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Linking Heterogeneities of Point Bar Deposits to Large Scale Channel Belt Geometry with Computational Stratigraphy


A significant challenge for the petroleum industry is the exploration for and development of reservoirs at great subsurface depths in data-challenged sedimentary basins. Moreover, the rising cost of field development requires accurate forecasts of important reservoir characteristics, such as connectivity, and management of uncertainty at scales finer than seismic data resolution. We simulate relationships between seismic scale channel belt geometry, e.g. rugosity, and sub-seismic scale internal stratigraphic architecture, e.g. point and scroll bar deposits, using a simple but fully physics based forward meandering channel model. We show that some features of channel belt geometry are related to patterns of channel migration processes, and, consequently, are predictive of certain internal architectures of channel deposits. These predictions can be applied to three dimensional seismic images of subsurface channel belts. We show that computational stratigraphy is an effective tool for characterization of reservoir connectivity by bridging large scale, seismically detectable features to their corresponding internal, smaller, sub-seismic scale features.