Hierarchical object-based stochastic modeling of fluvial reservoirs |
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| Authors: | Clayton V Deutsch and Libing Wang |
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| Institution: | (1) Stanford Center for Reservoir Forecasting, Stanford University, 94305-2220 Stanford, California |
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| Abstract: | This paper describes a novel approach to modeling braided stream fluvial reservoirs. The approach is based on a hierarchical set of coordinate transformations involving relative straingraphic coordinates, translations, rotations, and straightening functions. The emphasis is placed on geologically sound geometric concepts and realistically-attainable conditioning statistics including areal and vertical facies proportions. Modeling proceeds in a hierarchical fashion, that is (1) a stratigraphic coordinate system is established for each reservoir layer, (2) a number of channel complexes are positioned within each layer, and then (3) channels are positioned within each channel complex. The geometric specification of each sand-filled channel within the background of floodplain shales is a marked point process. Each channel is marked with a starting location, size parameters, and sinuosity parameters. We present the hierarchy of eight coordinate transformations, introduce an analytical expression for the channel cross-section shape, describe the simulation algorithm, and demonstrate how the realizations are made to honor local conditioning data from wells and global conditioning data such as areal and vertical proportions. |
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| Keywords: | marked point processes Boolean modeling geostatistical reservoir modeling coordinate transformation data conditioning |
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