Near real-time channel selection for Distributed Acoustic Sensing technology

Authors

  • Emanuele Bozzi Department of Earth Sciences, University of Pisa, Pisa, Italy
  • Giulio Pascucci Department of Earth Sciences, University of Pisa, Pisa, Italy https://orcid.org/0009-0008-3723-9003
  • Giacomo Rapagnani Department of Earth Sciences, University of Pisa, Pisa, Italy
  • Gian Maria Bocchini Institute of Geosciences, Ruhr University Bochum, Bochum, Germany https://orcid.org/0000-0001-9265-7859
  • Rebecca Harrington Institute of Geosciences, Ruhr University Bochum, Bochum, Germany https://orcid.org/0000-0002-3538-8020
  • Arantza Ugalde Department of Marine Geosciences, Institut de Ciències del Mar, CSIC, 08003 Barcelona, Spain https://orcid.org/0000-0003-2409-2002
  • Gilberto Saccorotti Istituto Nazionale di Geofisica e Vulcanologia, Pisa, Italy https://orcid.org/0000-0003-2915-1446
  • Francesco Grigoli Department of Earth Sciences, University of Pisa, Pisa, Italy

DOI:

https://doi.org/10.26443/seismica.v5i1.2251

Keywords:

DAS, automated channel selection, spatial clustering, event location, near-real time, hybrid networks, Seismology, earthquake seismology, earthquake monitoring, fiber-optic seismology

Abstract

Distributed Acoustic Sensing (DAS) technology enhances seismic monitoring by providing dense, array-like observations near earthquake sources. However, the resulting data volumes, typically on the order of thousands of channels, often limit real-time processing capabilities, with most seismological applications focusing on retrospective analysis of seismic sequences. To address this challenge, we introduce ORION (autOmatic near Real-time channel selectION), a near real-time selector of high-quality DAS channels that reduces the amount of data to process while maintaining key array-like features of the subsampled fiber-optic sensor. The method first adopts spatial clustering to identify cable segments with similar geometrical attributes (e.g., azimuth), and then performs channel selection within each segment using waveform attributes (e.g., signal-to-noise ratio). This approach enables spatial subsampling while preserving azimuthal and spatial coverage. We demonstrate the flexibility of ORION across several cable geometries. Finally, we analyze a seismic sequence recorded with a DAS system using ORION-selected channels and compare the resulting source locations with those obtained using a conventional spatially uniform subset of channels along the cable. The results show significant improvements in the accuracy of the estimated hypocenters.

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2026-05-24

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Bozzi, E., Pascucci, G., Rapagnani, G., Bocchini, G. M., Harrington , R., Ugalde, A., Saccorotti , G., & Grigoli, F. (2026). Near real-time channel selection for Distributed Acoustic Sensing technology. Seismica, 5(1). https://doi.org/10.26443/seismica.v5i1.2251

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Vol. 5 No. 1 (2026)

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Copyright (c) 2026 Emanuele Bozzi, Giulio Pascucci, Giacomo Rapagnani, Gian Maria Bocchini, Rebecca Harrington , Arantza Ugalde, Gilberto Saccorotti , Francesco Grigoli

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