1887
ASEG2013 - 23rd Geophysical Conference
  • ISSN: 2202-0586
  • E-ISSN:

Abstract

A reversible-jump Markov chain Monte Carlo inversion is used to generate an ensemble of millions of models that fit the forward response of a geoelectric target. Statistical properties of the ensemble are then used to assess the resolving power of the AEM system.

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/content/journals/10.1071/ASEG2013ab227
2013-12-01
2026-01-23
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References

  1. Bodin, T., and Sambridge, M., 2009, Seismic tomography with the reversible jump algorithm. Geophysical Journal International 178, 1411-36.
  2. Brodie, R., and Reid, J., E., 2013, Monte Carlo Inversion of SkyTEM AEM data from Lake Thetis, Western Australia: 23 rd International Geophysical Conference and Exhibition, Australian Society of Exploration Geophysicists, Extended Abstracts.
  3. Brodie, R., and Sambridge, M., 2012, Transdimensional Monte Carlo Inversion of AEM Data: 22nd International Geophysical Conference and Exhibition, Australian Society of Exploration Geophysicists, Extended Abstracts.
  4. Green, P.J., 1995, Reversible jump MCMC computation and Bayesian model selection. Biometrika 82, 711-32.
  5. Malinverno, A., 2002, Parsimonious Bayesian Markov chain Monte Carlo inversion in a nonlinear geophysical problem. Geophysical Journal International 151, 675-88.
  6. Minsley, B.J., 2011, A trans-dimensional Bayesian Markov chain Monte Carlo algorithm for model assessment using frequency-domain electromagnetic data. Geophysical Journal International 187, 252-72.
/content/journals/10.1071/ASEG2013ab227
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  • Article Type: Research Article
Keyword(s): AEM; inversion; Monte Carlo; resolvability
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