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Proceedings Paper

Genetic algorithm for conductivity imaging of airborne electromagnetic data
Author(s): Neil Pendock
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Paper Abstract

We present a genetic algorithm (GA) for solving an ill-posed inverse problem from exploration geophysics, namely the estimation of a distribution of conductivities from a set of electrical current penetration depths. We formulate the inversion as a Bayesian inference problem and use a GA to efficiently sample the posterior parameter distribution. In particular, the conductivity distribution with maximum entropy relative to the observed data is estimated. The method is illustrated on an airborne electromagnetic data set collected over the Karoo, South Africa.

Paper Details

Date Published: 15 November 1993
PDF: 8 pages
Proc. SPIE 1942, Underground and Obscured Object Imaging and Detection, (15 November 1993); doi: 10.1117/12.160334
Show Author Affiliations
Neil Pendock, Univ. of the Witwatersrand (South Africa)

Published in SPIE Proceedings Vol. 1942:
Underground and Obscured Object Imaging and Detection
Nancy K. Del Grande; Ivan Cindrich; Peter B. Johnson, Editor(s)

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