Microseismic Monitoring and Geomechanical Modelling of CO2 - bris

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CHAPTER 6. GENERATING ANISOTROPIC SEISMIC MODELS BASED ON GEOMECHANICAL SIMULATION 6.4 Calibration with literature data Thus far I have provided only a limited amount of stress-velocity data with which my theory can be calibrated. Many other works (e.g., Sayers, 2002; Hall et al., 2008; Prioul et al., 2004; Hornby, 1998) also only provide limited numbers of samples. What is required is a compilation of data from many samples from which trends and rules-of-thumb can be developed, as well as calibration of the typical value ranges. This information will be very useful for model population. With this in mind Doug Angus and I have used my model to invert for crack density and aspect ratio based on ultrasonic velocity measurements on over 200 samples from the literature. I am grateful to Doug Angus for compiling much of the ultrasonic velocity database upon which these calibration measurements could be made, and also for writing the shell scripts that allowed my code to work rapidly on many individual samples with minimal work input from the user. I am also grateful to Doug Schmitt for providing data compiled by many of his graduate students. Table 6.5 list the studies in which Doug Angus found usable data, in the form of stress versus ultrasonic velocity measurements made on drained core samples. There is a large range of experimental techniques deployed across these reports. Some of these reports have measured anisotropic velocities, while some only make isotropic measurements. Some studies have used triaxial stresses to deform the samples, while some use uniaxial and some hydrostatic stresses. Where anisotropic data is available, it was inverted for, while for isotropic measurements the inversion can be collapsed into isotropic form. Similarly, when triaxial stress have been used, this is included in the inversion, while these effects can be ignored for hydrostatic cases. Where mineral data have been provided this has been used to compute the background stiffness tensor C r , and where they have not we used the behaviour at high pressures to estimate this tensor. Figure 6.11 shows the inverted a 0 and ξ 0 values computed from 234 literature samples, coloured by lithology. Mean values for each lithology, and standard deviations, are plotted in Table 6.6. The overarching trend in Figure 6.11 is that, except for shales, the initial aspect ratios show remarkable consistency, with aspect ratios of approximately 0.0002 – 0.0006. The initial crack density estimates show greater scatter, falling between 0.0-0.5. In Table 6.6,variations between lithologies can be seen. The clearest lithology variation is that shales generally have low values for ξ 0 , and high values of a 0 . I also note that anhydrites have very low values for ξ 0 , implying a relative lack of stress sensitivity for these rocks. Carbonates also appear to be less sensitive to stress than clastic rocks. The most likely explanation is that the degree of chemical cementation found in carbonate and anhydrite rocks makes them less sensitive to stress than sandstones and conglomerates, which appear to have generally higher microcrack densities. We also examined the dependence of initial crack density and aspect ratio on the depth from which the sample was recovered and porosity (where this information has been provided) but did not find any noticeable trends. However, most of the samples have been recovered from reservoirs. Thus, the limited depth distribution in the data may not be sufficient to extract any trends. This highlights the need to sample and measure all of the overburden when attempting to predict velocity 126
6.4. CALIBRATION WITH LITERATURE DATA Lithology Study Sandstone King (1966), Nur and Simmons (1969), Han (1986), King (2002) Rojas (2005), He (2006), Hemsing (2007), Grochau and Gurevich (2008) Hall et al. (2008) Tight-gas sandstone Han (1986), Jizba (1991) Shale Johnston and Christensen (1995), Hornby (1998), Bolas et al. (2005) Hemsing (2007) Tight-gas shale Jizba (1991) Limestone Simmons and Brace (1965), Nur and Simmons (1969), Brown (2002) Dolostone Brown (2002) Conglomerate He (2006) Anhydrite Hemsing (2007) Clay Hornby (1998), Bolas et al. (2005) Table 6.5: Published core tests of stress dependent ultrasonic velocities for a variety of sedimentary lithologies. Lithology No. of samples Mean ξ 0 Mean a 0 St. dev. ξ 0 St. dev. a 0 Sandstone 174 0.10 4.1×10 −4 0.080 1.8×10 −4 Carbonate 12 0.054 5.9×10 −4 0.087 5.4×10 −4 Anhydrite 2 0.01 1.6×10 −4 0.0024 0.7×10 −4 Conglomerate 10 0.19 2.5×10 −4 0.18 0.5×10 −4 Shale 26 0.026 1.18×10 −3 0.026 9.4×10 −4 Table 6.6: Mean values for ξ 0 and a 0 for each lithology, and their standard deviations. changes through these layers. This may seem like an obvious statement to make, but rarely are such measurements made in practise. The variation in a 0 observed in shales is worthy of further discussion. Shales are defined as siliclastic rocks with over 50% made up of grains smaller than 50µm. Although, shales are usually very abundant in hydrocarbon plays, often providing impermeable seals or as an organic material enriched source rock, understanding of their mechanical properties is poor, partly due to their fine grain size, and partly due to a lack of industrial interest. In Figure 6.12 a 0 and ξ 0 are plotted for the clay-rich samples and the Clair samples discussed earlier. Of the shale samples, the ones that fall within the global trend for a 0 of between 0.0002-0.001 are the Manville shale cores from Hemsing (2007), which contain significant amounts of quartz grains as well as clay, hence, the clay content of these rocks is on the low end of typical shales. This may explain why these samples are found close to the global trend (i.e., sandstones). The tight gas samples from Jizba (1991) are also found to have a 0 estimates that are sensitive to clay content, with elevated a 0 for samples with a high clay content. 127
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Microseismic Monitoring and Geomech
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Abstract Capture of CO 2 produced a
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Author’s Declaration I declare th
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Acknowledgments There are many thin
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Table of Contents Abstract Author
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TABLE OF CONTENTS 5.4 Results . . .
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Preface ‘Research is not an end i
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6. D. Angus, J-M. Kendall, J.P. Ver
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1 Introduction A technology push ap
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1.2. CCS OVERVIEW Figure 1.2: CCS s
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1.3. THESIS OVERVIEW for CO 2 to be
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1.3. THESIS OVERVIEW as microseismi
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2 The Weyburn CO 2 injection projec
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2.2. WEYBURN GEOLOGICAL SETTING Fig
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2.2. WEYBURN GEOLOGICAL SETTING N F
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2.4. EVENT TIMING AND LOCATIONS 500
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2.4. EVENT TIMING AND LOCATIONS 500
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2.4. EVENT TIMING AND LOCATIONS Nor
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2.4. EVENT TIMING AND LOCATIONS Fig
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2.5. DISCUSSION 500 1000 1100 North
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2.6. SUMMARY 2.6 Summary • CO 2 s
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3 Inverting shear-wave splitting me
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3.2. INVERSION METHOD the additiona
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3.2. INVERSION METHOD 1. P-wave inc
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3.2. INVERSION METHOD 180 160 140 C
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3.2. INVERSION METHOD 2800 2800 260
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3.2. INVERSION METHOD Loop over γ,
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20 10 5 5 1 20 30 40 80 100 60 40 1
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3.4. SWS MEASUREMENTS AT WEYBURN th
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3.4. SWS MEASUREMENTS AT WEYBURN ei
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3.4. SWS MEASUREMENTS AT WEYBURN ξ
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3.4. SWS MEASUREMENTS AT WEYBURN da
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4 2 2 3.4. SWS MEASUREMENTS AT WEYB
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1 1 1 1 1 1 1 1 1 1 3.5. DISCUSSION
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3.6. SUMMARY 3.6 Summary • I have
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4 A comparison of microseismic moni
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4.2. EVENT LOCATIONS 2400 Velocity
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4.2. EVENT LOCATIONS 200 150 Northi
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4.3. EVENT MAGNITUDES Pressure (MPa
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4.3. EVENT MAGNITUDES 160 140 120 N
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4.4. SHEAR WAVE SPLITTING 50 −3 E
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4.5. INITIAL S-WAVE POLARISATION In
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4.5. INITIAL S-WAVE POLARISATION 6
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4.5. INITIAL S-WAVE POLARISATION of
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4.6. INTERPRETATION OF SHEAR WAVE S
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Page 95 and 96: 80 4.6. INTERPRETATION OF SHEAR WAV
Page 97 and 98: 2 3 3.5 4 5 2 1.8 1.4 4 4.6. INTERP
Page 99 and 100: 4.7. DISCUSSION 4.7 Discussion The
Page 101 and 102: pressure, P fl σ ′ ij = σ ij
Page 103 and 104: 5.2. EFFECTIVE STRESS AND STRESS PA
Page 105 and 106: 5.3. NUMERICAL MODELLING 5.3.1 Flui
Page 107 and 108: 5.3. NUMERICAL MODELLING MORE FLUID
Page 109 and 110: 5.3. NUMERICAL MODELLING (a) (b) Fi
Page 111 and 112: 5.4. RESULTS 0 500 1000 Depth (m) 1
Page 113 and 114: 5.4. RESULTS 1 0.9 0.8 Soft Med Sti
Page 115 and 116: 5.4. RESULTS Overburden Extension i
Page 117 and 118: 5.4. RESULTS 1z:100x:100y 1z:100x:5
Page 119 and 120: 5.5. SURFACE UPLIFT 1 0.9 0.8 Soft
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Page 123 and 124: 6 Generating anisotropic seismic mo
Page 125 and 126: 6.2. STRESS-SENSITIVE ROCK PHYSICS
Page 127 and 128: 6.3. A MICRO-STRUCTURAL MODEL FOR N
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Page 149 and 150: 6.5. COMPARISON OF ROCK PHYSICS MOD
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Page 153 and 154: 7 Forward modelling of seismic prop
Page 155 and 156: 7.2. SEISMODEL c⃝ WORKFLOW time s
Page 157 and 158: 7.3. RESULTS FROM SIMPLE GEOMECHANI
Page 163 and 164: 7.4. SUMMARY 7.4 Summary • I have
Page 165 and 166: 8 Linking geomechanical modelling a
Page 167 and 168: 8.2. MODEL DESCRIPTION Layer Thickn
Page 169 and 170: 8.2. MODEL DESCRIPTION Unit E (GPa)
Page 171 and 172: 8.3. RESULTS Marl Vugg 0.8 0.8 Norm
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Page 177 and 178: 8.4. A SOFTER RESERVOIR 8.4 A softe
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Page 181 and 182: 8.4. A SOFTER RESERVOIR 2000 Max SW
Page 183 and 184: 8.5. DISCUSSION pore-pressure being
Page 185 and 186: 8.6. SUMMARY 8.6 Summary • I appl
Page 187 and 188: 9 Conclusions Geological storage wi
Page 189 and 190: calibrate. This model has been cali
Page 191 and 192: 9.1. NOVEL CONTRIBUTIONS techniques
Page 193 and 194: 9.2. FUTURE WORK Finally, the compa
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Bibliography Abt, D. L., Fischer, K
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BIBLIOGRAPHY Gassmann, F., 1951. Ub
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BIBLIOGRAPHY Kendall, J.-M., Pilido
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BIBLIOGRAPHY Sayers, C. M., 2002. S
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BIBLIOGRAPHY White, D., 2009. Monit
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A List of Symbols The table below l
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B In Support of Carbon Capture and
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Both China and India are aggressive
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Utsira rock properties vary signifi
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