METHODOLOGY FOR RESOURCE ASSESSMENT OF THE UTICA SHALE OIL AND GAS PLAY, APPALACHIAN BASIN
The volumetric approach enabled assessment of resource potential from fundamental geologic data independent of development practice, well performance, economics and the limited geographic extent of exploratory activity that often characterize early stages of a hydrocarbon play. The approach was applied to individual wells from which summary data were gridded to estimate in-place resources for each of the Utica Shale, Point Pleasant Formation and Logana Member of the Trenton Limestone. Study wells were selected based on availability and quality of well log data, well location and orientation, structural complexity, reservoir depth and proximity to other wells. Petrophysical data provided the foundation for the assessment while additional input parameters included: thermal maturity, total organic carbon, gas content, pressure and temperature.
Parameters for calculating technically recoverable unconventional resources were: area of each AU, areas of sweet spots and non-sweet spots within each AU, drainage area per well, percentages of AU untested and of untested area in sweet spots, success ratios and estimated ultimate recoveries for both sweet spot and non-sweet spot areas and co-product ratios. For each parameter, the geologist provided estimates of expected minimum, maximum and average or mode. A Monte Carlo procedure yielded F5, F50 (Median), F95 and average volumes of oil and gas in each AU. These figures were compared with results of volumetric calculations as a check for the robustness of parameters and the geologic model.
The Utica assessment complements a West Virginia-specific Marcellus Shale assessment conducted in 2013. Insights gained from these two projects could be applied to the possible next frontier of shale development in the basin, the Rogersville Shale. Assessment of the Rogersville, however, will require greater understanding of the complex structure of this unit and may be limited by a paucity of deep well data in the region.