Application of Bayesian decision making tool in detecting oil-water contact in a carbonate reservoir

Abstract

Defining Oil-Water Contact (OWC) is essential for detail petrophysical evaluations and reservoir volumetric calculations. This paper presents Bayesian decision making tool as a sophisticated technique in OWC detecting from well log data. The proposed method is applied to data related to three wells of an oil field of the Southwestern Iran. The method’s performance is evaluated based on well testing reports and also through comparisons with the results of conventional approach based on permeability prediction. Results indicate that the proposed method is more accurate than conventional approach and may improve the results about 5% on average. In addition, using this method, any variation of water saturation (Sw) log and reservoir fluid types may be detectable.