mCSEM inversion for CO2 sequestration monitoring at a deep brine aquifer in a shallow sea
Seogi Kang 1 2 Kyubo Noh 1 Soon Jee Seol 1 3 Joongmoo Byun 11 Department of Natural Resources and Geoenvironmental Engineering, Hanyang University, Haengdang 1-dong, Seongdong-gu, Seoul 133-791, Korea.
2 University of British Columbia, Department of Earth and Ocean Sciences, UBC-GIF, British Columbia V6T1Z4, Canada.
3 Corresponding author. Email: ssjdoolly@hanyang.ac.kr
Exploration Geophysics 46(3) 236-252 https://doi.org/10.1071/EG14096
Submitted: 1 October 2014 Accepted: 2 October 2014 Published: 13 November 2014
Abstract
Carbon dioxide injection monitoring in offshore environments is a promising future application of the marine controlled-source electromagnetic (mCSEM) method. To investigate whether the mCSEM method can be used to quantitatively monitor variations in the distribution of the injected CO2, we developed a mCSEM inversion scheme and conducted numerical analyses. Furthermore, to demonstrate the monitoring capability of the mCSEM method in challenging environments, we used a deep brine aquifer model in shallow sea as an injection target. The mCSEM responses of the injected CO2 in the deep brine aquifer were severely decayed and heavily masked by the air wave due to the proximity of the free space. Therefore, the accurate computation of small mCSEM responses due to the injected CO2 and the proper incorporation into the inversion process are critically important for the mCSEM method to be successful. Additionally, in monitoring situations, some useful a priori information is usually available (e.g. well logs and seismic sections), and the proper implementation of this to our inversion framework is crucial to ensure reliable estimation of the distribution of the injected CO2 plume. In this study, we developed an efficient 2.5D mCSEM inversion algorithm based on an accurate forward modelling algorithm and the judicious incorporation of a priori information into our inversion scheme. The inversion scheme was tested with simplified and realistic CO2 injection models and successfully recovered the resistivity distributions of the injected CO2, although it still required the presence of a considerable amount of the injected CO2. Based on these inversion experiments, we demonstrated that the mCSEM method is capable of quantitatively monitoring variations in the distribution of injected CO2 in offshore environments.
Key words: a priori information, carbon dioxide, inversion, marine CSEM, monitoring.
References
Abubakar, A., Habashy, T. M., Druskin, V. L., Knizhnerman, L., and Alumbaugh, D., 2008, 2.5D forward and inverse modeling for interpreting low-frequency electromagnetic measurements: Geophysics, 73, F165–F177| 2.5D forward and inverse modeling for interpreting low-frequency electromagnetic measurements:Crossref | GoogleScholarGoogle Scholar |
Andreis, D., and MacGregor, L., 2011, Using CSEM to monitor production from a complex 3D gas reservoir—a synthetic case study: The Leading Edge, 30, 1070–1079
| Using CSEM to monitor production from a complex 3D gas reservoir—a synthetic case study:Crossref | GoogleScholarGoogle Scholar |
Bhuyian, A. H., Ghaderi, A., and Landro, M., 2011, CSEM sensitivity study of CO2 layers with uniform versus patchy saturation distributions: SEG Technical Program Expanded Abstracts, 30, 655–659.
Bhuyian, A. H., Landro, M., and Johansen, S. E., 2012, 3D CSEM modeling and time-lapse sensitivity analysis for subsurface CO2 storage: Geophysics, 77, E343–E355
| 3D CSEM modeling and time-lapse sensitivity analysis for subsurface CO2 storage:Crossref | GoogleScholarGoogle Scholar |
Black, N., Wilson, G. A., Gribenko, A. V., Zhdanov, M. S., and Morris, E., 2011, 3D inversion of time-lapse CSEM data based on dynamic reservoir simulations of the Harding field: North Sea: SEG Technical Program Expanded Abstracts, 30, 666–670.
Brown, V., Hoversten, M., Key, K., and Chen, J., 2012, Resolution of reservoir scale electrical anisotropy from marine CSEM data: Geophysics, 77, E147–E158
| Resolution of reservoir scale electrical anisotropy from marine CSEM data:Crossref | GoogleScholarGoogle Scholar |
Chung, Y., Son, J. S., Lee, T. J., Kim, H. J., and Shin, C., 2014, Three-dimensional modelling of controlled-source electromagnetic surveys using an edge finite-element with a direct solver: Geophysical Prospecting, 62, 1468–1483
| Three-dimensional modelling of controlled-source electromagnetic surveys using an edge finite-element with a direct solver:Crossref | GoogleScholarGoogle Scholar |
Constable, S., 2010, Ten years of marine CSEM for hydrocarbon exploration: Geophysics, 75, 75A67–75A81
| Ten years of marine CSEM for hydrocarbon exploration:Crossref | GoogleScholarGoogle Scholar |
Constable, S. C., Parker, R. L., and Constable, C. G., 1987, Occam’s inversion: a practical algorithm for generating smooth models from electromagnetic sounding data: Geophysics, 52, 289–300
| Occam’s inversion: a practical algorithm for generating smooth models from electromagnetic sounding data:Crossref | GoogleScholarGoogle Scholar |
Demmel, J., 1997, Applied numerical linear algebra: Society for Industrial and Applied Mathematics.
Ellis, M., and Sinha, M., 2010, The potential of controlled source electromagnetic surveying in CO2 storage monitoring: SEG Technical Program Expanded Abstracts, 29, 843–847.
Gribenko, A., and Zhdanov, M., 2007, Rigorous 3D inversion of marine CSEM data based on the integral equation method: Geophysics, 72, WA73–WA84
| Rigorous 3D inversion of marine CSEM data based on the integral equation method:Crossref | GoogleScholarGoogle Scholar |
Kang, S., Seol, S. J., and Byun, J., 2012, A feasibility study of CO2 sequestration monitoring using the mCSEM method at a deep brine aquifer in a shallow sea: Geophysics, 77, E117–E126
| A feasibility study of CO2 sequestration monitoring using the mCSEM method at a deep brine aquifer in a shallow sea:Crossref | GoogleScholarGoogle Scholar |
Kaputerko, A., Gribenko, A., and Zhdanov, M. S., 2007, Sensitivity analysis of marine CSEM surveys: SEG Technical Program Expanded Abstracts, 26, 609–613.
Key, K., 2009, 1D inversion of multicomponent, multifrequency marine CSEM data: methodology and synthetic studies for resolving thin resistive layers: Geophysics, 74, F9–F20
| 1D inversion of multicomponent, multifrequency marine CSEM data: methodology and synthetic studies for resolving thin resistive layers:Crossref | GoogleScholarGoogle Scholar |
Kim, H. J., and Kim, Y. H., 2011, A unified transformation function for lower and upper bounding constraints on model parameters in electrical and electromagnetic inversion: Journal of Geophysics and Engineering, 8, 21–26
| A unified transformation function for lower and upper bounding constraints on model parameters in electrical and electromagnetic inversion:Crossref | GoogleScholarGoogle Scholar |
Lee, K. H., and Morrison, H. F., 1985, A numerical solution for the electromagnetic scattering by a two-dimensional inhomogeneity: Geophysics, 50, 466–472
| A numerical solution for the electromagnetic scattering by a two-dimensional inhomogeneity:Crossref | GoogleScholarGoogle Scholar |
Li, Y., and Key, K., 2007, 2D marine controlled-source electromagnetic modeling: part 1 — an adaptive finite-element algorithm: Geophysics, 72, WA51–WA62
Li, Y., and Oldenburg, D. W., 2000, Incorporating geological dip information into geophysical inversions: Geophysics, 65, 148–157
| Incorporating geological dip information into geophysical inversions:Crossref | GoogleScholarGoogle Scholar |
McGillivray, P. R., Oldenburg, D. W., Ellis, R. G., and Habashy, T. M., 1994, Calculation of sensitivities for the frequency-domain electromagnetic problem: Geophysical Journal International, 116, 1–4
| Calculation of sensitivities for the frequency-domain electromagnetic problem:Crossref | GoogleScholarGoogle Scholar |
Mittet, R., and Morten, J., 2012, Detection and imaging sensitivity of the marine CSEM method: Geophysics, 77, E411–E425
| Detection and imaging sensitivity of the marine CSEM method:Crossref | GoogleScholarGoogle Scholar |
Nakatsuka, Y., Xue, Z., Garcia, H., and Matsuoka, T., 2010, Experimental study on CO2 monitoring and quantification of stored CO2 in saline formations using resistivity measurements: International Journal of Greenhouse Gas Control, 4, 209–216
| Experimental study on CO2 monitoring and quantification of stored CO2 in saline formations using resistivity measurements:Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXls1Cns74%3D&md5=a7dbe93f0c901c5c43364680b8a20ca1CAS |
Newman, G. A., Commer, M., and Carazzone, J. J., 2010, Imaging CSEM data in the presence of electrical anisotropy: Geophysics, 75, F51–F61
| Imaging CSEM data in the presence of electrical anisotropy:Crossref | GoogleScholarGoogle Scholar |
Sasaki, Y., 1989, Two-dimensional joint inversion of magnetotelluric and dipole-dipole resistivity data: Geophysics, 54, 254–262
| Two-dimensional joint inversion of magnetotelluric and dipole-dipole resistivity data:Crossref | GoogleScholarGoogle Scholar |
Sasaki, Y., 2011, Anisotropic, joint 3D inversion of marine CSEM and MT data: SEG Technical Program Expanded Abstracts, 30, 547–551.
Song, H., Seol, S. J., and Byun, J., 2010, 2D prestack generalized-screen migration: Mulli-Tamsa, 13, 315–332
Stoyer, C. H., and Greenfield, R. J., 1976, Numerical solutions of the response of a two-dimensional earth to an oscillating magnetic dipole source: Geophysics, 41, 519–530
| Numerical solutions of the response of a two-dimensional earth to an oscillating magnetic dipole source:Crossref | GoogleScholarGoogle Scholar |
Tikhonov, A. N., and Arsenin, V. Y., 1977, Solutions of ill-posed problems: Winston and Sons.