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Refracture Candidate Selection Considering Natural Fracture Orientation in the Near-Fault Damage Zone


A large degree of uncertainty when characterizing natural fracture density and orientation exists in the overall management of unconventional assets. As a result, the understanding and application of natural fracture network characterization in reservoir management has been limited and often contradictory among practitioners. (As a corollary, this uncertainty extends to refracture candidate selection.) For the case of natural fracture plane parallelism with respect to the fault damage zone, the stress field is anticipated to simultaneously drive the formation of faults and fractures within an approximately concurrent time period. Alternatively, fracture plane orthogonality relative to the fault damage zone manifests away from the strongly nonproportional plastic loading zone after the reorientation of the stress-field post-faulting. As a result, value exists in evaluating the natural fracture network considering well placement and subsurface mechanical constraints. An integrated Eagle Ford case study is discussed that leverages: 1) a fault likelihood attribute currently used that spatially characterizes natural fractures considering the existence of sufficient correlation between faulting and natural fracture formation and 2) the petro-elastic modeling (PEM) embedded in a reservoir simulator used to combine dry rock elastic properties with the dynamic determination of changes in saturation. In an integrated workflow, these methods support the model-driven, time-dependent analysis of refracture candidates linking geophysics to reservoir simulation. Typically, the simulated pressure description alone is insufficient to properly characterize refracture candidates because of the diffusive behavior of pressure. Instead, a novel and dimensionless analysis of spatio-temporal saturated elastic properties is used that is more discrete and allows the fine-scale characterization. The combination of fault likelihood and PEM for an integrated, multidisciplinary analysis exploits geophysics in static and dynamic reservoir models to preserve the subsurface description between seismic attributes and flow simulation.