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A Weighting Inversion Method of Spectrum Induced Polarization

Received: 28 December 2018     Accepted: 23 May 2019     Published: 4 July 2019
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Abstract

The inversion results of complex resistivity method are four Cole-Cole model parameters. Among the four parameters, the frequency dependence and the time constant are more difficult to invert. It is necessary to study an algorithm that can invert the four Cole-Cole model parameters at the same time. In this paper, the least squares and OCCAM inversion algorithms are used to invert four Cole-Cole model parameters. In other words, two model constraints are added to the objective function. When inverting different Cole-Cole model parameters, the real and imaginary parts of the data are weighted to adjust the proportion of real part and imaginary part of data in inversion. Firstly, the formula of the algorithm is deduced. Then the theoretical models are designed for inversion trial calculation. In the inversion process, the inversion converges steadily by adjusting the Lagrange factor, and the inversion effect is improved by adjusting the weighting coefficients of real part and imaginary part. This method can get better inversion results by adjusting the proportion of the real and imaginary parts of the data in the inversion. The model trial results show that the weighting inversion algorithm significantly improves the results of the inversion of the four Cole-Cole parameters.

Published in Earth Sciences (Volume 8, Issue 3)
DOI 10.11648/j.earth.20190803.16
Page(s) 178-189
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

Spectral Induced Polarization, Cole–Cole Model Parameters, Occam Inversion, The Least Squares Inversion, Weighting Inversion

References
[1] Ahmad Ghorbani, ChristianCamerlynck, NicolasFlorsch. 2009. CR1Dinv: A Matlab program to invert 1D spetral induced polarization data for the Cole–Cole model including electromagnetic effects. Computers&Geosciences 35 (2009) 255–266.
[2] Brown R J. 1985. EM coupling in multi-frequency IP and a generalization of the Cole-Cole impedancemodel. Geophysical prospecting, 33 (2): 282~302.
[3] Fan C S, Li T L, Yan J Y. 2012. Research and application experiment on 2.5D SIP inversion. Geophys. (in Chinese), 55 (12): 4044-4050.
[4] Ingeman-Nielsen, T, Baumgartner, F. 2006. CR1Dmod: a Matlab program to model 1D complex resistivity effects in electrical and EM surveys. Computers & Geosciences 32, 1411–1419.
[5] Liu B, Li S C, Li S C, et al. 2012. 3D electrical resistivity inversion with least-squares method based on inequality constraint and its computation efficiency optimization. Geophys. (in Chinese), 55 (1): 260-268.
[6] Liu S, Guan S Y, Gao PF. 1994. A polarization inversion method of Cole-Cole parameters of the polarizing sphere. Geophys. (in Chinese), 37 (S2): 542~551.
[7] Liu Y H, Yin C C. 2013. 3D inversion for frequency-domain HEM data. Chinese J. Geophys. (in Chinese), 56 (12): 4278-4287.
[8] Liu Y L, Li T L, Hu Y C, et al. 2015. Fast quasi-linear approximation and the three-dimensional spectrum of induced polarization inversion study. Geophys. (in Chinese), 58 (12): 4709-4717.
[9] Luo Y Z, Fang S. 1986. An approximate method to invert the spectrum of complex resistivity. Earth Science, 11 (1): 93-102.
[10] Major J, Silic J. 1981. Restrictions on the use of Cole-Cole dispersion models in complex resistivity interpretation. Geo- physics, 46 (6): 916~931.
[11] Pelton W H, Ward S H, Hallof P G, et al. 1978. Mineral discrimination and removal of inductive coupling with multifrequency IP. Geophysics, 43 (3): 588~609.
[12] Sunde, E. D. 1968. Earth Conduction Effects in Transmission Systems. Dover, New York, p. 370.
[13] Shang T X. 2008. 1D full-region inversion of CSAMT of bipolar source [Master's Degree Thesis] (in Chinese). Changchun: Jilin University.
[14] Yu L B. 2010. The study of simulation and inversion of 1D spectrum induced polarization method [Master's Degree Thesis] (in Chinese). Changchun: Jilin University.
[15] Zhou F. 2015. 1D and 2.5D Modeling and Inversion of Complex Resistivity Data [Master's Degree Thesis]. East China institute of technology.
[16] Zhang S Z, Li Y X, Zhang S C. 1984. Characteristics and influencing factors of phase in low frequency of rocks (ore) in several metal mining areas in China. Geophys. (in Chinese), 27: 176~189.
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    Wu Yu Hao. (2019). A Weighting Inversion Method of Spectrum Induced Polarization. Earth Sciences, 8(3), 178-189. https://doi.org/10.11648/j.earth.20190803.16

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    Wu Yu Hao. A Weighting Inversion Method of Spectrum Induced Polarization. Earth Sci. 2019, 8(3), 178-189. doi: 10.11648/j.earth.20190803.16

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    Wu Yu Hao. A Weighting Inversion Method of Spectrum Induced Polarization. Earth Sci. 2019;8(3):178-189. doi: 10.11648/j.earth.20190803.16

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  • @article{10.11648/j.earth.20190803.16,
      author = {Wu Yu Hao},
      title = {A Weighting Inversion Method of Spectrum Induced Polarization},
      journal = {Earth Sciences},
      volume = {8},
      number = {3},
      pages = {178-189},
      doi = {10.11648/j.earth.20190803.16},
      url = {https://doi.org/10.11648/j.earth.20190803.16},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.earth.20190803.16},
      abstract = {The inversion results of complex resistivity method are four Cole-Cole model parameters. Among the four parameters, the frequency dependence and the time constant are more difficult to invert. It is necessary to study an algorithm that can invert the four Cole-Cole model parameters at the same time. In this paper, the least squares and OCCAM inversion algorithms are used to invert four Cole-Cole model parameters. In other words, two model constraints are added to the objective function. When inverting different Cole-Cole model parameters, the real and imaginary parts of the data are weighted to adjust the proportion of real part and imaginary part of data in inversion. Firstly, the formula of the algorithm is deduced. Then the theoretical models are designed for inversion trial calculation. In the inversion process, the inversion converges steadily by adjusting the Lagrange factor, and the inversion effect is improved by adjusting the weighting coefficients of real part and imaginary part. This method can get better inversion results by adjusting the proportion of the real and imaginary parts of the data in the inversion. The model trial results show that the weighting inversion algorithm significantly improves the results of the inversion of the four Cole-Cole parameters.},
     year = {2019}
    }
    

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  • TY  - JOUR
    T1  - A Weighting Inversion Method of Spectrum Induced Polarization
    AU  - Wu Yu Hao
    Y1  - 2019/07/04
    PY  - 2019
    N1  - https://doi.org/10.11648/j.earth.20190803.16
    DO  - 10.11648/j.earth.20190803.16
    T2  - Earth Sciences
    JF  - Earth Sciences
    JO  - Earth Sciences
    SP  - 178
    EP  - 189
    PB  - Science Publishing Group
    SN  - 2328-5982
    UR  - https://doi.org/10.11648/j.earth.20190803.16
    AB  - The inversion results of complex resistivity method are four Cole-Cole model parameters. Among the four parameters, the frequency dependence and the time constant are more difficult to invert. It is necessary to study an algorithm that can invert the four Cole-Cole model parameters at the same time. In this paper, the least squares and OCCAM inversion algorithms are used to invert four Cole-Cole model parameters. In other words, two model constraints are added to the objective function. When inverting different Cole-Cole model parameters, the real and imaginary parts of the data are weighted to adjust the proportion of real part and imaginary part of data in inversion. Firstly, the formula of the algorithm is deduced. Then the theoretical models are designed for inversion trial calculation. In the inversion process, the inversion converges steadily by adjusting the Lagrange factor, and the inversion effect is improved by adjusting the weighting coefficients of real part and imaginary part. This method can get better inversion results by adjusting the proportion of the real and imaginary parts of the data in the inversion. The model trial results show that the weighting inversion algorithm significantly improves the results of the inversion of the four Cole-Cole parameters.
    VL  - 8
    IS  - 3
    ER  - 

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Author Information
  • Tianjin Institute of Geotechnical Investigation and Surveying, Tianjin, China

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