In 1992, there was a collaborative effort in reservoir geophysics involving Amoco, Conoco, Schlumberger and Stanford University in an attempt to delineate variations in reservoir properties of the Grayburg unit in a West Texas CO 2 pilot at North Cowden field. Our objective was to go beyond traveltime tomography in characterizing reservoir heterogeneity and flow anisotropy. This effort involved a comprehensive set of measurements to do traveltime tomography, reflector imaging, analysis of channel waves, shear wave splitting for borehole stress estimation, seismic anisotropy, combined with 3D surface seismic and sonic log interpretation. Results are to be validated with cores and engineering data by history matching of primary, water and CO 2 injection performance. The implementation of these procedures should provide critical information on reservoir 229 heterogeneities and preferential flow directions.
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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