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Earthquake transformer—an attentive deep-learning model for simultaneous earthquake detection and phase picking

Author

Listed:
  • S. Mostafa Mousavi

    (Stanford University)

  • William L. Ellsworth

    (Stanford University)

  • Weiqiang Zhu

    (Stanford University)

  • Lindsay Y. Chuang

    (Georgia Institute of Technology)

  • Gregory C. Beroza

    (Stanford University)

Abstract

Earthquake signal detection and seismic phase picking are challenging tasks in the processing of noisy data and the monitoring of microearthquakes. Here we present a global deep-learning model for simultaneous earthquake detection and phase picking. Performing these two related tasks in tandem improves model performance in each individual task by combining information in phases and in the full waveform of earthquake signals by using a hierarchical attention mechanism. We show that our model outperforms previous deep-learning and traditional phase-picking and detection algorithms. Applying our model to 5 weeks of continuous data recorded during 2000 Tottori earthquakes in Japan, we were able to detect and locate two times more earthquakes using only a portion (less than 1/3) of seismic stations. Our model picks P and S phases with precision close to manual picks by human analysts; however, its high efficiency and higher sensitivity can result in detecting and characterizing more and smaller events.

Suggested Citation

  • S. Mostafa Mousavi & William L. Ellsworth & Weiqiang Zhu & Lindsay Y. Chuang & Gregory C. Beroza, 2020. "Earthquake transformer—an attentive deep-learning model for simultaneous earthquake detection and phase picking," Nature Communications, Nature, vol. 11(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-17591-w
    DOI: 10.1038/s41467-020-17591-w
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    Cited by:

    1. Alberto Ardid & David Dempsey & Corentin Caudron & Shane Cronin, 2022. "Seismic precursors to the Whakaari 2019 phreatic eruption are transferable to other eruptions and volcanoes," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    2. Weiqiang Zhu & Ettore Biondi & Jiaxuan Li & Jiuxun Yin & Zachary E. Ross & Zhongwen Zhan, 2023. "Seismic arrival-time picking on distributed acoustic sensing data using semi-supervised learning," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    3. Daniel Rathmaier & Fawz Naim & Andikan Charles William & Dwaipayan Chakraborty & Christopher Conwell & Matthias Imhof & Gordon M. Holmes & Luis E. Zerpa, 2024. "A Reservoir Modeling Study for the Evaluation of CO 2 Storage Upscaling at the Decatur Site in the Eastern Illinois Basin," Energies, MDPI, vol. 17(5), pages 1-18, March.
    4. Corentin Caudron & Yosuke Aoki & Thomas Lecocq & Raphael Plaen & Jean Soubestre & Aurelien Mordret & Leonard Seydoux & Toshiko Terakawa, 2022. "Hidden pressurized fluids prior to the 2014 phreatic eruption at Mt Ontake," Nature Communications, Nature, vol. 13(1), pages 1-9, December.

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