About

Background

The easyQuake package combines earthquake waveform download, event detection at individual stations, event association, magnitude determination, and absolute location with hypoinverse.

Each module in the easyQuake package is called, individually, with a driver script and we include several example driver scripts in these docs and in the Github repository: https://github.com/jakewalter/easyQuake

The easyQuake platform utilizes a choice between the GPD picker (Ross et al., 2019) and the EQTransformer (Mousavi et al., 2020) deep-learning pickers and easyQuake will utilize the default models for those pickers. However, in most circumstances, you may want to train your own picker if you have a sufficient dataset for your experiment or region of interest.

It then takes those picks and utilizes a modified version of the Python-based PhasePApy (Chen and Holland, 2016) 1D associator. The associated events can then be passed through easyQuake modules to get a local magnitude, an absolute location from Hypoinverse, and output pick information in various formats for relative relocation (e.g. HypoDD). All the relevant metadata (picks, station amplitudes, station magnitudes, origins from association and Hypoinverse) is aggregated into a QuakeML format and can be output as an Obspy catalog or single event QuakeML file.

In implementation at OGS, we use the single event QuakeML file and add that directly into our SeisComP system. If you would like the script to add that to SeisComP, then please email us.

Detection Improvement

At OGS, we run the seismic network and create scientific products (location, magnitude, etc.) that are released through USGS as part of our membership in the national Advanced National Seismic System (ANSS). In adding easyQuake to augment detection, we have found a factor of 2 more earthquakes since May 2020.

Oklahoma seismicity detection improved

In addition, as a test scenario, we can run it on FDSN-downloaded waveforms and find significant detection improvementrelative to the regional seismic network in the case of the March 2020 M6.5 Central Idaho eartquake

Idaho detection example

In Development

We have some tailored some of the standard easyQuake modules to large-N node datasets and other special applications. Those will be available at the next major release. Also, we have a quasi-realtime detection workflow, utilizing easyQuake on short snippets of data gathered from a seedlink stream, that is currently being tested.

References

  • Chen, C., and A. A. Holland (2016), PhasePApy: A Robust Pure Python Package for Automatic Identification of Seismic Phases, Seismological Research Letters, 87(6), doi: 10.1785/0220160019.

  • Ross, Z. E., M.-A. Meier, E. Hauksson, and T. H. Heaton (2018), Generalized seismic phase detection with deep learning, Bull. Seismol. Soc. Am., 108, doi: 10.1785/0120180080.

  • 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

  • Walter, J. I., P. Ogwari, A. Thiel, F. Ferrer, and I. Woelfel (2021), easyQuake: Putting machine learning to work for your regional seismic network or local earthquake study, Seismological Research Letters, 92(1): 555–563, https://doi.org/10.1785/0220200226.