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Reservoir Modeling, OPL 248, Deepwater Nigeria: Facies Characterization, Reservoir Modeling and Performance Prediction of Isolated and Stacked Multi-Story Channel Complexes


McGee, David T., Douglas S. Moore, Gary Wu, David W. Burge, Nathan Geier, ConocoPhillips, Houston, TX


Geoscientists commonly employ high-quality three-dimensional seismic data to reduce deepwater prospect risk. For years, direct hydrocarbon Indicators (DHIs) have addressed hydrocarbon presence, however only more recently have three-dimensional datasets been employed to render detailed images of the subsurface reservoir architecture of deepwater sinuous channel systems. Such architectural understanding, particularly in multi-story deepwater channel complexes, is key to predicting well count and spacing, thus ultimately prospect value.

By combining seismic profile channel interpretation, volume interpretation and analog studies, detailed geocellular models were created for both isolated and stacked multi-story channel complexes. Gross rock volume was defined by interpreting channel complex top and base horizons, defining the reservoir ‘container’. Applying a process model approach, seismic facies analysis was applied to amplitude extractions representative of interpreted discrete architectural zones within the reservoir container. In turn, interpreted facies maps were used for conditioning layers within the geocellular model. Dimensional information for facies objects was recorded from both the three-dimensional seismic volume and from sub­surface and outcrop analogs. Individual facies objects were stochastically placed, heavily conditioned to seismic control, with an overall aim of replicating analog end members. Key uncertainties identified were net to gross and sand object connectivity. Geocellular model­ing ranged results were assigned within the flow simulation process to condition well per­formance, and ultimately, risked pre-drill prospect value was assigned.