提高地震数据信噪比的PCA方法

Enhancement of singal to noise ratio of seismic date based on the PCA method

由于地震数据中存在各种各样的噪声,怎样去压制或者滤除这些噪声,以至提高信噪比成为当前地震信号处理中关键步骤.本文根据地震数据中随机噪声干扰和可能存在的工业单频噪声干扰的特点,采用主成分分析技术,即通过正交分解得到数据矩阵的主分量,并利用不同的主分量进行信号重构,从而达到去除单频干扰和随机噪声的目的,有效地提高了地震数据的信噪比.

How to denoise or filter interference has become a key part of seismic signal processing for improving the signal to noise ratio because there exist different kinds of noise in seismic data. In this paper, principal component analysis （PCA） is applied to denoise according to the features of random noise and single frequency interference from industry. This method proposed can be divided into two steps. First, principal component is obtained by single value decomposition of seismic data matrix. Second, the signal reconstruction is gained using different principal components. The experimental results show that the method presented can obtain higher signal to noise ratio owing to the suppression of single frequency interference and random noise.