3D anisotropic modeling and identification for airborne EM systems based on the spectral-element method

• Published in: Applied geophysics 2017-09, Vol.14 (3), p.419-430
• Main Authors: Huang, Xin, Yin, Chang-Chun, Cao, Xiao-Yue, Liu, Yun-He, Zhang, Bo, Cai, Jing
• Format: Article
• Language: English
• Subjects: Accuracy; Anisotropy; Basis functions; Computer applications; Costs; Earth; Earth and Environmental Science; Earth Sciences; Electrical & Electromagnetic Methods; Electrical resistivity; Finite element method; Galerkin method; Geological structures; Geology; Geophysics/Geodesy; Geotechnical Engineering & Applied Earth Sciences; Half spaces; Identification; Interpolation; Linear equations; Magnetic dipoles; Mathematical analysis; Mathematical models; Modelling; Rocks; Spectra; Spectral element method; Spectral methods; Surveying; Three dimensional models
• ISSN: 1672-7975; 1993-0658
• DOI: 10.1007/s11770-017-0632-y

The airborne electromagnetic (AEM) method has a high sampling rate and survey flexibility. However, traditional numerical modeling approaches must use high-resolution physical grids to guarantee modeling accuracy, especially for complex geological structures such as anisotropic earth. This can lead to huge computational costs. To solve this problem, we propose a spectral-element (SE) method for 3D AEM anisotropic modeling, which combines the advantages of spectral and finite-element methods. Thus, the SE method has accuracy as high as that of the spectral method and the ability to model complex geology inherited from the finite-element method. The SE method can improve the modeling accuracy within discrete grids and reduce the dependence of modeling results on the grids. This helps achieve high-accuracy anisotropic AEM modeling. We first introduced a rotating tensor of anisotropic conductivity to Maxwell’s equations and described the electrical field via SE basis functions based on GLL interpolation polynomials. We used the Galerkin weighted residual method to establish the linear equation system for the SE method, and we took a vertical magnetic dipole as the transmission source for our AEM modeling. We then applied fourth-order SE calculations with coarse physical grids to check the accuracy of our modeling results against a 1D semi-analytical solution for an anisotropic half-space model and verified the high accuracy of the SE. Moreover, we conducted AEM modeling for different anisotropic 3D abnormal bodies using two physical grid scales and three orders of SE to obtain the convergence conditions for different anisotropic abnormal bodies. Finally, we studied the identification of anisotropy for single anisotropic abnormal bodies, anisotropic surrounding rock, and single anisotropic abnormal body embedded in an anisotropic surrounding rock. This approach will play a key role in the inversion and interpretation of AEM data collected in regions with anisotropic geology.