Fibre optic distributed acoustic sensing of volcanic events

Philippe Jousset (), Gilda Currenti (), Benjamin Schwarz, Athena Chalari, Frederik Tilmann, Thomas Reinsch, Luciano Zuccarello, Eugenio Privitera and Charlotte M. Krawczyk
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Philippe Jousset: GFZ, German Research Centre for Geosciences, Telegrafenberg
Gilda Currenti: Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo
Benjamin Schwarz: GFZ, German Research Centre for Geosciences, Telegrafenberg
Athena Chalari: Silixa Ltd., Silixa House, 230 Centennial Park
Frederik Tilmann: GFZ, German Research Centre for Geosciences, Telegrafenberg
Thomas Reinsch: GFZ, German Research Centre for Geosciences, Telegrafenberg
Luciano Zuccarello: Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Pisa
Eugenio Privitera: Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo
Charlotte M. Krawczyk: GFZ, German Research Centre for Geosciences, Telegrafenberg

Nature Communications, 2022, vol. 13, issue 1, 1-16

Abstract: Abstract Understanding physical processes prior to and during volcanic eruptions has improved significantly in recent years. However, uncertainties about subsurface structures distorting observed signals and undetected processes within the volcano prevent volcanologists to infer subtle triggering mechanisms of volcanic phenomena. Here, we demonstrate that distributed acoustic sensing (DAS) with optical fibres allows us to identify volcanic events remotely and image hidden near-surface volcanic structural features. We detect and characterize strain signals associated with explosions and locate their origin using a 2D-template matching between picked and theoretical wave arrival times. We find evidence for non-linear grain interactions in a scoria layer of spatially variable thickness. We demonstrate that wavefield separation allows us to incrementally investigate the ground response to various excitation mechanisms. We identify very small volcanic events, which we relate to fluid migration and degassing. Those results provide the basis for improved volcano monitoring and hazard assessment using DAS.

Date: 2022
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DOI: 10.1038/s41467-022-29184-w

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