Abstract
An automatic, adaptive, correlation-based algorithm for adjusting
phase picks in large digital seismic data sets provides significant
improvement in resolution of microseismic structures using only a
small fraction of the time and manpower which would be required to
re-analyze waveforms manually or semi-automatically. We apply this
technique to induced seismicity at the Soultz-sous-Forêts geothermal
site, France. The method is first applied to a small, previously
manually repicked subset of the catalogue so that we may compare
our results to those obtained from painstaking, visual, cross-correlation-based
techniques. Relative centroid-adjusted hypocenters show a decrease
in median mislocation from 31 to 7m for preliminary and automatically
adjusted picks, respectively, compared to the manual results. Narrow,
intersecting joint features not observed in the preliminary hypocenter
cloud, but revealed through manual repicking, are also recovered
using the automatic method. We then address a larger catalogue of
7000 microearthquakes. After relocating the events using automatic
repicks, the percentage of events clustering within 5m of their nearest
neighbor increases form 5 to 26\% of the catalogue. Hypocenter relocations
delineate narrow, linear features previously obscured within the
seismic cloud, interpreted as faults or fractures which may correspond
to fluid propagation paths, or to changes in stress as a result of
elevated pore pressures. RMS travel-time residuals for the larger
data set are reduced by only 0.2\%; however, phase-pick biases in
the preliminary catalogue have influenced both the velocity model
and station correction calculations, which will affect location residuals.
These pick biases are apparent on the adjusted, stacked waveforms
and correcting them will be important prior to future velocity model
refinements.
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