Utilizing microseismicity to define stimulated surface area and effective permeability
The appropriateness of hydraulic fracture stimulation designs can have a significant impact on stimulation effectiveness and the potential productivity of a reservoir. Frac model designs are based on an integration of static (formation geology, velocity structure) and dynamic (bottomhole flowing pressure-normalized oil and gas production, Diagnostic Fracture Injection Testing (DFIT)) data streams. Further constraint on model development can be provided by including additional parameters recorded either prior to or during stimulations. In this regard microseismic monitoring has long been considered as a tool to provide insight into the nature of the stimulation and the effectiveness in developing a well-connected fracture network capable of flow. Most attempts at utilizing microseismic data have been shown to be ineffective in terms of defining the Stimulated Reservoir Volume (SRV). The approaches have focused on the distribution of seismicity and, in some instances, the relative magnitude of the events. In general, this simplistic approach has resulted in an over-estimation of the SRV that far exceeds actual well production. In going to a more fundamental description of microseismic events, we can consider that each event is related to a fracture, pre-existing or newly generated, that uniquely ruptures depending on local stress and geologic conditions. Utilizing well-defined models of earthquake rupture, it is possible to obtain characteristics of individual failures from the recorded waveforms for sensors distributed around the area of interest. As well as considering the arrival times for the main body wave types to locate events, we can also extract information about the relative stress and energy released during the failure process, and estimates of the relative deformation of the volume surrounding any particular failure. By assuming that the rupture is related to a penny-shaped crack, we can also define the dominant frequency and obtain estimates of the source radius of the individual fractures. In this manner, each observed event can be characterized by a series of observations that uniquely define their occurrence in space and time.