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Processing automatic seismic event detections: an iterative sorting algorithm improving earthquake hypocentres using interevent cross-correlation
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Geophysics.
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Geophysics.ORCID iD: 0000-0002-2511-187X
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Geophysics.
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Geophysics.
2019 (English)In: Geophysical Journal International, ISSN 0956-540X, E-ISSN 1365-246X, Vol. 219, no 2, p. 1268-1280Article in journal (Refereed) Published
Abstract [en]

We present an iterative classification scheme using interevent cross-correlation to update an existing earthquake catalogue with similar events from a list of automatic seismic event detections. The algorithm automatically produces catalogue quality events, with improved hypocentres and reliable P- and S-arrival time information. Detected events are classified into four event categories with the purpose of using the top category, with the highest assessed event quality and highest true-to-false ratio, directly for local earthquake tomography without additional manual analysis. The remaining categories have varying proportions of lower quality events, quality being defined primarily by the number of observed phase onsets, and can be viewed as different priority groups for manual inspection to reduce the time spent by a seismic analyst. A list of 3348 event detections from the geothermally active volcanic region around Hengill, southwest Iceland, produced by our migration and stack detector (Wagner et al. 2017), was processed using a reference catalogue of 1108 manually picked events from the same area. P- and S-phase onset times were automatically determined for the detected events using correlation time lags with respect to manually picked phase arrivals from different multiple reference events at the same station. A significant improvement of the initial hypocentre estimates was achieved after relocating the detected events using the computed phase onset times. The differential time data set resulting from the correlation was successfully used for a double-difference relocation of the final updated catalogue. The routine can potentially be implemented in real-time seismic monitoring environments in combination with a variety of seismic event/phase detectors.

Place, publisher, year, edition, pages
2019. Vol. 219, no 2, p. 1268-1280
National Category
Geophysics
Identifiers
URN: urn:nbn:se:uu:diva-376655DOI: 10.1093/gji/ggz362ISI: 000491050200039OAI: oai:DiVA.org:uu-376655DiVA, id: diva2:1286822
Funder
Swedish Research Council, 2008:3754Available from: 2019-02-07 Created: 2019-02-07 Last updated: 2020-01-03Bibliographically approved
In thesis
1. Toward fully automatic earthquake detection and processing for tomography in the Hengill area
Open this publication in new window or tab >>Toward fully automatic earthquake detection and processing for tomography in the Hengill area
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis focuses on the automation of seismic data analysis, in particular, event detection, quality assessment of detected events, and preparation of an earthquake catalogue for seismic tomography.

The developed event detector uses back-propagation and stacking of a seismic trace attribute with a known velocity model to detect and locate events. A four-dimensional volume in space and time is probed for local maxima of coherently stacking signals. These local maxima define event location and origin time. Application of the detection algorithm to data from a dense 26-station 3-component seismic network in the Hengill area, SW Iceland, produced an increased true-to-false detection ratio compared to the local detection routine.

The detected events were analysed using inter-event cross-correlation with a manually picked reference catalogue to determine their similarity with real events. Automatic P- and S-phase picks were derived using the time delay information from highly correlated events. Relocation with the determined phase picks improves hypocentre uncertainty. A multi-stage selection process is implemented to categorise the detected events into different classes of varying priority for a potential manual analysis. Depending on the used parameters, the top quality category of events can be used in e.g. local-earthquake tomography without manual inspection. Iterative application of the algorithm improved the reference catalogue by almost 40% with events of at least equal quality.

The final local-earthquake tomography with the updated reference catalogue confirms the success of the implemented workflow. The resulting Vp, Vs, and Vp/Vs models show structures that can be associated with the local geothermal activity. A higher resolution and extended ray coverage was achieved compared to previous tomographic studies. Double-difference location of the events using differential times from waveform correlation significantly improved event hypocentres revealing detailed fault geometry in the known seismicity pattern. A preliminary double-difference tomography shows promising results for high resolution imaging.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2019. p. 53
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1774
Keywords
Earthquake detection, local-earthquake tomography, Iceland, induced seismicity, geothermal activity
National Category
Geophysics
Research subject
Geophysics with specialization in Seismology
Identifiers
urn:nbn:se:uu:diva-376658 (URN)978-91-513-0574-5 (ISBN)
Public defence
2019-03-28, Hambergsalen, Villavägen 16, Uppsala, 13:00 (English)
Opponent
Supervisors
Available from: 2019-03-05 Created: 2019-02-08 Last updated: 2019-03-18

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