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An improved approach for suppressing noise based on empirical mode decomposition

机译:基于经验模态分解的噪声抑制方法

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Noise attenuation always played very important role in seismic signal processing. The predictive filter designed in temporal frequency (f) and space (x) domain can remove only random noise. This paper presented an improved filtering method for suppressing coherent noise and stochastic disturbance in seismic signals. For every frequency slice in f-x domain, we convert the data into a series of intrinsic mode functions (IMFs) by empirical mode decomposition algorithm. In order to eliminate noise, we remove the first IMF. The method can remove both stochastic disturbance and regular noise with steep dip. Applying in prestack as well as poststack sections compares well with the f-x predictive filtering. Real data examples are provided to show the effectiveness of presented approach.
机译:噪声衰减在地震信号处理中一直起着非常重要的作用。在时间频率(f)和空间(x)域中设计的预测滤波器只能去除随机噪声。本文提出了一种抑制地震信号中相干噪声和随机干扰的改进滤波方法。对于f-x域中的每个频率切片,我们通过经验模式分解算法将数据转换为一系列固有模式函数(IMF)。为了消除噪声,我们删除了第一个IMF。该方法可以消除陡峭倾角的随机干扰和常规噪声。在叠前和叠后部分中的应用与f-x预测性过滤相比非常好。提供了实际数据示例,以显示所提出方法的有效性。

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