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Applied Geophysics

, Volume 13, Issue 1, pp 13–24 | Cite as

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

  • Zhi-Yong Zhang
  • Han-Dong Tan
  • Kun-Peng Wang
  • Chang-Hong Lin
  • Bin Zhang
  • Mao-Bi Xie
Article

Abstract

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.

Keywords

Spectral induced polarization 2D inversion data-space method Cole—Cole model MPI parallel computation 

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Copyright information

© Editorial Office of Applied Geophysics and Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Zhi-Yong Zhang
    • 1
    • 2
  • Han-Dong Tan
    • 1
    • 2
  • Kun-Peng Wang
    • 1
    • 2
  • Chang-Hong Lin
    • 1
    • 2
  • Bin Zhang
    • 3
  • Mao-Bi Xie
    • 1
    • 2
  1. 1.School of Geophysics and Information TechnologyChina University of GeosciencesBeijingChina
  2. 2.Key Laboratory of Geo-detection (China University of Geosciences, Beijing)Ministry of EducationBeijingChina
  3. 3.China Non-ferrous Metals Resource Geological SurveyBeijingChina

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