Show simple item record

dc.contributor.authorWinder, Tom
dc.contributor.authorBacon, Conor
dc.contributor.authorSmith, Jonathan
dc.contributor.authorHudson, Thomas
dc.contributor.authorGreenfield, Tim
dc.contributor.authorWhite, Robert
dc.date.accessioned2022-04-01T07:07:56Z
dc.date.available2022-04-01T07:07:56Z
dc.date.issued2020-12-11
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/335653
dc.description.abstractDetecting and locating microearthquakes from continuous waveform records is the fundamental step in microseismic processing. Dense local networks and arrays have introduced the possibility to detect large numbers of far weaker events, but when viewed on seismic records from individual stations their waveforms are often obscured by noise. Furthermore, areas of interest for microseismic monitoring often feature extremely high event rates, highlighting the limitations of traditional techniques based on phase picking and association. In order to maximise the new insights gained, we require fully automated techniques which can exploit modern recordings to produce highly complete earthquake catalogues containing few artefacts. QuakeMigrate is a new modular, open-source Python package providing a framework to efficiently, automatically and robustly detect and locate microseismicity. The user inputs continuous seismic data, a velocity model or pre-calculated look-up table and list of station locations. Instead of reducing the raw waveforms to discrete time picks, they are transformed (by amplitude, frequency and/or polarisation analysis) to continuous functions representing the probability of a particular phase arrival through time. These ‘onset functions’ from stations across the network are then migrated according to a travel-time look-up table and stacked to perform a grid-search for coherent sources of energy in the subsurface. This enables detection of earthquakes at close to or below the signal-to-noise ratio at individual stations, and implicitly associates phase arrivals even at very small inter-event times. We demonstrate the flexibility and power of this approach with examples of basal icequakes detected at the Rutford Ice Stream, Antarctica, dike- and caldera-collapse induced seismicity at Bárðarbunga central volcano, Iceland, and the aftershock sequence from a M5 earthquake at Mt. Kinabalu, northern Borneo. The modular nature of the workflow and wide range of automatic plotting options makes parameter choice straightforward, and robust event location uncertainty statistics facilitate filtering to produce a robust catalogue. QuakeMigrate also outputs phase picks and local magnitude estimates, with an architecture designed to promote further community-driven extension in future.
dc.rightsAttribution 4.0 International (CC BY 4.0)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectearthquake detection
dc.subjectearthquake location
dc.subjectseismology
dc.subjectvolcano seismology
dc.subjecticequakes
dc.subjectopen source software
dc.titleQuakeMigrate: a Modular, Open-Source Python Package for Automatic Earthquake Detection and Location
dc.typePresentation
dc.publisher.departmentDepartment of Earth Sciences
dc.date.updated2022-03-16T17:16:20Z
prism.publicationDate2020
dc.identifier.doi10.17863/CAM.83083
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0/
dc.contributor.orcidWinder, Tom [0000-0001-7047-8673]
rioxxterms.typeOther
pubs.conference-nameAmerican Geophysical Union Fall Meeting 2020
cam.depositDate2022-03-16
pubs.licence-identifierapollo-deposit-licence-2-1
pubs.licence-display-nameApollo Repository Deposit Licence Agreement


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

Attribution 4.0 International (CC BY 4.0)
Except where otherwise noted, this item's licence is described as Attribution 4.0 International (CC BY 4.0)