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QuakeMigrate: a Python Package for Automatic Earthquake Detection and Location Using Waveform Migration and Stacking

QuakeMigrate: a Python Package for Automatic Earthquake Detection and Location Using Waveform Migration and Stacking

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Authors

Tom Winder , Conor Andrew Bacon , Jonathan Daniel Smith, Thomas Samuel Hudson , Robert Stephen White

Abstract

QuakeMigrate is a modular, open-source Python package providing a framework to efficiently and automatically detect and locate microseismicity. From raw seismic waveforms and a modest number of physically meaningful inputs and tuneable parameters, it produces catalogues of earthquakes including hypocentres, their associated uncertainties, phase arrival times, and local magnitude estimates, all of which are compatible with other common software within the field of (micro-)seismic analysis. The waveform migration and stacking approach on which the software is founded enables phase arrivals with very low signal-to-noise ratios at individual stations to be successfully incorporated in the network-based detection and location. It also implicitly associates phase arrivals across a network even at very small inter-event times, which commonly poses difficulties for traditional pick-then-locate methods. Here, we use a synthetic test-case to outline the fundamental concepts that underpin QuakeMigrate and its implementation, before presenting its application to two real-world datasets with different characteristics to highlight its flexibility and performance.

DOI

https://doi.org/10.31223/X53447

Subjects

Geophysics and Seismology, Glaciology, Volcanology

Keywords

Earthquake Detection, Earthquake Location, Cryoseismology, volcano seismology, Seismology, open-source software, Microseismicity, python

Dates

Published: 2025-07-26 01:32

Last Updated: 2025-07-26 01:32

License

CC BY Attribution 4.0 International

Additional Metadata

Data Availability (Reason not available):
Software to recreate all figures is available in an openly accessible Github repository. A subset of the accompanying data is archived in Zenodo (DOI: 10.5281/zenodo.16419322) but the repository is not yet published; it will be finalised and published after review.