Improvement of accuracy for estimating reservoir properties by Markov-Bayes method using two soft data

Geostatistics has been playing an important role in reservoir characterization and modeling. The principal objective of reservoir characterization is to provide a reservoir model for accurate reservoir performance prediction. To attain this objective, the integration of information from various data sources is an essential task in reservoir characterization. In this study, the geostatistical program that includes the sub-programs for kriging and conditional simulation was coded. Especially, the sub-program for Markov-Bayes simulation that enables the estimation of reservoir property distribution using two soft data was developed. This process is not available in conventional geostatistical software. This paper presents the results of reservoir property distributions estimated by various geostatistical methods and discusses the comparison among them. Through this comparison, the advantage of Markov-Bayes method using two soft data for the improvement of the accuracy for estimating reservoir properties is demonstrated.