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Optimization‐based recursive filtering for separation of signal from harmonics in vibroseis
Geophysical Prospecting ( IF 2.6 ) Pub Date : 2021-03-04 , DOI: 10.1111/1365-2478.13084
M.S. Denisov 1 , A.A. Egorov 1 , M.B. Shneerson 2
Affiliation  

Harmonic noise may significantly complicate the processing of slip‐sweep vibroseis data. We propose a model of this noise and an optimal recursive filtering algorithm based on this model. In contrast to some alternatives, this method can remove harmonic noise caused by all the events on the seismic gather, instead of only removing the noise associated with the first arrivals. First, the algorithm predicts a number of noise models that correspond to the harmonics of different orders. Second, these models are subtracted from the input gather via adaptive subtraction, which estimates frequency‐dependent relative amplitudes of harmonics and introduces the needed phase shifts into the noise models. When applied to the field vibroseis data, the proposed algorithm successfully separates the harmonic noise from the signal.

中文翻译:

基于优化的递归滤波可将信号与振动中的谐波分离

谐波噪声可能会使滑动扫频振动数据的处理变得非常复杂。我们提出了这种噪声的模型以及基于该模型的最佳递归滤波算法。与某些替代方法相比,此方法可以消除由地震道上所有事件引起的谐波噪声,而不仅仅是消除与初次到达有关的噪声。首先,该算法可预测许多与不同阶次谐波相对应的噪声模型。其次,通过自适应减法从输入集合中减去这些模型,该模型可估计与频率相关的谐波相对幅度,并将所需的相移引入噪声模型。当应用于现场振动数据时,所提出的算法成功地将谐波噪声与信号分离。
更新日期:2021-04-18
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