Focal-time analysis is a straightforward data-driven method to obtain robust stratigraphic depth control for microseismicity or induced seismic events. The method eliminates the necessity to build an explicit, calibrated velocity model for hypocenter depth estimation, although it requires multicomponent 3D seismic data that are colocated with surface or near-surface microseismic observations. Event focal depths are initially expressed in terms of zero-offset focal time (two-way P-P reflection time) to facilitate registration and visualization with 3D seismic data. Application of the focal-time method requires (1) high-quality P- and S-wave time picks, which are extrapolated to zero offset and (2) registration of correlative P-P and P-S reflections to provide [Formula: see text] and [Formula: see text] time-depth control. We determine the utility of this method by applying it to a microseismic and induced-seismicity data set recorded with a shallow-borehole monitoring array in Alberta, Canada, combined with high-quality multicomponent surface seismic data. The calculated depth distribution of events is in good agreement with hypocenter locations obtained independently using a nonlinear global-search method. Our results reveal that individual event clusters have distinct depth distributions that can provide important clues about the mechanisms of fault activation.
Characterization of induced seismicity and associated microseismicity is an important challenge for enhanced oil recovery and development of tight hydrocarbon reservoirs. In particular, accurately correlating hypocenters of induced events to stratigraphic layers plays an important role in understanding the mechanisms of fault activation. Existing methods for estimating focal depth, however, are prone to a high degree of uncertainty. A comprehensive analysis of inferred focal depths is applied to induced events that occurred during completions of horizontal wells targeting the Montney Formation in British Columbia, Canada. Our workflow includes a probabilistic, nonlinear global-search algorithm (NonLinLoc), a hierarchical clustering algorithm for relative relocation (GrowClust) and depth refinement using the recently developed focal-time method. The focal-time method leverages stratigraphic correlations between P-P and P-S reflections to eliminate the need for an explicit velocity model developed specifically for hypocenter depth estimation. We show that this approach is robust in the presence of noisy picks and location errors from epicenters obtained using a global-search algorithm, but it is limited to areas where multicomponent 3-D seismic data are available. A novel method to determine statics corrections is developed here, to ensure that both passive seismic observations and 3-D seismic data share a common datum in areas of moderate to high topography. Our results highlight the importance of transverse faults, which appear to provide permeable pathways for activation of other faults at distances of up to 2 km from hydraulic fracturing operations.
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