Hodogram analysis and back-azimuth projection is one method used for mapping microseismic hypocenter locations in a homogeneous isotropic velocity field. The method works well when the input microseismograms have high signal-to noise ratios. However, when there are high levels of random noise on the raw seismograms, the mapping accuracy decreases significantly. To suppress noise and increase signal-to-noise ratios (SNRs) before hodogram/back-azimuth analysis, we applied frequency domain filtering, time domain windowing, trace averaging, and signal-noise separation (NSS). After noise suppression, the back-azimuth method coupled with statistical averaging of raypath intersections produces reasonably accurate hypocenter locations.
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