Seismic P Phase Picking Using a Kurtosis-Based Criterion in the Stationary Wavelet Domain

The seismic P phase first arrival identification is a fundamental problem in seismology. The accurate identification of the P -wave first arrival is not a trivial process, particularly when the seismograms present a very low signal-to-noise ratio (SNR) or are contaminated with artificial transients...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2008-11, Vol.46 (11), p.3815-3826
Main Authors: Galiana-Merino, J.J., Rosa-Herranz, J.L., Parolai, S.
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Applied geophysics
Discrete wavelet transforms
Earth sciences
Earth, ocean, space
Earthquakes, seismology
Event detection
Exact sciences and technology
Higher order statistics
Internal geophysics
Kurtosis
P phase identification
seismic signal processing
Seismology
Signal processing algorithms
Signal to noise ratio
stationary wavelet transform (SWT)
Wavelet analysis
Wavelet domain
Wavelet transforms
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Summary:The seismic P phase first arrival identification is a fundamental problem in seismology. The accurate identification of the P -wave first arrival is not a trivial process, particularly when the seismograms present a very low signal-to-noise ratio (SNR) or are contaminated with artificial transients that could produce false alarms. In this paper, a new approach based on higher order statistics and the stationary wavelet transform is presented. The P onset is obtained under a statistical criterion applied in the time-frequency domain. The results have been compared to those estimated by another P phase picking algorithm and P onsets picked by expert analysts. The comparison shows that our proposed method efficiently provides a good estimate of the P onset picks that are consistent with analyst picks, particularly in cases of very low SNR.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2008.2002647