1887

Abstract

Seismic data are typically irregularly and sparsely sampled along the spatial coordinates, leading to suboptimal further processing. Matching pursuit Fourier interpolation (MPFI) is a beyond aliasing interpolation technique for single component seismic data. The anti-aliasing capabilities of the method can be improved by using priors, which are typically derived from the lower frequencies in the data, and used to de-alias the higher frequencies. In this paper we investigate using a prior derived from a separate, more densely sampled data set. Practical examples are “dense-over/sparse-under” data and time-lapse data. Tests are done by decimating an existing dataset, deriving the prior from the non-decimated data, and using the priors for the interpolation of the decimated data. It is shown that using priors from a second data set can give a significant uplift in data reconstruction compared with deriving the priors in a conventional way. In particular, some steeply dipping diffraction events are reconstructed better, and a reduction of artefacts is observed.

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/content/papers/10.3997/2214-4609.20130384
2013-06-10
2020-04-09
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http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.20130384
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