Multiple attenuation of oceanic seismic signals is a critical step in enhancing the quality, resolution, and interpretability of subsurface images. Surface-related multiples, generated by repeated reflections of seismic waves at the water surface, often interfere with primary reflections, producing noise and potentially distorting significant geological features. These multiples, if not properly identified and suppressed, can lead to inaccurate interpretations, reduce the reliability of seismic analyses, and hinder effective exploration and mapping of subsurface structures. Therefore, accurate detection, prediction, and attenuation of surface-related multiples are essential for producing high-quality seismic datasets that can be reliably used in geological and geophysical research, reservoir characterization, and resource assessment.

The most commonly used techniques for suppressing surface-related multiples are Surface-Related Multiple Elimination (SRME) and Shallow Water Demultiple (SWD). SRME is a data-intensive approach that models and predicts surface-related multiples directly from recorded seismic data, without requiring detailed knowledge of subsurface structures. This method is particularly effective in complex geological settings and deep-water environments, where multiple generation is irregular, unpredictable, and highly variable. SWD, in contrast, is specifically optimized for shallow water conditions and exploits the unique wave propagation characteristics of these environments to efficiently suppress multiples. Both techniques possess distinct advantages and limitations, and their effectiveness depends on factors such as water depth, acquisition geometry, and the physical and geometrical characteristics of the recorded data.

This study focuses on three-dimensional (3D) marine seismic data, providing a detailed review of the mathematical models, algorithmic frameworks, and performance of both SRME and SWD. Key operational parameters, including filter lengths, operator design, adaptive weighting, and iterative processing strategies, are carefully optimized to maximize multiple attenuation while preserving the fidelity of primary signals. Comparative analyses on real 3D datasets indicate that a well-integrated application of SRME and SWD significantly outperforms the use of either method individually. This combined approach not only enhances the signal-to-noise ratio but also improves the overall interpretability of seismic images, enabling more accurate identification and mapping of subsurface geological features. Such precision is vital for exploration, reservoir evaluation, and informed decision-making in marine environments.

Overall, this research provides a practical and detailed guide for geophysicists, seismic data processors, and exploration professionals on how to effectively integrate SRME and SWD methodologies. Implementation of these strategies improves the final quality of seismic data, reduces artifacts caused by surface multiples, and enhances the reliability of subsurface interpretations. By adopting this recommended workflow, practitioners can achieve more precise seismic imaging, make better-informed exploration and development decisions, and fully utilize high-quality 3D marine seismic data for both scientific and industrial purposes. The study underscores the importance of comprehensive multiple attenuation workflows as a fundamental step toward producing reliable, interpretable, and high-fidelity seismic results in complex marine environments.