Geostatistical facies simulation with geometric patterns of a petroleum reservoir

During exploration and pre-feasibility studies of a typical petroleum project many analyses are required to support decision making. Among them is reservoir lithofacies modeling, preferably using uncertainty assessment, which can be carried out with geostatistical simulation. The resulting multiple equally probable facies models can be used, for instance, in flow simulations. This allows assessing uncertainties in reservoir flow behavior during its production lifetime, which is useful for injector and producer well planning. Flow, among other factors, is controlled by elements that act as flow corridors and barriers. Clean sand channels and shale layers are examples of such reservoir elements that have specific geometries. Besides simulating the necessary facies, it is also important to simulate their shapes. Object-based and process-based simulations excel in geometry reproduction, while variogram-based simulations perform very well at data conditioning. Multiple-point geostatistics (MPS) combines both characteristics, consequently it was employed in this study to produce models of a real-world reservoir that are both data adherent and geologically realistic. This work aims at illustrating how subsurface information typically available in petroleum projects can be used with MPS to generate realistic reservoir models. A workflow using the SNESIM algorithm is demonstrated incorporating various sources of information. Results show that complex structures (e.g. channel networks) emerged from a simple model (e.g. single branch) and the reservoir facies models produced with MPS were judged suitable for geometry-sensitive applications such as flow simulations.