基于相似匹配维纳滤波的地震资料噪声压制

Seismic signal noise suppression based on similarity matched Wiener filtering

针对强噪声背景下地震资料噪声压制困难的问题,提出一种基于地震信号相似性的维纳滤波传递函数优化算法。该算法将待处理资料分块,并依据地震同相轴的时空相似性构建三维相似组。经过低秩近似,信号与噪声差异明显,能够计算得出更为精确的维纳滤波传递函数。经过仿真信号与真实地震资料的对比验证,采用本文优化算法得到的传递函数进行维纳滤波,既能实现随机噪声的有效压制,又能极大地保护信号的有效成分。

Seismic exploration is the main method in oil and gas exploration. It becomes more and more difficult to identify the collected seismic signals, because of a sharp drop in resolution and the Signal to Noise Ratio （SNR）. Conventional seismic record processing methods have shown no adaptability to very low SNR. In order to realize the requirement of high SNR, high resolution and high fidelity of seismic data processing in strong noise, this paper proposes a novel method of seismic data noise suppression based on similarity matched Wiener filtering. In this method, based on the local and non- local similarity of seismic events, the whole record is divided into overlapping sub-blocks and the blocks containing similar signals are found out by some distance measures. Then, the low rank matrix is constructed by Singular Value Decomposition （SVD） and the smaller singular values are removed representing noise. The noise in the constructed signal is effectively suppressed. Using this estimation, the Wiener filter is able to obtain a more accurate transfer function. At the same time, the effect of prior information on noise suppression is eliminated. Experiment results illustrate that the proposed method improves the SNR and effectively retains the signal amplitude.