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

Abstract

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.