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PIERS Online
Vol. 4
No. 7
2008
pp: 755-760Regularized and Blocky 3D Controlled Source Electromagnetic InversionRene-Edouard Plessix and P. van der Sman doi:10.2529/PIERS071129160624 Downloads: 746 Abstract:Since the interpretation of controlled source electromagnetic (CSEM) data proves challenging in complex geological settings, 3D CSEM anisotropic resistivity imaging problem is formulated as an inverse problem. A least-squares misfit functional is minimized with a quasi-Newton algorithm to cope with the large number of unknowns. Furthermore, model and data weights are applied to speed up the convergence of the non-linear inversion. A-priori information obtained for instance from seismic interpretation can be included either in a blocky inversion, i.e., where the resistivity cube is arameterized with a small number of parameters or with a regularized inversion. Since earth resistivity contrasts can be high and spatially well defined, minimum norm support regularization terms are implemented. Although the blocky inversion proves quite powerful, we show that results can be misleading in complex geological settings. A combination of the blocky and regularized inversions may provide a more robust approach to interpret CSEM imaging results. We illustrate this with a deep-water example.References:1. Ellingsrud, S., T. Eidesmo, S. Johansen, M. C. Sinha, L. M. MacGregor, and S. Constable, "Remote sensing of hydrocarbon layers by seabed logging (SBL): Results from a cruise offshore Angola," The Leading Edge, Vol. 21, 972-982, 2002. 2. Darnet, M., M. C. K. Choo, R.-E. Plessix, M. L. Rosenquist, K. Yip-Cheong, E. Sims, and J. W. K. Voon, "Detecting hydrocarbon reservoir from controlled source electromagnetic (CSEM) data in complex settings: Application to deep water Sabah, Malaysia," Geophysics, Vol. 72, WA97-WA103, 2007. 3. Newman, G. A. and G. M. Hoversten, "Solution strategies for two- and three-dimensional electromagnetic inverse problems," Inverse Problems, Vol. 16, 1357-1375, 2000. 4. Haber, E., "Quasi-Newton methods for large-scale electromagnetic inverse problems," Inverse Problems, Vol. 21, 305-223, 2005. 5. Plessix, R.-E. and P. van der Sman, "3D CSEM modeling and inversion in complex geological settings," Proceedings of the 77th SEG Annual Meeting, 589-592, San-Antonio, USA, September, 2007. 6. Plessix, R.-E. and W. A. Mulder, "Resistivity imaging with controlled-source electromagnetic data M depth and data weighting," Inverse Problems, submitted, 2008. 7. Zhdanov, M. S., Geophysical Inverse Theory and Regularization Problem, Elsevier, 2002. 8. Mulder, W. A., "A multigrid solver for 3D electromagnetic diffusion," Geophysical Prospecting, Vol. 54, 633-649, 2006. |
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