一种基于近似不规则离散傅里叶变换的地震数据插值算法

A. Oliveira, H. Haas
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引用次数: 0

摘要

本文结合近似不规则离散傅立叶变换(AIDFT),提出了一种在傅里叶域中对不规则采样地震数据进行插值/正则化的替代算法。贪婪算法用于在统计和/或物理约束下填充由缺陷采样产生的空箱,从而获得可接受的傅立叶谱。与其他实现非常相似,最小二乘范数傅立叶谱是该过程的输入。这里,最小二乘初始解由AIDFT提供。提出的贪婪算法是一个迭代过程,包括一步一步地校正主要傅立叶分量的测量足迹。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A greed algorithm for seismic data interpolation using the approximate irregular discrete Fourier transform
In this paper, an alternative greed algorithm for interpolation/regularization of irregularly-sampled seismic data in the Fourier domain is described in connection with the approximate irregular discrete Fourier transform (AIDFT). The greed algorithm is used to fill in empty bins, generated by defective sampling, under statistical and/or physical constraints, so as to achieve an acceptable Fourier spetrum. Much like in other implementations, a least square norm Fourier spectrum is the input for the process. Here, this least square initial solution is provided by the AIDFT. The greed algorithm proposed is an iterative procedure that consists in, step by step, correcting for survey’s footprints of main Fourier components.
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