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Accelerating the Frequency Domain Controlled-Source Electromagnetic Data Inversion Using Rational Krylov Subspace Algorithm

delete2022-01-01
delete6
PRE
AI
J
Jiren Liu
任政勇 (Zhengyong Ren)
X
Xiao Xiao *
汤井田 (Jingtian Tang)
P
Pinrong Lin
DOI:10.1109/TGRS.2022.3183838delete
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摘要

摘要

En 中文
Controlled-source electromagnetic (CSEM) method is crucial for detecting and locating underground anomalies and structures. However, it is challenging to interpret the field data with multifrequency via 3-D CSEM inversion. To fully excavate and utilize the valuable information of CSEM data at different frequencies, we propose an efficient algorithm for 3-D multifrequency CSEM (MFCSEM) inversion based on rational Krylov (RK) subspace. Within the framework of our algorithm, we first use the three-term Lanczos recursion to construct the RK basis matrix quickly; thus, the fast MFCSEM forward modeling can be realized via the RK approximation. Subsequently, we present a novel cyclic projection and correction (CPC) algorithm to solve the MFCSEM adjoint forward problems. Finally, the nonlinear conjugate gradient (NLCG) method is adopted to seek a solution to this nonlinear inverse problem. We demonstrate the excellent performance of our algorithm by synthetic and field datasets. The inversion results show that our algorithm is computationally efficient, resulting in considerable speedup compared with the conventional method. Our algorithm provides a new idea that would significantly improve the efficiency of MFCSEM inversion.
Keyword:
Mathematical models
Three-dimensional displays
Data models
Sparse matrices
Geology
Electromagnetics
Frequency-domain analysis
3-D inversion
adjoint forward problems
forward modeling
multifrequency controlled-source electromagnetic (MFCSEM)
rational Krylov (RK) subspace method

期刊

IEEE Transactions on Geoscience and Remote Sensing 封面图
IEEE Transactions on Geoscience and Remote Sensing
IF:
8.6
论文数:
2.1W
被引数:
10.7W

机构

C
China Geological Survey
学者数:
8.0K
论文数: 5.6K
被引数: 3.3K
C
Central South University
学者数:
10.0W
论文数: 7.2W
被引数: 10.9W
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