SeisBlue

Github Pages: https://seisblue.github.io/seisblue/

A deep-learning data processing platform for seismology

Warning

The code is still in the development state, API will change frequently.

Beta version will be released soon.

Please star us for upcoming updates!

Prerequisite:

• S-File catalog from SEISAN

• SeisComP Data Structure (SDS) database. The directory and file layout of SDS is defined as:

  SDSROOT/YEAR/NET/STA/CHAN.TYPE/NET.STA.LOC.CHAN.TYPE.YEAR.DAY
  

Installation:

• Follow the instructions in the Docker folder to create a Docker container.

Reference:

EQTansfomer | Github

Mousavi, S. M., Ellsworth, W. L., Zhu, W., Chuang, L. Y., & Beroza, G. C. (2020). Earthquake transformer—an attentive deep-learning model for simultaneous earthquake detection and phase picking. Nature communications, 11(1), 1-12.

PhaseNet | Github

Zhu, W., & Beroza, G. C. (2018). PhaseNet: A Deep-Neural-Network-Based Seismic Arrival Time Picking Method. arXiv preprint arXiv:1803.03211.

U-net

Ronneberger, O., Fischer, P., & Brox, T. (2015, October). U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-assisted intervention (pp. 234-241). Springer, Cham.

U-net ++ | Github

Zhou, Z., Siddiquee, M. M. R., Tajbakhsh, N., & Liang, J. (2018). Unet++: A nested u-net architecture for medical image segmentation. In Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support (pp. 3-11). Springer, Cham.

PhasePApy | GitHub

Chen, C., & Holland, A. A. (2016). PhasePApy: A robust pure Python package for automatic identification of seismic phases. Seismological Research Letters, 87(6), 1384-1396.

PyAPA | GitHub

Chang, Y. H., Hung, S. H., & Chen, Y. L. (2019). A fast algorithm for automatic phase picker and event location: Application to the 2018 Hualien earthquake sequences. Terr. Atmos. Ocean. Sci, 30, 435-448.

Personal Blog (Traditional Chinese only):

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