4D Deblending Using Sparse Inversion

Abstract Simultaneous-source seismic acquisition improves acquisition efficiency. However, strong blending interference poses challenges for deep and ultra-deep seismic exploration, where weak-signal preservation is critical. Most industrial sparse-inversion-based deblending methods operate in the three-dimensional (3D) common-receiver gather (CRG) domain. These methods process each CRG independently, without making use of signal coherence along the receiver-inline direction. Exploiting additional signal coherence in higher dimensions has the potential to improve seismic signal processing performance and weak-signal preservation. In this study, we develop a four-dimensional (4D) sparse-inversion-based deblending framework that exploits receiver-inline signal coherence. Here, 𠇄D” refers to a processing volume with dimensions of receiver-inline, source-inline, source-crossline, and time, rather than conventional time-lapse seismic. The proposed method jointly processes multiple neighboring CRGs from the same receiver line and employs a windowed 4D fast Fourier transform (FFT) to obtain a higher-dimensional sparse representation of the seismic wavefields. By incorporating receiver-inline coherence into the inversion, the 4D method provides a sparser representation of coherent seismic signals and helps separate weak signals from strong blending interference. Synthetic data and blended ocean-bottom-node (OBN) field data examples show that the proposed 4D method achieves better deblending performance compared with the 3D sparse-inversion-based method. These results indicate that using high-dimensional signal coherence can provide a simple and practical improvement to existing deblending workflows.

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Publication Details

Journal
Geophysics
Published
2026-10-14
DOI
https://doi.org/10.1190/geo-2026-1391
Primary Topic
Seismic Imaging and Inversion Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

4D Deblending Using Sparse Inversion

Tongtong Mo, Zhenhua Rui, Benfeng Wang
Geophysics
Seismic Imaging and Inversion Techniques
article

4D Deblending Using Sparse Inversion

Tongtong Mo, Zhenhua Rui, Benfeng Wang
article en

Abstract

Abstract Simultaneous-source seismic acquisition improves acquisition efficiency. However, strong blending interference poses challenges for deep and ultra-deep seismic exploration, where weak-signal preservation is critical. Most industrial sparse-inversion-based deblending methods operate in the three-dimensional (3D) common-receiver gather (CRG) domain. These methods process each CRG independently, without making use of signal coherence along the receiver-inline direction. Exploiting additional signal coherence in higher dimensions has the potential to improve seismic signal processing performance and weak-signal preservation. In this study, we develop a four-dimensional (4D) sparse-inversion-based deblending framework that exploits receiver-inline signal coherence. Here, 𠇄D” refers to a processing volume with dimensions of receiver-inline, source-inline, source-crossline, and time, rather than conventional time-lapse seismic. The proposed method jointly processes multiple neighboring CRGs from the same receiver line and employs a windowed 4D fast Fourier transform (FFT) to obtain a higher-dimensional sparse representation of the seismic wavefields. By incorporating receiver-inline coherence into the inversion, the 4D method provides a sparser representation of coherent seismic signals and helps separate weak signals from strong blending interference. Synthetic data and blended ocean-bottom-node (OBN) field data examples show that the proposed 4D method achieves better deblending performance compared with the 3D sparse-inversion-based method. These results indicate that using high-dimensional signal coherence can provide a simple and practical improvement to existing deblending workflows.

Geophysics
Tongji University (CN), China University of Petroleum, Beijing (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 17%
Seismic Imaging and Inversion Techniques
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