In complex land areas with rugged topography, seismic imaging alternatives are usually limited to Kirchhoff prestack time and depth migration, often used in combination with refraction and reflection tomography. This is not the case for marine data, where wave-equation and reverse-time migrations have become the norm; nor is it the case for some land areas in the Middle East, for which high-density, wide-azimuth acquisition geometries allow the use of advanced imaging methods. Why the discrepancy? The reason is partly a difference in data quality (extremely noisy data will possibly defeat attempts at advanced imaging), and partly a difference in acquisition parameters, which themselves are often influenced by anticipated data quality (inadequately sampled data will certainly defeat attempts at advanced imaging). In this paper, we address the problem of spatial sampling for noise attenuation, Kirchhoff and more advanced imaging, and velocity estimation, and we point out the mismatch between the theoretical sampling requirements for advanced imaging and the realities of present-day land acquisition in rugged areas. Perhaps we cannot always achieve a sufficiently well sampled data volume for wave-equation migration by acquisition and seismic data interpolation in rugged areas. Nevertheless, we suggest that moving towards the goal of adequate sampling whenever possible (for example, using denser receiver grids with existing source grid spacing and lower effort per source) will improve our images even when we use standard imaging methods.


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