复电阻率法二维数据空间反演并行算法研究（英文）

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Bibliographic Details
Published in应用地球物理：英文版 Vol. 13; no. 1; pp. 13 - 24
Main Author 张志勇 谭捍东 王堃鹏 林昌洪 张斌 谢茂笔
Format Journal Article
LanguageEnglish
Published 2016
Subjects
Cole-Cole模型
MPI并行计算
二维反演
复电阻率
数据空间
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ISSN1672-7975
1993-0658

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Bibliography:Zhang Zhi-Yongl,,Tan Han-Dong,,Wang Kun-Peng,,Lin Chang-Hong,,Zhang Bin,and Xie Mao-Bi,（1. School of Geophysics and Information Technology, China University of Geosciences, Beijing 100083, China. 2. Key Laboratory of Geo-detection（China University of Geosciences, Beijing）, Ministry of Education, Beijing 100083, China. 3. China Non-ferrous Metals Resource Geological Survey, Beijing 100012, China.）
Traditional two-dimensional（2D） complex resistivity forward modeling is based on Poisson＇s equation but spectral induced polarization（SIP） data are the coproducts of the induced polarization（IP） and the electromagnetic induction（EMI） effects.This is especially true under high frequencies,where the EMI effect can exceed the IP effect.2D inversion that only considers the IP effect reduces the reliability of the inversion data.In this paper,we derive differential equations using Maxwell＇s equations.With the introduction of the Cole-Cole model,we use the finite-element method to conduct2 D SIP forward modeling that considers the EMI and IP effects simultaneously.The data-space Occam method,in which different constraints to the model smoothness and parametric boundaries are introduced,is then used to simultaneously obtain the four parameters of the Cole-Cole model using multi-array electric field data.This approach not only improves the stability of the inversion but also significantly reduces the solution ambiguity.To improve the computational efficiency,message passing interface programming was used to accelerate the 2D SIP forward modeling and inversion.Synthetic datasets were tested using both serial and parallel algorithms,and the tests suggest that the proposed parallel algorithm is robust and efficient.
11-5212/O
Spectral induced polarization; 2D inversion; data-space method; Cole-Cole model; MPI parallel computation
ISSN:1672-7975
1993-0658