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Play-scale 3-D Modeling and Novel Risk Ranking Concepts for Developing Unconventional Assets


Vertical and spatial heterogeneity are attributed to be major controls on unconventional mudrock reservoir behavior. Success is determined by not only reservoir quality, but also drilling and completion quality. Geoscientists are challenged in characterizing unconventional petroleum systems and hydraulic fracture barriers with the existing 2D solutions. Zonal 2D maps are limited by averaging, and detailed facies model approaches are constrained by project scale, scope of effort, and calibration data density. These challenges are amplified in plays with multiple horizontal wellbore landing horizons, where target selection may not be consistent area to area. This paper presents a new scalable tool suite to efficiently predict spatial heterogeneity and rank landing zones and asset-scale well placement using existing 3D geomodeling technologies. The 3D assessment workflow is structured to characterize relevant production drivers including reservoir quality, charge access, and completion quality with quantitative property models. A measurement-calibrated 3D geomodel maximizes data investment value by quantifying spatial variation of reservoir and completion quality. Asset and well-scale ranking are implemented by incorporating risk mapping elements on a grid cell and proximity basis. Reservoir and completion quality risks are defined independently for a given play by a desired set of conditions. The superposition of desired conditions at the geocellular level integrates the concepts of reservoir and completion quality into spatial rank that provides a technical basis for decisions. The 3D modeling and ranking workflow increases efficiencies for evaluation and operations teams. Production driver property models represent the statistical variation of measurements and the uncertainty is quantifiable. The software technology ensures that the process is rapidly repeatable and efficiently incorporates new calibration data within the drilling cycle. Decisions regarding well placement, target selection, and resource deployment are founded on an integrated multidiscipline and technical basis enabling consistent implementation of optimization evaluation and design results.