A Ghost Wave Suppression Method for Towed Cable Data Based on the Hybrid LSMR

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Bibliografske podrobnosti
izdano v:Processes vol. 13, no. 11 (2025), p. 3689-3708
Glavni avtor: Wang Zhaoqi
Drugi avtorji: Li, Ya, Sun Zhixue, Li, Zhonghua, Ge Dongsheng
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MDPI AG
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100 1 |a Wang Zhaoqi  |u Hangzhou Research Institute of Geology, PetroChina, Hangzhou 310023, China; wangzq_hz@petrochina.com.cn 
245 1 |a A Ghost Wave Suppression Method for Towed Cable Data Based on the Hybrid LSMR 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a In marine seismic exploration, ghost waves distort reflection waveforms and narrow the frequency band of seismic records. Traditional deghosting methods are susceptible to practical limitations from sea surface fluctuations and velocity variations. This paper proposes a τ-p domain deghosting method based on the Hybrid Least Squares Residual (HyBR LSMR) algorithm. We first establish a linear forward model in the τ-p domain that describes the relationship between the total wavefield and upgoing wavefield, transforming deghosting into a linear inverse problem. The method then employs the hybrid LSMR algorithm with Tikhonov regularization to address the inherent ill-posedness. A key innovation is the integration of the Generalized Cross Validation (GCV) criterion to adaptively determine regularization parameters and iteration stopping points, effectively avoiding the semi-convergence phenomenon and enhancing solution stability. Applications to both synthetic and field data demonstrate that the proposed method effectively suppresses ghost waves under various acquisition conditions, significantly improves the signal-to-noise ratio and resolution, broadens the effective frequency band, and maintains good computational efficiency, providing a reliable solution for high-precision seismic data processing in complex marine environments. 
653 |a Marine environment 
653 |a Regularization 
653 |a Waveforms 
653 |a Data processing 
653 |a Cables 
653 |a Algorithms 
653 |a Seismic exploration 
653 |a Wave reflection 
653 |a Inverse problems 
653 |a Sensors 
653 |a Seawater 
653 |a Frequencies 
653 |a Regularization methods 
653 |a Linear equations 
653 |a Signal to noise ratio 
700 1 |a Li, Ya  |u Research Institute of Exploration and Development, Southwest Oil & Gasfield Company, PetroChina, Chengdu 610400, China 
700 1 |a Sun Zhixue  |u School of Petroleum Engineering, China University of Petroleum, Qingdao 266580, China; upcszx@upc.edu.cn (Z.S.); s23020068@s.upc.edu.cn (Z.L.) 
700 1 |a Li, Zhonghua  |u School of Petroleum Engineering, China University of Petroleum, Qingdao 266580, China; upcszx@upc.edu.cn (Z.S.); s23020068@s.upc.edu.cn (Z.L.) 
700 1 |a Ge Dongsheng  |u CN00C Energy Technology & Services Limited, Shanghai 200335, China; gedsh3@cnooc.com.cn 
773 0 |t Processes  |g vol. 13, no. 11 (2025), p. 3689-3708 
786 0 |d ProQuest  |t Materials Science Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3275550398/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3275550398/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3275550398/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch