A svd Adaptive Seismic Data Noise Suppression Method

Abstract

The invention relates to an SVD self-adaptive seismic data noise suppression method. First, the mean filter is used to preprocess the data smoothing, and the strong periodic noise channel is marked according to the difference between the average energy values ​​of each channel. Secondly, the average value of the average time period of each channel is rounded up, and used as the number of columns to construct the Hankel matrix for a single channel, and the correlation between the channels of the reconstruction matrix is ​​strengthened. Finally, SVD is performed on each reconstruction matrix one by one, and the singular values ​​are sent to the constructed K-K joint network for identification and distinction, so as to determine the corresponding values ​​of different correlation strengths in the signal, and the effective signal singular values ​​are retained for data reconstruction. Adaptive noise suppression in the temporal domain. The present invention introduces the K-K joint network to determine the SVD reconstruction order, reducing the situation of relying on human experience. This method can simultaneously suppress periodic noise and random noise with strong regularity in single-channel data, such as power frequency interference, at the same time for shallow formation seismic data, and improve the quality of seismic data.

Description

technical field [0001] The invention belongs to the field of denoising seismic data in shallow strata, and aims at strong periodic noise and random noise in seismic data, in particular an SVD adaptive seismic data noise suppression method based on K-K joint network. Background technique [0002] The shallow stratum seismic data collected in the field contains a large amount of information such as underground structure and lithology, as well as random noise, and strong periodic noise such as power frequency interference throughout the data, that is, there is a mixture of effective information and different noises. Stacking directly affects the quality and signal-to-noise ratio of seismic data, which is not conducive to further analysis and processing of data. SVD analysis technology, one of the data processing methods, has been applied to noise suppression of seismic data by many scholars because of its advantages such as easy implementation. The essence of SVD is an orthogo...

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Article "Denoising method of surface microseismic data based on single-channel SVD and amplitude ratio" (Hu Yongquan, Huang Jianbo, Tian Zhihua, Pan Shulin. Denoising method of surface microseismic data based on single-channel SVD and amplitude ratio[J]. Petroleum Geophysical Prospecting, 2019,58(01):43-52+62.) Simultaneous suppression of strong periodic interference and random interference in surface microseismic data, pointing out that the large, medium, and small parts of the singular values ​​correspond to periods with strong correlation Signals, effective signals with a certain correlation, and random interference without correlation, the reconstruction singular value is compared with the reconstruction results of different selection ratios by trial and error, which reduces the data processing efficiency

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