Open AccessPolarization analysis in the wavelet domain based on the adaptive covariance method
Author(s) -
Kulesh M.,
Diallo M. S.,
Holschneider M.,
Kurennaya K.,
Krüger F.,
Ohrnberger M.,
Scherbaum F.
Publication year - 2007
Publication title -
geophysical journal international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.302
H-Index - 168
eISSN - 1365-246X
pISSN - 0956-540X
DOI - 10.1111/j.1365-246x.2007.03417.x
Subject(s) - wavelet , covariance , covariance matrix , algorithm , time domain , frequency domain , polarization (electrochemistry) , time–frequency analysis , computer science , wavelet transform , mathematics , mathematical analysis , artificial intelligence , statistics , filter (signal processing) , computer vision , chemistry
SUMMARY We present an improved method for computing polarization attributes of particle motion from multicomponent seismic recordings in the time–frequency domain by using the continuous wavelet transform. This method is based on the analysis of the covariance matrix. We use an approximate analytical formula to compute the elements of the covariance matrix for a time window which is derived from an averaged instantaneous frequency of the multicomponent record. The length of the time‐window is automatically and adaptively set to match the dominant period of the analysing wavelet at each time–frequency point. Then the eigenparameters are estimated for each time–frequency point without interpolation. With these key features, our method provides a suitable approach for polarization analysis of dispersive signals or overlapping seismic arrivals in multicomponent seismic data. For polarization analysis in the time domain, we show that the proposed method is consistent with existing polarization analysis methods. We apply the method to real data sets from exploration and earthquake seismology to illustrate some filtering applications and wave type characterizations.