TL;DR
This paper introduces HADES-R, an improved seismic event location method that uses distance geometry and minimal station data to accurately locate clusters, especially in sparse or single-borehole seismic networks.
Contribution
HADES-R extends the original HADES approach by solving a least-squares problem with only one master event, enabling cluster location with minimal station data and improving applicability in challenging environments.
Findings
Successfully benchmarked on Ridgecrest sequence data.
Effectively located seismic clusters at FORGE geothermal site.
Demonstrated potential for microseismic monitoring with limited instrumentation.
Abstract
The determination of seismic event locations with sparse networks or single-borehole systems remains a significant challenge in observational seismology. Leveraging the advantages of the location approach HADES, which was initially developed for locating clustered seismicity recorded at two stations, we present here an improved version of the methodology: HADES-R. Where HADES previously needed a minimum of 4 absolutely located master events, HADES-R solves a least-squares problem to find the relative inter-event distances in the cluster, and uses only a single master event to find the locations of all events, and subsequently applies rotational optimiser to find the cluster orientation. It can leverage iterative station combinations if multiple receivers are available, to describe the cluster shape and orientation uncertainty with a bootstrap approach. The improved method requires P-…
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