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A new algorithm for SIP parameter estimation from multi-frequency IP data: preliminary results  

Son, Jeong-Sul (Engineering Geophysics Group, Korea Institute of Geoscience and Mineral Resources)
Kim, Jung-Ho (Engineering Geophysics Group, Korea Institute of Geoscience and Mineral Resources)
Yi, Myeong-Jong (Engineering Geophysics Group, Korea Institute of Geoscience and Mineral Resources)
Publication Information
Geophysics and Geophysical Exploration / v.10, no.1, 2007 , pp. 60-68 More about this Journal
Abstract
Conventional analysis of spectral induced polarization (SIP) data consists of measuring impedances over a range of frequencies, followed by spectral analysis to estimate spectral parameters. For the quantitative and accurate estimation of subsurface SIP parameter distribution, however, a sophisticated and stable inversion technique is required. In this study, we have developed a two-step inversion approach to obtain the two-dimensional distribution of SIP parameters. In the first inversion step, all the SIP data measured over a range of frequencies are simultaneously inverted, adopting cross regularisation of model complex resistivities at each frequency. The cross regularisation makes it possible to enhance the noise characteristics of the inversion by imposing a strong assumption, that complex resistivities should show similar characteristics over a range of frequencies. In numerical experiments, we could verify that our inversion approach successfully reduced inversion artefacts. As a second step, we have also developed an inversion algorithm to obtain SIP parameters based on the Cole-Cole model, in which frequency-dependent complex resistivities from the first step are inverted to obtain a two-dimensional distribution of SIP parameters. In numerical tests, the SIP parameter images showed a fairly good match with the exact model, which suggests that SIP imaging can provide a very useful subsurface image to complement resistivity.
Keywords
Cole-Cole model; complex resistivity; cross regularisation; inversion; SIP; SIP parameter;
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1 Borner, F. D., Gruhne, M., and Schon, J. H., 1993, Contamination indications derived from electrical properties in the low frequency range: Geophysical Prospecting 41, 83-93. doi: 10.1111/j.1365- 2478.1993.tb00566.x   DOI
2 deGroot-Hedlin, C., and Constable, S. C., 1990, Occam's inversion to generate smooth, two-dimensional models from magnetotelluric data: Geophysics 55, 1613-1624. doi: 10.1190/1.1442813   DOI
3 Pelton, W. H., Ward, S. H., Hallof, P. G., Sill, W. R., and Nelson, P. H., 1978, Mineral discrimination and removal of inductive coupling with multifrequency IP: Geophysics 43, 588-609. doi: 10.1190/1.1440839   DOI   ScienceOn
4 Routh, P. S., Oldenburg, D. W., and Li, Y., 1998, Regularized inversion of spectral IP parameters from complex resistivity data: 68th Annual International Meeting, Society of Exploration Geophysicists, Expanded Abstracts, 810-813
5 Vanhala, H., Soininen, H., and Kukkonen, I., 1992, Detecting organic chemical contaminants by spectral-induced polarization method in glacial till environment: Geophysics 57, 1014-1017. doi: 10.1190/1.1443312   DOI
6 Weller, A., and B¨orner, F. D., 1996, Measurement of spectral induced polarization for environmental purposes: Environmental Geology 27, 329-334. doi: 10.1007/s002540050066   DOI
7 Yi,M. J., Kim, J. H., and Chung, S. H., 2003, Enhancing the resolving power of least-squares, inversion with active constraint balancing: Geophysics 68, 931-941. doi: 10.1190/1.1581045   DOI   ScienceOn
8 Loke, M. H., Chambers, J. E., and Ogilvy, R. D., 2006, Inversion of 2D Spectral induced polarization imaging data: Geophysical Prospecting 54, 287-301.doi: 10.1111/j.1365-2478.2006.00537.x   DOI   ScienceOn
9 Fink, J. B., McAlister, E. O., Sternberg, B. K., Wieduwilt, W. G., and Ward, S. H. (eds), 1990, Induced Polarization, Society of Exploration Geophysics
10 Kemna, A., Binley, A., Ramirez, A. L., and Daily, W. D., 2000, Complex resistivity tomography for environmental applications: Chemical Engineering Journal 77, 11-18. doi: 10.1016/S1385-8947(99)00135-7   DOI   ScienceOn
11 Kemna, A., Binley, A., and Slater, L., 2004, Crosshole IP imaging for engineering and environmental applications: Geophysics 69, 97-105. doi: 10.1190/1.1649379   DOI   ScienceOn
12 Yuval, and Oldenburg, D. W., 1997, Computation of Cole-Cole parameters from IP data: Geophysics 62, 436-448. doi: 10.1190/1.1444154   DOI   ScienceOn
13 Olhoeft, G. R., 1985, Low-frequency electrical properties: Geophysics 50, 2492-2503. doi: 10.1190/1.1441880   DOI   ScienceOn
14 Yang, J. S., and Kim, H. J., 2004, Estimation of Cole-Cole parameters from multi-frequency IP data: Journal of the Korean Society for Geosystem Engineering 41, 228-234