Deblending of simultaneous source data using a structure-oriented space-varying median filter
Deblending of simultaneous source data using a structure-oriented space-varying median filter
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DOI：
10.1093/gji/ggy487
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发表时间：
2018-11
影响因子：
2.8
通讯作者：
Yangkang Zhang;S. Zu;Yufeng Wang;Xiaohong Chen
中科院分区：
文献类型：
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作者：
Yangkang Zhang;S. Zu;Yufeng Wang;Xiaohong Chen
在地震资料处理中，为了滤除不规则或尖峰状噪声，通常沿地震资料的构造方向沿着进行中值滤波。面向结构的中值滤波器的性能在很大程度上取决于从噪声数据中估计局部斜率的准确性。当局部斜率包含较大误差时，结构中值滤波仍会对有用能量造成严重损害，这在噪声数据中是常见的。我们提出了一种面向结构的中值滤波器，即使在局部斜率没有准确估计的情况下，也可以有效地衰减尖峰噪声，我们称之为面向结构的空间变化中值滤波器。面向结构的空变中值滤波器在输入地震数据的局部平坦维数上自适应地压缩和拉伸中值滤波器的窗长，以处理由于斜率估计不准确而引起的倾斜同相轴。详细分析了不同类型中值滤波器的主要区别，并阐述了面向结构的空变中值滤波方法的基本原理。我们应用面向结构的空间变化中值滤波方法来去除同时源采集中产生的尖峰状混合噪声。合成数据和真实的数据实例表明，面向结构的空变中值滤波可以显著提高地震数据中曲线同相轴的信号保持性能。面向结构的空间变化中值滤波器也可以很容易地嵌入到基于成形正则化框架的迭代去混合过程中，并且可以帮助获得更好的去混合性能。
In seismic data processing, the median filter is usually applied along the structural direction of seismic data in order to attenuate erratic or spike-like noise. The performance of a structure-oriented median filter highly depends on the accuracy of the estimated local slope from the noisy data. When local slope contains significant error, which is usually the case for noisy data, the structure-oriented median filter will still cause severe damages to useful energy. We propose a type of structure-oriented median filter that can effectively attenuate spike-like noise even when the local slope is not accurately estimated, which we call structure-oriented space-varying median filter. A structure-oriented space-varying median filter can adaptively squeeze and stretch the window length of the median filter when applied in the locally flattened dimension of an input seismic data in order to deal with the dipping events caused by inaccurate slope estimation. We show the key difference among different types of median filters in detail and demonstrate the principle of the structure-oriented space-varying median filter method. We apply the structure-oriented space-varying median filter method to remove the spike-like blending noise arising from the simultaneous source acquisition. Synthetic and real data examples show that structure-oriented space-varying median filter can significantly improve the signal preserving performance for curving events in the seismic data. The structure-oriented space-varying median filter can also be easily embedded into an iterative deblending procedure based on the shaping regularization framework and can help obtain much improved deblending performance.