Flow in a reservoir is controlled predominantly by connectivity of permeability extremes, such as those associated with clear sand channels and shale layers. These elements usually feature complex spatial patterns which are difficult to describe with two-point statistics. Furthermore, specific relationships between the facies are often an important factor in reservoir geology, requiring the use of simulation methods capable of reproducing these associations in order to generate reliable reservoir models. In this work, we were able to bestow physical realism to the geostatistical realizations of a reservoir composed by submarine fans. Multiple-point geostatistics (MPS) relies on training images to model the spatial structure of variables. The MPS simulations were conditioned to seismic and geology data and yielded realistic maps of distributary channels within sand lobes interleaved with shale layers. We concluded that MPS enhances data conditioning and uncertainty assessment with reproduction of specific geometry and facies relationships, making it suitable for geometry-sensitive applications like flow simulations.


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