子空间增强在大地电磁信噪分离中的应用研究
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摘要
为了提高强干扰地区大地电磁测深数据质量、保留大地电磁信号低频段的有用信息,压制大尺度强干扰已刻不容缓。针对矿集区典型的强干扰类型,引入子空间增强方法对大地电磁信号与强干扰进行信噪分离研究。通过计算机模拟常见的大尺度方波和充放电三角波干扰,讨论了子空间增强算法中帧长与特征值判别阈值的最优选取范围,给出了算法流程,并对矿集区实测大地电磁数据进行了信噪分离处理。实验结果表明:该方法是切实可行的,能有效剔除时间域序列中的大尺度强干扰,近源效应得到了有效压制;经处理后,重构的大地电磁信号中包含了更为丰富的细节成分,视电阻率曲线更为光滑、连续,低频段的大地电磁数据质量得到了明显改善。
In order to improve the quality of magnetotelluric sounding data and retain the useful information of low frequency band for magnetotelluric,suppressing the large-scale strong interference is imperative.Aimed at typical strong interference types of ore concentration area,we introduced the subspace enhancement method to study signal to noise separation of magnetotelluric data and strong interference.Through simulated large-scale square wave and charge and discharge triangle wave by computer,we discussed the optimal range of frame and criterion threshold of eigenvalue in subspace enhancement,and the concrete steps of the algorithm are presented.Then,the measured magnetotelluric data of ore concentration area were processed by signal to noise separation.Experiment results show that the method is feasible,which can effectively eliminate the large-scale strong noise interference in the time domain and the near source interference of ore concentration area has been effectively suppressed.At the same time,the apparent resistivity curve is more smoothly and continuously.Moreover,the quality of magnetotelluric sounding data is improved significantly in the low frequency band.
In order to improve the quality of magnetotelluric sounding data and retain the useful information of low frequency band for magnetotelluric,suppressing the large-scale strong interference is imperative.Aimed at typical strong interference types of ore concentration area,we introduced the subspace enhancement method to study signal to noise separation of magnetotelluric data and strong interference.Through simulated large-scale square wave and charge and discharge triangle wave by computer,we discussed the optimal range of frame and criterion threshold of eigenvalue in subspace enhancement,and the concrete steps of the algorithm are presented.Then,the measured magnetotelluric data of ore concentration area were processed by signal to noise separation.Experiment results show that the method is feasible,which can effectively eliminate the large-scale strong noise interference in the time domain and the near source interference of ore concentration area has been effectively suppressed.At the same time,the apparent resistivity curve is more smoothly and continuously.Moreover,the quality of magnetotelluric sounding data is improved significantly in the low frequency band.
引文
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[10]王辉,魏文博,金胜,等.基于同步大地电磁时间序列依赖关系的噪声处理[J].地球物理学报,2014,57(2):531-545.WANG H,WEI W B,JIN S,et al.Removal of magnetotelluric noise based on synchronous time series relationship[J].Chinese Journal Geophysics,2014,57(2):531-545.(In Chinese)
[11]唐贵基,庞彬,刘尚坤.基于奇异差分谱和平稳子空间分析的滚动轴承故障诊断[J].振动与冲击,2015,34(11):83-87.TANG G J,PANG B,LIU S K.Fault diagnosis of rolling bearings based on difference spectrum of singular value and stationary subspace analysis[J].Journal of Vibration and Shock,2015,34(11):83-87.(In Chinese)
[12]陆文凯,丁文龙,张善文,等.基于信号子空间分解的三维地震资料高分辨率处理方法[J].地球物理学报,2009,52(8):2174-2181.LU W K,DING W L,ZHANG S W,et al.A high resolution processing technique for 3_D seismic data based on signal subspace decomposition[J].Chinese Journal Geophysics,2009,52(8):2174-2181.(In Chinese)
[13]DENDRINOS M,BAKAMIDIS S,CARAYANNI G.Speech enhancement from noise:A regenerative approach[J].Speech Communication,1991,10(2):45-57.
[14]EPHRAIM Y,VAN TREES H L.A signal subspace approach for speech enhancement[J].IEEE Transactions on Speech and Audio Processing,1995,3(4):251-266.
[15]JENSEN S H,HANSEN P C,HANSEN S D,et al.Reduction of broad-band noise in speech by truncated QSVD[J].IEEE Transactions on Speech and Audio Processing,1995,3(6):439-448.
[16]李晋,汤井田,王玲,等.基于信号子空间增强和端点检测的大地电磁噪声压制[J].物理学报,2014,63(1):019101.LI J,TANG J T,WANG L,et al.Noise suppression for magnetotelluric sounding data based on signal subspace enhancement and endpoint detection[J].Acta Physica Sinica,2014,63(1):019101.(In Chinese)
[17]汤井田,刘子杰,刘峰屹,等.音频大地电磁法强干扰压制试验研究[J].地球物理学报,2015,58(12):4636-4647.TANG J T,LIU Z J,LIU F Y,et al.The denoising of the audio magnetotelluric data set with strong interferences[J].Chinese Journal Geophysics,2015,58(12):4636-4647.(In Chinese)
[18]代小威.基于V5-2000格式MT时间序列处理与功率谱估计及软件开发[D].武汉:长江大学,2015.DAI X W.Processing and power spectrum estimation of MT time serizes in V5-2000format and software development[D].Wuhan:Yangtze University,2015.(In Chinese)
[2]CAGNIARD L.Basic theory of the magnetotelluric method of geophysical prospecting[J].Geophysics,1953,18(3):605-635.
[3]朱威,范翠松,姚大为,等.矿集区大地电磁噪声场源分析及噪声特点[J].物探与化探,2011,35(5):658-662.ZHU W,FAN C S,YAO D W,et al.Noise source analysis and noise characteristic study of MT in an ore concentration area[J].Geophysical and Geochemical Exploration,2011,35(5):658-662.(In Chinese)
[4]王书明,王家映.大地电磁信号统计特征分析[J].地震学报,2004,26(6):669-674.WANG S M,WANG J Y.Analysis on statistic characteristics of magnetotelluric signal[J].Acta Seismologica Sinca,2004,26(6):669-674.(In Chinese)
[5]王书明,王家映.大地电磁信号非最小相位性的讨论[J].地球物理学进展,2004,19(2):216-221.WANG S M,WANG J Y.Discussion on the nonminimum phase of magnetotelluric signals[J].Progress in Geophysics,2004,19(2):216-221.(In Chinese)
[6]汤井田,化希瑞,曹哲民,等.Hilbert-Huang变换与大地电磁噪声压制[J].地球物理学报,2008,51(2):603-610.TANG J T,HUA X R,CAO Z M,et al.HilbertHuang transformation and noise suppression of magnetotelluric sounding data[J].Chinese Journal Geophysics,2008,51(2):603-610.(In Chinese)
[7]景建恩,魏文博,陈海燕,等.基于广义S变换的大地电磁测深数据处理[J].地球物理学报,2012,55(12):4015-4022.JING J E,WEI W B,CHEN H Y,et al.Magnetotelluric sounding data processing based on generalized S transformation[J].Chinese Journal Geophysics,2012,55(12):4015-4022.(In Chinese)
[8]KAPPLE K N.A data variance technique for automated despiking of magnetotelluric data with a remote reference[J].Geophysical Prospecting,2012,60(1):179-191.
[9]汤井田,李晋,肖晓,等.数学形态滤波与大地电磁噪声压制[J].地球物理学报,2012,55(5):1784-1793.TANG J T,LI J,XIAO X,et al.Mathematical morphology filtering and noise suppression of magnetotelluric sounding data[J].Chinese Journal Geophysics,2012,55(5):1784-1793.(In Chinese)
[10]王辉,魏文博,金胜,等.基于同步大地电磁时间序列依赖关系的噪声处理[J].地球物理学报,2014,57(2):531-545.WANG H,WEI W B,JIN S,et al.Removal of magnetotelluric noise based on synchronous time series relationship[J].Chinese Journal Geophysics,2014,57(2):531-545.(In Chinese)
[11]唐贵基,庞彬,刘尚坤.基于奇异差分谱和平稳子空间分析的滚动轴承故障诊断[J].振动与冲击,2015,34(11):83-87.TANG G J,PANG B,LIU S K.Fault diagnosis of rolling bearings based on difference spectrum of singular value and stationary subspace analysis[J].Journal of Vibration and Shock,2015,34(11):83-87.(In Chinese)
[12]陆文凯,丁文龙,张善文,等.基于信号子空间分解的三维地震资料高分辨率处理方法[J].地球物理学报,2009,52(8):2174-2181.LU W K,DING W L,ZHANG S W,et al.A high resolution processing technique for 3_D seismic data based on signal subspace decomposition[J].Chinese Journal Geophysics,2009,52(8):2174-2181.(In Chinese)
[13]DENDRINOS M,BAKAMIDIS S,CARAYANNI G.Speech enhancement from noise:A regenerative approach[J].Speech Communication,1991,10(2):45-57.
[14]EPHRAIM Y,VAN TREES H L.A signal subspace approach for speech enhancement[J].IEEE Transactions on Speech and Audio Processing,1995,3(4):251-266.
[15]JENSEN S H,HANSEN P C,HANSEN S D,et al.Reduction of broad-band noise in speech by truncated QSVD[J].IEEE Transactions on Speech and Audio Processing,1995,3(6):439-448.
[16]李晋,汤井田,王玲,等.基于信号子空间增强和端点检测的大地电磁噪声压制[J].物理学报,2014,63(1):019101.LI J,TANG J T,WANG L,et al.Noise suppression for magnetotelluric sounding data based on signal subspace enhancement and endpoint detection[J].Acta Physica Sinica,2014,63(1):019101.(In Chinese)
[17]汤井田,刘子杰,刘峰屹,等.音频大地电磁法强干扰压制试验研究[J].地球物理学报,2015,58(12):4636-4647.TANG J T,LIU Z J,LIU F Y,et al.The denoising of the audio magnetotelluric data set with strong interferences[J].Chinese Journal Geophysics,2015,58(12):4636-4647.(In Chinese)
[18]代小威.基于V5-2000格式MT时间序列处理与功率谱估计及软件开发[D].武汉:长江大学,2015.DAI X W.Processing and power spectrum estimation of MT time serizes in V5-2000format and software development[D].Wuhan:Yangtze University,2015.(In Chinese)