Sparse land seismic data, when acquired in areas with sand and detrital materials overlying faster velocity strata, are often marred by intense near-surface noise moving at slow speeds. This noise persists, even with the fine source and receiver spacing of high-channel-count 3D surveys, leading to aliasing issues. Traditional velocity-based filtering, whether in the frequency-wavenumber (f-k) or radon domains, is ineffective at removing this noise during data processing. Addressing the aliasing of slow near-surface noise through proper regularization before denoising can significantly enhance data quality. We introduce a novel approach called full-wavefield regularization and present its application for the first time on a sparse 3D low-fold offshore seismic data set. This technique aims to regularize both the seismic signals and coherent noise wave trains to a spacing where aliasing is not an issue. Consequently, the reflection and surface-wave components can be easily distinguished, and the noise can be eliminated. The results depict a marked improvement in the signal-to-noise ratio. This makes the data set usable and improves the computation of high-quality seismic attributes such as coherence and curvature, which supports better interpretation of the seismic data.

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