3D inversion of large-scale frequency-domain airborne electromagnetic data using unstructured local mesh
3D inversion of large-scale frequency-domain airborne electromagnetic data using unstructured local mesh
复制标题
使用非结构化局部网格对大规模频域机载电磁数据进行 3D 反演
DOI:
10.1190/geo2020-0243.1
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发表时间:
2021-05
期刊:
影响因子:
3.3
通讯作者:
Bin Xiong
中科院分区:
文献类型:
--
作者:
Zhang Bo;Changchun Yin;Yunhe Liu;Xiuyan Ren;Vicas C. Baranwal;Bin Xiong
Airborne electromagnetic (AEM) methods have been more and more widely used in mineral exploration, environmental and engineering studies, and ground water investigation. However, compared with ground-based electromagnetic (EM) methods, such as magnetotelluric or controlled-source EM, AEM methods generally produce large amounts of data, which leads to very costly 3D EM inversions. We have developed a new 3D AEM inversion scheme based on the finite-element method and unstructured tetrahedral local meshes. This is different from the traditional local mesh method in that the traditional method uses regular cuboids for 3D AEM inversions, whereas our scheme uses irregular tetrahedral meshes that can easily accommodate the topography and complex underground structure. Moreover, because we create our local mesh by extracting from part of the global model mesh, the relationship between the local and global meshes is straightforward, so we can easily create a projection of the Jacobian matrix between global and local meshes and rapidly construct the global Jacobian matrix for 3D EM inversions. After formulating the boundary value problem based on the finite-element method, we verify the accuracy of our modeling algorithm by checking against the semianalytical solution for a homogeneous half-space model, and we test our inversion algorithm by running inversions on synthetic and survey data collected over Vesterålen, Norway. The numerical experiments demonstrate that our method can model the AEM responses at high accuracy and recover the subsurface main resistivity structures from synthetic and field data.
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影响因子:
2.8
作者:
Yunhe Liu;Colin G. Farquharson;Changchun Yin;Vikas C. Branwal
通讯作者:
Vikas C. Branwal
影响因子:
3.3
作者:
Dikun Yang;D. Oldenburg
通讯作者:
Dikun Yang;D. Oldenburg
影响因子:
3.3
作者:
Changchun Yin;Bo Zhang;Yunhe Liu;Jing Cai
通讯作者:
Jing Cai
DOI:
10.1190/1.2792464
发表时间:
2007
期刊:
Seg Technical Program Expanded Abstracts
影响因子:
--
作者:
L. Cox;M. Zhdanov
通讯作者:
L. Cox;M. Zhdanov
影响因子:
2.6
作者:
E. Auken;A. Christiansen;B. Jacobsen;N. Foged;K. Sørensen
通讯作者:
E. Auken;A. Christiansen;B. Jacobsen;N. Foged;K. Sørensen