Geostatistical simultaneous facies inversion based on the Bayesian inference method is presented. Recent debate on the topic has been focused on the one-step versus the two-step approach. Here we side-step this topic by investigating and discussing the trace-by-trace versus the spatial full 3D inversion method. Experiments are done to compare several variations of trace-by-trace with no lateral conditioning, trace-by-trace with lateral conditioning and full 3D methods with lateral conditioning. Conditioning is based on either exponential or Gaussian variograms. With several QCs it is shown that quality of results improves going from trace-by-trace to full 3D inversion. Likewise quality of results improves going from conditioning based on exponential variograms to conditioning based on Gaussian variograms. The full 3D method with lateral conditioning based on Gaussian variograms beats the other schemes with respect to the look and feel and statistics of the facies realizations.


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