GNGTS 2024 - Atti del 42° Convegno Nazionale

Session 1.1 GNGTS 2024 Tracking the evoluton of seismic sequences in the normal fault environment of Southern Apennines using deep catalogues F. Scoto di Uccio 1 , M. Michele 2 , C. Strumia 1 , G. Festa 1 , M. Supino 2 , L. Chiaraluce 2 , N. D’Agostno 2 , G. C. Beroza 3 1 Department of Physics ‘Etore Pancini’, University of Napoli Federico II, Italy. 2 Isttuto Nazionale di Geofsica e Vulcanologia, Italy. 3 Department of Geophysics, Stanford University, USA. Seismic sequences, featuring events clustered in space and tme and generatng seismicity with a higher rate than the background, are a powerful tool for investgatng the geometry and the mechanical state of faults that may host large magnitude earthquakes in the future. The knowledge about the involved structures and processes achievable from the analysis of the sequences strongly depends on the content and the magnitude of completeness of available catalogues. Enhanced catalogues obtained using advanced techniques, such as machine learning models or similarity-based detectors have contributed to decrease the magnitude of completeness of one point or more, increasing the number of events buried in the noise of more than one order of magnitude, with respect to manual earthquake identfcaton. Furthermore, accurate locaton and source parameter estmaton can provide direct access to mechanical propertes of the structures hostng sequences. Earthquake locaton for deep catalogues can provide a high- resoluton imaging of fault structures and their mutual interacton (e.g., Ross et al. 2019, Sugan et al. 2023) and defne paths for fuid migraton (Vuan et al. 2020), while evolutve models can be constructed accessing to the source parameters (Yoon et al., 2017).