Thin-Sheet Inversion Modeling of Geomagnetic Deep Sounding Data Using MCMC Algorithm
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 th...
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | International Journal of Geophysics |
| Online Access: | http://dx.doi.org/10.1155/2013/531473 |
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| _version_ | 1849306184705638400 |
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| author | Hendra Grandis Michel Menvielle Michel Roussignol |
| author_facet | Hendra Grandis Michel Menvielle Michel Roussignol |
| author_sort | Hendra Grandis |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-38c94d2d24424d2e86f25e7db7249ffe |
| institution | Kabale University |
| issn | 1687-885X 1687-8868 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Geophysics |
| spelling | doaj-art-38c94d2d24424d2e86f25e7db7249ffe2025-08-20T03:55:11ZengWileyInternational Journal of Geophysics1687-885X1687-88682013-01-01201310.1155/2013/531473531473Thin-Sheet Inversion Modeling of Geomagnetic Deep Sounding Data Using MCMC AlgorithmHendra Grandis0Michel Menvielle1Michel Roussignol2Faculty of Mining and Petroleum Engineering, Bandung Institute of Technology, Jalan Ganesha 10, Bandung 40132, IndonesiaCentre d’Etude de l’Environnement Terrestre et Planétaires, 3 avenue de Neptune, 94107 Saint-Maur-des-Fosses, FranceLaboratoire d’Analyse et de Mathématique Appliquée, Université de Marne la Vallée, 5 boulevard Descartes, 77454 Marne-la-Vallée, FranceThe 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.http://dx.doi.org/10.1155/2013/531473 |
| spellingShingle | Hendra Grandis Michel Menvielle Michel Roussignol Thin-Sheet Inversion Modeling of Geomagnetic Deep Sounding Data Using MCMC Algorithm International Journal of Geophysics |
| title | Thin-Sheet Inversion Modeling of Geomagnetic Deep Sounding Data Using MCMC Algorithm |
| title_full | Thin-Sheet Inversion Modeling of Geomagnetic Deep Sounding Data Using MCMC Algorithm |
| title_fullStr | Thin-Sheet Inversion Modeling of Geomagnetic Deep Sounding Data Using MCMC Algorithm |
| title_full_unstemmed | Thin-Sheet Inversion Modeling of Geomagnetic Deep Sounding Data Using MCMC Algorithm |
| title_short | Thin-Sheet Inversion Modeling of Geomagnetic Deep Sounding Data Using MCMC Algorithm |
| title_sort | thin sheet inversion modeling of geomagnetic deep sounding data using mcmc algorithm |
| url | http://dx.doi.org/10.1155/2013/531473 |
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