The scale consistent reservoir modeling scenario presented in the abstract aims to build reservoir models that are scale consistent and honor the data at different scales. The basic idea is to construct a large model by integrating all available data, and then downscaling or upscaling to different scales for different modeling purposes. The downscaling must exactly honor the large scale model to ensure models consistency. There are three major steps: (1) construct a large scale model over the entire lease by integrating multivariate information; Gaussian-based Bayesian Updating technique can be used; local uncertainty assessment is provided, (2) perform petroleum resource estimation with global uncertainty assessment from the large scale model; a spatial/multivariate simulation approach can be used to account for the spatial and multivariate correlations among the local uncertainties, (3) construct fine scale 3-D models of heterogeneity that are consistent with the large scale model and well data using the exact downscaling techniques.<br>This modeling scenario is developed from the oil sands geostatistical modeling project for the Surmont lease, Alberta, Canada. A case study of the modeling techniques in Surmont will be presented. <br>


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