Seismic Data Deblending by Block Matching and Sparse 3-D Transform | IEEE Journals & Magazine | IEEE Xplore

Seismic Data Deblending by Block Matching and Sparse 3-D Transform


Abstract:

Simultaneous source acquisition can reduce survey time and expense. Deblending is a typical method for processing simultaneous source seismic data, which is achieved by r...Show More

Abstract:

Simultaneous source acquisition can reduce survey time and expense. Deblending is a typical method for processing simultaneous source seismic data, which is achieved by removing as much blending noise as feasible while maintaining as much useful signal as possible. We propose a novel deblending method with the shaping regularization-based iterative framework in the sparse 3-D transform domain in this letter. The core concept behind this method is to process the 2-D blended data block by block. Using the block-matching technique, we can extract similar blocks from the pseudo-deblended data and then put these 2-D blocks together to make 3-D arrays. The arrays are then transformed to the sparse 3-D transform domain to eliminate blending noise. Due to the correlation between similar blocks, the signal can be represented with greater sparsity in the 3-D transform domain than in the conventional 2-D transform domain. It is this sparsity that threshold shrinkage can be particularly successful at attenuating blending noise while retaining the characteristics of useful signals. To get the final deblended seismic data, the overlapping deblended blocks are restored to their original places and combined using a specific averaging procedure. To verify the practicability of our method, we test it with noisy blended data. The experimental results indicate that our approach can effectively remove blending and white Gaussian noise.
Published in: IEEE Geoscience and Remote Sensing Letters ( Volume: 20)
Article Sequence Number: 7504505
Date of Publication: 07 August 2023

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