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

Detection of Oil-Water Contacts (OWCs) is one of the primary tasks before evaluation of reservoir’s hydrocarbon in place, determining net pay zones and suitable depths for perforation operation. This paper introduces Bayesian decision making tool as an effective technique in OWC detecting using wire line logs. To compare strengths of the suggested method in detecting OWC with conventional one, the same database was used. Proposed method was applied to wire line logs in three wells of a carbonate reservoir in an oil field of the southwestern Iran and its results have been evaluated by well testing results. Results indicate that the usage of Bayesian method in detecting OWC is more accurate than conventional method 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.