马海涛,
李月,
吉林大学信息工程系, 长春 130012
基金项目: 国家高技术研究发展计划（863计划）重大项目"深部矿产资源探测技术"第5课题（2014AA06A605）和国家自然科学基金项目（41574096）联合资助
详细信息
作者简介: 董新桐, 男, 1993年生, 博士研究生, 从事信号处理.E-mail:18186829038@163.com
通讯作者: 李月, 女, 博士生导师, 教授, 从事信号处理、地震勘探数字处理.E-mail:liyue@jlu.edu.cn
中图分类号: P631收稿日期:2018-10-08
修回日期:2019-07-26
上线日期:2019-10-05
The new technology for suppression of hilly land seismic random noise: Shearlet transform and the high order weighted threshold function
DONG XinTong,MA HaiTao,
LI Yue,
Department of Information and Engineering, Jilin University, Changchun 130012, China
More Information
Corresponding author: LI Yue,E-mail:liyue@jlu.edu.cn
MSC: P631--> Received Date: 08 October 2018
Revised Date: 26 July 2019
Available Online: 05 October 2019
摘要
摘要:随着山地和丘陵地震勘探环境的复杂化，传统的消噪方法已经难以有效地压制地震记录中的随机噪声.Shearlet变换是一种新的多尺度多方向的时频分析方法，具有良好的稀疏表示特性，并且在每个尺度进行方向分解，非常适合用于地震信号随机噪声的压制.但是传统的Shearlet变换去噪方法采用的是硬阈值，在抑制随机噪声的同时也消除了很多有效信号，使得去噪之后的地震资料出现虚假的同相轴，为了解决这一问题我们提出高阶加权阈值函数.高阶加权阈值函数不但整体上连续性较好，而且克服了硬阈值函数存在剧烈的变化的缺点以及软阈值在处理较大Shearlet系数总存在恒定偏差的问题，同时保留了传统的软硬阈值函数的优点.实验结果表明这种基于高阶加权阈值函数的Shearlet变换去噪的方法，可以有效的消除模拟地震信号和实际丘陵地带地震信号中的随机噪声，同时很好的保留有效信号的幅度.
关键词: 低信噪比地震信号/
随机噪声压制/
Shearlet变换/
高阶加权阈值函数
Abstract:As the seismic exploration environment is becoming more and more complicated, the SNR (Signal to Noise Ratio) of the obtained seismic data is much lower than before, the conventional method can not suppress the random noises effectively. Shearlet transform is a new multi-scale and multi-direction time frequency analysis method, the Shearlet transform has huge advantages in sparse representation characteristic and direction sensitivity, so Shearlet transform is suitable for seismic data processing. In conventional Shearlet denoising method, the hard threshold function is applied to choose the Shearlet coefficients. However, through hard threshold function, many valid signals are eliminated when the random noises are suppressed. This phenomenon leads to the appearance of false axis. In order to solve this problem, we propose the high order weighted threshold function, this new proposed threshold function has better continuity than hard threshold function and overcome the disadvantage of soft threshold function. Experiment shows the new method can eliminate the random noise of simulative seismic data and hilly land actual seismic data effectively and retain the amplitude of valid signals.
Key words:Low SNR seismic signals/
Random noise suppression/
Shearlet transform/
High order weighted threshold function
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