SHEAR-WAVE SPLITTING AND ATTENUATION ANALYSIS OF DOWNHOLE MICROSEISMIC DATA FOR RESERVOIR CHARACTERIZATION OF THE MONTNEY FORMATION, POUCE COUPE, ALBERTA

by Ben P. Andrews © Copyright by Ben P. Andrews, 2016 All Rights Reserved A thesis submitted to the Faculty and the Board of Trustees of the Colorado School of Mines in partial fulfillment of the requirements for the degree of Master of Science (Geo- physics).

Golden, Colorado Date

Signed: Ben P. Andrews

Signed: Dr. Thomas L. Davis Thesis Advisor

Golden, Colorado Date

Signed: Dr. Terence K. Young Professor and Head Department of Geophysics

ii ABSTRACT

Two microseismic waveform analysis methods were performed for reservoir characteri- zation of the Montney Formation at Pouce Coupe, Alberta. Microseismic events recorded on two downhole arrays during the hydraulic fracture stimulation of three production wells formed the dataset for both methods. The first method involved the calculation of shear-wave attenuation factors through a comparison of observed and expected P/Sh amplitude ratios. The method was anticipated to help infer the presence of fluid-filled fractures however a number of limitations were identified. The assumption of a single source mechanism introduced significant uncertainty to the expected amplitude ratios. This uncertainty becomes increasingly amplified as source- vectors approach the modeled nodal planes, resulting in a strong azimuthal bias to the shear- wave attenuation factors. The accuracy of this method was also degraded by not accounting for variable baseline attenuation of the P- and Sh-waves. Future success with this method will likely require simultaneous surface and downhole microseismic monitoring such that source-mechanisms can be accurately determined for each event. The second method performed was a microseismic shear-wave splitting analysis. A total of 48,987 3C seismograms yielded 1,136 reliable splitting measurements. Measurements indicate at least orthorhombic symmetry within the Pouce Coupe reservoir consisting of horizontally layered fabric and two near-vertical natural fracture sets roughly parallel and

perpendicular to SHMax. This interpretation corroborates previous image log analysis from nearby Farrell Creek Field as well as focal mechanism and surface shear-wave splitting studies at Pouce Coupe. A strong temporal correlation was observed between shear-wave splitting measurements and completion data. A continued increase in the magnitude of splitting during hydraulic stimulation coupled with a rotation of the fast polarization indicate that reservoir anisotropy

iii becomes dominated by near-vertical hydraulic fractures roughly parallel to SHmax. Temporal observations made perpendicular to SHmax display a similar but less significant response at the onset of the completion process. This may suggest activation of the natural fracture set perpendicular to SHmax, but limited propagation of any hydraulic fractures in that direction. This study highlights the value as well as some of the practical challenges associated with microseismic waveform analysis for reservoir characterization purposes. Future improvement of semi-automated analysis techniques that are adaptive to the waveform characteristics of individual source-receiver records will help make the most of large microseismic datasets for such purposes.

iv TABLE OF CONTENTS

ABSTRACT ...... iii

LISTOFFIGURES ...... viii

LISTOFTABLES ...... xii

LISTOFSYMBOLS...... xiii

LISTOFABBREVIATIONS ...... xv

ACKNOWLEDGMENTS ...... xvi

DEDICATION ...... xvii

CHAPTER1 INTRODUCTION ...... 1

1.1 Motivation...... 2

1.2 AimsandObjectives ...... 3

1.3 Geology ...... 4

1.4 HydrocarbonProductionfromtheMontney ...... 6

1.5 PouceCoupe ...... 11

CHAPTER 2 DATA AVAILABILITY AND PREVIOUS STUDIES ...... 15

2.1 SeismicData ...... 15

2.2 MicroseismicData ...... 16

2.3 CompletionsandProductionData...... 22

2.4 PreviousStudiesatPouceCoupe ...... 25

CHAPTER 3 SHEAR-WAVE ATTENUATION FROM MICROSEISMIC EVENTS . . 30

3.1 Methodology ...... 30

v 3.2 AssumptionsandUncertainties ...... 32

3.3 ResultsandInterpretation ...... 35

3.3.1 Example 1 - Inferring Areas of Natural Increased Attenuation . . . . . 35

3.3.2 Example 2 - Inferring the Presence of Hydraulic Fluid-Filled Fractures . 37

3.3.3 Example 3 - Implications for Understanding Production ...... 39

3.4 ConclusionsandRecommendations ...... 43

CHAPTER 4 SHEAR-WAVE SPLITTING THEORY ...... 45

4.1 SeismicAnisotropy ...... 45

4.2 Shear-WaveSplittingTheory...... 46

4.2.1 TransverselyIsotropicMedia...... 47

4.2.2 OrthorhombicMedia ...... 49

4.3 Interpretation Theory for Microseismic Shear-Wave Splitting ...... 51

4.4 Advantages of Anisotropy Estimation from Microseismic ...... 53

CHAPTER 5 SHEAR-WAVE SPLITTING FROM MICROSEISMIC ...... 56

5.1 Methodology ...... 56

5.1.1 DataSelection...... 56

5.1.2 WaveformFiltering ...... 60

5.1.3 Multi-WindowParameterConfiguration ...... 65

5.1.4 Semi-AutomatedSplittingAnalysis ...... 67

5.1.5 Results...... 72

CHAPTER 6 INTEGRATED INTERPRETATION OF MICROSEISMIC SHEAR-WAVE SPLITTING AT POUCE COUPE ...... 78

6.1 SingleHomogeneousAnisotropySystem ...... 78

vi 6.2 Temporal Variations in Shear-Wave Splitting ...... 83

6.2.1 Cluster 1 - Temporal Splitting Variations Parallel to SHmax ...... 86

6.2.2 Cluster 2 - Temporal Splitting Variations Perpendicular to SHmax . . . 88

6.3 LimitationsandUncertainties ...... 93

CHAPTER 7 CONCLUSIONS, RECOMMENDATIONS AND FUTURE WORK . . . 96

7.1 Recommendations...... 98

7.2 FutureWork...... 99

REFERENCESCITED ...... 101

APPENDIX - FREQUENCY FILTERING ...... 106

vii LIST OF FIGURES

Figure1.1 LocationmapofPouceCoupe ...... 5

Figure 1.2 Paleogeographic map of the Western Canadian SedimentaryBasin . . . . .6

Figure 1.3 Regional map of the Montney and its major rock types ...... 7

Figure 1.4 A schematic of the depositional environment of the Montney ...... 8

Figure 1.5 Map displaying the distribution of Montney productionwells ...... 9

Figure 1.6 Hydrocarbon production from Montney gas wells ...... 9

Figure 1.7 Average gas production rates in the Montney ...... 10

Figure 1.8 Schematic stratigraphic section of the Montney reservoir...... 11

Figure 1.9 A regional stress map of Alberta and Eastern British Columbia ...... 12

Figure 1.10 A 3D view of the well geometry at Pouce Coupe ...... 13

Figure 1.11 Vertical section of the well geometry at Pouce Coupe ...... 14

Figure 2.1 Timeline of data acquisition at Pouce Coupe ...... 16

Figure 2.2 Seismic acquisition geometry at Pouce Coupe ...... 17

Figure 2.3 Downhole 12-tool array deployed in the 9-7 vertical observation well . . . 19

Figure 2.4 Velocity model used for microseismic processing atPouceCoupe . . . . . 20

Figure 2.5 Event maps of the five single array microseismic subsets...... 21

Figure 2.6 Completions chart for the 7-7 treatment well ...... 24

Figure 2.7 Production rates for the three study wells at Pouce Coupe ...... 25

Figure 2.8 Time-lapse shear-wave splitting analysis from 3D surfaceseismic . . . . . 26

Figure 2.9 Composite focal mechanism solutions at Pouce Coupe...... 27

viii Figure 2.10 Isochron map of the two best rock quality clusters and microseismic eventsfromtheMontneyCandD ...... 28

Figure 2.11 Microseismic events, production data, and time-lapse time-shifts of the overburdenatPouceCoupe...... 29

Figure 3.1 Source mechanism coordinate geometry for a strike-slipfailure ...... 32

Figure 3.2 The influence of a single source mechanism assumption and nodal planes on the calculation of shear-wave attenuation factors ...... 34

Figure 3.3 Map of shear-wave attenuation factors for the 2-7 treatmentwell . . . . . 36

Figure 3.4 Shear-wave attenuation factors vs event time for the 8-7 treatment well . 37

Figure 3.5 Map of shear-wave attenuation factors for the 8-7 treatmentwell . . . . . 38

Figure 3.6 Shear-wave attenuation factors vs event time for the 7-7 treatment well . 39

Figure 3.7 Map of shear-wave attenuation factors for the 7-7 treatmentwell . . . . . 40

Figure 3.8 Surface shear-wave splitting map from the baseline 3D seismic survey . . 41

Figure 3.9 Vertical section of microseismic events from the 7-7 treatment well scaled by their shear-wave attenuation factors ...... 42

Figure 3.10 Spinner log production data compared to time-lapse time-shifts in the overburden...... 43

Figure 4.1 A schematic of shear-wave splitting in Transversely Isotropic Media . . . 48

Figure 4.2 An Orthorhombic model consisting of two vertical and orthogonal fracture sets embedded within a horizontally layered background . . . . . 49

Figure 4.3 Phase velocity sheets for an Orthorhombic medium ...... 51

Figure 4.4 Upper hemisphere projections of the shear-wave splitting signature for VTI,HTI,andOrthorhombicmedia ...... 53

Figure 4.5 Polar plot of source-vectors for all recorded source-receiver pairs . . . . . 55

Figure 5.1 Waveform moveout for an event recorded on the horizontal 8-7 array . . . 57

Figure 5.2 Waveform moveout for an event recorded on the vertical9-7array . . . . 58

ix Figure 5.3 Polar plots of the source-vectors for all source-receiver pairs used for shear-wavesplittinganalysis ...... 59

Figure 5.4 An example of the adaptive multi-notch filtering ...... 61

Figure 5.5 Dominant period analysis for a given shear-wave ...... 63

Figure 5.6 Graph of the dominant shear-wave period vs the time-pick separation . . 64

Figure5.7 Multi-windowanalysisgrid ...... 66

Figure 5.8 Shear-wave splitting analysis workflow ...... 68

Figure 5.9 A schematic of 3C receiver rotation into the frame oftheray ...... 69

Figure 5.10 The rotation of a 3C seismogram into the frame of theray ...... 70

Figure 5.11 Determination of the quality factor through comparison of the shear-wave splitting measurements from the XC and EV methods ....71

Figure 5.12 Diagnostic plot for a reliable shear-wave splittingresult ...... 73

Figure 5.13 Diagnostic plot for a reliable shear-wave splittingresult ...... 74

Figure 5.14 Diagnostic plot for a reliable shear-wave splittingresult ...... 75

Figure 5.15 Diagnostic plot for a non-reliable shear-wave splittingresult...... 76

Figure 6.1 A polar plot showing all reliable shear-wave splitting results obtained at PouceCoupe...... 79

Figure 6.2 Shear-wave anisotropy log for the 7-7 well ...... 80

Figure 6.3 Histograms of microseismic and log based shear-wave anisotropy for sub-horizontalsource-vectors ...... 81

Figure 6.4 Natural fracture sets interpreted from microseismic shear-wave splitting andimageloganalysis ...... 82

Figure 6.5 Map of all source-receiver pairs with reliable splitting measurements . . . 84

Figure 6.6 Polar and cylindrical plots of all reliable shear-wave splitting measurements ...... 85

Figure 6.7 Map view and vertical section of source-receiver pairs within cluster 1 . . 86

x Figure 6.8 Polar and cylindrical plots of cluster 1 ...... 87

Figure 6.9 Integrated temporal analysis of splitting measurements from cluster 1 . . 89

Figure 6.10 Map view and vertical section of source-receiver pairs within cluster 2 . . 90

Figure 6.11 Polar and cylindrical plots of cluster 2 ...... 91

Figure 6.12 Integrated temporal analysis of splitting measurements from cluster 2 . . 92

Figure 6.13 Polar plots depicting shear-wave splitting shadowzones ...... 93

Figure 6.14 A 3C source-receiver record providing an example of poor rotation into theframeoftheray...... 95

Figure A.1 Adaptive notch and low-pass filtering example ...... 106

xi LIST OF TABLES

Table 2.1 An overview of the hydraulic fracturing operation and downhole microseismicmonitoring...... 18

Table 2.2 Summary of the hydraulic fracture characteristics at Pouce Coupe as determined by the microseismic monitoring survey ...... 22

Table 4.1 Seven anisotropy parameters for an Orthorhombic medium ...... 46

Table 5.1 Summary of all 3C seismograms selected for shear-wave splitting analysis. . 57

Table 5.2 The adaptive parameters for multi-window analysis...... 67

Table 5.3 A summary of reliable shear-wave splitting measurements ...... 77

xii LIST OF SYMBOLS

Arrival-timeseparation...... ∆T

Componentsofthestiffnesstensor ...... cij

Cross-correlationmethod ...... XC

Delay-timeratio ...... ∆

Density ...... ρ

Dipofthefastshear-wavepolarization ...... δp

Dominantperiodoftheshear-wave ...... Tdom

Eigenvaluemethod ...... EV

Estimated dominant period of the shear-wave ...... Test.dom

Fastandslowshear-wavedelay-time ...... δt

Fastwavepolarization ...... ψ

Horizontallypolarizedshear-wave ...... Sh-wave

Maximumhorizontalstress ...... SHMax

Maximumprincipalstress ...... SV

Meanshear-wavevelocity ...... Vsmean

Minimumhorizontalstress...... SHMin

Normalized difference in the fast-shear polarization ...... Ω

P-wavetimepick ...... Tp

Qualityfactorofmeasurement...... Qw

Qualitythresholdvalue ...... τ

xiii S-wavetimepick ...... Ts

Shear-wave splitting parameter at vertical incidence ...... γ(s)

Shear-wavevelocityanisotropy ...... δ Vs

Source-receiverraypathlength...... r

Strikeofthe fast shear-wave polarization ...... φp

Thomsen’sparameter...... ǫ

Thomsen’sparameter...... δ

Thomsen’sparameter...... γ

xiv LIST OF ABBREVIATIONS

BillionCubicFeet ...... Bcf

ColoradoSchoolofMines ...... CSM

FourDimensional...... 4D

HorizontalTransverseIsotropy ...... HTI

Millidarcy...... mD

MillionCubicFeet ...... MMcf

NaturalGasLiquid...... NGL

OneDimensional ...... 1D

PouceCoupe ...... PC

ReservoirCharacterizationProject ...... RCP

SeismicAnalysisCode ...... SAC

Shear-WaveBirefringenceAnalysis ...... SHEBA

Shear-WaveSplitting...... SWS

StimulatedReservoirVolume ...... SRV

ThreeComponent ...... 3C

ThreeDimensional ...... 3D

TrillionCubicFeet ...... Tcf

VerticalTransverseIsotropy ...... VTI

xv ACKNOWLEDGMENTS

I would first like to acknowledge my advisor Tom Davis. I am incredibly grateful for the opportunity you gave me to return to Mines, and feel particularly fortunate to be one of your last students. I wish you the best of luck for the future both on and off the ice. To Sue Jackson. It has been a pleasure getting to know you over the last couple of years. You are the beating heart of RCP and I hope we can stay in touch. I would like to thank my committee. Walt Lynn has continued to be a mentor and friend since taking his class in the Fall of 2012. His humility, good humor, and passion for teaching opitimizes this school and was a large factor in my decision to pursue a Masters. My utmost thanks go to Shawn Maxwell. This thesis would not have been possible without your support and the generous loan of software. My thanks must also be extended to Bob Benson for his hours of technical support and for tolerating my endless barrage of naive questions. I would like to give significant credit to previous students of the Pouce Coupe project and to David D’Amico. David has been a constant driving force behind the project and is largely responsible for its success over the last 8 years. I also thank Junwei Huang, Sebastian Goodfellow, Jon Haycox, Ted Shuck, James Wookey, James Verdon, and Leon Foks. This study would not have been possible without your generosity and expertise. It’s been a pleasure to be a part of such a special group of RCP’ers. I would especially like to thank Travis Pitcher, Matt White, Isabel White, and Matt Bray for their friendship and invaluable contributions to this study. To my Colorado Family - Ron, Yvette, Chris, Bretani, Casey, Lindsey, Matt and Sophia. I would not be where I am today without you all. Thank you for being such great role models and for the numerous adventures over the past two years. Finally, I would like to thank my parents for their continued support throughout my education. I love you both and I am certainly looking forward to being a little closer to home.

xvi I dedicate this thesis to my Grandad. GB.

xvii CHAPTER 1 INTRODUCTION

The Reservoir Characterization Project (RCP) is an industry-funded academic research consortium focused on understanding and optimizing hydrocarbon production from uncon- ventional reservoirs. The Pouce Coupe project represents a multiscale and multidisciplinary study in collaboration with Talisman Energy Inc., now Repsol. Since initiation of the project in 2008, seven RCP students have studied a comprehensive dataset, providing an integrated evaluation of the Montney Formation’s response to hydraulic stimulation. The mature nature of the Pouce Coupe project offers a rare opportunity to explore new and developing approaches for reservoir characterization. This study focuses on the downhole microseismic survey acquired at Pouce Coupe during the hydraulic fracture treatment of three horizontal wells. Two microseismic waveform analysis methods were performed to better constrain the physical rock properties of the Montney and its response to hydraulic stimulation. The first involves a comparison of observed and expected amplitude ratios to calculate shear-wave attenuation factors for event-receiver raypaths. The method can be used to identify areas of naturally occurring increased attenuation and may also be used to infer the presence of fluid-filled fractures following hydraulic stimulation. The second method performed is a shear-wave splitting analysis. Global seismologists have long measured shear-wave splitting from earthquake sources (teleseismic data) to char- acterize anisotropy within the earth. Following the symbiotic emergence of hydraulic fracture stimulation and microseismic monitoring, the phenomenon of shear-wave splitting is now be- ing measured from completions operations. An appropriate dataset for such a study exists in the Pouce Coupe project. The splitting analysis performed demonstrates how shear-wave splitting measurements can be used to estimate anisotropy and help determine the physical rock properties of an

1 unconventional reservoir. Temporal and spatial variations of these measurements may also be assessed, providing insight into reservoir heterogeneity and the nature of enhanced per- meability networks following hydraulic stimulation. The framework of this thesis is as follows. Chapter 1 gives an introduction consisting of the motivation, aims, and objectives of this study. The geology and hydrocarbon production history for the Montney Formation are also discussed, as are the characteristics of Pouce Coupe Field. Chapter 2 describes the data available for this study with particular emphasis on the downhole microseismic survey. The previous studies from the Pouce Coupe project that are most relevant to this work are also discussed. Chapter 3 is a self-contained overview of the shear-wave attenuation work that was first performed in this study. The limitations and shortcomings of this method, which ultimately lead to the pursuit of the shear-wave splitting analysis, are presented. Chapter 4 describes the theory of shear-wave splitting in various anisotropic media. A certain paradigm shift from conventional spitting studies that use surface seismic is required to appreciate the nuances of the splitting signature in a down- hole geometry. Polar plots of the available ray coverage alongside synthetic anisotropy models help visualize the value of such an analysis for reservoir fabric and fracture characterization. The methodology and results of the shear-wave splitting analysis performed at Pouce Coupe are presented in Chapter 5. Chapter 6 is an integration of the splitting measurements with other forms of data and previous studies at Pouce Coupe. An interpretation of temporal variations in the splitting measurements is also presented, evaluating reservoir heterogeneity and the response of the Montney to hydraulic stimulation. Conclusions, recommendations, and future work are discussed in Chapter 7.

1.1 Motivation

Shear-wave splitting has been observed in microseismic waveforms since the development of multicomponent downhole receivers. In recent years, significant strides have been made to improve and semi-automate the workflow required to measure this phenomenon (Wuestefeld et al., 2010). As a result, splitting parameters can now be measured on large volumes of

2 microseismic data. There are numerous incentives for measuring shear-wave splitting from microseismic events in the Montney. The ability to accurately quantify seismic anisotropy within the reser- voir will greatly benefit seismic and microseismic data processing in the future (Tsvankin and Grechka, 2011). An understanding of the anisotropy can also be used to invert for the physical rock parameters that render the reservoir anisotropic. Multiple studies have exploited this approach to infer the strength and orientation of aligned fracture sets and sedimentary fabrics within producing reservoirs (Teanby et al., 2004b; Verdon and Kendall, 2011). Spatial variations in microseismic shear-wave splitting can been used to identify reservoir heterogeneity. Al-Harrasi et al. (2011a) use shear-wave splitting magnitudes to infer both lateral and vertical variations in fracture density within a carbonate gas field in Oman. Temporal variations in microseismic shear-wave splitting can provide insight into the re- sponse of reservoirs during hydraulic fracture stimulation. Baird et al. (2013a) observe a rotation in the fast shear-wave polarization during a multistage hydraulic fracture stimu- lation. The rotation is believed to represent a 20-30◦ shift between natural and hydraulic fracture orientations, coupled with an increase in the normal to tangential compliance ratio. Wuestefeld et al. (2011) observed a clear increase in the magnitude of splitting during indi- vidual treatment stages. These temporal variations are believed to indicate the generation of fluid-filled cracks and fissures associated with hydraulic stimulation. The comprehensive downhole survey at Pouce Coupe provides a great opportunity to develop the value and understand the limitations of this approach. Research and development studies such as this will support the commercial value of this work.

1.2 Aims and Objectives

The aim of this study is to evaluate microseismic waveform analysis methods to further characterize the Montney reservoir and its response to hydraulic fracture stimulation. In order to fulfil this aim the following objectives have been set:

3 • Explore the potential for using P/Sh amplitude ratios to infer the presence of fluid-filled fractures

• Accurately measure shear-wave splitting from downhole microseismic data

• Use microseismic shear-wave splitting measurements to interpret a single homogeneous anisotropy model for the Montney reservoir. Relate this interpretation to the rock physics at Pouce Coupe as observed from previous studies and other datasets.

• Investigate temporal variations in shear-wave splitting measurements that may provide insight into the response of the Montney Formation to hydraulic stimulation

The value generated from this study is greatly enhanced through an integrated inter- pretation of the various datasets and previous studies available within the Pouce Coupe Project.

1.3 Geology

Pouce Coupe Field is located in Northwestern Alberta, 20 km east of the border with British Columbia. The field covers an area of approximately 10 km2 and produces from a mixed siltstone and sandstone region of the Montney Formation. The location of Pouce Coupe is indicated in Figure 1.1. The Lower Triassic Montney Formation is located in the Western Canadian Sedimentary Basin. It was deposited in the westward facing Peace River Embayment on the Northwest- ern margin of Pangaea (Davies, 1997)(Figure 1.2). The Montney is recognized today as a world class shale gas reservoir with production rates climbing to over 2.8 Bcf per day since commercial production began in 1993 (Unconventional Gas Resources, 2014) . The Montney Formation straddles the border between Northeastern British Columbia and Western Alberta covering an area of 130,000 km2 (Figure 1.3). Its depositional en- vironment has been characterized as a continental ramp with progressive parasequences prograding toward the southwest (Norton et al., 2010). The formation ranges in thickness

4 Figure 1.1: A location map of oil and gas (green and red) fields within the Peace River Embayment. The Pouce Coupe gas field is located 70 km northwest of Grand Prairie and 25 km west of Dawson Creek. Modified from Zonneveld et al. (2011). from 100-300m and generally thickens and deepens downdip from northeast to southwest (National Energy Board, 2013a). Facies within the Montney become increasingly finer grained and organic rich towards the west as the depositional environment transitions from a shelfal/deltaic setting to a more distal marine environment. Figure 1.4 displays a generalized schematic of the depositional environment for the Montney. Mass wasting events on the ramp slope caused sediment slumps and turbidity currents to be the dominant depositional processes between the break in slope of the shelf and the basinal marine shales.

5 Figure 1.2: Paleogeographic maps of North America and the Western Canadian Sedimentary Basin during deposition of the Montney in the Early Triassic (∼ 245Ma). The Peace River Embayment is represented by the paleo-continental shelf occupying a latitude from 20-30◦ North through present day British Columbia and Western Alberta. Note the island arc to the west placing the Peace River Embayment in a back-arc tectonic setting (Blakey, 2014).

The reservoir is unconformably bound by the underlying Belloy Formation and the overly- ing Doig Phosphate, both of which are clearly distinguished in well logs and seismic response. The Montney is often divided into six units (A, B, C, D, E and F). The Lower Montney (comprised of units from A to C) is unconformably overlain by the Upper Montney (D to F) and the two are separated by a maximum flooding surface.

1.4 Hydrocarbon Production from the Montney

Development of the Montney began in the 1950’s targeting conventional sandstone and dolostone reservoirs predominantly in the east. Following the first horizontal development program by Encana in 2005 the Montney has experienced an unconventional revolution (Hayes, 2009). Advancements in horizontal drilling and multistage hydraulic fracturing have

6 Figure 1.3: A regional map of Northwest Canada showing the areal extent and major rock types of the Montney Formation. The Montney straddles the border between Northeastern British Columbia and Western Alberta covering a total area of 130,000 km2. The major rock types of the Montney become increasingly finer grained toward the west. The major rock type of the Montney at Pouce Coupe, as indicated by the black star, is described as siltstone with some sandstone (National Energy Board, 2013b). opened up the extensive and more distal siltstone within the western half of the Montney as an economically viable resource (Gatens, 2015). While reservoir pressure increases, the natural gas liquid (NGL) and oil content typically decreases from northeast to southwest (National Energy Board, 2013a) The unconventional petroleum potential of the Montney Formation has recently been assessed at 449 trillion cubic feet (Tcf) of marketable natural gas, 14,521 million barrels of marketable NGL, and 1,125 million barrels of marketable oil (National Energy Board, 2013a).

7 Figure 1.4: A generalized schematic of the depositional environment for the Montney For- mation. Sediment slump and turbidite deposits dominate the setting downslope and to the west of the ramp slope. Facies become increasingly finer grained and organic rich to the west, transitioning from shoreface/deltaic sandstones, through a mixture of turbiditic silts, sands, and shales, into dark and fine grained marine shales (Davey, 2012).

Unconventional Gas Resources (2014) identified 4 macro “sweet spots” that have recently evolved within the Montney: a liquids-rich area in Alberta, the Regional Heritage area straddling the Alberta - British Columbia border, and the Altares and Northern Montney in British Columbia. Figure 1.5 displays the distribution of Montney wells and their first year of production highlighting the recent shift from conventional oil and gas wells in the northwest to dominantly horizontal gas wells in the unconventional region of the formation. As a result, the total production rate from the Montney has seen a dramatic increase (Figure 1.6). Figure 1.7 displays the average daily production rate for horizontal gas wells in the Montney. The large distribution in production between wells highlights an inconsistency in the effectiveness of Montney completions. While the majority of recent drilling in the Regional Heritage area has shifted west of Pouce Coupe, its relative proximity and extensive dataset continue to make it an incredibly valuable research project for optimizing completions in this rapidly expanding play.

8 Figure 1.5: a.) The distribution of Montney wells and their first year of production alongside b.) the type of production well emphasizes the recent shift to the southwest from conventional reservoirs toward tighter, more distal unconventional reservoirs. Areas of yellow highlight the evolution of the 4 macro “sweet spots” discussed by Gatens (2015) with the study area (black star) located toward the eastern extent of the Regional Heritage area.

Figure 1.6: Production rates from unconventional Montney gas wells has dramatically in- creased since 2007, reaching over 2.8 Bcf per day by 2014 (Unconventional Gas Resources, 2014).

9 Figure 1.7: Average gas production rates for horizontal wells in the Montney between 2006 and the second half of 2015. Red and blue circles correspond to wells within the top 10 producing fields. The large discrepancy in production identifies the continuing need to improve understanding of completion effectiveness in the Montney (Gatens, 2015).

10 1.5 Pouce Coupe

The Montney reservoir at Pouce Coupe consists of organic-rich shelfal siltstones and shales, with the potential for turbidite deposits (Figure 1.8). Across the field, the Montney ranges in depth from 1,700 to 2,000m with a maximum thickness of 300m. While the entire formation is gas charged, the thick Montney C and D represent the most common target intervals. Reservoir permeability is approximately 0.01-0.02 mD with porosity values from 6-10%. The degree of economic success at Pouce Coupe is largely dependent upon the effectiveness of hydraulic stimulations; hence the motivation for this project.

Figure 1.8: A schematic stratigraphic section of the Montney formation showing the approx- imate location and reservoir target for Pouce Coupe Field (EIA and ARI, 2013)

The regional stress of the Montney is remnant of the formation of the Canadian Rocky Mountains. The stress regime at Pouce Coupe can be classified as compressional, strike-slip

◦ (SHmax >SV >SHmin) with a maximum horizontal stress direction of approximately N40 E. The orientation of borehole breakout indicates the NE-SW direction of maximum horizontal stress is consistent across most of the Montney (Figure 1.9).

11 Figure 1.9: Borehole breakout information indicate a consistent NE-SW direction of maxi- mum horizontal stress throughout the Montney. A schematic of the compressional strike-slip stress regime at Pouce Coupe (red star) is shown in the bottom left (Steinhoff, 2013).

The study area specific to the Pouce Coupe project focuses on the hydraulic stimulation of three horizontal wells. From this point on, the three treatment wells, in the order of stimulation (UWID = 102-02-07-078-10-W6-00, 102-07-07-078-10-W6-00, 100-08-07-078-10- W6-00), will be referred to as the 2-7, 7-7, and 8-7. Each treatment well is oriented NW-SE, perpendicular to the regional maximum hori- zontal stress (SHmax). The horizontal section of each well averages approximately 1500m in length from heel to toe (Figure 1.10). While the 2-7 and 8-7 wells were landed in the Mont- ney C (average TVD of ∼ 2180m and ∼ 2160m respectively), the 7-7 well was placed in the Montney D (average TVD of ∼ 2110m) (Figure 1.11). Note that the fourth well displayed in Figure 1.10 and Figure 1.11 is the vertical 9-7 well (UWID = 100-09-07-078-10-W6-00) used for microseismic monitoring of all three treatment wells. As the downhole microseismic survey is the main focus of this study, it is discussed in particular detail within the following chapter.

12 Figure 1.10: A 3D view of the well geometry at Pouce Coupe. The red spheres represent the 16 treatment stages across the three wells. The green spheres indicate the receiver locations of two of the downhole observation arrays within the 8-7 horizontal and 9-7 vertical wells.

13 Figure 1.11: A vertical section displaying the well geometry at Pouce Coupe looking roughly northwest along the horizontal wells (toe to heel). The 2-7 and 8-7 wells were landed in the Montney C while the 7-7 was landed in the Montney D.

14 CHAPTER 2 DATA AVAILABILITY AND PREVIOUS STUDIES

The Pouce Coupe project includes a wide range of information including 4D multicom- ponent seismic, microseismic, well logs, and production data. This chapter introduces the data available for this study with particular emphasis on the downhole microseismic survey. Also discussed in this chapter are the previous studies from Pouce Coupe that are specifically relevant to this work.

2.1 Seismic Data

During December 2008, three time-lapse (4D) multicomponent (3C) surface seismic sur- veys were acquired at Pouce Coupe. These included a baseline and two monitor surveys acquired 24 hours after hydraulic stimulation of the 2-7 and 7-7 horizontal wells. Acquisi- tion of these surveys was designed for optimum repeatability in order to best characterize and monitor the response of the Montney to hydraulic stimulation. A detailed overview of the seismic acquisition parameters is provided by Atkinson (2010) and Steinhoff (2013). A timeline of the seismic acquisition relative to the well completions is displayed in Figure 2.1. The acquisition layout covered an area of approximately 50 km2 centered over the 2-7 and 7-7 treatment wells (Figure 2.2). It is important to note that a third monitor survey was not acquired following treatment of the 8-7 well. The P-wave and converted-wave volumes from Pouce Coupe have been studied extensively by previous RCP students as discussed later in this chapter (2.4). The observations and conclusions from these studies are related to the findings from this work (Chapter 6) to provide an integrated evaluation of the Montney.

15 Figure 2.1: Timeline showing the relative timing of the time-lapse seismic acquisition relative to the three treatment wells at Pouce Coupe. The downhole microseismic monitoring arrays and their respective observation wells are also indicated.

2.2 Microseismic Data

Surface, shallow water well, and downhole microseismic surveys were independently ac- quired to monitor the completions operations at Pouce Coupe. The surface and shallow water well surveys, acquired by Microseismic Inc. and Apex HiPoint respectively, are not relevant to this study and are not discussed further. The downhole microseismic monitoring acquired and processed by Pinnacle is the focus of this study. Detailed documentation of the microseismic setup, including individual array location, receiver orientation, and event attribute files were available for all three treatment wells (2-7, 7-7, 8-7). Time-windowed event files containing the three-component (3C) wave- forms required for shear-wave splitting analysis were also provided. Great care was taken to understand the microseismic survey such that setup and event specific information could be correctly mapped to the individual waveforms. Two observation arrays were used to monitor treatment of the 2-7 and 7-7 wells (Ta- ble 2.1). A 10-tool array was tractored approximately 450 m past the heel of the horizontal

16 Figure 2.2: A map of the 3D seismic acquisition geometry. Source and receiver locations are displayed along with the study wells discussed. The total acquisition geometry as indicated by the blue box covers an area of approximately 50 km2. Modified from Atkinson (2010).

8-7 well. A 50-tool array was placed within the vertical 9-7 well but was unable to reach its planned depth due to the presence of a perforation sleeve (Figure 1.10 and Figure 1.11). Because of this issue, P- and S-arrivals were only consistently observed by the lower half of receivers, limiting the observational ability of the array. Only the 9-7 observation well was used to monitor treatment of the 8-7 well. A smaller 12- tool array was redeployed, passing the perforation sleeve and reaching the originally planned depth, just above the 8-7 lateral. Receiver depths ranged from 1984 - 2151 m as shown in Figure 2.3.

17 Table 2.1: An overview of the hydraulic fracturing operation and downhole microseismic monitoring of the three study wells at Pouce Coupe.

Date TreatmentWell ObservationWell(s)

Dec 12, 2008 2-7 (Montney C) Horizontal 8-7 (10 receivers) Vertical 9-7 (50 receivers)

Dec 17, 2008 7-7 (Montney D) Horizontal 8-7 (10 receivers) Vertical 9-7 (50 receivers)

Jan 09, 2009 8-7 (Montney C) Vertical 9-7 (12 receivers)

An initial velocity model was constructed by Pinnacle based upon a dipole sonic log from the 2-7 treatment well. Velocity calibration was then performed using a series of stringshots. A final one-dimensional velocity model consisting of seven isotropic layers was adopted to locate microseismic events. Figure 2.4 displays a gamma ray type log, the sonic logs, and the 7-layer velocity model used at Pouce Coupe. Microseismic events are subdivided into those located by a “single array”, and those observed and located by the “dual array”. While the location and attributes of dual array events are typically better constrained, they provide a spatially limited representation of the total number of microseismic events. For the purpose of this study, single array events were used, providing maximum spatial and temporal coverage of the reservoir. The 5 subsets of single array events and their respective observation array are displayed in Figure 2.5. The hydraulic fracture characteristics for each individual treatment stage are provided in the Pinnacle processing report (summarized in Table 2.2). Pinnacle (2009) observed that the fracture half-lengths (120-370 m) and heights (90-230 m) are large relative to the narrow event cloud width (50-250 m). These planar fractures indicate that no significant complex fracture network is being activated for most of the stages.

18 Figure 2.3: A diagram of the 12-tool array deployed in the 9-7 vertical observation well to monitor completion of the 8-7 well. The individual 3C receivers have a spacing of 15.24m with the array covering a measured depth range from 1984 to 2151.6m.

19 Figure 2.4: The one dimensional velocity model used to calculate microseismic event locations at Pouce Coupe. The blue diamonds show the position of the lower 24 receivers within the vertical 9-7 array. The orange, yellow, and pink circles depict the average depth for the horizontal leg of the 2-7, 7-7 and 8-7 treatment wells (2185m, 2105m, and 2155m).

20 Figure 2.5: Plan view images showing the events corresponding to the five microseismic subsets used in this study. Events are colored by stage. The distribution of events between subsets displays an observational bias based on event magnitude and proximity to the ob- servation array. Note the vertical 9-7 observation well is difficult to see in plan view (b, d, and e).

21 It is concluded that the fracture mapping results at Pouce Coupe are more typical of a tight gas sand than a highly heterogeneous shale with large scale fracture networks. This response is explained in part by the silty lithology of the Montney at Pouce Coupe, coupled with the characteristics of the in situ stress field. Nolen-Hoeksema (2013) describes how as fracturing pressure increases, hydraulic fractures open in the direction of minimum horizon- tal stress and propagate in the plane of the greatest and intermediate stresses. The large differential horizontal stress at Pouce Coupe therefore dictates the generation of long planar vertical hydraulic fractures.

Table 2.2: Summary of hydraulic fracture characteristics per stage as provided within the Pinnacle processing report.

Well Stage Maximum Half-length Height Growth Event Cloud Width

2-7 Stage 1 150m 90m 50m 2-7 Stage 2 120m 90m 50m 2-7 Stage 3 120m 90m 50m 2-7 Stage 4 150m 100m Uncertain 2-7 Stage 5 150m >100m 250m 7-7 Stage 1 250m >100m <200m 7-7 Stage 2 100m >100m 50m 7-7 Stage 3 300m 200m 200m 7-7 Stage 4 290m 230m 90m 7-7 Stage 5 350m 100m 90m 8-7 Stage 1 120m 130m 70m 8-7 Stage 2 110m 100m 100m 8-7 Stage 3 and 4 200m 200m 90m 8-7 Stage 5 and 6 200m n/a n/a

2.3 Completions and Production Data

The study wells at Pouce Coupe have a well spacing of approximately 1600 feet between the 2-7 and 7-7, and 1000 feet between the 7-7 and 8-7. Since 2008, the trend has been toward

22 more tightly spaced wells in the Montney with Shell and Canbriam reportedly spacing laterals at 1,000 (∼6 wells/section) or even 650 feet (∼8 wells/section), respectively (Unconventional Gas Resources, 2014). The 2-7 and 7-7 wells incorporated a multi-stage open hole packer system using ball drops to activate sliding sleeves in the lateral. The system appeared to work as designed with the majority of frac’ ports fracturing at the correct locations (Pinnacle, 2009). The cemented and cased 8-7 well incorporated a sleeve system with a limited entry perforation scheme. The distribution of microseismic events clearly nucleate in three clusters leading to the conclusion that the limited entry perforation strategy failed. Fractures were created at only one perforation location, and not simultaneously created at two sets of perforations per stage as designed (Pinnacle, 2009). Since treatment of the three study wells in this project, the open hole packer system with sliding sleeves has emerged as the most common completions technique for the Montney. The technique is preferred over cemented casing with plug and perf for a number of reasons. As there is no need for wireline work or plug drill-outs, treatment time can be significantly reduced, reportedly saving approximately half a million dollars (US) per well. Use of the openhole packer system also appears to lead to improved performance and allows for more stages per well (Unconventional Gas Resources, 2014). The planar fracture mapping and narrow cloud widths at Pouce Coupe explain the preference towards tighter stage spacing with 20-30 stages now common per well.

A visco-elastic fracturing fluid with 65-quality N2 was used for all stages at Pouce Coupe with a pump rate of around 4m3/min. Proppant volumes ranged from 95 to 200 tons per treatment stage. Figure 2.6 displays the recorded bottom hole pressure, slurry rate and proppant concentration during completion of the 2-7 well. The full completion reports are available for all three treatment wells and are directly compared with microseismic activity and shear-wave splitting observations in Chapter 6.

23 Figure 2.6: The proppant concentration, bottom hole pressure, and slurry rate during com- pletion of all 5 stages of the 7-7 treatment well.

Eighty-two months of production data from February 2009 through October 2015 are available. Figure 2.7 highlights the contrast in production rates between the three wells at Pouce Coupe. With an initial production rate of 5.2 MMcf/d, and a cumulative production of 2.4 Bcf, the 2-7 well is the most successful of the three. Considering the sub-standard completion of the 8-7 well, it is surprising that the 7-7 and 8-7 wells show similar production profiles. As the degree of economic success from the Montney is understood to be largely dependent upon the effectiveness of the hydraulic stim- ulation, this observation supports the hypothesis that the Montney C is a better production interval than the Montney D. Production logs from the 2-7 and 7-7 wells, acquired in January 2009, are also available for this study. The gas flow rate from the 2-7 production log shows a uniform distribution between stages. In contrast, the 7-7 production log shows large discrepancies between stages. While the third treatment stage contributes 43% of the well’s total gas flow, the fourth stage contributes only 10%.

24 The production data discussed emphasizes the importance of understanding reservoir heterogeneity and optimizing completions for economic success. As a result, the observations from this study are directly compared with the production data to help determine the factors controlling hydrocarbon production at Pouce Coupe.

Figure 2.7: The average daily gas production rate and the 82 month cumulative total for the three treatment wells at Pouce Coupe. The 2-7 well is clearly the most successful. All wells show a reasonably shallow decline rate after the first 12 months of production.

2.4 Previous Studies at Pouce Coupe

A time-lapse, shear-wave splitting analysis was previously performed at Pouce Coupe by Steinhoff (2013) to infer the magnitude of fracture-induced anisotropy. Exploiting the converted-wave seismic, shear-wave splitting magnitudes were observed to increase from 2% in the baseline survey, to a maximum of 8% following hydraulic stimulation of the 2-7 and 7-7 wells Figure 2.8. Measurements of the PS1-wave polarization, used to infer the orientation of the dominant fracture set, are predominantly parallel to SHmax but vary significantly across the survey. It is understood that shear-wave splitting observations from seismic and microseismic have not previously been compared, adding a unique aspect to this study.

25 Figure 2.8: Shear-wave splitting analysis from the (a) baseline, (b) monitor 1, and (c) monitor 2 surface seismic surveys. Splitting magnitudes are observed to increase from 2% in the baseline survey, to a maximum of 8% following hydraulic stimulation of the 2-7 and 7-7 wells. The orientation of the PS1-wave is predominantly NE-SW but varies significantly across the survey. Modified from Steinhoff (2013).

26 Lee (2014) was the first RCP student to focus on the downhole microseismic data at Pouce Coupe. He performed an amplitude ratio analysis of the recorded seismic modes to determine the dominant failure mechanisms for the microseismic events of each treatment stage. The results of Lee (2014) showed the majority of microseismic events at Pouce Coupe can be characterized as near-vertical, strike-slip failures, oriented in the general direction

of regional SHmax (Figure 2.9). An integration of this analysis with independent natural fracture determination techniques, including FMI and shear-wave splitting from surface seis- mic, provided a clear observation. Microseismic failures predominantly occur along existing planes of weakness in the form of natural fractures, suggesting the Montney at Pouce Coupe is a fracture-controlled reservoir.

Figure 2.9: Composite focal mechanism solutions for 10 of the treatment stages at Pouce Coupe as presented by Lee (2014).

Lee (2014) continued to show that the true value of microseismic can only be recognized following its integration with other geologic and engineering information. The combined interpretation of microseismic activity and rock type clusters, as defined by Due˜nas (2014), provided the best explanation of production variability at Pouce Coupe. Using textural, compositional, and elastic attributes, Due˜nas (2014) defined 6 rock type clusters within the Montney C and D. Using lambda-rho and mu-rho crossplots, two of these clusters were classified as the most easily frac-able. Microseismic activity within areas displaying an

27 increased thickness of the two best rock clusters was shown to result in higher production rates, both on a well-by-well and stage-by-stage basis (Figure 2.10). This supports the hypothesis, originally presented by Davey (2012), that rock quality is the biggest control on productivity at Pouce Coupe.

Figure 2.10: Isochron map of the two best quality rock clusters within the Montney C and D as determined by Due˜nas (2014). Microseismic events from the Montney C and D show the approximate areas of hydraulically stimulated reservoir. A correlation between the stimulated areas and the relative thickness of the highest rock quality in that area suggests rock quality is the biggest control on productivity.

MacFarlane (2014) also identified a strong correlation between the distribution of mi- croseismic events and regions of high shear velocity anisotropy. This supports the theory that stimulation energy and microseismic activity will preferentially nucleate in areas of pre- existing weakness, such as areas with increased natural fracture density (MacFarlane and Davis, 2015). Most recently, Vi˜nal (2015) calculated time-lapse time-shifts in the interval immediately overlying the reservoir (Montney C and D). Time-shifts within a 250m interval of the overbur- den were calculated to evaluate injection-induced stress-arching. Positive time-shifts within the PS volumes were shown to correlate with both pre-existing and hydraulically induced

28 zones of anisotropy in the reservoir as observed by Steinhoff (2013). These areas also display the highest flow rates as recorded by spinner log data (Figure 2.11).

Figure 2.11: On the left, microseismic events corresponding to the two horizontal wells along with stage by stage production data from spinner logs as percent of total flow volume. On the right, overlap of the microseismic events and the time-shifts between the monitor 2 and the baseline calculated using PS2 data. The highest producing area is highlighted.

In order to explain this correlation, Vi˜nal (2015) proposed the following hypothesis. Positive time-shifts may indicate areas where pressure has propagated upward along vertical fractures, yet the stimulated fractures do not extend into the overburden. In this case the sealing effect of the overburden would act to accumulate stress within the reservoir, causing stress arching of the overburden. In contrast, fractures that continue to propagate into the overburden would allow pressure to dissipate outside of the reservoir interval. The lack of stress accumulation within the reservoir and increased fracturing of the overburden would explain the negative time-shifts. This hypothesis would also explain why positive time- shifts correlate with increased production rates. As the top seal acts to retain pressure, one would expect fractures within the reservoir interval to remain open, providing increased permeability pathways for a sustained period.

29 CHAPTER 3 SHEAR-WAVE ATTENUATION FROM MICROSEISMIC EVENTS

This chapter presents a self-contained overview of the first microseismic waveform analysis method performed in this thesis. Shear-wave attenuation factors were calculated by com- paring observed and expected P/Sh amplitude ratios for each source-receiver pair following a methodology similar to that of Bergery et al. (2015). Interpretation of these shear-wave attenuation factors was anticipated to indicate areas of increased attenuation that could help to infer the presence of fluid-filled fractures. However, a number of significant limitations in the methodology were identified that hamper the ability to accurately model the expected amplitude ratio. The following sections discuss this methodology with particular emphasis on its assumptions and uncertainties.

3.1 Methodology

Studies such as Tan et al. (2014) discuss the relationship between reservoir fluid satu- ration and shear-wave attenuation. While shear-waves do not propagate within a fluid, lab experiments have shown shear-waves to experience high rates of attenuation within cracked and saturated rock (Toksoz et al., 1979). This observation suggests that shear-wave atten- uation may be the most diagnostic indicator of fluid-filled fractures and could therefore be used to map the growth of the stimulated reservoir volume. Studies including Tan et al. (2014) and Bergery et al. (2015) have looked to quantify shear-wave attenuation for such purposes using perforation shots and microseismic events respectively. For a number of reasons, the downhole microseismic from Pouce Coupe was believed to be a good dataset for such a study. First, the well geometry and two downhole observation arrays provide a high ray coverage with waveforms sampling both virgin and stimulated reservoir. Second, Lee (2014) performed an amplitude ratio analysis of the dataset to de- termine composite focal mechanisms for each treatment stage. Finally, as the Montney is

30 a tight gas reservoir, a high contrast in the attenuation signature between raypaths that sample natural gas-filled (dry) fractures and those that sample hydraulic fluid-filled (wet) fractures was anticipated. Such a contrast would likely provide the best opportunity to map the stimulated reservoir volume (Maxwell, 2014; Tan et al., 2014). The method performed first required calculation of the expected P/Sh amplitude ratio for each source-receiver pair. With the relative location of each source and receiver, and the source-mechanism of each microseismic event, the theoretical radiation pattern can be used to estimate the expected P- and Sh-wave amplitudes (Bergery et al., 2015). Based upon the anisotropic stress regime and the composite focal mechanisms determined by Lee (2014), a vertical strike-slip source mechanism oriented at N45◦E was assumed to represent all events at Pouce Coupe. This assumption represents the first major limitation in the application of this methodology. Under the single source-mechanism assumption, the far-field amplitude equations shown in Figure 3.1 were used to calculate the expected P/Sh amplitude ratio for each source- receiver pair. It is important to note that the amplitude equations displayed in Figure 3.1 do not correct for variable baseline attenuation (average intrinsic attenuation) of the P- and Sh-waves as they propagate within the reservoir. Each of the expected amplitude ratios calculated are therefore independent of the travel-path distance, suggesting that baseline attenuation of the P- and Sh-waves is equal (Qp = QSh). This assumption represents the second major limitation in the application of this methodology. The P- and Sh-wave amplitudes recorded by each receiver of the observation array were used to calculate the observed P/Sh amplitude ratio for each source-receiver pair. Using Equation 3.1, a shear-wave attenuation factor was then calculated for each source-receiver pair. These attenuation factors were then averaged to provide a single shear-wave attenuation factor for each event-array pair.

observed P/Sh Shear W ave Attenuation F actor = (3.1) expected P/Sh

31 Figure 3.1: Strike-slip coordinate system and the far-field amplitude equations for P- and Sh-waves. θ and Φ represent the relative azimuth and inclination between the microseismic failure plane and the receiver. Both far-field amplitude equations for the P- and Sh-wave contain a cos Φ term indicating that the expected amplitude ratio is independent of the source-vector inclination. It is important to note that the amplitude equations do not account for amplitude decay associated with baseline attenuation. Modified from Lee (2014).

3.2 Assumptions and Uncertainties

The methodology discussed and the assumptions it involves introduce significant uncer- tainty to the shear-wave attenuation factors. An explanation of these uncertainties will now be presented along with possible solutions to minimize their effect. First, any discrepancy between the true source mechanism and the single source mecha- nism assumption will introduce an uncertainty to the expected P- and Sh-wave amplitudes. As the accuracy of this assumption will vary for each microseismic event, the uncertainty introduced is random. Considering the wide range of modes of deformation feasible during hydraulic stimulation (Maxwell, 2014), the source-mechanism assumption likely represents a poor fit for a large number of events.

32 The error introduced from the source mechanism assumption is also increasingly amplified as source-vectors approach the modeled P- or Sh-wave nodal planes. This introduces a strong azimuthal bias to the shear-wave attenuation factors that is difficult to account for. Characterizing individual source-mechanisms for each event is the only way to minimize this uncertainty and reduce the azimuthal bias introduced to the shear-wave attenuation factors. Second, not accounting for variable baseline attenuation of the P- and Sh-wave also degrades the accuracy of the expected amplitude ratios. The magnitude of this uncertainty will increase for source-receiver pairs with greater travel-path distance. Estimates of the baseline attenuation factor for each phase (Qp, QSh) could be used to correct for this effect but are typically difficult to obtain. Spectral-ratio analysis over a range of travel-path distances could potentially be performed to determine a layered attenuation model (Maxwell, 2014). Correcting for baseline amplitude decay would likely result in more constrained and acceptable values for the shear-wave attenuation factors such that they represent deviation in the variable phase attenuation relative to the estimated baseline. Evidence of the uncertainties discussed will now be presented. Figure 3.2.a. displays a map view of the P- and Sh-wave theoretical radiation patterns for the single source mech- anism assumed. Figure 3.2.b. shows the expected P/Sh amplitude ratios as a function of azimuth for the same source mechanism. The azimuth of the P- and Sh-wave nodal planes are also shown on this plot along with the observed amplitude ratios from Pouce Coupe. The distribution of observed amplitude ratios in Figure 3.2.b. displays a large deviation from the single expected amplitude ratio. This distribution and the fact that over half of the observed ratios have a magnitude less than the expected ratio indicates the limitations of the methodology. The true source mechanism of individual events likely deviates signifi- cantly from the single fixed mechanism, such that it is a poor assumption. The uncertainty introduced to the shear-wave attenuation factors by this assumption is amplified toward the P- and Sh-wave nodal planes as the expected amplitude ratio approaches zero or infinity, respectively.

33 Accounting for variable baseline attenuation of the P- and Sh-wave would alter the shape of the expected amplitude ratio displayed in Figure 3.2. This would result in a re-scaling of the shear-wave attenuation factors and an improvement to the accuracy of this approach.

Figure 3.2: a.) Map view of the P- and Sh-wave propagation patterns for the single source mechanism assumed. P- and Sh-wave nodal planes are shown in orange and green respec- tively. b.) Graph of the expected amplitude ratio (black line) and the observed amplitude ratios as a function of azimuth (gray and blue data points correspond to attenuation fac- tors greater or less than 1 respectively). The azimuths of the expected nodal planes are also shown. The distribution of observed amplitude ratios relative to the expected ratio highlights the need to determine individual source mechanisms per event and to account for variable baseline attenuation of the P- and Sh-waves. A number of observed amplitude ra- tios near the Sh-wave nodal planes indicate the presence of a second shear failure mechanism approximately perpendicular to the one assumed. The single source mechanism displayed is a poor assumption introducing significant uncertainty to the expected amplitude ratio which is amplified as source-vectors approach the expected nodal planes.

34 The following section presents three examples of shear-wave attenuation results and their interpretation. The attenuation factors presented have been truncated at values between 1 and 80. While each example displays evidence of the limitations and bias discussed they also highlight the potential value to be gained from looking at the attenuation of downhole microseismic signal.

3.3 Results and Interpretation

Interpretation of the shear-wave attenuation results identify two spatio-temporal rela- tionships. Raypaths that sample regions of virgin reservoir typically display low attenuation factors but may occasionally highlight naturally occurring areas of increased attenuation. Raypaths that sample areas of the reservoir that have likely been stimulated, where fluid- filled fractures can be expected, generally display higher attenuation factors. The first and second examples presented display these two relationships, respectively. The third example displays both of these relationships. An integration of the third example with observations from previous studies reveals the most valuable insight gained from application of this anal- ysis at Pouce Coupe.

3.3.1 Example 1 - Inferring Areas of Natural Increased Attenuation

The first example refers to events associated with treatment of the 2-7 well as recorded by the vertical 9-7 array. Event-receiver raypaths for this example travel predominantly through unstimulated reservoir. Figure 3.3.a. shows the spatial distribution of these events relative to the treatment well (2-7) and the vertical observation array (9-7). Each event is scaled by its shear-wave attenuation factor. Events associated with the second treatment stage are seen to display significantly higher attenuation factors. This may lead to the interpretation that these raypaths sample a volume of reservoir with increased attenuation rates, perhaps due to a greater density of natural fracturing. Alternatively, these increased attenuation factors may correspond to events for which the assumed source-mechanism is a poor fit.

35 During later treatment of the 7-7 well, events associated with the first stage are observed to nucleate within the same localized cluster (Figure 3.3.b.). This supports the interpretation that shear-wave attenuation factors from the 2-7 treatment well identify an area of naturally increased attenuation toward the toe of the 7-7 well. The same area can also be identified as an area of increased anisotropy in the surface shear-wave splitting study of the baseline surface seismic (Steinhoff, 2013).

Figure 3.3: a.) Microseismic events associated with treatment of the 2-7 well as recorded by the vertical 9-7 observation array. Events are scaled relative to their calculated shear-wave attenuation factor. Higher attenuation factors suggest the presence of an area of increased attenuation as marked by the red oval. b.) Stage 1 events from treatment of the 7-7 well have been added and also scaled relative to the shear-wave attenuation factor. The clustering of a large number of microseismic events within this small area supports the interpretation for an area of increased natural fracture density.

It is important to consider the likelihood that the shear-wave attenuation factors dis- played in Figure 3.3 are biased relative to the event-receiver azimuth. Viewing individual raypaths and attenuation values in a 3D visualizer suggests this effect is present but not fully accountable for the pattern observed in this example.

36 3.3.2 Example 2 - Inferring the Presence of Hydraulic Fluid-Filled Fractures

The second example refers to treatment of the 8-7 well as monitored by the vertical 9-7 observation array. Figure 3.4 shows that attenuation factors are generally low for the first and second treatment stages but increase significantly for later fracture stages. The acquisition geometry in this example suggests higher attenuation factors could correspond to the sampling of fluid-filled fractures associated with areas of stimulated reservoir.

Figure 3.4: The calculated shear-wave attenuation factors for events associated with treat- ment of the 8-7 well, as recorded by the vertical 9-7 observation array.

To evaluate this hypothesis, events from this example scaled relative to their shear-wave attenuation factor are displayed in Figure 3.5. The location of 7-7 events (gray) are also shown to give an idea of previously stimulated reservoir. Events within cluster 2 show the typical pattern observed for a single fracture stage, with typically higher attenuation factors for events closer to the wellbore. These high attenuation factors may be attributed to “wet” raypaths that travel through a number of fluid-filled fractures. Attenuation factors are observed to decrease for events farther from the wellbore, at greater distances from the

37 immediate injection point of hydraulic fluid. Cluster 3 in Figure 3.5 encircles events observed during the fifth treatment stage of the 8-7 well. The majority of these events display relatively high attenuation factors potentially because they correspond to raypaths that intersect areas of stimulated reservoir.

Figure 3.5: Map view of events associated with the 8-7 treatment (orange) scaled relative to the shear-wave attenuation factor. Events associated with treatment of the 7-7 well (grey) have no scaling factor but are displayed to help identify areas or stimulated reservoir. The spatial and temporal distribution of high attenuation factors could infer areas of hydraulically stimulated reservoir but are almost certainly influenced by the azimuthal bias discussed.

The shear-wave attenuation factors presented in this example are almost certainly influ- enced by the azimuthal bias discussed in the previous section. Particularly high and low attenuation factors correspond with source-vectors that approach the P- and Sh-wave nodal planes respectively. Regardless of this bias, this example highlights the potential value of quantifying attenuation using downhole geometry. This example also suggests that observa- tion arrays placed toward the toe of the treatment well provide the best opportunity to map the growth of the stimulated reservoir volume.

38 3.3.3 Example 3 - Implications for Understanding Production

The third example refers to events associated with treatment of the 7-7 well as recorded by the horizontal 8-7 observation array. The calculated shear-wave attenuation factors are shown in Figure 3.6 with respect to relative event time. The same events scaled relative to their shear-wave attenuation factors are displayed in Figure 3.7.

Figure 3.6: Shear-wave attenuation factors for events observed by the horizontal 8-7 array during treatment of the 7-7 well.

Early stage events, represented by cluster 1 in Figure 3.7, correspond to event-receiver raypaths that run parallel and close to the full length of the horizontal 8-7 well. The par- ticularly high attenuation factors for these events suggest that certain areas of the reservoir sampled cause high rates of shear-wave attenuation. Distinguishing the exact location of this area of increased attenuation based solely on events from cluster 1 is difficult. Events observed during the third and fourth treatment stages are seen to dominantly propagate to the Northeast, nucleating in areas close to the 8-7 well (clusters 2 and 3). The observation that events propagate into this area, nucleate there and also display higher atten-

39 Figure 3.7: Events associated with treatment of the 7-7 well as recorded by the 8-7 horizontal array are scaled relative to their shear-wave attenuation factor. Particularly large attenuation factors are calculated for the blue events at the toe of the 7-7 well (cluster 1). The raypaths for these events to the 8-7 observation array suggest an area of increased attenuation in close proximity to the length of the 8-7 well. Events associated with later treatment stages 3 and 4 (clusters 2 and 3) show an unusual pattern. The events dominantly propagate to the northeast, nucleate within the vicinity of the 8-7 well, and also display high attenuation factors. These observations support the interpretation of an area of increased natural fracture density.

uation factors farther from the wellbore supports the interpretation for an area of naturally occurring increased attenuation. This pattern may suggest that hydraulic stimulation and microseismic activity preferentially occurs in areas of reservoir comprising increased natural fracture density. Integration of this example with previous studies provided valuable insight into the nature of hydraulic stimulation at Pouce Coupe. First, the baseline shear-wave splitting study clearly identifies a large area of increased fracture-induced anisotropy covering a similar area

40 (red polygon in Figure 3.8). Second, the same area corresponds to a negative time-lapse time-shift in the overburden following stimulation of the 7-7 well (Vi˜nal, 2015).

Figure 3.8: The baseline shear-wave splitting analysis performed on the converted-wave surface seismic clearly identifies an area of increased anisotropy immediately to the northeast of treatment stages 3 and 4 of the 7-7 well (red polygon). This observation supports the interpretation that high attenuation factors, and the relative distribution of microseismic events, indicate an area of naturally occurring increased attenuation. Modified from Steinhoff (2013).

In addition to these surface shear-wave splitting and time-shift observations, the vertical distribution of microseismic events within the same area shows an unusual pattern. While the majority of events observed at Pouce Coupe remain within the reservoir target interval (Montney C and D), events that nucleate within the area discussed clearly propagate through the vertical extent of the Montney E and F (Figure 3.9). This integrated interpretation helps validate the time-shift work and support the hypoth- esis presented by Vi˜nal (2015). Time-shifts observed in the overburden appear to correlate with the nature of hydraulic stimulation within the Montney reservoir. Negative time-shifts in the overburden correlate with hydraulic stimulation of Montney reservoir comprising in-

41 Figure 3.9: A vertical section looking southwest; roughly perpendicular to the orientation of the 7-7 horizontal well. Events associated with treatment of the 7-7 well as observed by the 8-7 observation array are colored by stage and scaled by their shear-wave attenuation factor. Stage 4 events which nucleate in the interpreted area of increased anisotropy and attenuation can be seen to propagate through the Montney E and F with a single event recorded in the overlying Doig Phosphate. creased anisotropy and increased attenuation. Microseismic activity in these areas is shown to propagate vertically out of the reservoir interval and into the overburden. Introduction of the stage-by-stage production discrepancies for the 7-7 well leads to the following hypothesis (Figure 3.10). Hydraulic fractures that remain within the target interval allow greater stress to accumulate and remain within the reservoir. This case corresponds to stress-arching and positive time-shifts in the overburden. This scenario likely causes

42 greater rubblizing of the reservoir interval, producing more sustainable permeability path- ways that lead to higher production rates. In contrast, stages for which microseismic activity propagates into the overburden correspond to negative time-shifts in the overburden. This scenario likely causes stimulation pressure to dissipate along hydraulic fractures outside of the reservoir interval. Such pathways are likely un-sustainable, resulting in lower production rates.

Figure 3.10: a.) Well 7-7 microseismic events and flow rates recorded by spinner log. b.) Large discrepancies in the production data between stages can be seen to correlate with positive and negative time-lapse time-shifts in the overburden (250m interval above the Montney D) as presented by Vi˜nal (2015).

3.4 Conclusions and Recommendations

A number of conclusions are drawn from this analysis. The first and second conclusions refer to the limitations of the methodology applied. Possible recommendations to reduce these limitations in future studies are also discussed. The remaining conclusions discuss the value specifically gained from application of this analysis at Pouce Coupe. First, the assumption of a single source mechanism introduces significant uncertainty to the expected amplitude ratios. This uncertainty is increasingly amplified as source-vectors approach the modeled nodal planes, resulting in a strong azimuthal bias of the shear-wave attenuation factors. Second, not accounting for variable baseline attenuation of the P- and

43 Sh-wave also degrades the accuracy of the expected amplitude ratio. Future success with this method will likely require the ability to constrain an accurate source-mechanism for each event. Bergery et al. (2015) perform this successfully using a time synchronized surface and downhole monitoring. While a surface network was acquired at Pouce Coupe, simultaneous re-processing would likely be required to tie events between the two surveys. Estimates of variable phase attenuation through spectral ratio analysis could also be performed in future studies. This would provide a means to account for variable baseline attenuation between phases improving the accuracy of this approach. The third conclusion refers to the integrated interpretation discussed in example three. High shear-wave attenuation factors are interpreted to identify an area of increased fracture density previously identified from the surface shear-wave splitting study. This corroboration supports the hypothesis initially proposed by Vi˜nal (2015). Hydraulic fractures that remain within the target interval allow greater stress to accumulate and remain within the reservoir. This typically corresponds to positive time-shifts in the overburden and higher production rates. Areas of increased natural fracture density, where microseismic activity propagates into the overburden, often correspond to negative time-shifts in the overburden and lower production rates. Finally, application of this methodology at Pouce Coupe suggests downhole observation arrays placed toward the heel of the treatment well are best suited for identifying reservoir heterogeneity in pre-stimulated regions of the reservoir. Downhole arrays placed at reservoir level toward the toe of the treatment well will be best suited for monitoring dynamic changes in the reservoir that could help map the growth of the stimulated reservoir volume. Due to the limitations of the attenuation analysis presented in this chapter, microseismic shear-wave splitting analysis was pursued to further characterize the Montney reservoir at Pouce Coupe.

44 CHAPTER 4 SHEAR-WAVE SPLITTING THEORY

To appreciate the value of this study, it is first necessary to integrate the theory of shear- wave splitting, the anisotropic nature of the reservoir at Pouce Coupe, and the ray coverage available from the downhole microseismic.

4.1 Seismic Anisotropy

Seismic anisotropy refers to the directional dependence of the velocity of elastic waves as they propagate through the subsurface (Tsvankin and Grechka, 2011). Estimation of the strength and symmetry axes of an anisotropic medium, as described by its anisotropic pa- rameters can be used to infer the physical rock properties that render a medium anisotropic. Due to the nature of bedding and faults in the subsurface, orthorhombic models are commonly used to represent sedimentary formations of interest. Orthorhombic media are characterized by three mutually orthogonal planes of mirror symmetry and are often regarded as the simplest realistic symmetry applicable in seismology (Bakulin et al., 2000; Tsvankin and Grechka, 2011). As presented by Tsvankin (1997), seven dimensionless anisotropy parameters and two isotropic reference velocities describe any homogeneous orthorhombic medium with a known orientation of the symmetry planes (Table 4.1). Each anisotropy parameter and reference velocity can be defined by components of the stiffness tensor, cij, and the density, ρ (Tsvankin and Grechka, 2011). Detailed discussion of wave propagation in orthorhombic media is complex and outside the scope of this work. Rather, emphasis is applied to the detection of anisotropy using shear-wave splitting analysis for reservoir characterization purposes.

45 Table 4.1: Orthorhombic anisotropy with a known orientation of the symmetry planes can be completely described by seven dimensionless anisotropy parameters (plus two vertical velocities). Their relationship to the VTI and HTI parameters are also shown (R¨uger, 2002).

4.2 Shear-Wave Splitting Theory

As a shear-wave propagates through an anisotropic medium, energy is split into two or- thogonally polarized shear phases that display slightly different velocities. This phenomenon is known as shear-wave splitting and is regarded as the most direct and unambiguous indi- cator of seismic anisotropy (Crampin, 1984; Teanby et al., 2004a). Shear-wave splitting along a given raypath can be characterized by two parameters, the fast-wave polarization (ψ), and the delay-time (δt) between the fast and slow shear-waves (Teanby et al., 2004a; Verdon et al., 2009). Measurements of shear-wave splitting can be used to determine the strength and symmetry axes of an anisotropic medium, as described by its anisotropic parameters. Estimations of these parameters can then be used to infer the physical rock properties that render the medium anisotropic.

46 The directional dependence of shear-phase velocities, and the relevant anisotropy param- eters responsible will now be discussed for variations of anisotropic models that are feasible for the Pouce Coupe reservoir.

4.2.1 Transversely Isotropic Media

Transverse isotropy represents a special case of orthorhombic symmetry with a horizontal symmetry plane (Tsvankin and Grechka, 2011). Transversely isotropic media are character- ized by a single axis of rotational symmetry that is perpendicular to the plane of symmetry. Horizontally layered shale formations are often represented using Vertical Transverse Isotropy (VTI) models. Orthorhombic symmetry will reduce to VTI if all vertical planes have identical properties, and the velocity of each mode in the isotropy plane is independent of azimuth (Tsvankin and Grechka, 2011). VTI models are therefore characterized by a horizontal isotropy plane and a vertical axis of rotational symmetry. Wave propagation in VTI media is governed by Thomsen’s VTI parameters ǫ, δ and γ (Thomsen, 1986). The relative velocity of each shear phase for a given source-vector is dependent on both these parameters and the orientation of the source-vector relative to

the isotropy plane [x1,x2]. Importantly, shear-waves in a VTI medium split into strictly horizontal and vertically polarized phases (Crampin and Love, 1991). As a result, the differ- ential velocity of shear phases in a VTI medium cannot technically be defined as shear-wave splitting.

Intuitively, shear phases propagating in the isotropy plane of a VTI medium [x1,x2] will experience the greatest magnitude of separation (Figure 4.1.a). The velocity of each shear phase, and therefore the degree of separation, is independent of azimuth (δ(3) = 0, γ(1) = γ(2) = γ, Table 4.1). In contrast, for a source-vector at vertical incidence, propagating perpendicular to the isotropy plane, shear-wave separation does not occur (γ(1) = γ(2) = γ, Table 4.1) (Figure 4.1.a). Let us now consider a Horizontal Transverse Isotropy (HTI) model consisting of a single set of azimuthally invariant vertical fractures within an isotropic background (Figure 4.1.b).

47 Figure 4.1: a.) Shear-wave propagation in a VTI medium. A vertically travelling shear-wave propagates perpendicular to the isotropy plane representing a null case. A shear-wave trav- elling horizontally experiences a maximum velocity difference and a horizontal polarization of the fast shear-wave. b.) Shear-wave propagation in an HTI medium. A horizontally trav- elling shear-wave represents the null case. A shear-wave with vertical incidence splits into fast and slow shear-waves, characterized by a maximum delay-time and a fast shear-wave polarization parallel to the fracture (isotropy) plane. Modified from Wuestefeld et al. (2010).

Assuming the fracture set is parallel to the [x2,x3]-plane, the single axis of symmetry will be

in the x1 direction. Wave propagation for this HTI medium is governed by the anisotropy

(V ) (V ) (V ) parameters ǫ , δ and γ defined in the [x1,x3]-plane and the vertical velocities VP 0 and

VS0 as developed by Tsvankin (1997).

(V ) The anisotropy coefficient γ is determined by the density (e2) of vertical fractures par-

allel to the x2 axis. The degree of shear-wave splitting is therefore dependent upon the mag-

(V ) nitude of γ and the orientation of the source-vector relative to the isotropy plane [x2,x3]. At vertical incidence, the shear-wave splitting parameter γ(s) is equal to the anisotropy

48 coefficient γ(V ) and can therefore be described by c − c γ(s) ≈ γ(V ) = 66 44 (4.1) 2c44 where the polarization of the fast shear phase is aligned with the isotropy plane. Equation 4.1 describes the basis for how shear-wave splitting studies from 3D surface seismic can be used to evaluate the dominant fracture orientation and relative fracture density of subsurface intervals. In contrast to the vertical incidence case, horizontal source-vectors perpendicular to the isotropy (fracture) plane, will not experience splitting (Figure 4.1.b).

4.2.2 Orthorhombic Media

As the Montney Formation likely has an orthorhombic symmetry (Steinhoff, 2013), we will now discuss shear-wave splitting theory directly applicable to studies at Pouce Coupe. Let us consider an orthorhombic model consisting of two vertical and orthogonal fracture sets, within a finely layered background (Figure 4.2). The anisotropy coefficients γ(1) and

(2) γ are defined in the [x2,x3] and [x1,x3]-planes, and are governed by the density of each

fracture set, e1 and e2, respectively.

Figure 4.2: An orthorhombic model resulting from the combination of two vertical fracture sets embedded within a horizontally layered VTI background. The azimuthally invariant fracture sets parallel the [x2,x3] and [x1,x3]-planes forming two vertical planes of symmetry. Modified from Tsvankin (1997).

49 The shear-wave splitting parameter (γs) has the same form for general orthorhombic as for TI models such that the splitting parameter at vertical incidence is described by the fractional difference between the stiffness coefficients c44 and c55 or, approximately the fast and slow shear-wave velocities:

− (1) − (2) − (s) ≡ c44 c55 γ γ ≈ VS1 VS2 γ = (2) (4.2) 2c55 1+2γ VS2

≡ c44 ≡ c55 where VS1 ρ and (S1) and VS2 ρ represent the vertical velocity of the fast and q q slow shear-wave respectively (Steinhoff, 2013; Tsvankin and Grechka, 2011). Equation 4.2 describes the basis for the converted-wave splitting study conducted at Pouce Coupe. Steinhoff (2013) related the magnitude of the shear-wave splitting parameter to the difference between the crack densities of the two dominant fracture sets. Under the assumption of vertical-incidence, the polarization of the fast shear-wave was used to infer the orientation of the dominant open fracture set. The introduction of downhole microseismic geometry requires the shear-wave splitting signature to be considered for any given source-vector. The 3D diagram displayed in Fig- ure 4.3 displays typical phase-velocity sheets within an orthorhombic medium (Tsvankin and Grechka, 2011). The diagram helps determine the anisotropy parameters responsible for the relative shear phase velocities along any source-vector feasible within a downhole survey. The seven dimensionless anisotropy parameters for orthorhombic symmetry (Tsvankin, 1997; Tsvankin and Grechka, 2011) are displayed on the plane in which they are defined. The density-normalized stiffness coefficients, aij, that govern the velocity of the shear phases at vertical incidence (a44 and a55) correspond to those presented in Equation 4.2. In addition, the stiffness coefficients responsible for the relative velocity of shear phases perpendicular to the vertical symmetry planes (i.e. along the x1 and x2 axis) are displayed. Point A represents a singularity at which the difference between fast and slow shear-velocities approaches zero resulting in no shear-wave splitting (Crampin and Love, 1991).

50 Figure 4.3: Typical P, fast-shear, and slow-shear phase velocity sheets for an orthorhombic medium. Importantly, the three symmetry planes of the medium are represented by the planes of the cartesian coordinate system. The seven dimensionless anisotropy parameters for orthorhombic symmetry are displayed on the plane in which they are defined (Tsvankin and Grechka, 2011).

4.3 Interpretation Theory for Microseismic Shear-Wave Splitting

The geometry of a downhole microseismic survey allows shear-wave splitting measure- ments to be made for a wide range of source-vectors. While this provides an opportunity to characterize multiple anisotropy systems it also complicates interpretation of the shear-wave splitting signature. Similar to all shear-wave splitting studies, the following equation is used to calculate the magnitude of anisotropy as defined by the percentage difference between fast and slow shear-wave velocities: Vs xdtx 100 δVs (%) = mean (4.3) r

where Vsmean equals the mean shear-wave velocity, dt represents the delay-time between the fast and slow shear-waves, and r represents the length of the source-receiver raypath

51 (Wuestefeld et al., 2010). Equation 4.3 assumes splitting occurs uniformly over the length of the raypath. A mean shear-wave velocity of 3250m/s was used in this study, representative of the Montney C as displayed in Figure 2.4. The biggest difference to the interpretation of the splitting signature in a downhole en- vironment relates to the polarization of the fast shear-wave. At non-vertical incidence the polarization of the fast shear-wave no longer corresponds to just an azimuth, but a vector described by both an azimuth and an inclination. For this study, the nomenclature devel- oped by Wuestefeld et al. (2010) is applied. The fast shear polarization in geographical coordinates is described by the “strike of the fast shear-wave polarization”, φp, and the “dip

of the fast shear-wave polarization”, δp. Further clarification regarding the coordinate sys- tems and associated angles used in microseismic shear-wave splitting analysis can be found in Wuestefeld et al. (2010). The shear-wave splitting signature over a full range of source-vectors can be visualized using synthetic models. The upper hemisphere projections shown in Figure 4.4 display the magnitude of anisotropy (δVs (%) ) as modeled for specific VTI, HTI, and orthorhombic cases. The tick marks on the projections represent the strike of the fast shear-wave polar-

ization (φp). In both transverse isotropy cases, point singularities at which the magnitude of anisotropy is zero (dark blue), correspond to the axis of rotational symmetry. In the VTI case the strike of the fast shear-wave polarization is consistently perpendicular to the source-vector

representing a horizontally polarized shear-wave (Sh-wave). In the HTI case, the strike of the fast shear-wave polarization becomes increasingly similar to the strike of the vertical fracture set for source-vectors with increasing inclination and azimuths that approach that of the fracture set. For the orthorhombic case, the shear-wave splitting signature is influenced by both hor- izontal layering and the vertical fracture set. The fracture set dominates the strike of the fast shear-wave polarization at higher inclination while the influence of the VTI background

52 dominates at lower inclination. It may also be noted that the location of singularities is determined by the combination of anisotropy systems and not by the model’s axes of sym- metry.

Figure 4.4: Synthetic upper hemisphere projections of the shear-wave splitting signature for (a) VTI, (b) HTI, and (c) orthorhombic cases. Any discrete position on the upper hemisphere represents a source-vector from the centroid of the projection. The center of each projection therefore corresponds to a vertical source-vector while the top of each projection corresponds to a horizontal source-vector with an azimuth of zero degrees. The magnitude of anisotropy is displayed by the color while the tick marks indicate the strike of the fast shear polarization, φp (Baird et al., 2013a).

4.4 Advantages of Anisotropy Estimation from Microseismic

The models and theory discussed in the previous section speak to the challenges of imag- ing anisotropy in the subsurface. The relatively limited sampling range recorded from surface seismic hinders the degree to which certain anisotropy parameters can be resolved. This lim- itation directly translates into the physical rock properties we are able to characterize. The predominantly vertical and sub-vertical incidence angles observed in surface seismic are best suited to resolving azimuthally anisotropic media. As discussed, shear-wave splitting studies are regularly performed to determine the nature of vertical or near vertical fractures

53 within HTI or orthorhombic media. This insight has direct value in evaluating the perme- ability networks of fractured reservoirs. The ability to image vertical transverse isotropy and infer physical rock properties such as horizontal layering requires offset-depth ratios of 1.2 or greater. Shear-wave splitting studies from downhole microseismic potentially offer a means to better characterize horizontally layered heterogeneity within and above reservoirs. It is likely this study will also provide insight into the contribution of bedding planes as fluid pathways for hydrocarbon production. A certain paradigm shift from conventional surface studies is required to consider shear- wave splitting from microseismic. Perhaps the most obvious difference is the use of a passive source. Fortunately, the hydraulic fracturing process generates strong shear-waves, making them ideal for splitting analysis (Baird et al., 2013a; Kendall et al., 2012). Other differences include the study of direct waves and the relative proximity of the source and receiver in a downhole environment. This reduces many of the challenges common to surface studies, such as isolating the correct shear reflection and removing the effects of an anisotropic overburden (layer stripping). The proximity of a downhole array also means the shear-waves travel predominantly within the reservoir and can be observed over a wide range of azimuths and inclinations. In addition to the wide ray coverage possible, there are a number of other factors that make downhole surveys particularly suitable for anisotropy estimation. Shear-waves gener- ated by microseismic events often have a high frequency content. As a result, microseismic wavelengths are more comparable to the length of permeability enhancing fractures (10−2 to 10−1m) than typical seismic wavelengths (10+1 to 10+2m) (Tsvankin and Grechka, 2011). This observation suggests splitting measurements from microseismic will be more sensitive to physical rock properties such as fracture sets and bedding planes that are known to contribute to hydrocarbon production (Tsvankin and Grechka, 2011). The ability to identify anisotropy is highly dependent upon the combination of anisotropy systems and the ray coverage available (Verdon et al., 2009). The fine-grained nature of the

54 Montney, and the observation of two dominant fracture sets at Pouce Coupe (Davey, 2012), make it reasonable to expect a reservoir with at least orthorhombic symmetry. To consider the reservoir orthorhombic and not monoclinic, the assumption must be made that the two fracture sets are both vertical and orthogonal. The source-vectors calculated for all of the 3C seismograms available at Pouce Coupe are displayed in Figure 4.5. The range of azimuths and inclinations is significant and highlights the benefit of having both horizontal and vertical observation arrays for this type of study. Figure 4.5 suggests a single homogeneous orthorhombic anisotropy model for the Pouce Coupe reservoir is realizable.

Figure 4.5: Polar plots displaying the source-vectors for all of the source-receiver pairs recorded within the downhole microseismic at Pouce Coupe. a.) Source-vectors recorded by the horizontal 8-7 array during treatment of the 2-7 and 7-7 wells. Note the distribution of inclinations increases for events closer to the array. b.) Source-vectors recorded by the vertical 9-7 array during treatment of the 2-7, 7-7, and 8-7 wells. Source-vectors for the 2-7 and 7-7 treatment all have inclinations above the horizontal while the deeper array for the 8-7 treatment recorded source-vectors with both positive and negative inclinations relative to the horizontal.

55 CHAPTER 5 SHEAR-WAVE SPLITTING FROM MICROSEISMIC

This chapter presents the methodology and results of the shear-wave splitting analysis performed on the downhole microseismic dataset at Pouce Coupe.

5.1 Methodology

The methodology for this analysis is divided into three sections. The first two sections consist of the data selection and waveform filtering steps necessary to develop a consistent dataset of acceptable quality. The third section describes the parameters required to semi- automate the splitting analysis. The justification of each parameter chosen is provided and is most often based upon the characteristics of the microseismic dataset. The final section of the methodology discusses the individual steps performed during the semi-automated splitting analysis.

5.1.1 Data Selection

All of the time-windowed events and arrival picks were assessed in InSite-HFTM. A total of 5574 single array events corresponded to a total of 169,114 3C seismograms. Of these, only 50,157 had P-arrival picks, and 87,602 had S-arrival picks. As both P- and S-arrival picks are required for the receiver rotation, a total of 48,987 3C seismograms were selected for the shear-wave splitting analysis (Table 5.1). Table 5.1 shows there is a large variation in the percentage of seismograms selected for splitting analysis between each subset. Typically, high quality P- and S-arrivals were observed and picked for the majority of seismograms recorded by the horizontal 8-7 array (Figure 5.1). In contrast, P- and S-arrivals are rarely recorded by the upper majority of the vertical 50 receiver array as it was unable to reach the desired depth. As a result, only 15% and 17% of the total 3C seismograms available were selected (Figure 5.2).

56 Table 5.1: The number of 3C seismograms (source-receiver records) selected for shear-wave splitting analysis. The percentage of 3C seismograms selected relative to the total available for that subset is also displayed.

Subset SeismogramsSelected(oftotalavailable) 2-7Treatment,8-7Observation 1,196(77%) 2-7Treatment,9-7Observation 1,205(15%) 7-7Treatment,8-7Observation 8,594(83%) 7-7Treatment,9-7Observation 22,591(17%) 8-7Treatment,9-7Observation 15,401(79%) Total 48,987(29%)

Figure 5.1: The waveform moveout for an event recorded by the horizontal 10 receiver array (8-7 well) during hydraulic stimulation of the 7-7 well. Note the 3C receivers are un-rotated. The P- and S-arrivals display a high signal-to-noise ratio and are easily picked (blue and orange respectively) on all 10 receivers.

57 Figure 5.2: The waveform moveout for an event recorded by the vertical 50 receiver array (9-7 well) during hydraulic stimulation of the 7-7 well. Note the 3C receivers are un-rotated. Time picks for the P- and S-arrival are marked in blue and green respectively. The S-arrival is picked for the deepest 23 receivers while the P-arrival is only picked on the deepest 8 receivers. The signal-to-noise ratio decreases dramatically for receivers at shallower depths due to the increased source to receiver travel-path distance.

58 For monitoring of the 8-7 treatment well, a smaller 12 receiver vertical array was deployed to successfully reach the desired depth. This explains why P- and S-arrivals with higher frequency content and signal-to-noise ratio were recorded and picked on the majority (79%) of the seismograms. Limiting the shear-wave splitting analysis to the selected seismograms reduces the range of source-vectors that can be studied. The source-vectors corresponding to the selected seismograms are shown in Figure 5.3. When compared to the total seismograms available (Figure 4.5) it can be seen that the majority of seismograms removed correspond to the source-vectors with sub-vertical inclinations recorded by the vertical 9-7 array.

Figure 5.3: Polar plots displaying the source-vectors for all source-receiver pairs with both P- and S-arrivals. a.) Source-vectors for the selected seismograms recorded by the horizontal 8-7 array. b.) Source-vectors for the selected seismograms recorded by the vertical 9-7 array. Note source-vectors with near-vertical inclinations as observed during the 2-7 and 7-7 treatment are removed when compared with Figure 4.5.

59 5.1.2 Waveform Filtering

Two noise-reduction techniques were performed to improve the signal quality of the shear-waves prior to the splitting analysis. Introducing phase distortions that would alter the relative amplitude of the three component seismograms was avoided by sticking to causal filtering techniques (Maxwell, 2014). It was first necessary to remove periodic noise from the selected seismograms. The presence and frequency of this noise was typically inconsistent between seismograms but was often strongest toward the end of an array at frequencies of ≈ 60Hz. The source of this distortion is likely attributed to harmonic electrical noise pickup or mechanical movement of the instrument (Al-Harrasi et al., 2011b; Maxwell, 2014). Based upon the inconsistent nature of this periodic noise, a single filter was deemed un- suitable. Based upon the recommendation of Wuestefeld et al. (2010), the following steps were taken to design an adaptive multi-notch filter specific to each of the selected 3C seis- mograms. A noise window was defined from the beginning of the seismogram to 50 samples

before the P-wave time pick, Tp (Figure 5.4). An autocorrelation of this noise window was performed to amplify any periodic noise relative to random noise. Taking the Fourier transform of this autocorrelation, the multi-notch filter, F, is described by

S F =1 − Noise (5.1) max(SNoise) where SNoise represents the normalized amplitude spectrum of the autocorrelation of the noise window. The inverse Fourier transform of the product of the original seismogram spectrum, Soriginal, and the multi-notch filter, F, provides the filtered seismogram T.

T = ifft ( Soriginal × F ) (5.2)

An example of the multi-notch filter, and the original and filtered time series and ampli- tude spectra are shown in Figure 5.4.

60 Figure 5.4: a.) The original (top) and filtered (bottom) waveforms for a single component seismogram. Note energy from the P-arrival is more clearly observed after application of the multi-notch filter. The noise window is defined from the beginning of the seismogram to 50 samples prior to the P-arrival. Periodic noise seen throughout the time series is significantly reduced following filtering. b.) The adaptive multi-notch filter designed for this seismogram. The filter is constructed by taking the fast Fourier transform of an autocorrelation of the noise window. c.) The original (blue) and filtered (red) amplitude spectra show that periodic noise at frequencies of approximately 60 and 100Hz are significantly reduced after the filtering. Note the frequency content of the shear-wave ranges from approximately 300-430Hz.

61 High frequency noise that is not periodic is also present throughout the dataset (Fig- ure 5.4). When designing filters to reduce this noise, it was important to consider the highly variant frequency content of shear-waves within the dataset. To address this issue, a rep- resentative selection of seismograms from each of the microseismic subsets were analyzed. Studying the waveform and frequency content of both shear components, it was possible to

estimate the arrival-time separation, ∆T, and the dominant period of the shear-wave, Tdom (Figure 5.5). A relationship between the dominant shear-wave period and the arrival-time separation was identified, effectively representing the attenuation of the shear-wave within the formation (Figure 5.6). The dominant period of shear-wave is shown to range from 2-10ms, correspond- ing to a frequency range of 100-500Hz. This analysis shows that the ideal low-pass filter is seismogram specific and will be largely dependent on the travel-time of the shear-wave. It is also necessary to consider the effect of the shear-wave frequency content with respect to the shear-wave splitting analysis. Frequency-dependent shear-wave splitting has been observed within microseismic data and has occasionally been exploited to determine the length-scale of the mechanisms causing anisotropy (Al-Harrasi et al., 2011b; Baird et al., 2013b). The range in frequency content of shear-waves within the Pouce Coupe dataset make it well-suited to studying frequency-dependent anisotropy. While this is not the focus of this study, it is an important factor to consider when comparing splitting results from shear-waves with highly variable frequency content. Based upon the shear-wave period and frequency analysis discussed, a single low-pass butterworth filter with a cutoff frequency of 400Hz was applied to all selected seismograms prior to the shear-wave splitting analysis. An example of the adaptive multi-notch and low-pass frequency filtering process is provided in the Appendices (Figure A.1).

62 Figure 5.5: An example of the shear-wave analysis performed for a given source-receiver pair (7-7 stage 4 event recorded on the 8-7 array). a.) The waveform and sonogram of the rotated shear horizontal component. b.) The waveform and sonogram of the rotated shear vertical component. The x-axis displays an extract from the 0.5 second duration time- windowed event. Both components show a dominant shear-wave period, Tdom, of 0.0024s (approximately 410Hz). The P- and S-arrival times are also shown with a time separation ∆T of 0.044 seconds.

63 Figure 5.6: Graph displaying the dominant period of the shear-wave versus the time-pick separation for 225 3C seismograms. The equation and R2 value of the linear trend is shown. The seismograms were selected to give a fair representation of the entire dataset. The dominant period is shown to increase from a minimum of 2 ms to a maximum of 10ms with increasing travel-time. This relationship indicates attenuation of the shear-energy. The relationship could therefore be used to account for baseline amplitude decay of Sh-waves to improve the accuracy of the attenuation analysis presented in Chapter 3.

64 5.1.3 Multi-Window Parameter Configuration

All methods that calculate shear-wave splitting require selection of a shear-wave analysis time-window. Manual window selection can be time consuming and is unrealistic for large volumes of data. In addition, shear-wave splitting measurements can be particularly sensi- tive to the analysis window chosen, making manual window selection quite subjective. For this reason, a semi-automated multi-window splitting analysis, developed by Teanby et al. (2004a), is performed in this study. By performing the multi-window analysis it is possible to determine the window that provides the most robust splitting measurement. Teanby et al. (2004a) state that an ideal analysis window should be representative of the S-wave only and include several periods of the dominant frequency. Splitting measurements from windows smaller than one period tend to produce unstable results with unrealistically low errors as only parts of the wavelength need matching. The inclusion of several periods helps to prevent cycle skipping and reduce the effects of noise. However, the window must not be too long as to include energy from the P-arrival or spurious secondary phases that will degrade the measurement. To perform the multi-window analysis, a grid of analysis windows must be defined for each 3C seismogram. Each grid of analysis windows is defined by the following parameters. The beginning of the analysis window can vary between Tbeg0 and Tbeg1 with Nbeg increments

of ∆Tbeg. The end of the analysis window can vary between T end0 and Tend1 with Nend

increments of ∆Tend. This provides a total number of analysis windows N, equal to Nbeg ×

Nend. Tbeg0, Tbeg1, Tend0, and Tend1 are all defined relative to the shear-wave arrival time Ts (Figure 5.7). To constrain the most suitable grid of analysis windows, the nature of shear-waves recorded within the Pouce Coupe dataset was considered. As the dominant period of the shear-wave varies from 2-10 ms, it was decided that a single fixed grid of analysis windows would not be suitable. Using the linear trend displayed in Figure 5.6 it is possible to estimate

the dominant period of the shear-wave Test.dom as a function of the arrival-time separation

65 Figure 5.7: A diagram of the analysis window grid and the parameters that characterize the multi-window splitting analysis. The upper and lower traces represent the Sh and Sv components for a single source-receiver record, respectively. for any given seismogram. This serves as a basis for determining the minimum possible window length for each seismogram. It may be noted that the data points in Figure 5.6 show some deviation away from the linear trend. This deviation can be attributed to both variation in source characteristics and attenuation. To account for this deviation, the minimum possible window length used in the multi-window analysis, defined by Tbeg1 and Tend0, was set equal to 1.5 times the estimated dominant period, Test.dom. Using 1.5 times the estimated dominant period ensures the minimum window length includes at least one wavelength of the dominant shear-wave on occasions for which the dominant period is underestimated. This window reduces the likelihood of matching only parts of the wavelength, leading to unstable results with unreal- istically low errors (Teanby et al., 2004a).

66 It was also necessary to determine the maximum delay-time, dtmax, in the grid search. This maximum delay-time must be shorter than the minimum length of the splitting window to avoid the wavelet being shifted out of the analysis window. Wuestefeld et al. (2010) explains how the maximum delay-time should be based on the dominant frequency of the shear-wave, suggesting half the average dominant period of the shear-wave as a good rule of thumb. Table 5.2 provides a summary of all the adaptive parameters used to constrain the multi-window aspect of the shear-wave splitting analysis performed.

Table 5.2: The adaptive parameters selected for the multi-window aspect of the shear-wave splitting analysis. The window grid is positioned relative to the shear-wave arrival time, Ts. The estimated dominant period of the shear-wave, Test.dom, is determined using the linear trend in Figure 5.6.

Parameter Value

Tbeg0 0.004s before Ts

Tbeg1 0.001s before Ts

Tend0 (1.5 x Test.dom) after T s

Tend1 (5 x Test.dom) after T s

Nbeg 5

Nend 50 N 250

dtmax 0.5 x Test.dom

5.1.4 Semi-Automated Splitting Analysis

After data selection and filtering, the workflow outlined in Figure 5.8 was followed to perform the shear-wave splitting analysis. Each of the 3C seismograms required a rotation into the frame of the ray. Using the event and receiver location, and the velocity model shown in Figure 2.4, a ray-tracing technique was performed in InSite-HFTM to determine the theoretical source-vector for each 3C seismogram. An Alford rotation of each source-receiver pair was then performed, transforming the un- rotated components of each 3C seismogram into the frame of the ray (Figure 5.9).

67 Figure 5.8: The workflow followed to semi-automate the shear-wave splitting analysis. Mod- ified from Wuestefeld et al. (2010).

Once rotated into the frame of the ray, the component oriented parallel with the source- vector displays maximum compressional energy, and is termed the “P” component. Energy associated with the shear-wave is isolated onto two orthogonal shear components aligned horizontally and quasi-vertically, termed the “Sh” and “Sv” components (Figure 5.10). Shear-wave splitting analysis was performed on the rotated 3C seismograms within the Seismic Analysis Code (SAC) package (Goldstein and Snoke, 2005; Goldstein et al., 2003; Helffrich et al., 2013). A modified version of the SAC macro known as SHEBA (Shear-Wave Birefringence Analysis), was used in this study to semi-automate the splitting analysis. The macro was developed by James Wookey of the University of Bristol. While the key steps are discussed below, the original source code remains the primary reference for this macro

68 Figure 5.9: A schematic of 3C receiver rotation. The X and Y components of the receivers display an arbitrary orientation with the Z component aligned parallel to the wellbore. A ray- tracing technique was performed in InSite-HFTM to determine the theoretical source-vector for each source-receiver pair. An Alford rotation rotates each 3C receiver into the frame of the ray. While this schematic shows straight rays, the ray tracing technique incorporates Snell’s Law using the isotropic velocity model at Pouce Coupe. Note the frame of reference for this schematic could correspond to either a vertical or horizontal observation array. Modified from Itasca (2014).

(Wookey, 2014). To use the SHEBA macro, a large effort was required to re-format the rotated seismo- grams. As SAC uses a single file per trace, a MatlabTM script was developed to map the header and trace information from SEGY to SAC format. The multiple window analysis performed within SHEBA removes the subjectivity of win- dow selection providing higher quality shear-wave splitting measurements (Teanby et al., 2004a). As splitting results can be very sensitive to the chosen analysis window, this tech-

69 Figure 5.10: a.) An un-rotated 3C seismogram (X, Y, Z). b.) The same 3C seismogram rotated into the frame of the ray (P, Sh, Sv). Both seismograms correspond to a single receiver from the horizontal 8-7 array. As the Z-component is aligned along the horizontal wellbore, at a similar orientation to the source-vector, the majority of energy associated with the P-wave is observed on the Z-component. nique is used to identify the most robust splitting measurements, selecting the most suitable analysis window both objectively and automatically. The process is presented in detail by Teanby et al. (2004a). For each analysis window, two methods are applied to estimate the shear-wave split- ting parameters. The first is the cross-correlation method (XC) presented by Ando et al. (1980). The XC method works by systematically rotating the two shear components of the corrected seismogram while performing a cross correlation of the time series. Searching for the maximum of the cross correlation coefficient returns the splitting parameters ΦXC and dtXC . The second method is the eigenvalue method (EV). The method searches for the most singular covariance matrix of rotated and time-shifted seismograms based on its eigenvalues λ1 and λ2 (Fukao, 1984; Wuestefeld et al., 2010).

Estimates from the XC and EV method are compared to assign a quality factor, Qw, to each analysis window. The comparison involves the calculation of a delay-time ratio (∆ =

70 dtXC / dtEV ) and the normalized difference in the fast shear-wave polarization (Ω = ΦEV

- ΦXC ). The process of assigning a quality factor to the results from each window can be best visualized by cross plotting the delay-time ratio and the normalized difference in the fast shear-wave polarization (Figure 5.11).

Figure 5.11: A comparison of the shear-wave splitting measurements from the XC and EV method is performed to assess the quality of the measurements from each analysis window. The distance from the ideal “null” and ideal “good” end members is used to assign a quality factor to the result from each analysis window (Wuestefeld et al., 2010).

A measurement characterized by identical delay-times and identical fast polarization estimates (∆ = 1, Ω =0) would be considered an ideal ’good’ measurement (represented by the dark green in Figure 5.11). In contrast, a measurement would be considered an ideal

’null’ if the XC method estimates no delay-time (dtXC = 0) while the two fast polarization estimates differ by 45◦ (∆ = 0, Ω =1) (represented by the dark red in Figure 5.11). The distance of individual measurements from these end members is used to determine the quality

factor, Qw to the results from each window. The last step within SHEBA is a cluster analysis performed to identify the measurements that are most robust over the multiple analysis windows. The final shear-wave splitting measurement is defined as the measurement with the highest quality factor in the cluster with the lowest variance (Teanby et al., 2004a). This workflow was repeated providing delay-time and fast shear-wave polarization measurements, along with a measurement quality factor,

71 Qw, for each source-receiver record. A quality threshold value, τ, is assigned such that only measurements of an acceptable quality are considered for further analysis.

5.1.5 Results

Due to the large dataset analyzed, a high threshold value of τ = 0.75 was assigned such that measurements with a quality factor less than 0.75 were discarded. Manual quality control of all measurements above this threshold was performed to evaluate if the semi- automated analysis had returned a reliable result. The criteria for a reliable result include (1) energy on the corrected transverse component is minimized to a similar level as the noise, (2) fast and slow waveforms are similar and match well after correction, (3) particle motion within the analysis window is transformed from elliptical to linear following the correction, and (4) the error surface shows a unique and well constrained solution Teanby et al., 2004a; Wuestefeld et al., 2010. All splitting measurements that pass the quality threshold, τ, but are deemed non-reliable following manual inspection of the diagnostic plot were also discarded from further analysis. The diagnostic plots for three splitting measurements that were deemed reliable are presented. Figure 5.12 shows an example from the 2-7 treatment well as observed by the horizontal 8-7 array. The low signal-to-noise ratio observed is typical for source-receiver records from this subset. The second reliable result shown in Figure 5.13 displays fast and slow shear-waves that are extremely similar highlighting the advantage of retaining a wide frequency bandwidth. This example also displays the benefit of windowing some time prior to the shear arrival, helping to stabilize the results. Figure 5.14 presents an example of a particularly high signal-to-noise ratio for a source-receiver record observed on the 9-7 vertical array during treatment of the 8-7 well. An example of a shear-wave splitting result with a high quality factor, that did not pass the manual quality control, is presented in Figure 5.15. Table 5.3 shows the number of splitting measurements that pass the automated quality control threshold. The number that pass manual inspection of the diagnostic plots is also shown.

72 Figure 5.12: The diagnostic plot for a reliable splitting result. a.) From top to bottom the Sh, Sv, and P seismogram components. b.) The radial and transverse component before and after the splitting correction with the final analysis window marked. c.) The waveforms and particle motion in Sh-Sv coordinates before (left) and after (right) the splitting correction. The top middle box displays waveforms after the splitting correction with a scaling factor. d.) The stacked error surface for the XC and EV methods (left) and the splitting measurements for each analysis window (top right). Bottom right shows each measurement in the cluster analysis, with red triangles marking the cluster locations and the final measurement indicated by the blue cross. For this example the 4 criteria for a reliable result are passed. (1) Energy on the corrected transverse component is minimized to a similar level as the noise. (2) The fast and slow waveforms are similar and match well after correction. (3) The particle motion is transformed from elliptical to linear following the correction. (4) The error surface shows a unique and well constrained solution. Note the splitting measurements are similar for approximately half of the analysis windows indicating a robust result. 73 Figure 5.13: The diagnostic plot for a reliable shear-wave splitting result. a.) From top to bottom the Sh, Sv, and P seismogram components. b.) The radial and transverse component before and after the splitting correction with the final analysis window marked. c.) The waveforms and particle motion in Sh-Sv coordinates before (left) and after (right) the splitting correction. The top middle box displays waveforms after the splitting correction with an amplitude scaling factor. d.) The stacked error surface for the XC and EV methods (left) and the splitting measurements for each analysis window (top right). Bottom right show each measurement in the cluster analysis, with red triangles marking the cluster locations and the final result indicated by the blue cross. The fast and slow waveforms in this example match particularly well, providing a single robust plateau of measurements across all 250 analysis windows.

74 Figure 5.14: The diagnostic plot for a reliable shear-wave splitting result. a.) From top to bottom the Sh, Sv, and P seismogram components. b.) The radial and transverse component before and after the splitting correction with the final analysis window marked. c.) The waveforms and particle motion in Sh-Sv coordinates before (left) and after (right) the splitting correction. The top middle box displays waveforms after the splitting correction with a scaling factor. d.) The stacked error surface for the XC and EV methods (left) and the splitting measurements for each analysis window (top right). Bottom right show each measurement in the cluster analysis, with red triangles marking the cluster locations and the final result indicated by the blue cross. For this example the 4 criteria for a reliable result are passed. (1) Energy on the corrected transverse component is minimized to a similar level as the noise. (2) The fast and slow waveforms are similar and match well after correction. (3) The particle motion is transformed from elliptical to linear following the correction. (4) The error surface shows a unique and well constrained solution. 75 Figure 5.15: An example of a diagnostic plot that was deemed not-reliable and therefore not included . a.) From top to bottom the Sh, Sv, and P seismogram components. b.) The radial and transverse component before and after the splitting correction with the final analysis window marked. c.) The waveforms and particle motion in Sh-Sv coordinates before (left) and after (right) the splitting correction. The top middle box displays waveforms after the splitting correction with a scaling factor. d.) The stacked error surface for the XC and EV methods (left) and the splitting measurements for each analysis window (top right). Bottom right show each measurement in the cluster analysis, with red triangles marking the cluster locations and the final result indicated by the blue cross. This example fails to pass a number of the criteria required for a reliable result. The fast and slow waveforms do not match well after correction, The particle motion is linear prior to the correction, and the stacked error surface does not display a unique solution.

76 Table 5.3: The number of source-receiver records that return a shear-wave splitting mea- surement with a quality factor greater than the threshold (Q > 0.75). The number that pass manual inspection of the diagnostic plots is also shown.

Subset Selected Q > τ Manual QC 2-7Treatment,8-7Observation 1,196 88 37 2-7Treatment,9-7Observation 1,205 40 20 7-7Treatment,8-7Observation 8,594 415 327 7-7Treatment,9-7Observation 22,591 360 263 8-7Treatment,9-7Observation 15,401 629 489 Total 48,987 1,532 1,136

77 CHAPTER 6 INTEGRATED INTERPRETATION OF MICROSEISMIC SHEAR-WAVE SPLITTING AT POUCE COUPE

A comprehensive interpretation of the shear-wave splitting measurements is performed. All reliable measurements are first analyzed independently of any spatial or temporal vari- ations under the assumption of a single homogeneous anisotropy model. Clusters of mea- surements that correspond to volumes of reservoir with high sample density are then used to interpret temporal variations associated with the dynamic response of the reservoir to hydraulic stimulation. Various datasets and observations from previous studies are used to compare and corroborate all interpretations.

6.1 Single Homogeneous Anisotropy System

The shear-wave splitting measurements obtained from this study are first interpreted assuming a single homogeneous anisotropy system that is invariant with time. That is, this interpretation does not take into account spatial or temporal variations that are likely introduced from both reservoir heterogeneity and the hydraulic fracturing process. To visualize the splitting measurements with respect to the ray coverage, all reliable results are displayed on a polar plot (Figure 6.1). The magnitude of anisotropy, as defined by the velocity difference between the fast and slow shear-waves, is represented by the tick- length of each data point. The orientation of each tick indicates the strike of the fast shear-wave polarization, φp. Splitting measurements corresponding to sub-horizontal raypaths typically display rel- atively low magnitudes of anisotropy with the strike of the fast shear-wave polarization approximately perpendicular to the azimuth of the source-vector. This observation indicates sampling of the VTI system introduced by horizontally-layered fabric within the Montney as modeled in Figure 4.4.a.

78 Figure 6.1: Polar plot displaying all reliable shear-wave splitting results. The position on the plot represents the azimuth and inclination of the source-vector. The magnitude of anisotropy as defined by the velocity difference between the fast and slow shear-waves is represented by the tick length. The orientation of the tick represents the strike of the fast shear-wave polarization, φp. Measurements with low magnitude of anisotropy and a fast polarization strike near perpendicular to the source-vector are commonly observed at low inclinations and are indicative of the VTI system. Measurements that show a rotation of the fast-shear polarization strike toward the source-vector indicate vertical planes of symmetry associated with near-vertical fracture sets.

An analysis of the splitting measurements from sub-horizontal source-vectors was per- formed in an attempt to investigate the strength of anisotropy introduced through horizontal layering. Measurements corresponding to source-vectors with an inclination from the hori- zontal of less than 20◦ were used. By only using the first three subsets, measurements were also restricted to waveforms that predominantly sample un-stimulated reservoir.

79 A dipole sonic log acquired in the horizontal leg of the 7-7 well provides an opportunity to corroborate these microseismic-based measurements. Figure 6.2 shows an extract of the log at a true vertical depth of 2105m (toward the base of the Montney D). The time-based method displays a shear-wave anisotropy value between 2% and 4%. The more reliable velocity-based (DT) method shows higher values ranging from 2% to 8%. The fast shear azimuth relative to vertical is approximately 85◦ corresponding to a fast polarization in the horizontal plane (Sh-wave).

Figure 6.2: An extract from the shear-wave anisotropy log acquired in the 7-7 well. The measured depth corresponds to the middle of the lateral at a depth just above the base of the Montney D. The time-based method displayed in track 4 returns an average shear- wave anisotropy value of approximately 2%. The azimuth displayed in track 3 represents a fast shear-wave with a polarization close to the horizontal plane. The extract displayed is representative of much of the lateral section for the 7-7.

Histograms comparing shear-wave anisotropy as measured from microseismic waveforms with sub-horizontal source-vectors to the velocity-based anisotropy values from the dipole

80 sonic log are displayed in Figure 6.3. The two histograms display a similar range of values from 0-10%. Microseismic-based values show a bimodal distribution with peaks at 1.5% and 6%. The log based values show a normal distribution with a peak of 5%. The normal distribution of the dipole-sonic values can be expected as the well stays within the same interval of the Montney D. In contrast, the microseismic waveforms sample a large volume of the reservoir introducing a greater influence from reservoir heterogeneity. Discrepancies between the two methods could also be attributed to the different frequency content between the shear-waves or drilling induced damage in the vicinity of the wellbore.

Figure 6.3: a.) A histogram of microseismic shear-wave splitting magnitudes observed for sub-horizontal source-vectors (less than 10◦ inclination from the horizontal). A bi-modal distribution is observed with the dominant peak at approximately 1.5%. b.) Velocity-based anisotropy values acquired in the horizontal section of the 7-7 well show a normal distribution with a peak at 5%. The two histograms show a range of anisotropy values from 0-10%.

Considering all reliable splitting measurements again, a further pattern is distinguishable in each of the three quadrants containing results in Figure 6.1. As data points approach certain azimuths the tick orientation is observed to rotate progressively toward that of the source-vector (i.e. toward the origin of the polar plot). This effect is exaggerated for source- vectors of higher inclination. Interpretation of this pattern indicates the presence of two planes of vertical symmetry associated with two near-vertical fracture sets. These fracture

81 sets are interpreted to strike at approximately N42◦E and S118◦E (±∼10◦) as displayed in Figure 6.4.a. Other datasets and previous studies have interpreted similar natural fracture sets within the Montney. The narrow planar distribution of the microseismic events as well as the composite focal mechanisms determined by Lee (2014) suggest a dominant natural fracture

orientation parallel to SHmax at Pouce Coupe. The orientation of the dominant fracture set inferred from the surface shear-wave splitting study is also predominantly oriented toward the Northeast (Steinhoff, 2013). This particular corroboration is especially evident when the region of the Montney reservoir sampled by the microseismic waveforms is considered.

Figure 6.4: Natural fracture sets as interpreted from microseismic shear-wave splitting and FMI analysis. a.) All reliable shear-wave splitting results displayed on a polar plot. The strike of the fast shear-wave polarization, indicated by the orientation of the ticks, rotates progressively closer to the origin as source-vectors approach planes of vertical symmetry. Two planes of vertical symmetry are interpreted to represent two near-vertical natural fracture sets with strikes of approximately N42◦E and S118◦E( ±∼ 10◦). b.) Image log analysis from nearby Farrell Creek Field indicates similar dominant and sub-dominant natural fracture sets within the Montney roughly parallel and perpendicular to SHmax. Modified from Davey (2012).

82 Finally, the image log analysis performed at nearby by Farrell Creek Field identified a

dominant natural fracture set roughly parallel to SHmax (Davey, 2012). Perhaps most im- portantly, a sub-dominant fracture set roughly perpendicular to SHmax was also interpreted in this study. The interpreted shear-wave splitting results confirm the presence of a similar

natural fracture-set perpendicular to SHmax within the Pouce Coupe reservoir (Figure 6.4). The presence of this complex natural fracture network, comprising two near-orthogonal frac- ture sets, has significant implications for optimizing hydraulic stimulation and production at Pouce Coupe. Based upon this simple interpretation, the Pouce Coupe reservoir can be said to comprise both horizontally-layered fabric and two near-vertical fracture sets roughly parallel and per-

pendicular to SHmax. Any future inversion of the shear-wave splitting measurements should therefore be constrained to determine a single homogeneous anisotropy model of at least orthorhombic symmetry.

6.2 Temporal Variations in Shear-Wave Splitting

Microseismic waveforms used in this study sample a wide region of the Montney reservoir. The real-time nature of a microseismic survey means that certain regions of the reservoir are sampled before, during, and after hydraulic stimulation. Analysis of spatial and temporal variations in the shear-wave splitting measurements may therefore provide further insight into the Montney and its response to hydraulic stimulation. Any significant spatial variations may be used to infer reservoir heterogeneity while temporal variations can be related to the dynamic response of the reservoir. The ability to resolve such variations is dependent upon the geometry of observation arrays as well as the relative distribution and timing of microseismic activity. Various plots were therefore constructed to assess the shear-wave splitting measurements best suited to this type of analysis. Figure 6.5 shows the linear raypath for source-receiver pairs that returned reliable shear-wave splitting measurements. The relative sample density for various areas of the reservoir can be inferred with the area between the 7-7 and 8-7 lateral clearly

83 Figure 6.5: Map displaying the linear raypaths for all source-receiver pairs with a reliable splitting measurement. Each event and raypath is colored by its respective subset with each event scaled by the splitting magnitude. The relative sample density of virgin and stimulated reservoir can be inferred when the well-completion order is taken into account (2-7,7-7,8-7).

experiencing the highest sample density. Taking the well-completion order into account it is also possible to infer the degree to which raypaths may have sampled stimulated reservoir. Figure 6.6 presents polar and cylindrical plots of all reliable splitting measurements col- ored by their respective subset. For both plots, the position of each data point represents the source-vector, and the tick length the magnitude of splitting. The tick orientation in

Figure 6.6.a. represents the strike of the fast polarization (φp). The tick orientation in Fig- ure 6.6.b. represents the dip of the fast polarization (δp) such that vertical ticks indicate quasi-vertical shear-waves and horizontal ticks indicate Sh waves (Baird et al., 2013a). In order to best distinguish temporal variations associated with hydraulic stimulation, from spatial variations introduced by reservoir heterogeneity, splitting measurements from tightly clustered microseismic events are required. Two suitable clusters were selected and are now discussed.

84 Figure 6.6: a.) A polar plot of all reliable splitting measurements colored by their respective subset. The tick length indicates the splitting magnitude and the tick orientation the strike of the fast polarization. b.) A cylindrical plot of all reliable splitting measurements colored by their respective subset. The tick length again indicates the splitting magnitude but the tick orientation indicates the dip of the fast polarization. Vertical ticks correspond to quasi- vertical shear-waves and horizontal ticks Sh waves. Clusters of measurements of the same color correspond to volumes of reservoir with a high sample density. Such clusters are well suited for analyzing temporal variations in splitting measurements.

85 6.2.1 Cluster 1 - Temporal Splitting Variations Parallel to SHmax

The first cluster of measurements assessed correspond to events observed by the vertical 9-7 array, during the first and second treatment stages of the 7-7 well. The microseismic event cloud propagates parallel to the source-receiver azimuth and progressively away from the observation array (Figure 6.7) making this cluster of measurements particularly well suited to analyzing the dynamic response of the reservoir during hydraulic stimulation.

Figure 6.7: The first cluster of events used to study temporal variations in the splitting measurements correspond to the first and second treatment stages of the 7-7 well as observed by the vertical 9-7 array. a.) Map view of the linear raypaths for source-receiver pairs of the first cluster. b.) A vertical section of the linear raypaths for source-receiver pairs of the first cluster looking toward the Northwest. Both images show a region of the reservoir with a very high sample density. This provides a good opportunity to analyze temporal variations in the splitting measurements that may provide insight into the response of the reservoir to hydraulic stimulation.

As shown in Figure 6.8, the measurements form a tight cluster between an azimuth of 35◦ to 75◦, and an inclination of 10◦ to 60◦. The strike of the fast polarization varies from near perpendicular to near parallel to the source-vector (Figure 6.8.a.), while the dip of the fast polarization is commonly horizontal or near-vertical (Figure 6.8.b.). It is important to note that the maximum dip of the fast polarization is limited by the inclination of the

86 source-vector. Measurements with a strike of the fast polarization perpendicular to the source-vector and a dip of the fast polarization close to horizontal indicate the splitting signature is dominated by horizontal layering (VTI). Measurements indicate an increasing influence of near-vertical fractures as the strike of the fast polarization rotates toward the source-vector and the dip of the fast polarization approaches a quasi-vertical shear-wave.

Figure 6.8: Polar and cylindrical plots show the source-vectors from cluster 1 are restricted between an azimuth of 35 to 75◦, and an inclination of 10 to 60◦. a.) The polar plot displays the strike of the fast polarization ranging from perpendicular to near-parallel to the source- vector indicating the approximate azimuth of the fracture set interpreted parallel to SHmax. b.) The cylindrical projection shows the dip of the fast polarization ranges from horizontal to near-vertical.

Temporal variations in the splitting measurements were directly compared with the mi- croseismic event count and the completion chart (Figure 6.9). During completion of the two treatment stages, the average magnitude of splitting increases from a minimum of approx- imately 5% to a maximum of 12%. The average strike of the fast polarization also rotates from a maximum of 120◦ to a minimum of approximately 65◦. The magnitude of shear-wave

87 splitting displays a strong negative correlation with the strike of the fast polarization. Both splitting measurements correlate with the slurry rate and appear to return toward their original values toward the end of the second completion stage. This analysis shows the dynamic response of the Montney to hydraulic stimulation can be observed through temporal variations in shear-wave splitting measurements. The majority of early measurements display lower splitting magnitudes and a strike of the fast polarization perpendicular to the source-vector; indicative of sampling the VTI system. As the hydraulic fracturing process continues the magnitude of splitting increases dramatically with the fast polarization rotating toward the azimuth of the source-vector. The majority of measurements therefore correspond to fast shear-waves that are quasi-vertical; indicating that reservoir anisotropy becomes dominated by near-vertical hydraulic fractures that are roughly parallel

to SHmax. Series of steady increases in the splitting magnitude, punctuated by a sharp decrease, may also indicate successive pressure build up and release. This could correspond to an increase in localized pressure and an increase in the vertical fracture aperture followed by frac’ tip extension. Further temporal and spatial analysis to distinguish between individual raypaths that sample hydraulic fractures or un-stimulated reservoir could help map the growth of hydraulic fractures. Such work could help to constrain the propped rock volume from the larger microseismic volume.

6.2.2 Cluster 2 - Temporal Splitting Variations Perpendicular to SHmax

The second cluster of measurements assessed correspond to events observed during the third treatment stage of the 8-7 well. These events nucleate toward the northeast of the

9-7 observation array with the microseismic event cloud again propagating parallel to SHmax (Figure 6.10). Source-vector azimuths for this cluster are similar to that of the natural

fracture set interpreted perpendicular to SHmax. This provides a good opportunity to analyze the dynamic response of this fracture set during hydraulic stimulation.

88 Figure 6.9: Integrated temporal analysis of splitting measurements from cluster 1. The first and second panels show a moving-average of the splitting magnitude and the fast polariza- tion strike. The third panel displays the microseismic event count for the first and second treatment stages associated with cluster 1. The fourth panel shows the completion chart during this period with proppant concentration on the left hand axis, and slurry rate and bottom hole pressure on the right hand axis. The splitting magnitude increases throughout the completion process and appears to return toward its original value following the second treatment stage. The strike of the fast polarization shows quite a dramatic rotation from a maximum of 120◦ to a minimum of around 65◦ during completion. When compared with the event count and the completion chart the splitting signature is interpreted to represent sampling of near-vertical hydraulic fractures trending roughly parallel to SHmax.

89 Polar and cylindrical plots of this cluster show the source-receiver vectors to range from 100◦ to 170◦ in azimuth and -30◦ to +40◦ in inclination (Figure 6.11). The strike of the fast polarization ranges from perpendicular to near parallel to the source-vector, rotating progressively toward the source-vector at azimuths approaching that of the near vertical fracture set roughly perpendicular to SHmax (Figure 6.11.a.). The dip of the fast polarization is either predominantly horizontal or vertical (Figure 6.11.b).

Figure 6.10: The second cluster of events used to study temporal variations in the splitting measurements correspond to the third treatment stages of the 8-7 well as observed by the vertical 9-7 array. a.) Map view of the source-receiver pairs for this cluster with linear raypaths. b.) A vertical section of the source-receiver pairs for this cluster looking toward the Northeast. Both images show a region of the reservoir within the Montney D with a very high sample density. This cluster provides a good opportunity to analyze temporal variations in the splitting measurements perpendicular to SHmax.

Splitting measurements were compared with the microseismic event count and the com- pletion chart over the period of this treatment stage (Figure 6.12). The splitting magnitude displays a sharp increase from 6% to a maximum of 9% with an average of approximately 7.5% during the period. Again the magnitude of splitting decreases following the completion process and returns toward its original value. The strike of the fast polarization shows a negative correlation with the splitting magnitude decreasing at the start of the completion process and returning toward its original value following the completion.

90 Figure 6.11: Polar and cylindrical plots of the second cluster show the source-receiver vectors to range from 100 to 170◦ in azimuth and -30 to +40◦ in inclination. a.) The strike of the fast polarization rotates progressively toward the source-vector at azimuths approaching that of the near vertical fracture set perpendicular to SHmax. b.) The dip of the fast polarization is predominantly either horizontal or vertical.

The initial splitting signature is interpreted to reflect activation and increased aperture

of the near-vertical natural fracture set perpendicular to SHmax at the onset of hydraulic stimulation. The fact that the splitting magnitude does not steadily increase throughout the completion process, as observed in the previous example, suggests hydraulic fractures

do not propagate any significant distance perpendicular to SHmax. The residual increase in the splitting magnitude from a baseline of 6% prior to the completion, to 7% following the completion could also be indicative of the propped rock volume. Calculating a moving-average of the strike of the fast polarization as shown in the second panel of Figure 6.12 is perhaps technically incorrect. The effect that is believed to occur during the completion process is an increase in the rotation of the strike of the fast polar-

ization toward the near-vertical natural fracture set interpreted perpendicular to SHmax. As measurements converge toward this azimuth from both directions, a moving average does not provide a correct representation of this effect.

91 Figure 6.12: Integrated temporal analysis of splitting measurements from cluster 2. The first and second panels show a moving-average of the splitting magnitude and the fast po- larization strike. The third panel displays the microseismic event count for the treatment stage associated with cluster 2. The fourth panel shows the completion chart during this period with proppant concentration on the left hand axis, and slurry rate and bottom hole pressure on the right hand axis. The splitting magnitude increases sharply at the beginning of the completion process to a maximum of 9%. An average of around 7.5% is maintained throughout the completion with the value decreasing to an average of 7% after completion. The strike of the fast polarization decreases during completion and returns toward its origi- nal value following completion. The splitting signature is interpreted to reflect an increased aperture of the near-vertical natural fracture set perpendicular to SHmax at the onset of hydraulic stimulation. An increased splitting magnitude is maintained until the end of the completion process indicating hydraulic fractures did not propagate any significant distance in the direction perpendicular to SHmax.

92 6.3 Limitations and Uncertainties

A comparison between the range of source-vectors available for the shear-wave splitting analysis, and the source-vectors that return reliable shear-wave splitting results was per- formed. This comparison provides insight into both the rock physics of the reservoir and the limitations of this analysis. Figure 6.13 identifies two azimuth zones at which source-vectors are available but no reliable shear-wave splitting results are obtained. These shadow zones are approximately 20-30◦ wide and both bisect the azimuths of the interpreted fracture sets.

Figure 6.13: A comparison between the range of source-vectors available for the shear-wave splitting analysis, and the source-vectors that return reliable shear-wave splitting results identifies three clear shadow zones. Source-vectors observed on the (a) horizontal 8-7 array and the (b) vertical 9-7 array that were used for the splitting analysis. (c) Two azimuth zones and inclinations of greater than 40◦ from the horizontal (purple shade) represent shadow zones where data was available but no reliable splitting measurements were obtained. These zones are likely due to a combination of increased attenuation, the influence of shear-wave nodal planes, and poor rotation into the frame of the ray at increased inclination.

There are likely multiple causes for the two shadow azimuths observed. First, the ori- entation of these shadow zones supports the interpretation of the two vertical fracture sets. Raypaths propagating at approximately 45◦ to both fracture sets will likely inherit a compli- cated splitting signature and experience particularly high attenuation rates. Greater attenu-

93 ation of the slow shear-wave can be expected explaining why a number of null measurements were observed within these azimuth zones. Further discussion regarding the measurement of splitting toward null directions can be found in Wuestefeld et al. (2010). Second, the majority of microseismic events at Pouce Coupe are characterized with strike-

slip source-mechanisms parallel to SHmax (Lee, 2014). Such source-mechanisms have a hori- zontal shear-wave nodal plane at 45◦ to the failure plane suggesting limited shear energy is generated at the shadow azimuths observed (see Figure 3.2). Reliable splitting results are also sparse at higher inclinations. Although limited source- vectors are available at inclinations greater than 40◦ from the horizontal, very few splitting results are obtained within this zone. This observation can be explained by the high at- tenuation rates expected for raypaths propagating through multiple bedding planes. The theoretical rotation performed is also increasingly degraded for source-vectors of higher in- clination due to the uncertainty of the 1D velocity model (Figure 2.4). Evidence of poor rotation into the frame of the ray was commonly observed for source-vectors at high incli- nations highlighting the inadequacy of the 1D velocity model (Figure 6.14).

94 Figure 6.14: 3C source-receiver record giving an example of poor rotation into the frame of the ray. Energy associated with the P-arrival is evident on the Sv-component while shear energy is clearly observed on the P-component. This error is introduced when using the insufficient 1D isotropic velocity model. The velocity model is a poor assumption of the subsurface such that the ray tracing technique does a poor job of estimating the theoretical source-vector, particularly at increased inclination. An improvement of the velocity model or individual hodogram analysis of the P-arrival for each source-receiver record would help reduce this error.

95 CHAPTER 7 CONCLUSIONS, RECOMMENDATIONS AND FUTURE WORK

The following conclusions can be drawn from the shear-wave attenuation work presented in Chapter 3:

• The amplitude-ratio method performed offers a promising means for inferring the pres- ence of fluid-filled fractures. However, the assumption of a single source mechanism at Pouce Coupe introduces significant uncertainty to the expected amplitude ratios. This uncertainty is increasingly amplified as source-vectors approach the modeled nodal planes, resulting in a strong azimuthal bias of the shear-wave attenuation factors. Not accounting for variable baseline attenuation of the P- and Sh-wave also degrades the accuracy of the expected amplitude ratio. Future success with this method likely re- quires the ability to determine an individual source-mechanisms for each event using simultaneous surface and downhole monitoring.

• High shear-wave attenuation factors indicate a localized area of increased natural frac- ture density that was previously observed in the surface shear-wave splitting study (Steinhoff, 2013). Paired with the vertical distribution of microseismic events, this ob- servation helps validate the hypothesis initially proposed by Vi˜nal (2015). Microseis- mic activity is observed to propagate into the overburden in areas of increased natural fracture density. Such areas correspond to negative time-shifts in the overburden and lower production rates. Stages that display microseismic activity confined within the target interval allow greater stress to accumulate and remain within the reservoir. This typically corresponds to positive time-shifts in the overburden and higher production rates.

The following conclusions are drawn from the microseismic shear-wave splitting analysis performed in this study:

96 • Microseismic shear-wave splitting measurements identify horizontally layered fabric

and two near-vertical natural fracture sets roughly parallel and perpendicular to SHmax. Any future inversion of the splitting measurements should be constrained to determine a single homogeneous anisotropy model of at least orthorhombic symmetry at Pouce Coupe.

• A strong correlation between completion data and splitting measurements suggest the dynamic response of the Montney to hydraulic stimulation can be analyzed through temporal variations in shear-wave splitting measurements.

• Temporal observations made parallel to SHmax identify a continued increase in the splitting magnitude (up to 7%) during the hydraulic fracture process. A rotation of the fast polarization strike and dip indicate that reservoir anisotropy becomes dominated

by near-vertical hydraulic fractures roughly parallel to SHmax.

• Temporal observations made perpendicular to SHmax display a sharp increase in the shear-wave splitting magnitude from 6% to 9% at the onset of hydraulic stimulation. The splitting signature is interpreted to reflect an increase in the aperture of the near-

vertical natural fracture set perpendicular to SHmax. The fact that the the splitting magnitude does not increase throughout the completion process suggests hydraulic

fractures do not propagate any significant distance perpendicular to SHmax.

• Microseismic shear-wave splitting provides an alternative approach for characterizing reservoir anisotropy. The ray coverage available can offer greater spatial coverage than a sonic log as well as a higher spatial resolution than surface seismic.

This study highlights the value as well as some of the practical challenges associated with downhole microseismic waveform analysis. The value of such studies for reservoir char- acterization purposes can be largely attributed to the proximity of the in-situ acquisition geometry and the range of ray coverage available. The majority of the practical challenges

97 can be attributed to uncertainties regarding the passive source. The variable location and failure-mechanism of microseismic events causes highly variable waveform characteristics and most often a low spatial sample density. Any automated studies of large quantities of data require adaptive filtering and analysis processes to make the most of the dataset. A shift toward full-waveform analysis, accounting for and modeling the dynamic response of a reservoir to hydraulic stimulation, will significantly enhance this type of study.

7.1 Recommendations

Typical completion protocols for the Montney Formation have developed significantly since initiation of the Pouce Coupe project. As a result, the majority of recommendations from this study refer to improving the shear-wave splitting analysis method for the benefit of future reservoir characterization studies. This study confirms that the ability to characterize the anisotropy of a reservoir is highly dependent upon the combination of anisotropy systems and the ray coverage available. Sig- nificant thought should therefore be given to the anisotropy system expected and the most diagnostic ray coverage that could be acquired when designing a future survey. As pre- sented by Verdon et al. (2009), synthetic modeling may be used in advance to assess how well splitting measurements from a certain ray coverage will image given fractures and/or sedimentary fabrics. As a rule of thumb, source-vectors with an azimuth similar to the strike of a fracture plane will be best suited for characterization of that fracture set. Source-vectors with increased inclination may also be sought to minimize the influence of sedimentary fabric on the splitting signature. In contrast source-vectors with inclinations close to horizontal will be best suited for characterizing any sedimentary fabric. Due to raypaths travelling predominantly through un-stimulated reservoir, downhole arrays placed at reservoir level toward the heel of the treatment well will be best suited for characterizing reservoir heterogeneity. In contrast, downhole arrays placed at reservoir level toward the toe of the treatment well will be best suited to analyze the response of the reservoir to hydraulic stimulation.

98 This study also highlighted some limitations associated with measuring shear-wave split- ting that may be considered when designing future surveys. First, shear-wave nodal planes for common source mechanisms may introduce shadow zones at which it is more difficult to acquire reliable splitting measurements. Second, reliable splitting measurements are more difficult to acquire toward null directions, as well as at certain azimuths and higher incli- nations due to increased attenuation from fractures or bedding planes, respectively. The accuracy of receiver rotation to a theoretical source-vector will also be increasingly sensitive to discrepancies in the velocity model at higher inclinations. It is therefore recommended that future studies perform an individual rotation of source-receiver records based upon hodogram analysis of the P-wave. It is recommended that future studies look to improve the process of data precondi- tioning. Application of a fixed low-pass filter to data with such variable frequency content undoubtedly degraded the number of reliable splitting measurements from the total that could potentially have been obtained. Aside from manually filtering each source-receiver record, an adaptive process that determines the optimum cutoff frequencies of a bandpass filter based upon the signal-to-noise characteristics of each shear-wave could be developed.

7.2 Future Work

The next logical step from this study would be to perform an inversion of the shear-wave splitting measurements to determine a single homogeneous anisotropy system for the Pouce Coupe reservoir. The interpretation of a horizontal sedimentary fabric and two near-vertical natural fracture sets suggest the inversion should be constrained for an orthorhombic model (Verdon and Kendall, 2011; Verdon et al., 2009; Wuestefeld et al., 2010, 2011). Estimates of the reservoir’s anisotropy parameters would contribute to improved seismic and microseismic processing of datasets of the Montney Formation. The analysis of differential shear-wave attenuation would be a significant step further from this study. The fast and slow shear-waves calculated from this study could be analyzed using the spectral ratio method following a workflow similar to Carter and Kendall (2006). As an

99 analogous but reciprocal relationship exists between the attenuation and velocity shear-wave splitting parameters, greater attenuation of the slow shear-wave could be expected (Crampin and Love, 1991; Tsvankin and Grechka, 2011). This type of analysis might help identify the mechanisms responsible for both velocity and attenuation anisotropy. Any temporal variations might also provide insight into the degree to which such mechanisms contribute to fluid distribution or local stress-changes within the reservoir during hydraulic stimulation (Carter and Kendall, 2006; Crampin and Love, 1991). The importance for temporal and spatial variations to be considered during the interpre- tation of microseismic data has become increasingly apparent during this study. It is critical that hydraulic fracture mapping, and other microseismic interpretation techniques, take into account the location and relative timing of individual events and measurements. Software capable of modeling these variations will be vital in transitioning toward more quantitative interpretations of the effective stimulated volume.

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105 APPENDIX - FREQUENCY FILTERING

Figure A.1: An example of the frequency filtering process. An adaptive multi-notch filter is applied to reduce periodic noise as well as a low-pass filter with a cutoff frequency of 400Hz.

106