Two-dimensional inversion of spectral induced polarization data using MPI parallel algorithm in data space

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...

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Veröffentlicht in:Applied geophysics Jg. 13; H. 1; S. 13 - 24
Hauptverfasser: Zhang, Zhi-Yong, Tan, Han-Dong, Wang, Kun-Peng, Lin, Chang-Hong, Zhang, Bin, Xie, Mao-Bi
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Beijing Chinese Geophysical Society 01.03.2016
Springer Nature B.V
School of Geophysics and Information Technology, China University of Geosciences, Beijing 100083, China%China Non-ferrous Metals Resource Geological Survey, Beijing 100012, China
Schlagworte:
Algorithms
Differential equations
Earth and Environmental Science
Earth Sciences
Electric resistance
Electromagnetic interference
Finite element analysis
Geophysics
Geophysics/Geodesy
Geotechnical Engineering & Applied Earth Sciences
Induced polarization
Inversions
Mathematical models
Modelling
Polarization
Spectra
Two dimensional
MPI parallel computation
data-space method
2D inversion
Spectral induced polarization
Cole—Cole model
Cole-Cole model
ISSN:1672-7975, 1993-0658
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Zusammenfassung: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 conduct 2D 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.
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ISSN:1672-7975
1993-0658
DOI:10.1007/s11770-016-0530-8