Array Analysis of Seismo-Volcanic Activity with Distributed Acoustic Sensing - Archive ouverte HAL
Article Dans Une Revue Geophysical Journal International Année : 2023

Array Analysis of Seismo-Volcanic Activity with Distributed Acoustic Sensing

Résumé

Continuous seismic monitoring of volcanoes is challenging due to harsh environments and associated hazards. However, the investigation of volcanic phenomena is essential for eruption forecasting. In seismo-volcanic applications, Distributed Acoustic Sensing (DAS) offers new possibilities for long-duration surveys. We analyse DAS strain rate signals generated by volcanic explosions and tremor at Stromboli volcano (Italy) recorded along 1 km of dedicated fibre-optic cable. We validate DAS recordings with co-located nodal seismometers. Converting node measurements to strain rate, we observe a perfect match in phase between DAS and node waveforms. However, DAS amplitudes appear to be around 2.7 times smaller than those of node records, which we explain as due to the inefficient ground-to-fibre strain transfer in the loose cable. We invert time delays between strain rate waveforms and confirm that the DAS enables us to retrieve a dominant and persistent seismic source in the proximity of active craters. This stable source location is confirmed by node array analyses. Despite an observed high noise level of strain rate signals outside a range of 2-15 Hz, our results demonstrate the potential of this new technology in monitoring volcanic areas.
Fichier principal
Vignette du fichier
Biagioli_DAS_Stromboli_2023.pdf (8.23 Mo) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04300894 , version 1 (22-11-2023)

Identifiants

Citer

Francesco Biagioli, Jean-Philippe Métaxian, Eléonore Stutzmann, Maurizio Ripepe, Pascal Bernard, et al.. Array Analysis of Seismo-Volcanic Activity with Distributed Acoustic Sensing. Geophysical Journal International, In press, ⟨10.1093/gji/ggad427⟩. ⟨hal-04300894⟩
90 Consultations
45 Téléchargements

Altmetric

Partager

More