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Deep learning and multi-station classification of volcano-seismic events of the Nevados del Chillán volcanic complex (Chile)

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Abstract

This paper presents a methodology for developing a volcano-seismic event classification system using a multi-station deep learning approach to support monitoring the Nevados del Chillán Volcanic Complex, which has been active since 2017. A convolutional network of multiple inputs processes the information from an event recorded up to five seismic stations. Each record is represented by its normalized spectrogram; thus, the network may receive from one to five spectrograms as input. The design includes entering additional information into the network, like the stations configuration and the event duration, information not provided by the spectrograms. Finally, this work includes the design and implementation of a relational database to access the continuous traces of events, showing different subsets of data quickly and efficiently. The results show that the classification of an event recorded up to five stations is substantially more effective than a single-station strategy. However, incorporating additional information of the signal does not significantly improve the classification performance.

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Data availability

The data that support the results of this study and model M1-Exp1 are available on request from the repository https://drive.google.com/drive/folders/1Jjq0p4TZeT2vLSD1vsGOJlM5Pz7SMOr8?usp=sharing.

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Acknowledgements

We thank OVDAS and the FONDEF ID19|10397 Project for having the data used in this work. In addition, thanks to the Department of Mathematical Engineering of the Universidad de La Frontera for having the Khipu Server to perform the computation and training of the models.

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Author notes

  1. Millaray Curilem, Walter Gomez and Ricardo Rios have contributed equally to this work.

Authors and Affiliations

  1. Departamento de Ingeniería Matemática, Universidad de La Frontera, Temuco, Chile

    Alejandro Ferreira & Walter Gomez

  2. Departamento de Ingeniería Eléctrica, Universidad de La Frontera, Temuco, Chile

    Millaray Curilem

  3. Institute of Computing, Federal University of Bahia, Salvador, Bahia, Brazil

    Ricardo Rios

Authors
  1. Alejandro Ferreira
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  2. Millaray Curilem
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  3. Walter Gomez
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  4. Ricardo Rios
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Correspondence to Alejandro Ferreira.

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Ferreira, A., Curilem, M., Gomez, W. et al. Deep learning and multi-station classification of volcano-seismic events of the Nevados del Chillán volcanic complex (Chile). Neural Comput & Applic 35, 24859–24876 (2023). https://doi.org/10.1007/s00521-023-08994-z

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