Irregular Sampling – From Aliasing to Noise

B025 Irregular Sampling – From Aliasing to Noise G. Hennenfent* (University of British Columbia) & F.J. Herrmann (University of British Columbia) SUMMARY Seismic data is often irregularly and/or sparsely sampled along spatial coordinates. We show that these acquisition geometries are not necessarily a source of adversity in order to accurately reconstruct adequately-sampled data. We use two examples to illustrate that it may actually be better than equivalent regularly subsampled data. This comment was already made in earlier works by other authors. We explain this behavior by two key observations. Firstly a noise-free underdetermined problem can be seen as a noisy