Llaima’s Volcano Seismic Event Classification Using The Cross-Correlation Function - Atmani, A; Ait Laasri, E.H; Agliz, D; Akhouayri, E (International Journal of Computer Sciences and Engineering, 2022)
Volcano seismic events are a source of great hazards implicating human lives and material damage. Consequently, continuous monitoring of this natural phenomenon is of great importance to reduce their dramatic effects on people and nearby economy. A seismic network is usually deployed around the crater to achieve this monitoring task. The different produced volcano seismic events (e.g., long period LP, tremor TR, volcano tectonic VT) are related to physical phenomenon (explosion, eruption, depressurization …etc) occurring at the source. The seismic network may also record seismic events that are not related to volcanoes such as tectonic events (TC) produced by geological faults. The first vital task in volcano monitoring is to recognize the source of each detected event. This task should be performed automatically due to the large amount of data recorded daily. In this work, we propose an easy and straightforward method to classify volcano seismic events using the cross-correlation function in time domain. We applied this method using three approaches. The application of these approaches to the seismic database of the Llaima volcano (Chile) gives good results, particularly the third approach that achieves a global accuracy of 92.7%.