Entropy QC for Bayesian facies estimations

We use the concepts of entropy and information theory to design a confidence measure for Bayesian facies estimations. Bayesian analyses provide the probabilities of occurrence of each constituent facies in a set. The entropy analysis uses all of these to establish a Confidence Index describing the reliability that the most-probable facies is in fact a clear best choice. We apply these ideas to various facies estimates from Gulf of Mexico inversions.