平行径向道时频峰值滤波消减地震资料的随机噪声

doi:10.13229/j.cnki.jdxbgxb201403048

吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (3): 882-887.doi: 10.13229/j.cnki.jdxbgxb201403048

平行径向道时频峰值滤波消减地震资料的随机噪声

张洁^1,2,李月¹

1.吉林大学通信工程学院,长春 130012;
2.吉林大学学报信息科学版编辑部,长春 130012

收稿日期:2013-03-15 出版日期:2014-03-01 发布日期:2014-03-01
通讯作者: 李月(1958),女,教授,博士生导师.研究方向:地震勘探信号处理, 微弱信号检测.E-mail:liyue@jlu.edu.cn E-mail:z_jie@jlu.edu.cn
作者简介:张洁(1981),女,博士研究生.研究方向:地震勘探信号处理.E-mail:z_jie@jlu.edu.cn
基金资助:
国家自然科学基金重点项目(41130421).

Reduction of random noise in seismic data by parallel radial-trace time-frequency peak filtering

ZHANG Jie^1,2, LI Yue¹

1.College of Communication and Engineering,Jilin University,Changchun 130012,China;
2.Editorial Board of Journal of Jilin UniversityInformation and Science Edition, Changchun 130012, China

Received:2013-03-15 Online:2014-03-01 Published:2014-03-01

摘要/Abstract

摘要： 针对传统时频峰值滤波(TFPF)算法在消减地震勘探资料中的随机噪声时,容易引起有效信号波峰和波谷处的误差问题,提出了平行径向道TFPF方法。该方法将地震信号从炮检距-双程旅行时域变换到视速度-双程旅行时域后,沿时空域径向道方向进行TFPF。讨论了不同径向道轨线对TFPF无偏估计的影响,并对人工合成的地震记录进行了仿真试验,将沿不同轨线的平行径向道TFPF与传统TFPF结果进行比较。结果表明:所选轨线平行于同相轴或与之夹角很小时,可使信号在一个TFPF时窗内更好地满足无偏估计的条件,从而减小了滤波后波峰及波谷处的误差,使本文方法具有更好的保幅性,其信噪比较传统TFPF算法提高了5 dB左右,通过对实际地震记录的仿真,证明了该方法的实用性。

关键词: 信息处理技术, 径向道变换, 时频峰值滤波, 随机噪声, 信号增强

Abstract: Traditional Time-frequency Peak Filtering (TFPF) usually causes errors at peaks and valleys of valid signal. This study proposed a parallel Radial Trace Transform (RTT)-TFPF with x-interpolation method to reduce these errors. The proposed method uses TFPF to eliminate noise after mapping seismic signals from coordinates of offset and traveltime to those of apparent velocity and traveltime, namely filtering the signals along the direction of the radial trace in the time-space domain. The effect of the different slope of radial trace on the unbiased estimation of TFPF was discussed. Simulation experiments of synthetic seismogram were carried out to compare the traditional TFPF and the RTT-TFPF with different slopes. The results show that when the selected radial traces and events are parallel or the angles between them are small, the proposed method can make the signals better meet the condition of unbiased estimation in one window length, reduce the errors of the peaks and valleys of filtered signal, and improve the property of amplitude-preservation, the SNR of the proposed method can increase about 5 dB.

Key words: information processing, radial-trace transform, time-frequency peak filtering, random noise, signal enhance

中图分类号:

TN911.73

张洁,李月. 平行径向道时频峰值滤波消减地震资料的随机噪声[J]. 吉林大学学报(工学版), 2014, 44(3): 882-887.

ZHANG Jie, LI Yue. Reduction of random noise in seismic data by parallel radial-trace time-frequency peak filtering[J]. 吉林大学学报(工学版), 2014, 44(3): 882-887.

参考文献

[1] Boashash B, Mesbah M. Signal enhancement by time-frequency peak filtering[J]. IEEE Transactions on Signal Processing, 2004,52(4):929-937.
[2] 金雷,李月,杨宝俊. 用时频峰值滤波方法消减地震勘探资料中随机噪声的初步研究[J]. 地球物理学进展, 2005, 20(3):724-728.
Jin Lei, Li Yue, Yang Bao-jun. Reduction of random noise for seismic data by time-frequency peak filtering[J]. Progress in Geophysics, 2005, 20(3):724-728.
[3] 林洪波,李月,潘伟. 时频峰值滤波信号增强方法在实际地震资料处理中的应用[J]. 吉林大学学报: 地球科学版, 2007, 37(5):1038-1041.
Lin Hong-bo, Li Yue, Pan Wei. Application of signal enhancement method based on time-frequency peak filteting to seismic data processing[J]. Journal of Jilin University: Earth Science Edition, 2007, 37(5):1038-1041.
[4] Lin Hong-bo, Li Yue, Yang Bao-jun. Recovery of seismic events by time-frequency peak filtering[C]∥IEEE International Conference on Image Processing, San Antonio, 2007:441-444.
[5] 李月,林红波,杨宝俊,等. 强随机噪声条件下时窗类型局部线性化对TFPF技术的影响[J]. 地球物理学,2009,52(7): 1899-1906.
Li Yue, Lin Hong-bo,Yang Bao-jun, et al. The influence of limited linearization of time window on TFPT under the strong noise background[J]. Chinese Journal of Geophysics,2009,52(7): 1899-1906.
[6] Lin Hong-bo, Li Yue, Yang Bao-jun. Varying-window-length time-frequency peak filtering and its application to seismic data[C]∥2008 International Conference on Computational Intelligence and Security, Suzhou, China, 2008: 429-432.
[7] Wu Ning, Li Yue, Yang Bao-jun. Noise attenuation for 2-d seismic data by radial-trace time-frequency peak filtering[J]. IEEE Geoscience and Remote Sensing Letters, 2011, 8(5):874-878.
[8] Lin Hong-bo, Li Yue, Ye Wen-hai. Data processing methods for time frequency peak filtering[C]∥2009 International Conference on Computer and Communications Security. Hong Kong, China, 2009: 115-118.
[9] Claerbout J F. Imaging the earth's interior[R]. Oxford, England: Black-well Scientific Publications, 1985:216-219.
[10] 余波,黄中玉,谈大龙,等. 径向道滤波法去线性干扰[J]. 石油物探, 2005,44(2):109-112.
Yu Bo, Huang Zhong-yu, Tan Da-long, et al. RT filter attenuating the linear noise[J]. Geophysical Prospecting for Petroleum, 2005, 44(2):109-112.
[11] 夏洪瑞,唐勇. 径向道技术在消除相干噪声中的应用[J]. 勘探地球物理进展,2007,30(6): 448-458.
Xia Hong-rui, Tang Yong. Application of radial trace technique in elimination of coherent noise[J]. Progress in Exploration Geophysis, 2007, 30(6): 448-458.
[12] 刘志鹏,陈小宏,李景叶. 径向道变换抑制相干噪声方法研究[J]. 地球物理学进展,2008, 23(4): 1199-1204.
Liu Zhi-peng, Chen Xiao-hong, Li Jing-ye. Study on coherent noise attenuation using radial trace transform filtering[J]. Progress in Geophysics, 2008, 23(4):1199-1204.
[13] Brown M, Claerbout J. A pseudo-unitary implementation of the radial trace transform[C]∥In Proc Soc Exploration Geophysicists, Calgary, Alberta, 2000: 2115-2118.
[14] Henley D C. Coherent noise attenuation in the radial trace domain[J]. Geophysics, 2003, 68(4): 1408-1416.
[15] Morgan B, Claerbout J. A pseudo-unitary implementation of the radial trace transform[C]∥2000 SEG Annual Meeting, Calgary, Alberta, 2000:2115-2118.

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平行径向道时频峰值滤波消减地震资料的随机噪声

Reduction of random noise in seismic data by parallel radial-trace time-frequency peak filtering

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