Microseismic Velocity Imaging of the Fracturing Zone

Abstract:

Hydraulic fracturing of low permeability reservoirs can induce microseismic events during fracture development. For this reason, microseismic monitoring using sensors on surface or in borehole have been widely used to delineate fracture spatial distribution and to understand fracturing mechanisms. It is often the case that the stimulated reservoir volume (SRV) is determined solely based on microseismic locations. However, it is known that for some fracture development stage, long period long duration events, instead of microseismic events may be associated. In addition, because microseismic events are essentially weak and there exist different sources of noise during monitoring, some microseismic events could not be detected and thus located. Therefore the estimation of the SRV is biased if it is solely determined by microseismic locations.

With the existence of fluids and fractures, the seismic velocity of reservoir layers will be decreased. Based on this fact, we have developed a near real time seismic velocity tomography method to characterize velocity changes associated with fracturing process. The method is based on double-difference seismic tomography algorithm to image the fracturing zone where microseismic events occur by using differential arrival times from microseismic event pairs. To take into account varying data distribution for different fracking stages, the method solves the velocity model in the wavelet domain so that different scales of model features can be obtained according to different data distribution.

We have applied this real time tomography method to both acoustic emission data from lab experiment and microseismic data from a downhole microseismic monitoring project for shale gas hydraulic fracturing treatment. The tomography results from lab data clearly show the velocity changes associated with different rock fracturing stages. For the field data application, it shows that microseismic events are located in low velocity anomalies. By combining low velocity anomalies with microseismic events, we should better estimate the SRV.