Abstract
The effects of irregular spatial sampling on prestack wave-equation processes such as DMO and migration have been noted by several authors for both 2-D and 3-D data. Phase and amplitude distortions arise as a result of applying DMO algorithms that assume regular spatial sampling to data not regularly sampled in offset, common midpoint (CMP), and azimuth. While algorithms now exist to compensate or equalize the DMO operator during data processing for such spatial irregularities, it is possible that random or systematic patterns in the data acquisition geometry leave deficiencies in the "DMO coverage" that cannot easily be remedied (Beasley and Klotz, 1992) . Traditional criteria for spatial sampling such as CMP fold and offset distribution are often set by rule of thumb and generally do not measure the quality of spatial sampling for DMO processing. In this paper, I demonstrate new methods of assessing the quality of data sampling for DMO that are based only on acquisition geometry and are independent of a geologic model or the actual seismic data.
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