Objectives of this Study:
The objectives were to perform a field study to:Evaluate geostatistical techniques to integrate data.Compare reservoir descriptions with and without crosswell tomography data integrated.Determine if reservoir descriptions constrained by synthetic crosswell tomography data reduce uncertainty, compared to reservoir descriptions not constrained by synthetic tomography data. (i.e., Can the uncertainty in reservoir performance be reduced measurably if crosswell tomography is acquired and used as additional data to constrain geostatistical reservoir descriptions?)Compare geostatistical to conventional reservoir descriptions.Assess uncertainty of reservoir performance (cumulative oil production, oil production rate, and water-oil ratio) for primary, secondary and tertiary production.
Overview of the Study:
Geostatistical methods stochastically generate multiple, equally-probable 3-D reservoir descriptions of facies, porosity, and permeability which usedwell log and core data for this study area. Ten of these reservoir descriptions were also constrained by synthetic crosswell tomography data and another ten reservoir descriptions were not constrained by synthetic crosswell tomography data. Each stochastically generated 3-D reservoir description honors the spatial information in the data (including anisotropy), all of the multidisciplinary data, histogram of the data, and likely heterogeneities of the reservoir.
Additionally, a conventional (deterministic) reservoir description using a layer-cake approach was generated assuming reservoir sub-layers with equal average K/, which were combined to create a few vertical layers.
Each of these twenty geostatistical reservoir descriptions and the conventional reservoir description, cited above, were appropriately upscaled and input to a numerical fluid flow simulator to predict future performance(cumulative oil recovery, oil production rate, and water-oil ratio, etc.).
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