2017
DOI: 10.1093/gji/ggx520
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A comparison of earthquake backprojection imaging methods for dense local arrays

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Cited by 26 publications
(35 citation statements)
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“…For example, McMechan et al (1985) preprocess the earthquake waveforms to construct a true amplitude section by filtering and extrapolating waveforms with a given velocity model. Beskardes et al (2018) compare three methods (envelope, short-term averaging/ long-term averaging, and kurtosis) to regularize the waveform as an input of waveform-based source imaging.…”
Section: Discussionmentioning
confidence: 99%
“…For example, McMechan et al (1985) preprocess the earthquake waveforms to construct a true amplitude section by filtering and extrapolating waveforms with a given velocity model. Beskardes et al (2018) compare three methods (envelope, short-term averaging/ long-term averaging, and kurtosis) to regularize the waveform as an input of waveform-based source imaging.…”
Section: Discussionmentioning
confidence: 99%
“…Increasing the array's density by a factor of 10 allows us to recover the location of events as small as M ≈ 0:8. Our method focuses energy envelopes onto the source and is hence relatively robust against small errors in the velocity model (Beskardes et al, 2018). However, scattering from small-scale heterogeneities or at layer interfaces may introduce artifacts to backprojection images.…”
Section: Discussionmentioning
confidence: 99%
“…Trojanowski and Eisner () tested the performance of several CFs with diffraction stacking and cross‐correlation stacking operators, showed the semblance and cross‐correlation stacking have better enhancement of the quality of the stacking profiles, and demonstrated that accounting for the source mechanism by polarization correction improves most efficiently the capability of noise suppression and retrieving weak microseismic events. Beskardes et al () compared the performance of envelope, STA/LTA, and kurtosis with raw waveforms for local earthquakes detection and location. The comparative study showed for an aftershock sequence that stacking of kurtosis waveforms produced the most robust results for detecting the weak events, while stacking of raw waveforms had the best spatial resolution and retrieved magnitude.…”
Section: Methodologiesmentioning
confidence: 99%
“…The comparative study showed for an aftershock sequence that stacking of kurtosis waveforms produced the most robust results for detecting the weak events, while stacking of raw waveforms had the best spatial resolution and retrieved magnitude. Therefore, a two‐phase backprojection imaging process is suggested (Beskardes et al, ): backprojection of kurtosis waveforms for event detection and location within large data volumes, followed by backprojection of raw seismograms of the previously detected events to improve the location accuracy and obtain more reliable magnitudes. A sketch of the principle for PWS methods is shown in Figure .…”
Section: Methodologiesmentioning
confidence: 99%
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