Damped multichannel singular spectrum analysis for diffraction separation based on the Cook-distance

Diffraction seismic exploration is a crucial technique for enhancing the lateral resolution of small-scale geological structure imaging. Diffracted waves in conventional seismic records can be obscured by stronger energy reflected waves, making it necessary to separate these two wavefields for imaging purposes. Damped multi-channel singular spectrum analysis(DMSSA)is a rank-constrained denoising method that separates wavefields by decomposing the seismic data into a Hankel matrix and performing singular value decomposition. In this process,reflected and diffracted waves correspond to larger and smaller singular values respectively. However,this method relies on manually determining the rank of the reflected wavefield,which is impractical for processing large volumes of seismic data. To address the issue of manual selection, this paper proposes using Cook - distance to automatically calculate the rank of the reflected wavefield. By combining Cook - distance with the DMSSA algorithm,this paper achieved effective separation of reflected and diffracted waves. Experiments on common-shot gathers and post-stack data demonstrate that this method can successfully obtain high-quality diffraction wavefields,highlighting the effectiveness of the proposed approach. © 2024 Editorial office of Oil Geophysical Prospecting. All rights reserved.