Estimation of seismic quality factor in the time-frequency domain using variational mode decomposition

Seismic attenuation as represented by the seismic quality factor Q has a substantial impact on seismic reflection data. To effectively eliminate the interference of reflection coefficients for Q estimation, a new method is proposed based on the stationary convolutional model of a seismic trace using variational mode decomposition (VMD). VMD is conducted on the logarithmic spectra extracted from the time-frequency distribution of the seismic reflection data generated from the generalized S transform. For the intrinsic mode functions after VMD, mutual information and correlation analysis are used to reconstruct the signals, which effectively eliminates the influence of the reflection coefficients. The difference between the two reconstructed logarithmic spectra within the selected frequency band produces a better linear property, and it is more suitably approximated with the linear function compared to the conventional spectral-ratio method. Least-squares fitting is finally applied for Q estimation. Application of this method to synthetic and real data examples demonstrates the stabilization and accuracy for Q estimation.