1887

Abstract

Summary

Seismic data interpolation is a currently popular research subject in modern reflection seismology. Compressed sensing (CS) based and rank-reduction based methods have great performances in recovering randomly missing traces, but their assumption or precondition, that traces miss randomly, is too hard to satisfy in real data. In this abstract, we propose a new morphology based method, which utilizes 2D mathematical morphological filtering (MMF) to recover missed energy of each frequency component. Because the morphological calculation is based on logical operation and set theory, which is different from the traditional mathematical transforms, this proposed f-xy domain 2D MMF method has strong anti-aliasing capability. Application of it on synthetic and field seismic data demonstrates a successful performance.

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/content/papers/10.3997/2214-4609.201700488
2017-06-12
2024-03-28
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References

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