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Incorporation of a non-linear image filtering technique for noise reduction in seismic data

机译:结合非线性图像滤波技术以减少地震数据中的噪声

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摘要

Seismic noise is a fundamental part of seismic data which cannot be avoided when conducting any seismic survey. It consists of coherent and random noise. Noise removal or filtering is one of the major concerns in the field of seismic processing. In this paper, we introduce an image filtering technique based on a detection-estimation algorithm for Gaussian and random noise removal in seismic data, namely the trilateral filter, based on a statistic called rank-ordered absolute differences. The non-linear and adaptive behaviour of this filter makes it very robust in the presence of random and coherent noise, in addition to its computational simplicity and its ability to automatically identify noise in data. We have modified the strategy of trilateral filtering by adapting the rank-ordered absolute differences formula in order to extract the signal component. We have successfully used this filter for the removal of surface waves and random spiky noise from synthetic and field data. Results are very encouraging and show the superiority of this filter compared with other filters, particularly when used recursively.
机译:地震噪声是地震数据的基本组成部分,在进行任何地震勘测时都无法避免。它由相干噪声和随机噪声组成。噪声消除或过滤是地震处理领域中的主要问题之一。在本文中,我们介绍了一种基于检测估计算法的图像滤波技术,该算法用于基于地震数据的高斯和随机噪声去除,即三边形滤波器,基于一种称为秩有序绝对差的统计量。该滤波器的非线性和自适应特性使其在存在随机和相干噪声的情况下非常健壮,此外它的计算简单且能够自动识别数据中的噪声。为了适应信号提取方法,我们通过调整有序绝对差公式对三边滤波策略进行了修改。我们已经成功地使用了该滤波器,以去除合成和现场数据中的表面波和随机尖峰噪声。结果非常令人鼓舞,并且显示了此过滤器相对于其他过滤器的优越性,尤其是在递归使用时。

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