奇异值分解压制随机噪声的方法及应用

针对随机噪声压制问题，通过对多项式确定的同相轴形状重新选取数据矩阵，再对新选取的数据矩阵进行SVD滤波，从而压制随机噪声。通过对矩阵奇异值分解的研究，揭示了奇异值分解的原理和SVD滤波原理，将一个多道地震记录看作一个图，它可分解为由一系列正交的子图，通过对子图适当选择并结合其它手段，从而达到提高信噪比的目的，为奇异值分解在地球物理中的进一步应用提供了理论依据。实际数据应用表明，该方法去噪手段灵活、保真性好、分辨率高，对一些突然的脉冲干扰、侧反射、以及其他的反向干扰有明显效果。

SVD Method and Its Application in Attenuating Random Noise

Singular value decomposition(SVD)is found to be extensive application in attenuating random noise of seismic data process-ing.Focusing on the random noise attenuation,seismic data matrix is reselected by event shapes determined with polynomial expression,the data matrix reselected is then filtered by SVD in order to attenuate random noise.The study of SVD reveals the principles of SVD and its fil-tering,which offer theoretical basis for further application of SVD in geophysical prospecting.Application with real data shows that this method used for removing noise is of flexibility,high reality and high resolution.Also,it has significant effects on sudden pulse interference,offside reflection and other reverse interferences.