How can we reduce the number of field measurements and still recover non-aliased wavefields?
Land seismic acquisition can be a challenging undertaking: acquisition gaps arise naturally from terrain obstacles and access restrictions while the near surface traps and scatters a lot of source-generated energy. The latter phenomenon has a big impact on data quality: since the trapped energy typically propagates with very slow velocities, non-aliased recording of such wavefields would require regular receiver sampling on the order of 1 m – an expensive and impractical choice for a big acquisition project. One possible alternative is to use ideas from compressive sensing: irregular data sampling and sparsity in the transform domain, to recover the missing traces, as illustrated in the figure on the right. Non-aliased wavefields are much easier to process and denoise than their regularly sampled, aliased counterparts.