A Microseismic-based Fracture Properties Characterization and Visualization Model for the Selection of Infill Wells in Shale Reservoirs

Abstract Microseismic monitoring is widely applied to detect microseisms touched off by shear slippage on bedding planes or natural fractures in the vicinity of the hydraulic fracture stages being stimulated, characterize full fracture geometry and orientation, fracture complexity and also measure the stimulated reservoir volume (SRV). Microseismic events are recorded by geophones at the surface, near-surface or in monitoring boreholes and their hypocenters are mapped via P and S wave arrival picking and hodogram analysis or seismic imaging technology. Fracturing treatment parameters and events attributes, such as seismic moment, rock rigidity, fluid efficiency, injected fluid volumes, displacement along the slip plane and hypocenter focal mechanism, can be used to measure the fracture geometry and orientation for 3D discrete fracture networks (DFNs) modeling. In the DFNs, every modeled fracture plane shaped by uniformly-spaced point arrays is centered on a microseismic event. All these pointsets are classified to different cells in a geocellular model. Then geocellular cubes with uniform dimension are created in the SRV and event-based fractures are mapped onto each cube. Based on the domain classification methodology, the total intersected fracture polygon area in each SRV cube was calculated for fracture properties (such as fracture intensity, fracture porosity) characterization. Fracture permeability scalar was proposed to capture the unscaled permeability enhancement in 3D geocellular framework. 3D visualization plots would be used to determine the high conductivity zone in the productive SRV, which further helps selecting the optimal position for the infill wells and further enhances the oil and gas recovery.