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Seismic arrival-time picking on distributed acoustic sensing data using semi-supervised learning.

Weiqiang Zhu1,2, Ettore Biondi3, Jiaxuan Li3

  • 1Seismological Laboratory, Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA. zhuwq@berkeley.edu.

Nature Communications
|December 11, 2023
PubMed
Summary

We developed a semi-supervised deep learning method, PhaseNet-DAS, to improve earthquake detection using Distributed Acoustic Sensing (DAS) data. This approach addresses challenges in DAS signal processing, enhancing seismic monitoring capabilities.

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