TY - JOUR
T1 - Geophysical electromagnetic modeling and evaluation
T2 - A review
AU - Wang, Bochen
AU - Liu, Jianxin
AU - Hu, Xiangping
AU - Liu, Jiawei
AU - Guo, Zhenwei
AU - Xiao, Jianping
N1 - Funding Information:
This research is supported by Basic Science Center Project for National Natural Science Foundation of China (No.72088101, the Theory and Application of Resource and Environment Management in the Digital Economy Era), and it has also been supported by the Natural Science Foundation of China (NSFC) (41804073; 42074171). It is supported by Changsha Municipal Natural Science Foundation (kq2014124). Furthermore, the research got the Grant from the Open Foundation of Key Laboratory of Submarine Geosciences, SOA(KLSG1905). This work was supported in part by Hunan Provincial Natural Science Foundation of China (Grant: 2019JJ40371).
Funding Information:
This research is supported by Basic Science Center Project for National Natural Science Foundation of China (No.72088101, the Theory and Application of Resource and Environment Management in the Digital Economy Era), and it has also been supported by the Natural Science Foundation of China (NSFC) (41804073; 42074171). It is supported by Changsha Municipal Natural Science Foundation (kq2014124). Furthermore, the research got the Grant from the Open Foundation of Key Laboratory of Submarine Geosciences, SOA(KLSG1905). This work was supported in part by Hunan Provincial Natural Science Foundation of China (Grant: 2019JJ40371). Data availability Statement: ?Not Applicable?. This review includes the number of the EM publication could be found by Google.
Publisher Copyright:
© 2021
PY - 2021/11
Y1 - 2021/11
N2 - Electromagnetic forward modeling is the cornerstone of geophysical electromagnetic inversion. During the last 50 years, numerical simulation methods have been rapidly developed and widely used in geophysical area as the computational capacity continued to increase, such as from single-core to the most modern multi-core processing cards. This paper reviews the literature of electromagnetic fields simulation, particularly focusing on the forward modeling methods include finite difference method, finite element method, integral equation method, and several hybrid methods. We also discuss the possibility of deep learning methods for EM modeling. By sorting out the work done by the predecessors, this review briefly introduces the basic principles and traces back the development of these methods. We propose a Qualitative Evaluation Model named STAMP Model and some criterias of qualitative evaluation on these methods will be discussed in this model.
AB - Electromagnetic forward modeling is the cornerstone of geophysical electromagnetic inversion. During the last 50 years, numerical simulation methods have been rapidly developed and widely used in geophysical area as the computational capacity continued to increase, such as from single-core to the most modern multi-core processing cards. This paper reviews the literature of electromagnetic fields simulation, particularly focusing on the forward modeling methods include finite difference method, finite element method, integral equation method, and several hybrid methods. We also discuss the possibility of deep learning methods for EM modeling. By sorting out the work done by the predecessors, this review briefly introduces the basic principles and traces back the development of these methods. We propose a Qualitative Evaluation Model named STAMP Model and some criterias of qualitative evaluation on these methods will be discussed in this model.
KW - Electromagnetic modeling
KW - Finite difference method
KW - Finite element method
KW - Integral equation method
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U2 - 10.1016/j.jappgeo.2021.104438
DO - 10.1016/j.jappgeo.2021.104438
M3 - Review article
AN - SCOPUS:85115614475
SN - 0926-9851
VL - 194
JO - Journal of Applied Geophysics
JF - Journal of Applied Geophysics
M1 - 104438
ER -