Since the introduction of dip moveout (DMO), various authors have extensively explored its amplitude and phase accuracy, the effects of variable velocity, operator aliasing, discretization, and computational efficiency. A lens familiar aspect of DMO that is often of crucial importance in everyday seismic data processing is the effect of sparse or irregular spatial sampling on DMO-processed data. While different facets of the problem have been addressed (see e.g., Black and Schleicher, 1989; Ronen, 1987; and Williams and Marcoux, 1989), a comprehensive, accurate, and efficient solution to the problem is still needed. In this paper, we propose a method based on the decomposition of DMO into its constituent dip components that accounts for the effects of irregular spatial sampling for both flat and dipping events, can be applied to any 2-D or 3-D DMO algorithm, and is computationally efficient.


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