Automatic detection of low-frequency earthquakes (LFEs) based on a beamformed network response


Low-frequency earthquakes (LFEs), which frequently originate from multiplet-generating sources that are closely linked with tectonic tremor in subduction zones around the world, are difficult to observe and characterize due to their low signal-to-noise ratios. This obstacle can be sidestepped by detecting and then stacking all of the multiplets of a master LFE event, or template, using a matched-filter search; the difficulty however lies in finding an LFE event to use as a template. We implement here an automated beamforming algorithm to detect LFEs within the Mexican subduction zone that can then be used as templates in a matched-filter search. Seismograms recorded on a network of seismic stations are aligned to match the moveout of a potential source at depth and their energies are then summed; any spikes in the summed energy indicate an event originating from that potential source. We apply this method to a 1-d test case and we are able to detect 381 unique, potential LFE templates. We then compare our method to a previously introduced LFE detection scheme based on multiplet correlations for three test cases and find that the two methods are complementary.

Geophysical Journal International
William B. Frank
William B. Frank
Assistant Professor

My research focuses on how the Earth’s crust deforms over a broad range spatiotemporal scales.