Local Seismicity: Matched Filter Detection Routine with Synthetic Templates using 1D velocity model
DOI:
https://doi.org/10.26443/seismica.v5i2.1784Keywords:
Microseismic Monitoring, Microseismicity, Template Matching, Geothermal, Induced Seismicity, magnitude of completeness, seismic network sensitivity, Focal mechanisms, Earthquake Location, automatic detection and location, synthetic seismogramsAbstract
This study evaluates the performance of Synthetic Template Matching for seismic event detection in the West Bohemia region (Czechia), comparing it with two established methods: the automated detector-locator PEPiN and Artificial Neural Network. Synthetic Templates are generated using a 1D velocity model and span a grid of five fundamental focal mechanisms (FMs), independent of any prior waveform or FM knowledge. The resulting catalog includes origin time, similarity, magnitude, location, number of detecting templates, and interpreted focal mechanism. In WEBNET data, Synthetic Template Matching with cross-correlation thresholds of 0.4 detected 264 events with completeness magnitude MC=0.1. All the detected seismicity is real and local, its FMs (interpreted within the seismic network) align dominantly with a strike-slip events. Although the method does not outperform PEPiN or Artificial Neural Network in MC, it reliably estimates focal mechanisms and epicentral locations.
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