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AbstractReservoir compartmentalization and flow barriers such as sealing faults or continuous low permeability trends can have a significant impact on the field development strategy. Identifying the location and spatial distribution of such barriers will be critical to optimizing infill well locations, particularly in the early stages of field development with limited well data.Recent advances in streamline modeling allows us to compute drainage volumes during primary production using a 'diffusive' or 'pressure' time of flight during streamline simulation. We propose a novel approach that utilizes the streamline-based drainage volume computations to infer reservoir compartmentalization during primary production. Our approach consists of two steps. First, we perform a traditional decline type curve analysis of the primary production data to identify well communications and estimate the drainage volume of individual wells. Second, starting with a geological model the drainage volumes of each well are recomputed using a streamline-based flow simulation. Finally, reservoir compartmentalization and flow barriers are inferred through a matching of the streamline-based drainage volumes with those from the decline curve analysis. Our approach is completely general and can be applied to reservoirs in the early stages of field development and with very few wells. It relies on commonly available data, that is, primary production and bottom-hole pressure data. Also, the results are relatively insensitive to the fine-scale heterogeneity that can be difficult to characterize.We demonstrate the power and utility of our proposed method using synthetic and field examples. The synthetic examples validate the approach and include a 3D compartmentalized reservoir with multiple wells. The field example is from a field in the Gulf of Mexico. Starting with a reservoir model based on well log and seismic data, reservoir compartmentalization and flow barriers are identified from three years of primary production response. The results are verified via performance forecasting and subsequently utilized to optimize field development and infill well locations.
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