王坤喜^1,2,,
毛伟建^1,,
1. 中国科学院精密测量科学与技术创新研究院计算与勘探地球物理研究中心; 大地测量与地球动力学国家重点实验室, 武汉 430077
2. 中国科学院大学, 北京 100049

基金项目: 国家重点研发计划（2018YFC0310104），国家自然科学基金（U1562216，41974163）和国家科技重大专项项目"新一代地球物理油气勘探软件系统"（2017ZX05018-001）联合资助


详细信息

作者简介: 王坤喜, 男, 1993年生, 在读硕士, 主要从事同时震源地震数据分离方法研究.E-mail:wangkunxi17@mails.ucas.ac.cn

通讯作者: 毛伟建, 男, 研究员, 博士生导师, 主要从事地震数据处理、成像和反演研究.E-mail:wjmao@whigg.ac.cn

中图分类号: P631

收稿日期:2020-03-04
修回日期:2020-11-22
上线日期:2021-01-10

Simultaneous-source wavefield separation based on adaptive Wiener threshold in Contourlet domain

WANG KunXi^1,2,,
MAO WeiJian^1,,
1. Center for Computational and Exploration Geophysics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences; and State Key Laboratory of Geodesy and Earth's Dynamics, Wuhan 430077, China
2. University of Chinese Academy of Sciences, Beijing 100049, China


More Information

Corresponding author: MAO WeiJian,E-mail:wjmao@whigg.ac.cn

MSC: P631

--> Received Date: 04 March 2020
Revised Date: 22 November 2020
Available Online: 10 January 2021


摘要
摘要:同时震源数据包含了多炮之间的串扰噪声，不能直接用于常规数据处理流程.因此，需要对混叠的波场进行分离得到常规采集的单炮记录.本文基于稀疏迭代反演分离，提出了一种具有尺度与空间自适应的Wiener阈值选取方法.该阈值选取方法能够根据不同迭代环境计算不同尺度下串扰噪声的方差和不同空间位置有效信号的方差，从而自适应调整阈值大小，最终通过对变换域系数进行收缩来达到去除串扰噪声的目的.理论模型数据和实际数据测试结果表明，本文方法能够快速有效地压制串扰噪声和保护弱有效信号，取得了比Contourlet域子带一致Wiener阈值方法和Curvelet域指数衰减阈值方法更好的分离效果.
关键词: 同时震源/
稀疏反演/
Contourlet变换/
自适应阈值/
Wiener滤波

Abstract:The simultaneous-source data cannot be directly used for seismic data processing workflow due to crosstalk noise of the interference guns. Therefore, the blended wavefield needs to be separated to obtain the conventional single shot record. Based on the threshold iterative inversion separation in sparse domain, a scale and spatially adaptive Wiener threshold method is proposed. With the method, the threshold values are adaptively calculated by using the variance of crosstalk noise at different scales and the variance of effective signals at different spatial positions at each iteration, and are used to attenuate the crosstalk noise by shrinking the coefficients in transform domain. The results tested by synthetic and field data show that the proposed method can more quickly and effectively suppress crosstalk noises and keep valuable weak signals than the traditional Wiener threshold method with subband consistent in Contourlet domain and the exponential attenuation threshold method in Curvelet domain.
Key words:Simultaneous-source/
Sparse inversion/
Contourlet transform/
Adaptive threshold/
Wiener filtering



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