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物探与化探  2020, Vol. 44 Issue (4): 784-789    DOI: 10.11720/wtyht.2020.1484
  方法研究·仪器研制 本期目录 | 过刊浏览 | 高级检索 |
改进的小波阈值法及其在地震数据降噪处理中的应用
刘剑1(), 秦飞龙2,3()
1.成都工业学院 汽车与交通学院,四川 成都 611730
2.成都工业学院 大数据与人工智能学院,四川 成都 611730
3.电子科技大学 数学科学学院,四川 成都 611731
The application of the improved wavelet threshold method to seismic data de-noising
LIU Jian1(), QIN Fei-Long2,3()
1. School of Automobile and Communications,Chengdu Technological University,Chengdu 611730,China
2. School of Big Data and Artificial Intelligence,Chengdu Technological University,Chengdu 611730,China
3. School of Mathematical Sciences,University of Electronic Science and Technology of China,Chengdu 611731,China
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摘要 

野外地震数据受到各种随机因素干扰,需要对随机噪声进行去除。小波分析中的软、硬阈值法是有效的地震数据降噪方法,但由于算法本身特性使得降噪具有一定的缺陷。因此,文中提出了一种改进的小波阈值降噪算法。首先构建了改进的阈值方法模型并对其功能进行了研究,确定了sym3为改进的阈值算法的最佳小波基以及最佳小波分解的层数为3层。利用仿真实验证明了改进的阈值方法降噪能力具有有效性,并通过均方差(RMSE)和信噪比(SNR)对新算法降噪效果进行了评价。最后,将本文提出的算法应用于实际地震数据降噪处理,结果发现改进的阈值法能够有效地去除地震数据中的各类随机噪声,通过与软、硬阈值法降噪效果进行对比研究,结果得出改进的阈值方法降噪效果更理想。

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刘剑
秦飞龙
关键词 软、硬阈值法改进的阈值法地震数据降噪    
Abstract

The field seismic data are disturbed by various random factors,and hence it is necessary to remove the random noise from seismic data.The soft and hard threshold functions of wavelet transform are effective methods for seismic data de-noising;nevertheless,due to the characteristics of the algorithm itself,their de-noising performance has some defects.In view of such a situation,the authors propose an improved wavelet threshold method for de-noising.Firstly,the improved wavelet threshold method is constructed and some of its functions are studied.It is shown that the best wavelet basis of the improved threshold method is sym3,and the best decomposition level is 3.The effect of the new algorithm in de-noising is evaluated by means of mean square error (RMSE) and signal-to-noise ratio (SNR).The proposed method was applied to the actual seismic data de-noising.The results show that the improved threshold method can effectively remove all kinds of random noise of seismic data.A comparison with soft and hard threshold method shows that the improved threshold method has a better effect in seismic data de-noising.

Key wordssoft and hard threshold method    improved threshold method    seismic data    de-noising
收稿日期: 2019-10-21      出版日期: 2020-08-28
:  P631.4  
基金资助:四川省科技厅计划项目(2019YJ0375);中国地质调查局地质调查项目(1212010916040);成都工业学院博士基金项目(2018RC014)
通讯作者: 秦飞龙
作者简介: 刘剑(1975-),男,博士,主要从事大数据处理研究工作。Email:641457637@qq.com
引用本文:   
刘剑, 秦飞龙. 改进的小波阈值法及其在地震数据降噪处理中的应用[J]. 物探与化探, 2020, 44(4): 784-789.
LIU Jian, QIN Fei-Long. The application of the improved wavelet threshold method to seismic data de-noising. Geophysical and Geochemical Exploration, 2020, 44(4): 784-789.
链接本文:  
https://www.wutanyuhuatan.com/CN/10.11720/wtyht.2020.1484      或      https://www.wutanyuhuatan.com/CN/Y2020/V44/I4/784
Fig.1  原始信号
a—有效信号;b—带有随机噪声的观测信号
Fig.2  数据降噪
a—软阈值降噪;b—硬阈值降噪;c—改进的阈值函数降噪
阈值函数 软阈值函数 硬阈值函数 新阈值函数
SNR 27.1341 28.3217 29.0232
RMSE 0.00029 0.00028 0.00018
Table 1  不同阈值函数的信噪比和均方根误差
Fig.3  不同symN小波基的信噪比(a)和均方根误差(b)
Fig.4  确定分解层数
a—观测信号;b、c、d、e、f—分别为改进的阈值降噪算法进行1~5层分解降噪效果
Fig.5  地震数据降噪
a—原始观察数据;b—软阈值函数降噪结果;c—硬阈值函数降噪结果;d—改进的阈值函数降噪结果
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