石油地球物理勘探2019，Vol.54Issue(2)：268-273,前插1,7.DOI:10.13810/j.cnki.issn.1000-7210.2019.02.004
基于稀疏反演的高效混采数据分离方法
High-productivity blended acquired data separation by sparse inversion
摘要
Abstract
The vibroseis blending acquisition improves greatly acquisition efficiency.However,this acquisition brings serious noise in massive blended seismic data due to the continuous shooting.Therefore accurate,stable, and fast noise-separation algorithms are needed. We propose in this paper an inversion-based de-blending method applied on 3Dcommon receiver gathers. Firstly,temporal-spatial seismic data is transformed into the frequency-wavenumber-wavenumber(FKK)domain data by 3Dfast Fourier transform.Then,the hard thresholding algorithm extracts coherent signals,and noise is predicted with the extracted coherent signals. Finally,driven by data residuals,signals are iteratively updated with shrinking thresholds until full noise separation from data is achieved.Tests on both synthetic and field data show that the proposed method can separate high-productivity blended acquired data in an accurate, stable and fast way.关键词
高效混采/信噪分离/三维共检波点道集/FKK域/稀疏反演Key words
high-productivity blending acquisition/signal and noise separation/3Dcommon receiver gather/frequency- wavenumber-wavenumber(FKK )domain/sparse inversion分类
天文与地球科学引用本文复制引用
宋家文,李培明,王文闯,王成祥,李合群,王宝彬..基于稀疏反演的高效混采数据分离方法[J].石油地球物理勘探,2019,54(2):268-273,前插1,7.基金项目
本项研究受国家科技重大专项"大型油气田及煤层气开发"子课题"新一代地球物理油气勘探软件系统"(2017ZX05018-001)和中国石油集团公司"可控震源超高效混叠地震采集处理配套技术研究与应用"(2017D-3501)联合资助. （2017ZX05018-001）
