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International Journal of Geophysics
Volume 2013 (2013), Article ID 531473, 7 pages
Research Article

Thin-Sheet Inversion Modeling of Geomagnetic Deep Sounding Data Using MCMC Algorithm

1Faculty of Mining and Petroleum Engineering, Bandung Institute of Technology, Jalan Ganesha 10, Bandung 40132, Indonesia
2Centre d’Etude de l’Environnement Terrestre et Planétaires, 3 avenue de Neptune, 94107 Saint-Maur-des-Fosses, France
3Laboratoire d’Analyse et de Mathématique Appliquée, Université de Marne la Vallée, 5 boulevard Descartes, 77454 Marne-la-Vallée, France

Received 31 May 2013; Accepted 18 September 2013

Academic Editor: Vincenzo Lapenna

Copyright © 2013 Hendra Grandis et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The geomagnetic deep sounding (GDS) method is one of electromagnetic (EM) methods in geophysics that allows the estimation of the subsurface electrical conductivity distribution. This paper presents the inversion modeling of GDS data employing Markov Chain Monte Carlo (MCMC) algorithm to evaluate the marginal posterior probability of the model parameters. We used thin-sheet model to represent quasi-3D conductivity variations in the heterogeneous subsurface. The algorithm was applied to invert field GDS data from the zone covering an area that spans from eastern margin of the Bohemian Massif to the West Carpathians in Europe. Conductivity anomalies obtained from this study confirm the well-known large-scale tectonic setting of the area.