一种基于Curvelet变换的地震数据去噪方法和应用
Application of Seismic Data Denoising Method Based on Curvelet Transform
郑晓雯1
作者信息
- 1. 上海市建筑科学研究院有限公司,上海市 200032;上海市工程结构安全重点实验室,上海市 200032
- 折叠
摘要
如何去除噪声且不损失有效信号是地震数据处理中的一个重难点.实验将一种Curvelet自适应阈值去噪法应用到地震数据处理中,Curvelet变换系数由自适应阈值约束,经阈值函数映射得到估计系数,最后对所得的估计系数进行逆变换,实现地震数据去噪,有效提高地震数据信噪比.模型和实际数据处理结果表明,Curvelet自适应阈值去噪法较好地压制了噪声的同时保护有效信号,克服了 F-X域滤波产生新噪声的缺陷,取得了较好去噪效果.
Abstract
How to remove noise without losing effective signals is a major challenge in seismic data processing.In the experiment,a Curvelet adaptive threshold denoising method is applied to seismic data processing.The Curvelet transform coefficient is constrained by the adaptive threshold,and the estimated coefficient is mapped by the threshold function.Finally,the estimated coefficient is inverted to achieve seismic data denoising,which effectively improves the signal-to-noise ratio of seismic data.The model and actual data processing results show that the Curvelet adaptive threshold denoising method effectively suppresses the noise while protecting the effective signals,overcomes the defect of new noise generated by F-X domain filtering,and achieves the good denoising results.
关键词
Curvelet变换/F-X域滤波/阈值/去噪/信噪比Key words
Curvelet transform/F-X domain filtering/threshold/denoising/signal-to-noise ratio引用本文复制引用
基金项目
上海市科委优秀技术带头人计划(2020)(20XD1432400)
上海建科集团科研创新项目(KY10000038.20210052)
出版年
2024
NETL
NSTL
万方数据