Inversion of slingram electromagnetic induction data using a Born approximation
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  • journal_title:Geophysics
  • Contributor:Jochen Kamm ; Michael Becken ; Laust B. Pedersen
  • Publisher:Society of Exploration Geophysicists
  • Date:2013-07-01
  • Format:text/html
  • Language:en
  • Identifier:10.1190/geo2012-0484.1
  • journal_abbrev:Geophysics
  • issn:0016-8033
  • volume:78
  • issue:4
  • firstpage:E201
  • section:Electrical and Electromagnetic Methods
摘要

We present an efficient approximate inversion scheme for near-surface loop-loop EM induction data (slingram) that can be applied to obtain 2D or 3D models on a normal desktop computer. Our approach is derived from a volume integral equation formulation with an arbitrarily conductive homogeneous half-space as a background model. The measurements are not required to fulfill the low induction number condition (low frequency and conductivity). The high efficiency of the method is achieved by invoking the Born approximation around a half-space background. The Born approximation renders the forward operator linear. The choice of a homogeneous half-space yields closed form expressions for the required electromagnetic normal fields. It also yields a translationally invariant forward operator, i.e., a highly redundant Jacobian. In connection with the application of a matrix-free conjugate gradient method, this allows for very low memory requirements during the inversion, even in three dimensions. As a consequence of the Born approximation, strong conductive deviations from the background model are underestimated. Highly resistive anomalies are in principle overestimated, but at the same time difficult to resolve with induction methods. In the case of extreme contrasts, our forward model may fail in simultaneously explaining all the data collected. We applied the method to EM34 data from a profile that has been extensively studied with other electromagnetic methods and compare the results. Then, we invert three conductivity maps from the same area in a 3D inversion.

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