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ISSN  2096-3955

CN  10-1502/P

Citation: XiaoZhong Tong, JianXin Liu, AiYong Li, 2018: Two-dimensional regularized inversion of AMT data based on rotation invariant of Central impedance tensor, Earth and Planetary Physics, 2, 430-437. doi: 10.26464/epp2018040

2018, 2(5): 430-437. doi: 10.26464/epp2018040


Two-dimensional regularized inversion of AMT data based on rotation invariant of Central impedance tensor


Key Laboratory of Metallogenic Prediction of Nonferrous Metals of Ministry of Education, Central South University, Changsha 410083, China


School of Geosciences and Info-physics, Central South University, Changsha 410083, China


Eastern China Bureau of Nonferrous Geological Exploration, Nanjing 210007, China

Corresponding author: XiaoZhong Tong,

Received Date: 2018-06-12
Web Publishing Date: 2018-09-01

Considering the uncertainty of the electrical axis for two-dimensional audo-magnetotelluric (AMT) data processing, an AMT inversion method with the Central impedance tensor was presented. First, we present a calculation expression of the Central impedance tensor in AMT, which can be considered as the arithmetic mean of TE-polarization mode and TM-polarization mode in the two-dimensional geo-electrical model. Second, a least-squares iterative inversion algorithm is established, based on a smoothness-constrained model, and an improved L-curve method is adopted to determine the best regularization parameters. We then test the above inversion method with synthetic data and field data. The test results show that this two-dimensional AMT inversion scheme for the responses of Central impedance is effective and can reconstruct reasonable two-dimensional subsurface resistivity structures. We conclude that the Central impedance tensor is a useful tool for two-dimensional inversion of AMT data.

Key words: audio-magnetotelluric/AMT; impedance tensor; rotation invariants; two-dimensional geo-electrical model; regularized inversion

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Two-dimensional regularized inversion of AMT data based on rotation invariant of Central impedance tensor

XiaoZhong Tong, JianXin Liu, AiYong Li