Reducing Acquisition Costs With Random Sampling And Multidimensional Interpolation

Seismic data must be migrated, preferably before stack. Prestack migration gives best results when traces are evenly and densely sampled in inline CMP, crossline CMP, offset, and azimuth (Vermeer, 2010). Otherwise one can generate artifacts such as lateral smearing, migration smiles, and acquisition footprint. Acquisition can not economically deliver such sampling. Recently, however, 5D prestack trace interpolation (in reality, interpolation in four spatial dimensions) has become commonplace (Abma, 2010; Trad 2009; Trickett et al., 2010). Its principle goal is to provide a data set to prestack migration which is well sampled in all spatial dimensions. Figure 1: Traces acquired and processed. On the left is the traditional situation, on the right is the current situation.