This paper presents a comprehensive reservoir study performed on a carbonate reservoir located offshore West Africa. Our study uses seismic information with pixel-based geostatistical techniques for the construction of fine-scale geological models. This field has eleven wells in the northern region. The information of the wells reveals that the field comprises some productive areas that have ensured commercial production, however others are less productive. In order to identify those productive areas in undeveloped region, especially southern portion of the reservoir, integration of the 3D seismic information into reservoir descriptions is necessary.

Our approach follows a four-step procedure. First, log data are correlated to core-measured porosity using the Alternating Conditional Expectation (ACE) algorithm. Second, more than 20 seismic attributes are investigated to specify relationships with well porosity. Third, fine-scale geological models are created based on well data and two seismic attributes with the Markov Bayes and cloud transform techniques. Finally, course-scale flow simulation models are generated by a scaleup technique for history matching purposes. An excellent history matching is achieved without any history match tunings. The prediction results obtained from fifty realizations indicate that the development of the southwestern portion is economically feasible.

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