Using Multiple Point Statistics and Facies Distribution Modeling to Understand Flow Behavior in Carbonate Reservoirs

Recently, Chevron developed a workflow combining Multiple Point Statistics (MPS) simulation, a new reservoir facies modeling approach that uses training images to reproduce complex geological patterns, and Facies Distribution Modeling (FDM), an innovative technique that generates facies probability cubes to better constrain the facies spatial distribution in geostatistical models. That workflow is used in this paper to explore the potential impact of architectural and textural parameters on static connectivity and dynamic flow behavior in a grainstone-dominated carbonate reservoir. Using Plackett-Burman experimental design, a variety of parameters were investigated including: proportions of reservoir facies vs. non-reservoir facies, ratio of barflank/barcrest reservoir facies, dimensions of facies geobodies, stratigraphic cyclicity, areal distribution of reservoir facies (distributed across platform vs. localized), porosity histogram, porosity/permeability transform, and dissolution or cemented diagenetic zones. <br><br>Flow simulations were analyzed to assess the impact of the range of the input parameters on different measures of the sub-surface flow. Models were compared on the basis of static measures of OOIP, reservoir connectivity and permeability heterogeneity; and on the basis of dynamic measures of recovery factor vs. time, recovery factor vs. pore volumes injected, net present oil, cumulative oil produced, and water breakthrough time.