A Wavelet Transform Method to Detect P and S-Phases in Three Component Seismic Data

Affiliation(s)

Earthquake Monitoring Center, Sultan Qaboos University, Muscat, Oman.

University of Newcastle upon Tyne, Newcastle upon Tyne, UK.

Institute of Geophysics and Planetary Physics, University of California, San Diego, USA.

Earthquake Monitoring Center, Sultan Qaboos University, Muscat, Oman.

University of Newcastle upon Tyne, Newcastle upon Tyne, UK.

Institute of Geophysics and Planetary Physics, University of California, San Diego, USA.

Abstract

The discrete time wavelet transform has been used to develop software that detects seismic P and S-phases. The detection algorithm is based on the enhanced amplitude and polarization information provided by the wavelet transform coefficients of the raw seismic data. The algorithm detects phases, determines arrival times and indicates the seismic event direction from three component seismic data that represents the ground displacement in three orthogonal directions. The essential concept is that strong features of the seismic signal are present in the wavelet coefficients across several scales of time and direction. The P-phase is detected by generating a function using polarization information while S-phase is detected by generating a function based on the transverse to radial amplitude ratio. These functions are shown to be very effective metrics in detecting P and S-phases and for determining their arrival times for low signal-to-noise arrivals. Results are compared with arrival times obtained by a human analyst as well as with a standard STA/LTA algorithm from local and regional earthquakes and found to be consistent.

The discrete time wavelet transform has been used to develop software that detects seismic P and S-phases. The detection algorithm is based on the enhanced amplitude and polarization information provided by the wavelet transform coefficients of the raw seismic data. The algorithm detects phases, determines arrival times and indicates the seismic event direction from three component seismic data that represents the ground displacement in three orthogonal directions. The essential concept is that strong features of the seismic signal are present in the wavelet coefficients across several scales of time and direction. The P-phase is detected by generating a function using polarization information while S-phase is detected by generating a function based on the transverse to radial amplitude ratio. These functions are shown to be very effective metrics in detecting P and S-phases and for determining their arrival times for low signal-to-noise arrivals. Results are compared with arrival times obtained by a human analyst as well as with a standard STA/LTA algorithm from local and regional earthquakes and found to be consistent.

Keywords

Discrete Time Wavelet Transform; P and S-phases; Automatic Detection; Rectilinearity Function

Discrete Time Wavelet Transform; P and S-phases; Automatic Detection; Rectilinearity Function

Cite this paper

S. Al-Hashmi, A. Rawlins and F. Vernon, "A Wavelet Transform Method to Detect P and S-Phases in Three Component Seismic Data,"*Open Journal of Earthquake Research*, Vol. 2 No. 1, 2013, pp. 1-20. doi: 10.4236/ojer.2013.21001.

S. Al-Hashmi, A. Rawlins and F. Vernon, "A Wavelet Transform Method to Detect P and S-Phases in Three Component Seismic Data,"

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