Wavelet transform methods for phase identification in three-component seismograms

We apply the wavelet transform to seismic signals for the purpose of automatically identifying the P and S phase arrivals of seismic events. In this article, an algorithm is presented that locates these arrivals in single-station three-component short-period seismograms using polarization and amplitude information contained in the wavelet transform coefficients of the signals. The main idea is that strong features of the seismic signal appear in the wavelet coefficients across several scales. The first step in the algorithm is the wavelet decomposition of each component of a three-component short-period seismogram. The resulting multi-scalar representation is used to construct “locator” functions that identify the P and S arrivals. The P locator function is constructed by using polarization information across scales, and the S locator function is constructed using transverse over radial amplitude information across scales. These functions prove to be very effective at identifying the important P and S arrivals in the test data. The results are compared with arrival times picked by an analyst.

[1]  Jelena Kovacevic,et al.  Wavelets and Subband Coding , 2013, Prentice Hall Signal Processing Series.

[2]  N. Ricker The Form and Laws of Propagation of Seismic Wavelets , 1951 .

[3]  R. A. Fowler,et al.  Polarization analysis of natural and artificially induced geomagnetic micropulsations , 1967 .

[4]  Kiyoshi Yomogida,et al.  Detection of anomalous seismic phases by the wavelet transform , 1994 .

[5]  Stéphane Mallat,et al.  Characterization of Signals from Multiscale Edges , 2011, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Frank L. Vernon,et al.  Frequency dependent polarization analysis of high‐frequency seismograms , 1987 .

[7]  A. Grossmann,et al.  DECOMPOSITION OF HARDY FUNCTIONS INTO SQUARE INTEGRABLE WAVELETS OF CONSTANT SHAPE , 1984 .

[8]  Ingrid Daubechies,et al.  Ten Lectures on Wavelets , 1992 .

[9]  Paul G. Richards,et al.  Quantitative Seismology: Theory and Methods , 1980 .

[10]  R. Wiggins Minimum entropy deconvolution , 1978 .

[11]  O. Rioul,et al.  Wavelets and signal processing , 1991, IEEE Signal Processing Magazine.

[12]  Peter M. Shearer,et al.  Characterization of global seismograms using an automatic-picking algorithm , 1994, Bulletin of the Seismological Society of America.

[13]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Martin Vetterli,et al.  Wavelets and filter banks: theory and design , 1992, IEEE Trans. Signal Process..

[15]  J. Means Use of the three‐dimensional covariance matrix in analyzing the polarization properties of plane waves , 1972 .

[16]  Olivier Rioul Regular wavelets: a discrete-time approach , 1993, IEEE Trans. Signal Process..

[17]  S. P. Jarpe,et al.  Performance of high-frequency three-component stations for azimuth estimation from regional seismic phases , 1991 .

[18]  N. Magotra,et al.  Single-station seismic event detection and location , 1989 .

[19]  J. Morlet,et al.  Wave propagation and sampling theory—Part I: Complex signal and scattering in multilayered media , 1982 .

[20]  E. R. Kanasewich,et al.  Time sequence analysis in geophysics , 1973 .

[21]  N. Ricker THE FORM AND NATURE OF SEISMIC WAVES AND THE STRUCTURE OF SEISMOGRAMS , 1940 .

[22]  R. Haddad,et al.  Multiresolution Signal Decomposition: Transforms, Subbands, and Wavelets , 1992 .

[23]  D. Okaya,et al.  Frequency‐time decomposition of seismic data using wavelet‐based methods , 1995 .

[24]  A. Grossmann,et al.  Cycle-octave and related transforms in seismic signal analysis , 1984 .

[25]  Randy K. Young Wavelet theory and its applications , 1993, The Kluwer international series in engineering and computer science.