3D DC Resistivity Inversion with Topography Based on Regularized Conjugate Gradient Method

During the past decades, we observed a strong interest in 3D DC resistivity inversion and imaging with complex topography. In this paper, we implemented 3D DC resistivity inversion based on regularized conjugate gradient method with FEM. The Fréchet derivative is assembled with the electric potentia...

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Main Authors: Jian-ke Qiang, Xue Han, Shi-kun Dai
Format: Article
Language:English
Published: Hindawi Limited 2013-01-01
Series:International Journal of Geophysics
Online Access:http://dx.doi.org/10.1155/2013/931876
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spelling doaj-169e24c753b04e989179239765250dce2020-11-24T22:59:19ZengHindawi LimitedInternational Journal of Geophysics1687-885X1687-88682013-01-01201310.1155/2013/9318769318763D DC Resistivity Inversion with Topography Based on Regularized Conjugate Gradient MethodJian-ke Qiang0Xue Han1Shi-kun Dai2School of Geosciences and Info-Physics, Central South University, Changsha 410083, ChinaSchool of Geosciences and Info-Physics, Central South University, Changsha 410083, ChinaSchool of Geosciences and Info-Physics, Central South University, Changsha 410083, ChinaDuring the past decades, we observed a strong interest in 3D DC resistivity inversion and imaging with complex topography. In this paper, we implemented 3D DC resistivity inversion based on regularized conjugate gradient method with FEM. The Fréchet derivative is assembled with the electric potential in order to speed up the inversion process based on the reciprocity theorem. In this study, we also analyzed the sensitivity of the electric potential on the earth’s surface to the conductivity in each cell underground and introduced an optimized weighting function to produce new sensitivity matrix. The synthetic model study shows that this optimized weighting function is helpful to improve the resolution of deep anomaly. By incorporating topography into inversion, the artificial anomaly which is actually caused by topography can be eliminated. As a result, this algorithm potentially can be applied to process the DC resistivity data collected in mountain area. Our synthetic model study also shows that the convergence and computation speed are very stable and fast.http://dx.doi.org/10.1155/2013/931876
collection DOAJ
language English
format Article
sources DOAJ
author Jian-ke Qiang
Xue Han
Shi-kun Dai
spellingShingle Jian-ke Qiang
Xue Han
Shi-kun Dai
3D DC Resistivity Inversion with Topography Based on Regularized Conjugate Gradient Method
International Journal of Geophysics
author_facet Jian-ke Qiang
Xue Han
Shi-kun Dai
author_sort Jian-ke Qiang
title 3D DC Resistivity Inversion with Topography Based on Regularized Conjugate Gradient Method
title_short 3D DC Resistivity Inversion with Topography Based on Regularized Conjugate Gradient Method
title_full 3D DC Resistivity Inversion with Topography Based on Regularized Conjugate Gradient Method
title_fullStr 3D DC Resistivity Inversion with Topography Based on Regularized Conjugate Gradient Method
title_full_unstemmed 3D DC Resistivity Inversion with Topography Based on Regularized Conjugate Gradient Method
title_sort 3d dc resistivity inversion with topography based on regularized conjugate gradient method
publisher Hindawi Limited
series International Journal of Geophysics
issn 1687-885X
1687-8868
publishDate 2013-01-01
description During the past decades, we observed a strong interest in 3D DC resistivity inversion and imaging with complex topography. In this paper, we implemented 3D DC resistivity inversion based on regularized conjugate gradient method with FEM. The Fréchet derivative is assembled with the electric potential in order to speed up the inversion process based on the reciprocity theorem. In this study, we also analyzed the sensitivity of the electric potential on the earth’s surface to the conductivity in each cell underground and introduced an optimized weighting function to produce new sensitivity matrix. The synthetic model study shows that this optimized weighting function is helpful to improve the resolution of deep anomaly. By incorporating topography into inversion, the artificial anomaly which is actually caused by topography can be eliminated. As a result, this algorithm potentially can be applied to process the DC resistivity data collected in mountain area. Our synthetic model study also shows that the convergence and computation speed are very stable and fast.
url http://dx.doi.org/10.1155/2013/931876
work_keys_str_mv AT jiankeqiang 3ddcresistivityinversionwithtopographybasedonregularizedconjugategradientmethod
AT xuehan 3ddcresistivityinversionwithtopographybasedonregularizedconjugategradientmethod
AT shikundai 3ddcresistivityinversionwithtopographybasedonregularizedconjugategradientmethod
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