Abstract：Based on a good relevance of the seismic data characteristics, singular value decomposition(SVD) technique can separate signals from noise. The seismic data can be decomposed by SVD, and then divided into a number of singular values in accordance with their energy values. The intrinsic images with big singular values can be mainly viewed as signals. We select the intrinsic images with the biggest singular values to reconstruct seismic records. This can effectively remove the random noise of seismic data. Post-stack seismic data can be obtained after a few processes such as static corrections, amplitude compensation, deconvolution, NMO and stack provided by GeoEast processing sub-system. Processing data results after forward modeling and Re-ou 3D in Liaohe Basin show that SVD can both effectively remove noise from seismic data and enhance seismic data signal to noise ratio.
桑雨, 高树生, 宋宏文, 赵军, 汤聪. 利用奇异值分解方法提高地震数据信噪比[J]. 石油地球物理勘探, 2014, 49(s1): 72-75.
Sang Yu, Gao Shusheng, Song Hongwen, Zhao Jun, Tang Cong. Signal to noise ratio improvement with the SVD method. OGP, 2014, 49(s1): 72-75.
