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Multiple attenuation plays a critical role in offshore wind farm site selection, as it helps in improving the accuracy of seismic data. However, conventional methods like CL-SRME often struggle with complex geological conditions due to their assumption of uniform wavelets. To overcome this limitation, we propose an enhanced CL-SRME framework that integrates a multi-channel surface correlation operator to account for spatial wavelet variability. This innovation improves inversion stability by preserving wavelet continuity and incorporates a low-rank approximation-based denoising engine within a Regularization by Denoising (RED) inversion strategy. Additionally, we introduce an advanced ADMM algorithm to optimize computational efficiency in the face of noisy, challenging geological scenarios. The effectiveness of our approach is validated using field data, demonstrating substantial improvements in seismic data processing. Our method not only enhances the identification of geological features but also significantly contributes to more accurate marine seabed surveys, offering valuable insights for offshore wind farm site selection and other subsea exploration applications.