Semi-automated template matching and machine-learning based analysis of the August 2020 Castelsaraceno microearthquake sequence (southern Italy)

The accurate characterization of microearthquake sequences allows seismologists to better understand the physical processes involved in earthquake nucleation and rupture propagation gain insights on fault geometry at depth. Standard procedures for seismic analysis are based manual detection phase-picking, requiring a huge amount work from expert seismologists, particularly case microseismic events. Here we show how investigation low-magnitude foreshock-mainshock-aftershock sequence, occurred August 2020 close Castelsaraceno village (southern Italy), greatly benefited application semi-automated template matching machine-learning workflow. phase-picking was automatically performed through deep-learning algorithm 202 microearthquakes detected between July October 2020, followed by an automatic multi-step absolute relative location procedure. 72 relocated events sequence were clustered time (7–12 August) narrow range depths (10–12 km). Ml 2.1 foreshock doublet 2.9 mainshock identified persistent asperity. joint aftershocks distribution, focal mechanism, geology study area suggest occurrence along NNE-SSW left-lateral, transtensional brittle portion crystalline basement.