Nonlinear Bayesian estimation of centroid moment tensors using multiple seismic data sets in the Kiskatinaw seismic monitoring and mitigation area
Date
2022-12-22
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Abstract
Centroid moment tensor (CMT) parameters of earthquakes are routinely estimated to gain information on structures and regional tectonics. However, for small earthquakes (M<4) it is still challenging to determine CMTs due to the lack of high-quality waveform data. In this study, we propose to improve solutions for small earthquakes by incorporating multiple seismic data types in Bayesian joint inversion: polarities picked on broadband signals, amplitude spectra for intermediate frequency bands (0.2--2.0 Hz), and waveforms at low frequencies (0.05--0.2 Hz). Both measurement and theory errors are accounted for by iterative estimation of non-Toeplitz covariance matrices, allowing to objectively determine weights for the different data types in the joint parameter estimation. Validity and applicability of the method are demonstrated on simulation and field data. Results demonstrate that the combination of data, such as a single high quality waveform, a few amplitude spectra and many waveform polarities are able to resolve CMT parameters to comparable quality as if many high quality waveforms were available.
Results of 10 induced events that occurred in northeastern British Columbia between January 2020 and February 2022 indicate predominant strike slip focal mechanisms with low non double-couple components. These events appear to be located at shallow depth with a short duration as expected for induced seismicity. These results are consistent with previous studies. Therefore, we learn that this method reduces the dependency of source inversion on high-quality waveforms and permits to resolve CMTs for earthquakes as small as ML 1.6.
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Keywords
Earthquake source observation, Induced seismicity, Computational seismology, Bayseian joint interference, Dynamics and mechanics of faulting
Citation
Hamidbeygi, M. (2022). Nonlinear Bayesian estimation of centroid moment tensors using multiple seismic data sets in the Kiskatinaw seismic monitoring and mitigation area (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.