Geophysical Monitoring for Geologic Carbon Storage. Группа авторов
Читать онлайн книгу.S., Kissling, E., Deichmann, N., Wiemer, S., Giardini, D., & Baer, M. (2003). Probabilistic earthquake location in complex three‐dimensional velocity models. Journal of Geophysical Research: Solid Earth, 108(B2). https://doi.org/10.1029/2002JB001778
9 Kaven, J. O., Hickman, S. H., McGarr, A. F., & Ellsworth, W. L. (2015). Surface monitoring of microseismicity at the Decatur, Illinois, CO2 sequestration demonstration site. Seismological Research. Letters, 86(4), 1096–1101. https://doi.org/10.1785/0220150062
10 Kijko, A. (1977a). An algorithm for the optimum distribution of a regional seismic network: I, Pure and Applied Geophysics, 115(4), 999–1009.
11 Kijko, A. (1977b). An algorithm for the optimum distribution of a regional seismic network: II, an analysis of the accuracy of location of local earthquakes depending on the number of seismic stations. Pure and Applied Geophysics, 115(4), 1011–1021.
12 Kissling, E. (1988). Geotomography with local earthquake data. Reviews of Geophysics, 26(4), 659–698.
13 Lin, G., & Shearer, P. (2005). Tests of relative earthquake location techniques using synthetic data. Journal of Geophysical Research, 110(B4). https://doi.org/10.1029/2004JB003380
14 Maxwell, S. C., & Urbancic, T. I. (2001). The role of passive microseismic monitoring in the instrumented oil field. The Leading Edge, 20(6), 636–639.
15 Miyazawa, M., Venkataraman, A., Snieder, R., & Payne, M. A. (2008). Analysis of microearthquake data at Cold Lake and its applications to reservoir monitoring. Geophysics, 73(3), 15–21.
16 Oye, V., Aker, E., Daley, T. M., Kühn, D., Bohloli, B., & Korneev, V. (2013). Microseismic monitoring and interpretation of injection data from the in Salah CO2 storage site (Krechba), Algeria. Energy Procedia, 37, 4191–4198. https://doi.org/10.1016/J.EGYPRO.2013.06.321
17 Paige, C. C., & Saunders, M. A. (1982). LSQR: An algorithm for sparse linear equations and sparse least squares. ACM Transactions on Mathematical Software, 8(1), 43–71.
18 Pesicek, J. D., Child, D., Artman, B., & CieśBlik, K. (2014). Picking versus stacking in a modern microearthquake location: Comparison of results from a surface passive seismic monitoring array in Oklahoma. Geophysics, 79(6), KS61–KS68. https://doi.org/10.1190/geo2013‐0404.1
19 Rabinowitz, N., & Steinberg, D. M. (1990). Optimal configuration of a seismographic network: A statistical approach. Bulletin of the Seismological Society of America, 80(1), 187–196.
20 Steinberg, D. M., Rabinowitz, N., Shimshoni, Y., & Mizrachi, D. (1995). Configuring a seismographic network for optimal monitoring of fault lines and multiple sources. Bulletin of the Seismological Society of America, 85(6), 1847–1857.
21 Stork, A., Nixon, C., Hawkes, C., Birnie, C., White, D., Schmitt, D., & Roberts, B. (2018). Is CO2 injection at Aquistore aseismic? A combined seismological and geomechanical study of early injection operations. International Journal of Greenhouse Gas Control, 75, 107–124. https://doi.org/10.1016/J.IJGGC.2018.05.016
22 Takagishi, M., Hashimoto, T., Toshioka, T., Horikawa, S., Kusunose, K., Xue, Z., & Hovorka, S. D. (2017). Optimization study of seismic monitoring network at the CO2 injection site: Lessons learnt from monitoring experiment at the Cranfield Site, Mississippi, U.S.A. Energy Procedia, 114, 4028–4039. https://doi.org/10.1016/J.EGYPRO.2017.03.1543
23 Verdon, J. P., Kendall, J.‐M., & White, D. J. (2012). Monitoring carbon dioxide storage using passive seismic techniques. Proceedings of the Institution of Civil Engineers: Energy, 165(2), 85–96. https://doi.org/10.1680/ener.10.00018
24 Verdon, J. P., Kendall, J.‐M., White, D. J., Angus, D. A., Fisher, Q. J., & Urbancic, T. (2010). Passive seismic monitoring of carbon dioxide storage at Weyburn. The Leading Edge, 29(2), 200–206.
25 Wagoner, J. (2009). 3D geologic modeling of the Southern San Joaquin Basin for the Westcarb Kimberlina demonstration project: A status report. Lawrence Livermore National Laboratory LLNL‐TR‐410813.
26 Waldhauser, F., & Ellsworth, W. L. (2000). A double‐difference earthquake location algorithm: Method and application to the northern Hayward fault, California. Bulletin of the Seismological Society of America, 90(6), 1353–1368. https://doi.org/10.1785/0120000006
27 Walter, A. W., & Mooney, W. D. (1987). Interpretations of the SJ‐6 seismic reflection/refraction profile, south central California, USA. USGS Open‐File Report 87–73.
28 Wuestefeld, A., Greve, S. M., Näsholm, S. P., & Oye, V. (2018). Benchmarking earthquake location algorithms: A synthetic comparison. Geophysics, 83(4), KS35–KS47. https://doi.org/10.1190/geo2017‐0317.1
29 Zhang, H., & Thurber, C. H. (2003). Double‐difference tomography: The method and its application to the Hayward fault. California. Bulletin of the Seismological Society of America, 93(5), 1875–1889.
5 Seismic Response of Fractured Sandstone During Geological Sequestration of CO2 : Laboratory Measurements at Mid (Sonic) Frequencies and X‐Ray CT Fluid Phase Visualization
Seiji Nakagawa and Timothy Kneafsey
Earth and Environmental Sciences, Lawrence Berkeley National Laboratory, Berkeley, California, USA
ABSTRACT
A series of laboratory supercritical carbon dioxide (scCO2) injection experiments (pore water drainage experiments) on small sandstone cores investigating the effects of a single discrete fracture is presented. The orientation and aperture of the fracture are varied across the series of tests. The dynamic Young's modulus and shear modulus along the axis of cylindrical core samples and their related attenuation are determined within a sonic frequency band of ~1 kHz to ~2 kHz, using a resonant bar technique. Concurrently, the distribution of scCO2 injected into the cores is examined using X‐ray CT. The orientation of the fracture with respect to the scCO2 migration and the wave propagation direction is shown to have a large impact on how the seismic wave velocities (or moduli) and attenuations change as a function of scCO2 saturation of porous, fractured rock.
5.1. INTRODUCTION
During geological sequestration of CO2, velocity and attenuation of seismic waves can be monitored to detect the invasion of supercritical CO2 (scCO2) and to determine its saturation in the reservoir rock. The scCO2 introduced in fluid‐saturated (typically by fresh or saline water) porous rock reduces the bulk modulus of the rock, causing reductions in the compressional (or P‐wave) wave velocity. These reductions are usually related to the amount of CO2 in the pore space through simple quasi‐static rock physics relationships such as the Gassmann's fluid substitution model (Gassmann, 1951). However, these models do not always provide satisfactory results, particularly when the seismic waves used by the measurements have relatively high frequency (e.g., Cadoret et al., 1995; Azuma et al, 2013).
Many laboratory experiments for the dynamic properties of CO2‐injected rock have been conducted at ultrasonic frequencies, for correlating a variety of reservoir conditions to seismic signatures as a function of scCO2 saturation. Wang and Nur (1989) conducted laboratory ultrasonic measurements during CO2