A rapid analysis of aftershock processes after a moderate magnitude earthquake with ML methods

Abstract

SUMMARY Moderate magnitude earthquakes and seismic sequences frequently develop on fault systems, but whether they are linked to future major ruptures is always ambiguous. In this study, we investigated a seismic sequence that has developed within a portion of the stretching region of the Apennines in Italy where moderate to large earthquakes are likely to occur. We captured a total of 2039 aftershocks of the 2023 September 18, Mw 4.9 earthquake occurred during the first week, by using machine-learning (ML) based algorithms. Aftershocks align on two 5–7 km long parallel faults, from a length that exceeds what is expected from the main shock magnitude. The segments are ramping at about 6 km depth on closely spaced N100 striking 70 N dipping planes, at a distance of some kilometres from the main shock hypocentre. Our results indicate that even moderate magnitude events trigger seismicity on a spread set of fault segments around the main shock hypocentre, revealing processes of interaction within the crustal layer. The possibility that larger earthquakes develop during seismicity spread is favoured by pore pressure diffusion, in relation with the closeness to criticality of fault segments. Based on the very rapid activation of seismicity on the entire system and a back-front signal from the hypocentre of the main event, we infer that fluid pressure, initially high within the crustal layer, rapidly dropped after the main shock. Our study reinforces the importance of timely extracting information on fault geometry and seismicity distribution on faults. ML-based methods represent a viable tool for semi-real-time application, yielding constraints on short-time forecasts.