【摘要】 奇异值分解(SVD)滤波是利用地震信号在横向上的相干性差异来实现地震波场的分离与去噪。由于P-P波和P-S波在传播特性、视速度和相干性上存在差异,本文应用视速度信息,通过两次正常时差校正(NMO),分别把P-P波和P-S波校平,使之在横向上达到最佳相干性,然后分别两次通过SVD,提取目标信号的奇异值重构信号,从而实现地震纵、横波波场分离与去噪。更多还原

【Abstract】 As one of seismic data processing approaches,singular value decomposition(SVD) filter uses the lateral coherence difference of seismic signals to achieve wavefield separation and denoising.However,the propagation characteristics,apparent velocities and coherences are quite different between P-P wave and P-S wave.In this paper,a new idea of SVD application is proposed.Based on apparent velocities information,we first apply normal moveout(NMO) processing respectively on P-P wave and P-S wave to align P-P wave and P-S wave into the best horizontal coherence.Then we extract reconstructed signals of singular values from target signals by SVD separately on P-P wave and P-S wave,Finally P-P wave and P-S wave separations as well as noise attenuation are obtained.更多还原