Phase spectrum estimation of the seismic wavelet is an important issue in high-resolution seismic data processing and interpretation. On the basis of two patterns of constant-phase rotation and root transform for wave...Phase spectrum estimation of the seismic wavelet is an important issue in high-resolution seismic data processing and interpretation. On the basis of two patterns of constant-phase rotation and root transform for wavelet phase spectrum variation, we introduce six sparse criteria, including Lu’s improved kurtosis criterion, the parsimony criterion, exponential transform criterion, Sech criterion, Cauchy criterion, and the modified Cauchy criterion, to phase spectrum estimation of the seismic wavelet, obtaining an equivalent effect to the kurtosis criterion. Through numerical experiments, we find that when the reflectivity is not a sparse sequence, the estimated phase spectrum of the seismic wavelet based on the criterion function will deviate from the true value. In order to eliminate the influence of non-sparse reflectivity series in a single trace, we apply the method to the multi-trace seismogram, improving the accuracy of seismic wavelet phase spectrum estimation.展开更多
This paper puts forward wavelet transform method to identify P and S phases in three component seismograms using polarization information contained in the wavelet transform coefficients of signal. The P and S wave loc...This paper puts forward wavelet transform method to identify P and S phases in three component seismograms using polarization information contained in the wavelet transform coefficients of signal. The P and S wave locator functions are constructed by using eigenvalue analysis method to wavelet transform coefficient across several scales. Locator functions formed by wavelet transform have stated noise resistance capability, and is proved to be very effective in identifying the P and S arrivals of the test data and actual earthquake data.展开更多
基金supported by the Major Basic Research Development Program of China (973 Project No. 2007CB209608)
文摘Phase spectrum estimation of the seismic wavelet is an important issue in high-resolution seismic data processing and interpretation. On the basis of two patterns of constant-phase rotation and root transform for wavelet phase spectrum variation, we introduce six sparse criteria, including Lu’s improved kurtosis criterion, the parsimony criterion, exponential transform criterion, Sech criterion, Cauchy criterion, and the modified Cauchy criterion, to phase spectrum estimation of the seismic wavelet, obtaining an equivalent effect to the kurtosis criterion. Through numerical experiments, we find that when the reflectivity is not a sparse sequence, the estimated phase spectrum of the seismic wavelet based on the criterion function will deviate from the true value. In order to eliminate the influence of non-sparse reflectivity series in a single trace, we apply the method to the multi-trace seismogram, improving the accuracy of seismic wavelet phase spectrum estimation.
基金supported by National Key Basic Research Development Program (Grant No. 2007CB209600)National Major Science and Technology Program (Grant No. 2008ZX05010-002)
文摘This paper puts forward wavelet transform method to identify P and S phases in three component seismograms using polarization information contained in the wavelet transform coefficients of signal. The P and S wave locator functions are constructed by using eigenvalue analysis method to wavelet transform coefficient across several scales. Locator functions formed by wavelet transform have stated noise resistance capability, and is proved to be very effective in identifying the P and S arrivals of the test data and actual earthquake data.
