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Detection of seismic phases on Distributed Acoustic Sensing (DAS) using the Discrete Cosine Transform (DCT).

Rubén García-Hernandez1, Luca D\'Auria1,2, José Luis Sánchez de la Rosa3, Nemesio M. Pérez1,2

  • Affiliations: 1Instituto Volcanológico de Canarias (INVOLCAN), Puerto de la Cruz, Tenerife, Canary Islands; 2Instituto Tecnológico y de Energías Renovables (ITER), Granadilla de Abona, Tenerife, Canary Islands; 3Department of Computer Engineering and Systems, Universidad de La Laguna (ULL), San Cristóbal de La Laguna, Spain

  • Presentation type: Talk

  • Presentation time: Monday 10:45 - 11:00, Room S150

  • Programme No: 3.1.8

  • Theme 3 > Session 1

Abstract

Distributed Acoustic Sensing (DAS) is revolutionising seismic monitoring and volcano seismology by transforming fibre optic cables into dense arrays of virtual sensors. This technology is particularly advantageous for studying seismo-volcanic processes, enabling high-resolution detection and characterisation of seismic phases such as P- and S-waves. However, DAS generates enormous volumes of data, often reaching terabytes, necessitating the development of efficient processing techniques to extract only meaningful information. This work introduces a novel approach for detecting seismic phases in DAS datasets. We used the Discrete Cosine Transform (DCT) to detect DAS recordings as images and apply edge-enhancement methods to highlight seismic phase arrivals. Once the different phases have been characterised, we can use absolute and relative location methodologies to determine the hypocenter location, considering that, unlike traditional sensors, it is not always possible to know the exact position of each cable section. This approach improves the spatial and temporal resolution of seismic event analysis, especially on volcanic islands or underwater areas where the seismic network distribution is geographically limited. We demonstrate the effectiveness of this methodology using DAS datasets from submarine cables located near the islands of Tenerife and La Palma (Canary Islands). The dataset includes the seismic activity recorded during the 2021 Tajogaite eruption, showcasing the potential of combining DCT-based detection with earthquake location techniques for real-time volcanic monitoring. These advancements emphasise the role of innovative data processing in harnessing DAS to improve our understanding of volcanic processes and hazard mitigation.