We present an overview of the practical application of the emerging geostatistical approach called multiple-point geostatistics (MPS), with an emphasis on its applications to reservoir modeling in the oil industry. MPS uses quantitative, pixel-based templates, called training images, to help us build geocellular models. MPS differs from traditional variogram-based or object-based geostatistical approaches. MPS has the virtues of being able to honor multiple types of absolute and probabilistic constraints while reproducing the features in the training image. In this paper, we highlight the significance of using training images to drive reservoir modeling, the pros and cons of pixel-based MPS vs. object-based modeling, and the utility of training image catalogs for the MPS workflow. In addition to using MPS at reservoir scales to build facies or petrophysical models, the technique can be used to reconstruct pore-scale features. We believe that within a few years MPS will be a key modeling technique, applicable to multiple scales of geological features.


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