Abstract

Seismic acquisition is a trade-off between image quality and cost. While there is an increasing need for higher quality images due to the more complex geologic settings of reservoirs, there is also a strong desire to reduce the cost and cycle time of seismic acquisition. Meeting these conflicting ambitions requires creative solutions. New hardware developments aim at improving survey efficiency and image quality. To optimally leverage new hardware and maximize survey efficiency, their development should go together with new insights gained from sparse sampling. Sparse sampling combines efficient data acquisition with the reconstruction of a signal by finding its coefficients as the solution of an underdetermined system. Greater survey efficiency results from compression during acquisition. For seismic wavefield sampling, the compression can take place in time, space, or both. Compression in time can be achieved by letting shot-records overlap, as in simultaneous-source acquisition for example. Compression in space can be achieved with spatial subsampling. Some recently introduced acquisition technologies already leverage the ideas from sparse sampling in practice. We believe sparse seismic wavefield sampling is not only a method to reduce costs; the flexibility to distribute sources and receivers in space and time in different ways than we are used to also will spark the acquisition technologies of the future.

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