Signal to noise ratio improvement with the SVD method

被引：0

作者：

Sang, Yu ^{[1
]}

Gao, Shusheng ^{[1
]}

Song, Hongwen ^{[1
]}

Zhao, Jun ^{[1
]}

Tang, Cong ^{[1
]}

机构：

[1] Research Institute of Exploration and Development, Liaohe Oilfield Company, PetroChina, Panjin, Liaoning 124010, China

来源：

Shiyou Diqiu Wuli Kantan/Oil Geophysical Prospecting | 2014年 / 49卷 / SUPPL.1期

关键词：

Signal to noise ratio - Data handling - Seismic response - Seismic waves;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

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.

引用

页码：72 / 75