LIU Ling,
YIN ChangChun,
LIU YunHe et al
.2018.Spectral element method for 3D frequency-domain marine controlled-source electromagnetic forward modeling.Chinese Journal Of Geophysics,61(2): 756-766,doi: 10.6038/cjg2018L0308
基于谱元法的频率域三维海洋可控源电磁正演模拟
刘玲, 殷长春, 刘云鹤, 邱长凯, 黄鑫, 张博
吉林大学地球探测科学与技术学院, 长春 130021
Spectral element method for 3D frequency-domain marine controlled-source electromagnetic forward modeling
LIU Ling, YIN ChangChun, LIU YunHe, QIU ChangKai, HUANG Xin, ZHANG Bo
College of Geo-exploration Science and Technology, Jilin University, Changchun, 130021, China
Abstract:Marine controlled-source electromagnetic (MCSEM) method is an important predrill reservoir appraisal method to reduce exploration risk in detecting sub-seafloor hydrocarbon reservoirs. Most 3D forward modelings for MCSEM are based on conventional numerical methods like finite-difference and finite-element method. In this paper, we introduce spectral element method (SEM) based on Gauss-Lobatto-Chebyshev (GLC) polynomials for 3D frequency-domain MCSEM. SEM is an accurate and efficient electromagnetic modeling methods due to its spectral accuracy and exponential convergence. The method combines the flexibility of finite-element method with the accuracy of spectral method by a simple application of spectral method to each element. Staring from the Maxwell's equations, we obtain a vector Helmholtz equation of electric field. Then we use Galerkin weighted residual method to discretize the vector Helmholtz equation, in which the curl-conforming Gauss-Lobatto-Chebyshev (GLC) polynomials are chosen as basis functions. As a kind of high-order complete orthogonal polynomials, the GLC polynomials have the characteristic of exponential convergence with the order and can derive the matrix elements analytically, which improves the modeling accuracy. Finally, we use the direct solver MUMPS to solve the final system of equations to speed up the modeling process. For numerical experiments, we first simulate responses of a 3-layer model and compare our SEM results with open-source software to check the accuracy of our SEM algorithm. After that, we analyze efficiency of SEM by comparing with finite-difference method. Finally, we apply SEM for typical 3D models and analyze the MCSEM responses. Numerical results show that SEM is an efficient and effective method for MSCEM modeling, and it can deliver very accurate results even with coarse meshes.
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