Stratigraphic Controls on Mississippian Limestone Reservoir Quality Through Integrated Electrofacies Classification and Seismic-Constrained Spatial Statistics, Hardtner Field, South-Central Kansas

Abstract

Generation of accurate electrofacies estimations is in many ways essential for effective reservoir characterization. Classifying electrofacies, especially those constrained to core observations, can elucidate key relationships between depositional environments and reservoir properties. In addition, these relationships require an appropriate understanding of both the vertical and lateral heterogeneity of the deposits of interest. Typical subsurface data, particularly from vertical wells, lacks sufficient spatial constraints on lateral variability. Thus this study uses 3-D seismic attributes of key reservoir lithologies to establish estimates of horizontal lithological variability. The integrated electrofacies classifications and seismic-based spatial statistics are used to analyze the stratigraphic controls on reservoir quality within the Mississippian Limestone. The Mississippian Limestone formed through complex structural, stratigraphic, and diagenetic processes involving subsidence, tectonic uplift leading to periodic subaerial exposure, changes in ocean chemistry, variability inherent with carbonate cyclicity, as well as post-depositional alteration. These geologic complexities have led to significant heterogeneity and compartmentalization within Mississippian mid-continent reservoirs. In the Hardtner field area, the Mississippian Limestone is approximately 350 ft (107 m) thick and is divided into 4 to 5 stacked shoaling-upward cycles. Historically, the most productive interval within this play has been the highly porous, diagenetically altered tripolitic chert. As is evidenced by characteristically low resistivity and high porosity, the tripolite facies (which is frequently associated with the sub-Pennslyvanian unconformity) occurs dominantly near the top of the formation. Stratigraphically lower tripolite intervals are often associated with small-scale high-frequency cycles. Through an integration of several electrofacies classification techniques, including an artificial neural network (ANN) and geostatistical clustering analysis, a “lithofacies log” is produced that predicts lithology and facies based only on the combined signatures of open-hole digital well logs in non-cored wells. Predictive lithology logs and seismic constrained spatial statistics are used to generate 3-D reservoir models that illustrate the stratigraphic control of high-frequency cycles on porosity development.

AAPG Datapages/Search and Discovery Article #90259 ©2016 AAPG Annual Convention and Exhibition, Calgary, Alberta, Canada, June 19-22, 2016