In order to suppress the surface wave in three-component seismic exploration, according to the polarization characteristics of body wave and surface wave, a time-frequency domain polarization filtering method based on...In order to suppress the surface wave in three-component seismic exploration, according to the polarization characteristics of body wave and surface wave, a time-frequency domain polarization filtering method based on wavelet transform was studied. A covariance matrix was constructed in the time-frequency domain for the three-component seismic data, measured the polarization parameters of seismic waves. Combining the corresponding eigenvalues and eigenvectors of the matrix, the elliptic rate and elevation angle were used as constraints, and the polarization filter function was built to separate the surface waves. The separated surface waves were inversely transformed and then were adaptively subtracted from the original records. After the polarization filtering suppressed the surface wave, the signal-to-noise ratio of the converted wave was effectively improved. It laid a good foundation for the next seismic data processing and seismic exploration development. The actual data processing results show that the method can effectively extract surface waves from three-component seismic records and avoid the interference of surface waves on seismic signals.展开更多
文摘In order to suppress the surface wave in three-component seismic exploration, according to the polarization characteristics of body wave and surface wave, a time-frequency domain polarization filtering method based on wavelet transform was studied. A covariance matrix was constructed in the time-frequency domain for the three-component seismic data, measured the polarization parameters of seismic waves. Combining the corresponding eigenvalues and eigenvectors of the matrix, the elliptic rate and elevation angle were used as constraints, and the polarization filter function was built to separate the surface waves. The separated surface waves were inversely transformed and then were adaptively subtracted from the original records. After the polarization filtering suppressed the surface wave, the signal-to-noise ratio of the converted wave was effectively improved. It laid a good foundation for the next seismic data processing and seismic exploration development. The actual data processing results show that the method can effectively extract surface waves from three-component seismic records and avoid the interference of surface waves on seismic signals.
