Estimating spatial distributions of heterogeneous subsurface characteristics by regionalized classification of electrofacies |
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Authors: | Gerilynn R. Moline and Jean M. Bahr |
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Affiliation: | (1) Environmental Sciences Division, Oak Ridge National Laboratory, P.O. Box 2008, 37831-6036 Oak Ridge, Tennessee;(2) Department of Geology and Geophysics, University of Wisconsin-Madison, 1215 W. Dayton, 53706 Madison, Wisconsin |
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Abstract: | Regionalized classification of electrofacies utilizes the statistical relationships between laboratory determined hydrologic properties and field-measured geophysical properties to estimate spatial distributions of porosity, permeability, and diagenetic characteristics. The method, illustrated with an application to the St. Peter Sandstone in the Michigan basin, combines techniques for multivariate analysis and spatial estimation. Core plug and borehole geophysical data are clustered into electrofacies that reflect the hydrologic properties and diagenetic characteristics of the formation. Electrofacies characteristics then are used to assign a class membership probability at locations where only geophysical data are available. Three-dimensional estimation of electrofacies occurrence is done by kriging datasets containing the probability of electrofacies membership at borehole locations. The discretization and kriging geometry allow three-dimensional estimation of hydrologic parameters for a large region that incorporates meter-scale heterogeneity. Finally, permeability and porosity are estimated at each grid location by probability-weighting. Because the electrofacies carry information about both the hydrologic and lithologic properties, the resulting spatial distributions provide an understanding of both the present-day flow characteristics and the extent of processes that control them.Managed by Martin Marietta Energy Systems. Inc., under contract DE-AC05-84OR21400 with the U.S. Department of Energy); Publication No. 4371, Environmental Sciences Division, ORNL. |
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Keywords: | electrofacies kriging classification regionalization geostatistics |
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