We show that fault intensity and AVO inversion offer insights into hydraulic fracturing operations in a shale-gas reservoir. This is supported by microseismic data using calculations of event density, SRV dimensions, b-value, D-value, and hydraulic diffusivity. We also demonstrate that fault intensity is linked to the azimuthal anisotropy of the AVO inversion. This helps both infer the presence of faults that are below seismic imaging resolution, and potentially determine the spatial scale at which anisotropy measurements relate to natural faults and fractures. Production is also shown to be related to the calculated geophysical properties. Our key message is that it is critical to demonstrate the link between geophysical measurements and the success of producing shale gas reservoirs in order to maintain the confidence in geophysical contributions.
One of the contributions that geophysics can make to the development of shale gas plays is to explain and predict the behaviour of hydraulic fracturing operations and the resulting gas production. To accomplish this, we look at the relationship between microseismic and surface seismic calculations, and attempt to back up the relationships with petrophysical and engineering measurements and analyses.
Surface seismic is used to determine the underlying rock properties of the shale reservoir. Seismic-scale faulting, either observed directly or inferred from curvature attributes, is useful for showing areas where natural fault and fracture activity is more likely to be present (Reine & Dunphy, 2011). This natural fault network can have a significant impact on the effectiveness of the hydraulic fracturing and production of the reservoir. Prestack AVO inversion allows seismic amplitudes to reveal useful mechanical properties such as Poisson's ratio and Young's modulus. These values can then be used to determine a measure of reservoir brittleness (Rickman, 2008), or " frac-ability". When extended to different azimuthal sectors, the anisotropy of the inverted results can be used as an indicator of natural fracturing (Bakulin et al., 2000) or local stress changes (Gray et al., 2012).
For hydraulic fracturing, microseismic data contains both spatial information and attribute information revealing the conditions under which the frac is occurring. Spatially, event density is a useful display of how microseismic energy is concentrated. This concentration is then useful for determining the stimulated reservoir volume (SRV), whose shape depends on the local reservoir conditions. The microseismic D-values (Grob & van der Baan, 2011) describe the spatial distribution of events by its fractal dimension (Grassberger & Procaccia, 1983). This value relates to the total spread in the microseismic cloud. Hydraulic diffusivity (Shapiro et al., 2002) describes the velocity of the microseismic triggering front as it moves away from the well, giving insight into the bulk permeability of the reservoir. Finally, the dominant mechanism of failure in a hydraulic fracture can be determined from the microseismic b-value (Wessels et al., 2011). The b-value describes the distribution of microseismic magnitudes, which are expected to obey a power-law relationship (Gutenberg & Richter, 1954).