Fluid diffusion and seismic clusters identification: results on the seismicity of Molise (southern Italy) in 2018

The identification of clusters is crucial for the statistical analysis of seismicity and the forecasting of earthquakes, because discrepancies in the methods used to identify clusters can lead to inconsistent results. In this work, the seismic activity in Molise, southern Italy, from April to November 2018 is analyzed as a case study. The focus is on how such discrepancies can affect forecasting algorithms such as NExt STrOng Related Earthquake (NESTORE), which are designed to forecast strong aftershocks following a first strong event

A detailed analysis was performed using an improved template matching catalog and a comparative evaluation of clustering methods, including window-based analysis techniques, Nearest Neighbor, and fractal dimension. Probabilistic information was integrated through the Epidemic Type Aftershock Sequence (ETAS) model.

Significant differences in cluster definition required further analysis, including principal component analysis (PCA) and ETAS modeling, to investigate spatiotemporal seismic patterns. The main results show an upward migration of seismicity, an extended duration of the sequence and relative quiescence between stronger events, all suggesting fluid-driven mechanisms. These observations suggest that the presence of fluids plays a crucial role in the sequence dynamics and the discrepancies between clustering methods.

The study highlights the importance of refining approaches to cluster identification, incorporating physical and geological factors, and encourages further investigation of anomalous seismic sequences such as the 2018 seismic cluster in Molise. The results also highlight the influence of fluids on seismicity in the Apennines and call for advanced analytical methods to improve the accuracy of strong events forecasting.

 

Funded by a grant from the Italian Ministry of Foreign Affairs and International Cooperation and Co-funded within the RETURN Extended Partnership and received funding from the European Union Next-Generation EU (National Recovery and Resilience Plan—NRRP, Mission 4, Component 2, Investment 1.3—D.D. 1243 2/8/2022, PE0000005) and by the and the grant “Progetto INGV Pianeta Dinamico: NEar real-tiME results of Physical and StatIstical Seismology for earthquakes observations, modelling and forecasting (NEMESIS)” - code CUP D53J19000170001 - funded by Italian Ministry MIUR (“Fondo Finalizzato al rilancio degli investimenti delle amministrazioni centrali dello Stato e allo sviluppo del Paese”, legge 145/2018).