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http://dx.doi.org/10.7582/GGE.2018.21.1.015

Petrophysical Joint Inversion of Seismic and Electromagnetic Data  

Yu, Jeongmin (Department of Earth Resources and Environmental Engineering, Hanyang University)
Byun, Joongmoo (Department of Earth Resources and Environmental Engineering, Hanyang University)
Seol, Soon Jee (Department of Earth Resources and Environmental Engineering, Hanyang University)
Publication Information
Geophysics and Geophysical Exploration / v.21, no.1, 2018 , pp. 15-25 More about this Journal
Abstract
Seismic inversion is a high-resolution tool to delineate the subsurface structures which may contain oil or gas. On the other hand, marine controlled-source electromagnetic (mCSEM) inversion can be a direct tool to indicate hydrocarbon. Thus, the joint inversion using both EM and seismic data together not only reduces the uncertainties but also takes advantage of both data simultaneously. In this paper, we have developed a simultaneous joint inversion approach for the direct estimation of reservoir petrophysical parameters, by linking electromagnetic and seismic data through rock physics model. A cross-gradient constraint is used to enhance the resolution of the inversion image and the maximum likelihood principle is applied to the relative weighting factor which controls the balance between two disparate data. By applying the developed algorithm to the synthetic model simulating the simplified gas field, we could confirm that the high-resolution images of petrophysical parameters can be obtained. However, from the other test using the synthetic model simulating an anticline reservoir, we noticed that the joint inversion produced different images depending on the model constraint used. Therefore, we modified the algorithm which has different model weighting matrix depending on the type of model parameters. Smoothness constraint and Marquardt-Levenberg constraint were applied to the water-saturation and porosity, respectively. When the improved algorithm is applied to the anticline model again, reliable porosity and water-saturation of reservoir were obtained. The inversion results indicate that the developed joint inversion algorithm can be contributed to the calculation of the accurate oil and gas reserves directly.
Keywords
Simultaneous joint inversion; Cross-gradient; Rock physics model; Relative weighting factor; Porosity; Water-saturation;
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