Monitoring of induced microseismic events usually results in locations for these events and a geometrical interpretation of these 'dots in the box'. In this study we show how additional information obtained from observed microseismic events, namely the source mechanisms, were used to generate a discrete fracture network. Using the wide aperture of a surface star-like array (FracStar®) allows inversion for both shear and non-shear source mechanisms. Both volumetric and shear-only source mechanism inversion was carried out on microseismic events from the treatment of a shale gas reservoir in the continental US. During the same hydraulic fracture stimulation treatment, both dip-slip and reverse faulting sources were active in this reservoir. The source mechanisms revealed fracture orientations more accurately than could be inferred from microseismic event locations alone. The activity associated with different mechanisms is interpreted as indicating reactivation of existing fractures in the rock, as well as suggesting generation of new fractures. Failure analysis using source mechanisms on individual events allows an integrated understanding of the complex fracture interactions taking place in the reservoir, and also provides a more complete understanding of the stress conditions in the reservoir during the treatment. Fracture orientations, locations, and failure mechanisms are translated into discrete fracture network (DFN) models that can be used to verify the extent and character of the fractures created or reactivated during the fracture treatment, and may ultimately be used to generate fracture flow properties for reservoir simulation.
Detection and location of microseismic events is generally limited by seismic noise and inversion velocity model accuracy. These issues can be overcome by using " a matched filter" in order to stack scattered energy and reduce demands on the accuracy of the inversion velocity model for events with similar mechanisms and nearby locations. We have applied the technique to a surface monitoring dataset of the microseismic events induced by hydraulic fracturing to detect and relatively locate events. We have benchmarked detection and relative location with a direct location technique (PSET ® technology).
We review important challenges in microseismic monitoring and interpretation of the microseismic events. We start with locations of microseismic events and the impact of temporal changes in velocity during hydraulic fracturing and consider effects of uncertainty in deviation surveys on both downhole and surface monitoring. We continue with source mechanism inversion affected by low and high frequency signal from microseismic events. Finally, we discuss inversion of corner frequency and its reliability in the presence of complex tube waves. Where available, we suggest potential solutions for these challenges.
Th e vocal behaviour of birds may be infl uenced by many factors, including the risk of being detected by a predator. In Do ñ ana Protected Area, the tawny owl co-exists alongside its intraguild predator, the eagle owl Bubo bubo . We considered four scenarios to study the vocal behaviour of tawny owls at dusk by analysing: A) the calling rate of all males in 29 sites; B) the calling rate at dusk of males living within the home range of the intraguild predator; C) the calling rate of males living within the home range of the intraguild predator between 60 and 90 min after sunset; and D) the duration of male vocal bouts in visits where eagle owls have called. In scenario A we found that only the number of conspecifi c males aff ected the calling rate of tawny owls. In scenario B we observed that the presence of an eagle owl calling constrained the calling rate of the intraguild prey. In scenario C we found that this eff ect seemed mostly associated to a contemporaneous detection of the intraguild predator's calls. Finally, in scenario D we found no signifi cant eff ects on bout duration. Th ese results seem to indicate that tawny owls use their intraguild predator's calls as a cue to assess predation risk, and then adjust their vocal behaviour in order to minimize predation risk by a predator that may locate its prey by its vocalizations.
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