2014 Rocky Mountain Section AAPG Annual Meeting

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


Spatial heterogeneity substantially affects mud-rock reservoir behavior. Success is determined by reservoir quality as well as drilling and completion quality. Geoscientists are challenged to characterize unconventional petroleum systems with existing 2D solutions. Zonal maps are limited by averaging, and detailed facies models are constrained by project scale, 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 that efficiently predicts spatial heterogeneity and ranks well placement and landing zones using 3D geomodeling technologies. The 3D assessment workflow characterizes reservoir quality, charge access, and completion quality with quantitative property models. A calibrated 3D geomodel maximizes data investment by quantifying spatial variability. 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 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, providing a technical basis for decisions. The 3D modeling and ranking workflow increases evaluation and operations team efficiencies. Production-driver property models represent the statistical variation of measurements, and uncertainty is quantifiable. The software ensures that the process repeatedly incorporates new calibration data within the drilling cycle. Decisions regarding well placement, target selection, and resource deployment are founded on an integrated, multidisciplinary, technical basis, enabling consistent implementation of optimization evaluation and design results.