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Studies of earthquakes and microearthquakes using near-field seismic and geodetic observations

The Centroid-Moment Tensor (CMT) method allows an optimal point-source description of an earthquake to be recovered from a set of seismic observations, and, for over 30 years, has been routinely applied to determine the location and source mechanism of teleseismically recorded earthquakes. The CMT approach is, however, entirely general: any measurements of seismic displacement fields could, in theory, be used within the CMT inversion formulation, so long as the treatment of the earthquake as a point source is valid for that data. We modify the CMT algorithm to enable a variety of near-field seismic observables to be inverted for the source parameters of an earthquake. The first two data types that we implement are provided by Global Positioning System receivers operating at sampling frequencies of 1,Hz and above. When deployed in the seismic near field, these instruments may be used as long-period-strong-motion seismometers, recording displacement time series that include the static offset. We show that both the displacement waveforms, and static displacements alone, can be used to obtain CMT solutions for moderate-magnitude earthquakes, and that performing analyses using these data may be useful for earthquake early warning. We also investigate using waveform recordings - made by conventional seismometers deployed at the surface, or by geophone arrays placed in boreholes - to determine CMT solutions, and their uncertainties, for microearthquakes induced by hydraulic fracturing. A similar waveform inversion approach could be applied in many other settings where induced seismicity and microseismicity occurs.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:581382
Date January 2013
CreatorsO'Toole, Thomas Bartholomew
ContributorsWoodhouse, John
PublisherUniversity of Oxford
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttp://ora.ox.ac.uk/objects/uuid:9dcaca2e-c141-4e8a-94f6-34a9ff50d061

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