Journal of Jilin University(Earth Science Edition) ›› 2019, Vol. 49 ›› Issue (2): 578-590.doi: 10.13278/j.cnki.jjuese.20180009

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Field Continuation for MCSEM Forward Modeling and Identification of Anisotropic Media

Zhang Wenqiang, Yin Changchun, Liu Yunhe, Zhang Bo, Ren Xiuyan   

  1. College of GeoExploration Science and Technology, Jilin University, Changchun 130026, China
  • Received:2018-01-15 Online:2019-03-26 Published:2019-03-28
  • Supported by:
    Supported by Key Project of National Key R & D Program of China (2018YFC0603300, 2016YFC0303100, 2017YFC0601903), National Natural Science Foundation of China (41530320, 41774125), and Strategic Priority Research Program of Chinese Academy of Sciences (XDA14020102)

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Abstract: Marine controlled-source electromagnetic (MCSEM) has been widely used in offshore hydrocarbon exploration in recent years. Huge drilling cost has been saved because of its high sensitivity to resistive oil reservoirs. The ocean sedimentary environment creates strong stratification and anisotropy in submarine media. Thus, the modeling for MCSEM needs to be made for anisotropic media. In this study, we solved the problem of electromagnetic (EM) field in wavenumber domain by introducing two scalar potentials that are continued upwards and downwards based on the continuation conditions of EM field and coupled to transmitting source at the location of transmitting dipole. The EM field in the space domain was calculated by using Hankel Transform. Through the analysis of anisotropic characteristics, we found that the anisotropy has a great influence on the responses of MCSEM, and only the vertical resistivity and the thickness have an influence on the responses of MCSEM for the resistive reservoir. We set up a procedure to distinguish the earth's anisotropy from the polar plots of marine apparent resistivity. This study lays a foundation for the inversion and interpretation of marine EM data.

Key words: marine CSEM, electrical anisotropy, forward modeling, apparent resistivity, anisotropic identification

CLC Number: 

  • P631.3
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