Data-driven interferometry method to remove spatially aliased and non-linear surface waves

We propose a data-driven interferometry technique to remove low frequency aliased and non-conical surface waves in cross-spread domain. Despite insufficient sampling of the constructive regions in the cross-spread domain, the proposed approach has been designed for effectively handling any kind of 3D sparse geometry from Narrow to Wide-Azimuth land data using prior regularization and/or densification. This implementation provides a cost-effective workflow for large datasets and produces good removal of spatially aliased non-linear surface waves with minimal primary leakage as observed in a sparse acquisition land survey where the characteristics of the surface waves vary strongly.