(1) Kansas Geological Survey, University of Kansas, Lawrence, KS
ABSTRACT: Geostatistical 3D Reservoir Modeling of Mississippian St. Louis Carbonate Reservoir Systems, Kansas
Numerous St. Louis Limestone oolite reservoirs have continued to be discovered and developed across the Hugoton Embayment of southwestern Kansas. In Kansas, upper St. Louis reservoirs contain over 300 million barrels of oil, but the heterogeneous nature of the oolitic reservoirs and other reservoir characteristics contribute to relatively low recovery efficiencies. A 3D reservoir model provides better delineation of external geometry, heterogeneity and spatial continuity within St. Louis oolite reservoirs. The 3D visualization can provide insight into the controls on geometry, distribution, and continuity of flow units in Mississippian oolite shoals.
Stratigraphic surfaces have been interpreted from cores and well logs. Lithofacies described from cores were calibrated to log-defined petrofacies using log curves and a non-parametric discriminant analysis approach in selected St. Louis oolite reservoirs in Southwestern Kansas. With over 200 wells available, an integrated geologic and geostatistical approach was introduced to model the 3D architectural framework, external and internal geometry, rock property distributions within the reservoirs. An object-based stochastic approach was used to build 3D stratigraphic and lithofacies frameworks and model the external geometries of St. Louis oolitic reservoirs. Internal geometries were incorporated by building 3D porosity, permeability and water saturation distribution models using various stochastic simulation methods. Geostatistical models were verified, selected and extracted to upscale for flow simulation study.
Quantitative 3D geostatistical models for St. Louis oolite reservoirs provide a basis for improving reserve evaluation, enhancing production management, and improving understanding of the depositional controls on Mississippian oolitic reservoirs.
AAPG Search and Discovery Article #90026©2004 AAPG Annual Meeting, Dallas, Texas, April 18-21, 2004.