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Covseisnet is a Python package for array signal processing, with a focus on data from seismic networks. The core mathematical object of the package is the network covariance matrix, used for signal detection, source separation, localisation, and plane-wave beamforming. More precisely, the signal detection and processing methods are based on the analysis of the covariance matrix spectrum. The covariance matrix can be used as input for classical array processing tools such as beamforming and inter-station cross-correlations.
In order to provide tools that are user-friendly and efficient, the package builts on ObsPy, a Python toolbox for seismology, on SciPy, and NumPy, two Python libraries for scientific computing and linear algebra.
This library is hosted on GitHub at leonard-seydoux/covseisnet and is distributed under the GNU General Public License v3.0. Contributions are welcome, and can be made via pull requests on the GitHub repository.
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How to cite this package#
Citation statement#
This package is released under the GNU General Public License v3.0 (see the License section for more information). Please include the following statement in the ackowledgements section of your publication, and/or reference one the paper listed in the References section below.
This work made use of Covseisnet, a Python package for array signal processing, developed by Léonard Seydoux, Jean Soubestre, Cyril Journeau, Francis Tong & Nikolai Shapiro.
Publications summary#
The method was first introduced in Seydoux et al. (2016) with an application to the monitoring of the Piton de la Fournaise eruptions. We then applied it to the analysis of USArrays data (Seydoux et al., 2016). We also proposed a pre-processing method for ambient noise cross-correlations (Seydoux et al., 2017).
The method was then applied to the detection and classification of seismovolcanic tremors (Soubestre et al., 2018) and to the depth migration of seismovolcanic tremor sources (Soubestre et al., 2019). The method was also applied to the study of localized modes on a metasurface (Lott et al., 2020), and to the detection, classification, and location of seismovolcanic signals at the Piton de la Fournaise volcano in (Journeau et al., 2020).
In the context of unsuperised learning, we also used the covariance matrix representation to reveal patterns in the continuous seismic wavefield during the 2009 L'Aquila earthquake (Shi et al., 2021). We also investigated the dynamics of the Kamchatka volcanic systen in Journeau et al. (2022).
References#
Léonard Seydoux, Nikolai M. Shapiro, Julien De Rosny, Florent Brenguier, and Matthieu Landès. Detecting seismic activity with a covariance matrix analysis of data recorded on seismic arrays. Geophysical Journal International, 204(3):1430–1442, March 2016. URL: https://academic.oup.com/gji/article-lookup/doi/10.1093/gji/ggv531, doi:10.1093/gji/ggv531.
Léonard Seydoux, N. M. Shapiro, Julien De Rosny, and Matthieu Landès. Spatial coherence of the seismic wavefield continuously recorded by the USArray. Geophysical Research Letters, 43(18):9644–9652, September 2016. URL: http://doi.wiley.com/10.1002/2016GL070320, doi:10.1002/2016GL070320.
Léonard Seydoux, Julien de Rosny, and Nikolai M. Shapiro. Pre-processing ambient noise cross-correlations with equalizing the covariance matrix eigenspectrum. Geophysical Journal International, 210(3):1432–1449, September 2017. URL: https://academic.oup.com/gji/article-lookup/doi/10.1093/gji/ggx250, doi:10.1093/gji/ggx250.
Jean Soubestre, Nikolai M. Shapiro, Léonard Seydoux, Julien de Rosny, Dmitry V. Droznin, Svetlana Ya. Droznina, Sergey L. Senyukov, and Evgeniy I. Gordeev. Network-Based Detection and Classification of Seismovolcanic Tremors: Example From the Klyuchevskoy Volcanic Group in Kamchatka. Journal of Geophysical Research: Solid Earth, 123(1):564–582, January 2018. URL: http://doi.wiley.com/10.1002/2017JB014726, doi:10.1002/2017JB014726.
Jean Soubestre, Léonard Seydoux, Nikolai M. Shapiro, Julien De Rosny, Dmitry V. Droznin, Svetlana Ya. Droznina, Sergey L. Senyukov, and Evgeniy I. Gordeev. Depth Migration of Seismovolcanic Tremor Sources Below the Klyuchevskoy Volcanic Group (Kamchatka) Determined From a Network‐Based Analysis. Geophysical Research Letters, 46(14):8018–8030, July 2019. URL: https://onlinelibrary.wiley.com/doi/10.1029/2019GL083465, doi:10.1029/2019GL083465.
Martin Lott, Philippe Roux, Léonard Seydoux, Benoit Tallon, Adrien Pelat, Sergey Skipetrov, and Andrea Colombi. Localized modes on a metasurface through multiwave interactions. Physical Review Materials, 4(6):065203, June 2020. URL: https://link.aps.org/doi/10.1103/PhysRevMaterials.4.065203, doi:10.1103/PhysRevMaterials.4.065203.
Cyril Journeau, Nikolai M. Shapiro, Léonard Seydoux, Jean Soubestre, Valérie Ferrazzini, and Aline Peltier. Detection, Classification, and Location of Seismovolcanic Signals with Multicomponent Seismic Data: Example from the Piton de La Fournaise Volcano (La Réunion, France). Journal of Geophysical Research: Solid Earth, August 2020. URL: https://onlinelibrary.wiley.com/doi/10.1029/2019JB019333, doi:10.1029/2019JB019333.
Peidong Shi, Léonard Seydoux, and Piero Poli. Unsupervised Learning of Seismic Wavefield Features: Clustering Continuous Array Seismic Data During the 2009 L'Aquila Earthquake. Journal of Geophysical Research: Solid Earth, January 2021. URL: https://onlinelibrary.wiley.com/doi/10.1029/2020JB020506, doi:10.1029/2020JB020506.
Cyril Journeau, Nikolai M. Shapiro, Léonard Seydoux, Jean Soubestre, Ivan Y. Koulakov, Andrei V. Jakovlev, Ilyas Abkadyrov, Evgeny I. Gordeev, Danila V. Chebrov, Dmitry V. Droznin, Christoph Sens-Schönfelder, Birger G. Luehr, Francis Tong, Gaspard Farge, and Claude Jaupart. Seismic tremor reveals active trans-crustal magmatic system beneath Kamchatka volcanoes. Science Advances, 8(5):eabj1571, February 2022. URL: https://www.science.org/doi/10.1126/sciadv.abj1571, doi:10.1126/sciadv.abj1571.
About us#
This package was mainly developed by Léonard Seydoux during his PhD at the Institut de Physique du Globe de Paris, under the supervision of Nikolai Shapiro. Several contributions for the core program were made by Jean Soubestre and Cyril Journeau. Francis Tong contributed to the distribution of the packge via PyPI and Conda.
Several other versions of this package are available (not distributed yet, planned for the future). A first version was developed in Matlab by Léonard Seydoux. For computational efficiency, a second version was developed in C++ by Matthieu Landès. For now, it works only with SAC files.
If you have any questions, please contact us via the GitHub repository at covseisnet/covseisnet. You can also consider opening an issue on the repository, or creating pull requests.