1887
1st Australasian Exploration Geoscience Conference – Exploration Innovation Integration
  • ISSN: 2202-0586
  • E-ISSN:

Abstract

Three-dimensional controlled-source electromagnetic (CSEM) surveys can be a useful technique for oil and gas hydrate detection in marine environments. Electromagnetic waves are emitted from sources, and the ensuing electric and/or magnetic fields are recorded at one, or more receivers. The number, frequency, and position of sources and the placement of receivers depends on the particular application. The solution of an inverse problem is required to recover the earth’s conductivity, which can be either isotropic or anisotropic in nature.

A major issue with either an isotropic or anisotropic CSEM inversion is the computational cost associated with the solution of many linear systems of equations. This is a result of a large spatial domain potentially containing complicated bathymetry, as well as the existence of thousands of source and frequency combinations. Overall, there could be thousands or even millions of systems of equations to solve on expansive meshes. To assist with these numerical issues, we use ideas developed for airborne electromagnetic inversions. First, we incorporate a locally refined mesh for the forward problem, specifically optimized for a source and set of receivers. Second, we use stochastic programming techniques to solve the CSEM problem with many sources and receivers. These methods dramatically reduce the numerical cost of each forward model as well as the total number of simulations. In this work we describe the methods used to overcome these computational difficulties.

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/content/journals/10.1071/ASEG2018abP071
2018-12-01
2026-01-13
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References

  1. Haber, E. and Schwarzbach, C., 2014, Parallel inversion of large-scale airborne time-domain electromagnetic data with multiple OcTree meshes: Inverse Problems, 30(5), 1-28.
  2. Newman, G.A., Commer, M. and Carazzone, J.J., 2010, Imaging CSEM data in the presence of electrical anisotropy: Geophysics, 75(2), P51-P61.
  3. Ruszczynski, A. and Shapiro, A., 2003, Stochastic programming. Amsterdam: Elsevier.
  4. Schwarzbach, C., Haber, E. and Columbia, B., 2011, Finite element based inversion for electromagnetic problems using stochastic optimization: 81st Annual International Meeting, SEG, Expanded Abstracts, 30, 567-572.
/content/journals/10.1071/ASEG2018abP071
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  • Article Type: Research Article
Keyword(s): Electromagnetics; Inversion; Marine
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