figure shows the volume of frac fluid usage over time. Oil production increases with frac fluid volume. The proppant to frac fluid concentration over time is shown in figure

104 Frac Fluid (1 gal) Proppant Weight( 1lbs) 88 Proppant over Time-Dunn County Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time (month-year) Figure : Total proppant weight over time for 9 wells in Dunn County Frac Fluid with Time-Dunn County Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time (month-year) Figure : Frac fluid volume over time for 9 wells in Dunn County From the proppant to fluid concentration we observe the same increasing trend with time as proppant and frac fluid usage for the same period. This is an indication of greater quantity of proppant usage relative to fluid volume.

105 Treatment Rate(bpm) Proppant to Fluid Ratio(lb/gal) 89 Proppant to Fluid vs Time-Dunn Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time(month-year) Figure : Proppant to fluid ratio (PPG) over time for 9 wells. Treatment Rate with Time-Dunn Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time(month-year) Figure : Treatment rate over time for 9 wells in Dunn County The treatment rate plot over time shows a bimodal range of 8-12bpm and 2-6 bpm for the treatment of longer and shorter laterals which gives different production response as shown in the figure for 3-month oil production to treatment rate.

106 Treatment Rate (bpm) 3 Month Oil (1 bbl) 9 3 Month Oil vs Treatment Rate-Dunn Treatment Rate (bpm) Figure : 3-month oil vs. treatment rate for wells in Dunn County Treatment Rate vs Lateral Length Lateral Length (ft) Figure : Treatment rate vs. lateral length for wells in Dunn County. From the figures above we observe two production responses associated with treatment rate for laterals. We see higher production for both longer and shorter laterals at lower treatment rates.

107 Lateral Length in (ft) Treatment Pressure(psi) 91 We also observe that higher treatment rates for longer laterals produced less oil than at lower rates. We will get a better understanding when we look at production pattern for the fields. Treatment Pressure over Time-Dunn Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time(month-year) Figure : Treatment pressure with time for wells in Dunn County 12 1 Lateral Length vs Time-Dunn Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Time (month-year) Figure : Lateral length drilled over time for 9 wells in Dunn County

108 3 Month Oil(1 bbl) 3 Month Oil (1bbl) 92 3Month Oil vs Lateral Length-Dunn Lateral Length(ft) Figure : 3-month oil vs. lateral length of 9 wells in the Dunn County The lateral length over time plot shows a bimodal range of lengths drilled. We have the ( ft.) and the shorter ( ft.) range of laterals with the longer lateral producing more 35 3 Month Oil vs. PPG-Dunn PPG ( lbs/gal) Figure : 3-month oil vs. PPG for 9 wells in the Dunn County.

109 93 oil on the average. 3-month oil vs. proppant to fluid concentration (PPG) shows the region A for the interval 1. to 1.5 PPG has the highest average oil production. In summary lower rate as depicted by region R in figure , higher proppant concentration at moderate to high treating pressures yield the most oil. We examine the fields for this trend in a summarized average treatment characteristic table. Table Summary of average treatment parameters for Dunn County Fields. Field Length Proppant Fluid Volume Rate Pressure PPG 3 Month Oil ft lb (gallons) bpm psi lb/gal bbl Killdeer , , N/A.38 16,32 Bailey ,989 82, N/A.78 81,766 Murphy Creek ,69,787 1,184, N/A.8 17,689 Lost Bridge ,29 766, ,833 Little Knife ,93,978 1,644, ,234 Dunn ,26,594 1,23, ,982 From the table, Little Knife and the Lost Bridge fields satisfies the characteristics for higher oil production followed by Murphy Creek s oil production which is aided by high amount of proppant pumped. Lost Bridge would have done better production with additional proppant. We explore the contributions to the production variation by studying the physical and geological attributes of the fields in Section 4.3. The 3-month oil production relationship with each of the treatment parameters is depicted by charts in figures a-e.

110 3-Month Oil (1 bbl) 3 Month Oil (1bbl) 94 3Month Oil vs Lateral Length-Dunn Lateral Length(ft). Figure a: 3-month oil vs. lateral lengths of 9 wells in Dunn County Month Oil vs Proppant-Dunn Proppant (1 lb) Figure b: 3-month oil vs. proppant for 9 wells in Dunn County

111 3 Month OIl (bbl) 3 Month Oil(1 bbl) 3-Month Oil (1 gal) Month Oil vs Fluid-Dunn Frac Fluid (1 gal) Figure c: 3-month oil vs. frac fluid for 9 wells in Dunn 4 3-month Oil vs PPG -Dunn PPG ( lbs/gal) Figure d: 3-month oil with PPG for 9 wells in Dunn County Month Oil vs Pressure Treatment Pressure(psi) 9 1 Figure e: 3-month oil with treatment pressure for wells in Dunn County

112 96 Next we study the standalone impact of controlling factors to the 3-month production metric and sum up their statistical significance in a table. Table Correlation of Controlling factors with 3 Month Oil Production for Dunn Controlling Factor Lateral Length Proppant Mass Frac Fluid Volume Number of Stages Treatment Rate Treatment Pressure Constant Coefficient SE of Coefficient T P R- Squared Significance; P No Yes Yes Yes Yes No Proppant, fracture fluid, number of stages and treatment rate are significant in predicting oil production response

113 Proppant (1lb) 3 Month Oil (bbl) : DIVIDE, WILLIAM AND BURKE COUNTIES 3 Month Oil with Time-DWB Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Sep-11 Time(mounth-year) Figure : 3-month oil vs. time for 5 wells in Divide, William and Burke (DWB) Counties The 3-month cumulative oil with time shows an upward increasing trend which is supported by increased number of proppant and fluid pumped as shown in the next two charts. 5, Proppant with Time-DWB 4, 3, 2, 1, Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Sep-11 Time(month-year) Figure : Proppant usage over time for 5 wells in Divide, William and Burke Counties.

114 Proppant to Fluid Ratio (lb/gal) Frac Fluid (1gal) 98 Frac Fluid with Time-DWB 5, 4,5 4, 3,5 3, 2,5 2, 1,5 1, 5 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Sep-11 Time(month-year) Figure : Frac fluid usage over time for 5 wells in Divide, William and Burke Counties. PPG with Time-DWB Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Sep-11 Time(month-year) Figure : Proppant to fluid ratio (PPG) over time for 5 wells in DWB Proppant to fluid ratio plot shows lower proppant concentration supporting increased production over the same time period.

115 Treatment Pressure (psi) Treratment Rate (bpm) 99 Treatment Rate with Time-DWB Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Sep-11 Time( month-year) Figure : Treatment rate over time for 5 wells in Divide, William and Burke Counties. We infer that relatively higher volume of fluid is pumped compared to the proppant used. Treatment rate and treatment pressure plots also show an upward trend with time which together with high volume low proppant concentration supports increased production. 1 Treatment Pressure with Time-DWB Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Sep-11 Time(month-year) Figure : Treatment pressure with time for 5 wells- Divide, William and Burke Counties.

116 3-Month Oil (1 bbl)) Lateral Length(ft.) Lateral Lengh(ft) Lateral Length-DWB Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Sep-11 Time(month-year) Figure Lateral length drilled for 5 Wells in the Divide, William and Burke Counties 12 Lateral length vs. PPG-DWB PPG (lb/gal) Figure : lateral length vs. PPG for fifty wells in Divide, William and Burke Counties Month Oil vs. PPG-DWB PPG(lb/gal) Figure : 3-month oil vs. PPG for 5 wells in the Divide, William and Burke Counties

117 3-Month Oil(1bbl) Month Oil vs. Lateral Length-DWB Lateral Length (ft) Figure : 3-month oil vs. Lateral length for 5 wells-divide, William & Burke Counties. Lateral length over time chart shows a bimodal distribution of 4-6ft and 8-1, ft. bands. The longer laterals within the 1-2 PPG band have higher 3-month cumulative oil production than the shorter laterals with low volume higher proppant concentration (2-2+ PPG). Shorter laterals in the 4-6ft band produce on the average 5,-55, barrel 3-month cumulative oil. All the controlling factors increase with increasing 3-month oil response, with longer laterals having higher oil per foot of lateral than shorter ones. We infer that longer laterals are significant for the area. William County has similar characteristics as the DWB grouping, with longer or increased lateral length and lower PPG (1-1.5 PPG) supporting increased production. We observe that larger fluid volumes, lower proppant concentration and longer reach of lateral wellbore are significant.

118 3-Month Oil(1bbl) 12 For Burke county, longer laterals within the (1 to 1.5 PPG) have better 3-month cumulative oil production than shorter laterals within the 4-6 foot band with higher proppant concentration. Divide county has better production with longer laterals, with PPG also within the range 1-2. Table : Summary of average treatment parameters. County and Length Proppant Fluid Volume Rate Pressure PPG 3 Month Oil Group ft lb (gallons) bpm psi lb/gal bbl William ,652,391 2,241, ,5 Burke ,286,981 1,219, ,155 Divide ,193,79 1,47, ,785 DWB 87 2,467,514 1,816, ,38 3-Month Oil relationship with Controlling Parameters Month Oil vs. Lateral Length- DWB Lateral Length (ft) Figure a: 3-month oil with lateral lengths for 5 wells in DWB Counties

119 3-Month Oil (1bbl) 3-Month Oil (1bbl) 3-Month Oil (1 bbl) 13 3-Month Oil vs. Proppant-DWB , 2, 3, 4, 5, Proppant(1 lb) Figure b: 3-month oil vs. proppant for 5 wells in DWB Counties 3-Month Oil vs. Frac Fluid-DWB , 2, 3, 4, 5, Frac Fluid(1 gal) Figure c: 3-month oil vs. frac fluid for 5 wells in DWB Counties 3 Month Oil vs Stages-DWB Number of Stages Figure d: 3-month oil vs. number of stages for Divide, William and Burke Counties

120 3 Month Oil (1bbl) 3-Month Oil (1 bbl) Month Oil vs Treatment Rate-DWB Treatment Rate (bpm) Figure e: 3-month oil vs. treatment rate for wells in DWB Counties 25 3Month Oil vs Treatment Pressure-DWB Treatment Pessure( psi) Figure f: 3-month oil vs. treatment pressure for wells in DWB counties We next summarize the significance and correlation r-squared values of stimulation parameters with the oil production response in table

121 15 Table : Correlation of controlling factors with 3-month Oil Production Controlling Factor Lateral Length Proppant Mass Frac Fluid Volume Number of Stages Treatment Rate Treatment Pressure Constant Coefficient SE of Coefficient T P R- Squared Significance; P No No Yes No Yes Yes Fracture fluid, treatment rate and treatment pressure are significant statistically with number of stages just outside the p-value threshold.5 for significance.

122 GEOLOGICAL AND STRUCTURAL INFLUENCES ON PRODUCTION This section analyses production variation in the fields and counties that are not sufficiently explained by the controlling stimulation factors. The Bakken formation is made of fields of varying depositional types and rates as well as basin structural movements that affect reservoir quality and petroleum production potential. Parshall The Parshall area under study exhibited three different production trends. The first, from July to December, 28 start of first production had the least average proppant and fluid volume per foot of lateral drilled and the highest production volume. The second from June-September 29 start date produced less than the first period, with an increase in fluid and proppant volumes. The third period from April-August 21 had more proppant and fluid per lateral foot than the first two periods but recorded the least production. Oil production was expected to grow for successive increase in treatment size, but the opposite trend was recorded from July, 28 to August, 21. The Parshall region in the Mountrail County of North Dakota is in an area of low resistivity and high Hydrogen index (HI) shown as P on the map by Nordeng et al., 29 in figure Parshall (P on figure 4.3.1) has HI above 4, which indicates less petroleum generation. It is therefore believed that oil migrated into the area aided by micro fissile and micro-fracture system created by over-pressured matrix rock to receive the oil in place. The geologic mapping of the area also indicates a progressive thinning of all Bakken members towards the southeast. There is a successive decrease in the reservoir thickness of the Bakken as you move from northwest toward southeast section of the field. This structural anomaly explains the reservoir potential; with production in areas towards the northwest, and close to the Sanish

123 17 reservoir requiring less proppant and volume per foot of lateral for more production. Regions A, B and C will respectively represents the three time periods discussed for Parshall. P Figure 4.3.1; Map of Hydrogen Index for North Dakota (Nordeng H., LeFever J., 29) The Parshall region A is closest to Sanish and more northwest than the two other regions B and C. The region C which is in the southeast, is separated from the thicker, over-pressured and more permeable formation towards the northwest as well as the thermal maturity boundary and requires more proppant and fluid per foot of lateral to produce oil economically.

124 18 Figure 4.3.2: Isopach of Bakken showing progressive increase in thickness in the direction of blue arrow for Parshall field (white arrow)-mountrail. (Murphy E., NDGS GI-9321) Resistivity values in ohmm and thickness of Bakken formation were taken from contour maps created by Hester and Schmoker (Hester and Schmoker, USGS-1985) to help explain production variation across the area under study. Resistivity values are used as common measure of oil generated in the reservoir, and thickness an indicator of volume of oil in place that can be successfully produced. The approximate values of these properties were plotted against the 3- month cumulative and the results used to explain variation in production. The normalized resistivity variable which is the resistivity per thickness of the well was also plotted with production volumes for further analysis.

125 19 Figure 4.3.3: Resistivity Contour map of the Middle Bakken (Hester and Schmoker, USGS-1985) Figure 4.3.4: Thickness map of the Bakken (Hester and Schmoker, USGS-1985)

126 11 The next major factor explaining the variability in production is the presence of structural lineaments in the Parshall field. Lateral wellbore intersection with these lineaments aid in oil and gas production in the Parshall field. Figure Snapshot of the Lineament System in Parshall (right-dark shaded area)-ndgs Geologic Investigation 153 Anderson F.J., 212 Anderson (212) reports categories of these lineament phenomena with varying oil production from the northwest trending to the southeast of the Parshall field, with the highest barrel of oil per day (bopd) of more than 1 barrels recorded in the Parshall region A (figure 4.2.2) of this current study. This is indicated by the purple lines with wells in the grouping intersecting one to nine lineaments, with an average of three. Orange lines represent 25-5 bopd and yellow bopd range of production. The green lines represented bopd wells with one to eleven

127 3 Month Cumulative oil(1bbl) Thickness of Well (ft.) 111 intersections with an average of 4. Again the production pattern generally follows the localized thinning trend of the Parshall field. 9 Well Thickness with Time-Parshall Nov-7 Jun-8 Dec-8 Jul-9 Jan-1 Aug-1 Feb-11 Start of Production(month-year) Figure 4.3.6: Well thickness with start of production for Parshall- Mountrail County Month Oil vs Thickness-Parshall Well Thickness (ft.) Figure 4.3.7; 3-Month cumulative oil with well thickness for Parshall- Mountrail County

128 112 The plot of well thickness with time and oil production with well thickness explains the anomaly observed in the Parshall field 3-Month oil production with time in section We observe that higher thickness correlates with more over-pressured reservoir rock that generates a fractured matrix to support greater production. For the Vanhook area the lesser thick formation were drilled first before the higher pay reservoirs, but the general trend for this play, is that of highly thick over-pressured reservoirs accumulating migrating oil and subsequently producing more than the less thick reservoir towards the southeast of the play. Dunn County Dunn area is in the region of thermally matured zone of the Bakken reservoir in North Dakota with hydrogen index (HI) values below 1 and temperature values above the 435 Fahrenheit threshold. Production variability is generally attributed to any of the underlisted; Reservoir thickness Structural elements (faults, anticlines, natural fractures) Geology Stimulation treatment size Five producing fields were studied based on well density according to Well Database information and the production contributing factors listed above. Killdeer, Bailey, Murphy Creek, Lost Bridge and Lost Knife are further evaluated based on variability in production. The Little Knife field production is structurally enhanced by intersecting the Little Knife anticline with large size treatments. From the data set of this study, Little Knife average treatments are more than twice the average sizes of any of the other four fields. The same

129 113 proppant type 2/4 and the finer 1 mesh size were used in Lost Bridge as in Lost Knife indicating variability could not be explained by geological contrast. Little Knife field runs vertically from township N and range 97W while Lost Bridge is spread laterally from range W and township 148N. Killdeer is along the north-south trending Little Knife field. According to Wittstroom et al (1991, 29), Little Knife is a combination of stratigraphic and structural trap with one third of the hydrocarbon in place held in a structural closure sealed by Little Knife anticline. The rest (two-thirds) of the 13 foot oil pay is held in lithological facies ranging from porous dolostones, dolomites to impermeable limestone. Little Knife massive stimulation treatments could be for intersecting these structural traps which according to Wittstroom et al accounts for approximately 5 percent of the original oil in place. Table Average field characteristic values- Dunn County FIELD Length Thickness Resistivity Proppant lbs. Fluid 3 Month feet feet ohm-m Volume gal. Oil (bbl.) Killdeer 8, , ,548 16,32 Bailey 9, ,989 82,663 81,766 Murphy Creek 9, ,787 1,184,259 17,689 Lost Bridge 9, ,29 766,939 16,833 Little Knife 8, ,93,978 1,644, ,234 The Killdeer field is located along the Little Knife field and oil production is aided by this structural anticline. It has higher resistivity than Little knife which implies more oil in place and the over-pressuring effects that produces micro-fractures in the reservoir rock. This explains its

130 114 production potential despite the low proppant to frac fluid concentration. Bailey field has good reservoir thickness and resistivity, which will imply ample oil resource in place. There appears to be no structural contribution to oil production and any future increase in oil recovery could be down to massive treatment job size. Murphy Creek shows the least reservoir thickness and resistivity values for the data set under consideration. There is one dominant operator whose average field characteristics are about twothirds what is shown for the group. The dominant operator s average proppant and fluid volumes are respectively 63,576 pounds and 842,145 gallons for 3-month cumulative oil of 79,7 barrels. The inclusion of the fringe operators with massive treatment sizes alters the averages and make for excellent recovery. The Murphy Creek oil recovery may be enhanced by the Heart River fault that runs northwest to the field and is known for creating reservoir traps and aiding in deposition of thicker reservoir sediments. Most of the productive wells in the Dunn County have been struck close to this fault by means of massive hydraulic stimulation jobs. Lost Bridge runs laterally on top of the Little Knife field. It has the highest thickness of all the fields with a good resistivity which is indication of oil in place. The thick strata and the thermal conversion of kerogen to oil help in the creation of natural fractures in the reservoir rock. The natural fractures are a major source of oil recovery as they reduce the size of stimulation treatment. Treatment sizes for wells in the Lost Bridge are within the Dunn County average for our data set and makes for economic oil recovery in the absence of structural elements. McKenzie County The wells under McKenzie were grouped in three areas using the township (T) and range (R) delineation. The average characteristics for the areas considered are summarized in table

131 115 Table Average field characteristic values- McKenzie County Region Length Thickness Resistivity Proppant Fluid 3 Month feet feet ohm-m (lbs.) Volume gal. Oil (bbl.) A ,719,898 1,396,15 13,93 B ,77,389 1,35, ,,43 C ,415,17 1,166, ,37 McKenzie Figure 4.3.8: Hydrogen Index Map of Bakken (orange arrow for McKenzie. Nordeng et al, 21)

132 3 Month Oil (1bbl) 116 Region A groups wells in township T148, 149N and range R92-98W, region B is for all wells in township T15, 151N and range R W and C for wells under T152, 153N and R92-98 W. The hydrogen index map in figure shows McKenzie County as a thermally matured reservoir with oil generation in place. The thickness of the formation implies the cooking process generated a lot of pressure which creates natural fractures within the reservoir rock. Region B has the highest resistivity and good reservoir thickness that explains its oil production potential. Region C thickness makes it the most naturally fractured of the three regions; however region B outperforms it due its massive stimulation treatment. Production potential for McKenzie will therefore be decided by reservoir thickness and the stimulation size for creating far-field fracture intensity. For the same thickness production variability is explained by the conductive pathwayby dilated and propped natural and created fractures Month Oil vs Thickness-McKenzie Thickness (feet) Figure 4.3.9: 3-Month oil with thickness of reservoir- McKenzie

133 3 Month Oil (1bbl) 117 The plot in figure shows that oil production increases with increased reservoir thickness and higher resistivity. The plot of normalized resistivity (with thickness) with 3-month oil production also agrees with higher resistivity and thickness being responsible for greater oil recovery Month vs Resistivity-Mckenzie Normalized resistivity per thickness (1E-3 ohm-m/ft) Figure 4.3.1: 3-Month oil with normalized resistivity per thickness for McKenzie Stanley, Ross, Robinson Lake and Alger Fields The area covered by the four fields Stanley, Ross, Robinson Lake and Alger is influenced by the north-south trending Nesson anticline. The anticline fold, the largest petroleum structure in North Dakota is a trap for millions barrel of oil which has been produced economically from different stratigraphic column by about 54 fields scattered along it (Lindsay et al ; Department of Geology, University of N. Dakota). The Nesson anticline accounts for more than 3 percent of oil produced in North Dakota from fields closer to it from the west, east and south directions. Alger and the Robison Lake are the closest to the Nesson anticline followed by Stanley and

134 3 Month Oil (1bbl) 118 Ross. The summary of averages of reservoir thickness, resistivity and treatment parameters is shown for wells studied in the area. Table Average field values- Stanley, Robinson Lake, Ross and Alger Fields Field Length Thickness Resistivity Proppant Fluid 3 Month feet feet ohm-m (lbs.) Volume gal. Oil (bbl.) Stanley 6, ,579,78 767,11 118,497 Ross 8, ,26,514 1,342, 137,268 Robinson Lake 9, ,183,6 1,83, 84,88 Alger 6, ,525,11 1,761, 117,125 For the data set under review we observe that Ross has the highest value of resistivity implying more thermal conversion of kerogen to oil. It is closely followed by Alger with Robinson Lake and Stanley showing lesser values Month Oil vs Thickness- SRRA Thickness (ft.) Figure : 3-Month Oil with thickness for SRRA wells

135 3 Month Oil (1bbl) 119 Robinson Lake and Alger which have higher average reservoir thickness and proximity to the Nesson anticline should have made them more prolific from geological view point but they have less 3-month cumulative oil than Ross. Figure shows the circled thickness range feet is responsible for more oil. The differences in production could be due to specific operator strategy in the field and we explore this in the plots that follow Month Oil vs Normalized Resistivity Normalised Resistivity with thickness( 1E-3 ohmm/ft) Figure : 3-month oil with normalized resistivity for SRRA wells The normalized resistivity plot with oil production also indicate that the smaller well thickness range have better production which is the opposite of the normal trend. The individual field plots explain this variability, which are down to less efficient treatment sizes for appropriate lateral length of horizontal well. The Stanley and Alger field plots of cumulative oil with well thickness show an upward trend for all lateral lengths. This implies that for all treatment sizes there is a corresponding increasing trend in production response.

136 3 Month Oil (1bbl) 3- month Oil (1bbl) 12 3-Month vs Thickness-Stanley Thickness (ft) Figure : 3-month oil with reservoir thickness for Stanley Month Oil with Resisitivity-Stanley Normalized Resistivity(1E-3 ohm-m/ft) Figure : 3-month oil with normalized resistivity for Stanley For all thickness values there is corresponding increase in production for increase in treatment size for all lateral length (ie. the treatment size per foot of lateral is not varied out of proportion).

137 3-Month Oil (1bbl) 3-Month Oil(1bbl) Month Oil vs Thickness-Alger Thickness(ft.) Figure : 3-month oil with reservoir thickness for Alger Month Oil vs Resistivity -Alger Normalized Resistivity (1E-3 ohm-m/ft) Figure : 3-month oil with normalized resistivity for Alger Alger field also maintains an average treatment size per foot of lateral for increased thickness.

138 3-Month Oil (1bbl) 3-month Oil(1bbl) Month Oil vs Thickness- Ross Thickness(ft.) Figure : 3-month oil with reservoir thickness for Ross Month Oil vs Resistivity-Ross Normalized Resistivity (1E-3 ohm-m/ft) Figure : 3-month oil with normalized resistivity for Ross The Ross field plots show on the average some wells are under stimulated per lateral foot of the horizontal wellbore. We expect an increase in production for every increase in pay thickness.

139 123 We either have a shorter lateral drilled instead of a longer reach one to maximize production or a smaller treatment job size used for similar horizontal laterals that has been massively treated. Table Treatment parameters for 3 wells in Ross Field Ross Length Thickness Resistivity Proppant Fluid 3 Month feet feet ohm-m (lbs.) Volume gal. Oil (bbl.) Ross ,7, 2,5, 257,761 Ross ,7, 2,6, 221,979 Ross ,2, 2,4, 129,828 For the treatment schedule shown above and the reservoir characteristics in place, increasing the lateral length of Ross-3 by 2 feet would have resulted in a better production performance. For the table shown below we observe that a shorter lateral for one operator has been treated with a larger treatment size than the two longer laterals from the second operator for varying results. Table Treatment parameters for 3 wells in Ross Field Ross Length Thickness Resistivity Proppant Fluid 3 Month feet feet ohm-m (lbs.) Volume gal. Oil (bbl.) Ross-4 1, ,68 486,822 89,962 Ross-5 1, ,615, 77,154 82,456 Ross-3 7, ,2, 2,4, 129,828

140 124 If the larger treatment for Ross-3 were applied to the longer laterals we would have had a better production response. We conclude that the production performance of wells in Ross are due to individual operators choice of design, but an overall better performance would have ensued if treatment size per foot of lateral had been consistent with increased thickness of reservoir rock. New Fracture Treatment The circled outliers on the Alger 3-month oil production with thickness plot in figure represents the new phase in the dynamic evolution of fracture stimulation in the Bakken. This current design employs massive proppant and fluid in higher staged treatment of long laterals. It has been referenced in the work of Grau et al (211) as the Brigham style treatment. A typical 38-4 staged treatment for a 95-1, feet lateral used 4+millon pounds of ceramic proppant and 3.5 million gallons of frac fluid to average an IP of 148 bopd. Divide, William and Burke This area shows variation in average reservoir thickness and resistivity values as captured in table Table Average field characteristic values-divide, William and Burke (DWB) Counties County Length Thickness Resistivity Proppant Fluid 3 Month feet feet ohm-m (lbs.) Volume gal. Oil (bbl.) Divide ,193,79 1,47,149 91,785 William ,652,391 2,241,94 153,5 Burke ,286,981 1,219,68 64,155

141 3-Month Oil (1bbl) 3-Month Oil (1bbl) Month Oil vs Thickness-DWB Thickness in feet Figure : 3-Month oil with thickness for Divide, William and Burke counties Month Oil vs Resistivity-DWB Resistivity (ohm-m) Figure 4.3.2: 3-Month oil with resistivity for Divide, William and Burke counties

142 126 The graph of 3-month oil against thickness shows a marginal increase in production with increase in reservoir pay. The plot of 3-month oil with resistivity values indicates a downward trend in oil production with increasing resistivity values. The oil production trend is influenced by the Nesson Anticline that runs through the William and the Divide counties and close to the longitude -13. Areas minutes and seconds further apart from the delineating longitude with higher resistivity and or thickness appear to have lesser production than those wells closer to it. D W B Long 13 Figure : Structures influencing oil and gas production.-(nordeng et al, 21) William County Wells in William County (W) have the lowest average of resistivity implying low oil saturation.

143 3-Month Oil (1bbl) 3-Month Oil (1 bbl) 127 However, it out performs the other wells located in Divide (D) and Burke (B) counties as shown on the map in figure Month Oil vs Thickness- William Thickness (feet) Figure : 3-Month oil with thickness for William County Month Oil vs Resistivity -William Resistivity (ohm-m) Fig : 3-Month oil with resistivity for William County

144 3 Month Oil (1 bbl)e 128 There is an appreciable oil production for the resistivities in the 5-8 ohm-m range for increasing pay thickness. The two plots in figures show this marginal trend but the normalized resistivity (resistivity per pay thickness) show a marked difference when plotted against oil production. Production variation for each resistivity value is explained by the influence of the Nesson anticline, pay thickness as well as stimulation treatment size as seen in table Month oil vs Resistivity-William Normalized resistiivity (ohm-m/ft) Figure : 3-Month oil with normalized resistivity values for William County Table Treatment parameters for 2 wells in William County Well Proximity Length Thickness Resistivity Proppant Fluid 3 Month to 13 feet feet ohm-m (lbs.) Volume gal. Oil (bbl.) William- 1 Close , ,914 46,837 William-2 Very close ,439,262 1,236, ,

145 Thickness (feet) 3-Month Oil (1bbl) 129 Burke County 3- Month Oil vs Thickness -Burke Thickness (feet) Figure4.3.25: 3-month oil with thickness Burke County Thickness vs Resistivity-Burke Resistivity (ohm-m) Figure : Thickness with resistivity for Burke County Burke s 3-month production decreases with thickness of the Bakken formation.

146 3-Month Oil (1bbl) 3-Month Oil (1bbl) 13 The plot of thickness with resistivity shows the shallow areas of the reservoir are thermally mature with more oil saturation to support production. Divide County 3-Month Oil vs Thickness -Divide Thickness (feet) Figure : 3-Month oil with thickness for Divide 2 3-Month Oil vs Resistivity-Divide Resistivity (ohm-m) Figure : 3-Month oil with resistivity for Divide County

147 131 The 3-month oil production increased with increased thickness of the formation and resistivity. The thicker reservoir had more oil saturation and produced better with increased stimulation treatment size and proximity to the Nesson anticline. Figure : Production from wells drilled close to structural elements in North Dakota Bakken-(Nordeng S. 21)

148 132 Figure 4.3.3: Map showing well density around structural elements for periods. (Nordeng S. 21). In summary, we observe that variation in production across fields and counties in the North Dakota are influenced by the thermally generated oil in place, reservoir thickness, geology, structural elements and the stimulation design consideration. Structural elements and the appropriate treatment size greatly influence production variation.