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Centre for Mathematical Physics and Stochastics
Department of Mathematical Sciences, University of Aarhus

Funded by The Danish National Research Foundation

MPS-RR 2001-22
July 2001

Bayesian inversion of geoelectrical resistivity data


Martin Bøgsted Hansen

Kim E. Andersen, Stephen P. Brooks


Enormous quantities of geoelectrical data are produced on a daily basis, and often used for large-scale reservoir modelling. Interpretation of these data requires reliable and efficient inversion methods which adequately incorporate prior information and use realistically complex modelling structures. In this paper we use random coloured polygonal models as a powerful and flexible modelling framework for the layered composition of the Earth and we contrast our approach with earlier methods based upon smooth Gaussian fields. We demonstrate how the reconstruction algorithm may be efficiently implemented through the use of multigrid Metropolis-coupled Markov chain Monte Carlo and illustrate the method on a set of field data.

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This paper has now been published in Submitted.