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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Series: | International Journal of Geophysics |
Online Access: | http://dx.doi.org/10.1155/2013/931876 |
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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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