Velocity analysis of noisy seismic data based on RSVD weighted semblance

Abstract

The accuracy of velocity spectrum affects the subsequent processing of seismic data. Though the singular value decomposition (SVD) weighted semblance has a higher velocity resolution than conventional semblance, its performance is degraded for noisy seismic data. A rectified SVD weighted semblance method (RSVD), aiming to improve the accuracy of velocity spectrum for seismic data contaminated by noise, is proposed. In this approach, the weighting function is constructed from the first two singular values and their mean square error obtained via SVD of noisy seismic data after normal moveout (NMO) with scanning velocity. Synthetic and field examples demonstrate that the proposed method performs better than the SVD weighted semblance in enhancing the accuracy of velocity spectra for noisy near-offset common midpoint gathers in layered isotropic media.