Microearthquake cluster detection based on waveform similarities, with an application to the western Swiss Alps

Abstract

SUMMARY Highly similar waveforms of different earthquakes are due to similar focal mechanisms and common propagation paths. The relative hypocentral locations of events in clusters of similar earthquakes can provide useful insights into geometry and style of faulting at depth within the crust. The detection of such earthquake clusters within large data sets can only be accomplished efficiently by means of an automatic procedure. Therefore, we developed an algorithm based on correlation analysis that detects and associates events with similar waveforms. The algorithm has been applied to a data set recorded in the western Swiss Alps: 619 out of a total of 1497 events exhibit similarities with other events. Based on a more detailed investigation of two selected clusters with known focal mechanisms, it could be shown that the active fault planes correspond to neotectonic structures mapped in the study area. Due to their oblique orientation relative to the larger-scale epicentral alignment, these faults have been interpreted as Riedel shears.