The use of geostatistics is becoming recognized as a standard means of representing reservoir heterogeneity, Geostatistics has enjoyed an extensive use and a fairly well developed theoretical base. This is a little less true of simulated annealing (SA), the form of geostatistics tested here, but it is also a mature technology.

Yet there remains a need to exercise these procedures under actual conditions of nonuniformly sampled data, non-Gaussian distributions and truncated data sets. Providing insights into how to deal with these nonidealities is the objective of this work,

We find that SA estimates are improved when the original data sets are power-transformed. However, SA estimates tend to deviate from the input cumulative distribution function (CDF) because of excessive rejections. This deviation can be corrected by including the CDF into the SA objective function.

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