ENHANCING RECOVERY IN SHALES THROUGH STIMULATION OF PRE-EXISTING FRACTURE NETWORKS

Microseismic monitoring has become an attractive option for tracking hydraulic fracture stimulations because, unlike most other monitoring techniques, it can illuminate the behavior of fractures away from a treatment well. However, in most cases, the potential for microseismics in terms of developing a full picture of the fracture interactions within the reservoir is not fully exploited. Based on the analysis of microseismicity associated with stimulations in naturally fractured shale reservoirs, we illustrate how, using advanced processing of seismic waveforms in seismic moment tensor inversion (SMTI), a pre-existing fracture network responds to stimulation. As well, we can identify: 1) the failure type, such as mixed-mode shear/tensile failure associated with rough fracture surfaces, 2) the fracture connectivity related to the number of intersecting fractures in a volume, 3) the fracture intensity based on the fracture lengths per volume, 4) the fluid flow pathways and enhanced fluid flow volume related to the relative degree of open fractures, and 5) the power law distribution distribution of fracture lengths. We identify that most failures observed are mixed-mode shear-tensile failures, with either crack opening or closure components of failure. The fractures themselves are related to the failure of pre-existing natural fractures rather than the creation of new fractures. Based on the finite sampling (bandwidth limitations), fracture sizes are limited to joint lengths and follow a power law distribution. By examining the spatial and temporal behavior of opening dominated failures, maps of over-lapping zones of potential enhanced fluid flow are identified. In many ways, stress induced fractures during single stages prepared the reservoir for subsequent stages that overall enhance the interconnectivity and complexity of fractures thereby enhancing fluid flow opportunities. We further discuss, how, using SMTI, the microseismic data show that the stimulation program as designed achieved its objectives. Overall, we further suggest that these defined seismic parameters can then be used to refine, validate and constrain geomechanical models used as input to reservoir models and further optimize well and stage spacing to effectively drain a reservoir and provide better defined reserve estimates.