Mitigating Mediterranean Sea Data Challenges before Imaging-Case Study

Recent large-scale 3D seismic acquisitions across the Mediterranean Sea, acquired with multisensor broadband and triple-source configurations, present new processing challenges including overlapping shots, complex multiples, and strong P–S conversions from Messinian salt. We propose an integrated workflow that combines machine-learning denoise for stable inputs, FISTA deblending for triple-source separation, and advanced demultiple approaches such as SRME, wavefield extrapolation, and SWIM for near-offset reconstruction. A modelling-based attenuation strategy further suppresses converted modes, enhancing sub-salt imaging. A case study offshore Egypt demonstrates significant improvements in noise suppression, multiple attenuation, and converted-wave removal, delivering efficient, high-quality imaging.