Multiscale Entropy (MSE) and Self Organizing Map (SOM): two useful tools for the interpretation of seismic signals in the Campi Flegrei Caldera

The Campi Flegrei caldera, located in Southern Italy, is one of the most hazardous volcanoes in the world. Seismic activity in the caldera has increased in the last year due to a new unrest phase of the volcano. This has driven the attention of the scientific community and both local and national media. The Campi Flegrei area is densely populated, with a very low signal-to-noise ratio, making the detection of small earthquakes or the recognition of non-seismic events more challenging.

This study introduces a novel approach to the detecting and clustering of seismic signals. Unlike conventional methods that primarily focus on the regularity of seismic patterns, our research pivots towards a complexity-centric perspective using the Multiscale Entropy (MSE) algorithm, in conjunction with the Self-Organized Map (SOM) algorithm for effective data clustering. This methodological shift allows for a more nuanced exploration of the intricate dynamics inherent in seismic activities.

Seismic signals are not random or chaotic but rather complex structures that vary across different scales. By employing the MSE algorithm, we unravel these complex patterns, offering insights into the seismic behaviours that traditional methods may overlook. Our findings indicate a significant correlation between the complexity of seismic signals and key geophysical events related to the dynamic of the volcano, suggesting that complexity analysis could be a significant tool in seismic monitoring and prediction.

The analysed dataset is a six-month long continuous signals recorded in period at the V0102 temporary seismic station installed by the INGV-Osservatorio Vesuviano close to the Pisciarelli area, located in the Campi Flegrei caldera. MSE has been applied to one-minute-long traces of signal and clusterized through the application of the SOM analysis, revealing hidden layers of complexity across multiple scales.

Moreover, the study explores the potential of integrating MSE analysis with other seismic analysis techniques to enhance the accuracy of seismic interpretations. By combining complexity analysis with traditional approaches, we aim to develop a more deep and comprehensive understanding of seismic signals, potentially leading to an improvement of the seismic risk assessment.