地震研究

提出由一维模板匹配滤波技术(MFT)和二维曲波(Curvelet)变换法穿插的数据处理方法,即先通过一维模板匹配滤波方法得到相关系数,将相关系数组成二维数据并用曲波变换法处理,最后将各道对应相关系数分别与模板信号褶积,得到高信噪比恢复信号。将该方法用于处理仿真数据和宾川主动源气枪信号,结果表明:在宾川主动源气枪信号的处理中,本方法较单一数据去噪方法恢复能力更好,可对气枪主动源的模拟与实际信号进行更好的数据提取与恢复,得到噪声干扰更少的地下介质波速变化,提高低信噪比数据的利用率与可分析性。

In this paper,we introduced a data processing method interspersed with two method that based on one-dimensional template Matching Filtering Technology(MFT)and two-dimensional Curvelet Transform method.Firstly,the correlation coefficients are obtained by the one-dimensional MFT,then the correlation coefficients are composed into two-dimensional data and processed by Curvelet Transform method.Finally,the corresponding correlation coefficients are respectively folded with the template signal to obtain the recovery signal.Then,we applied this method to the processing of simulation signal and air gun signal of Binchuan active source.Experiments show that this method is more better than that processing by one single method,with better recovery ability in Binchuan Air Gun Experimental Base,which can get better recovery signal in simulation and actual recorded data signal processing,and get the wave velocity variation with less noise interference in underground media.It is beneficial to the analysis and research of the following seismologists and improve the utilization and analyzability of low SNR data.

引言
1 方法原理简介
2 仿真数据计算
3 实际数据处理
4 结论与讨论

图1 匹配曲波结合法的数据处理流程<br/>Fig.1 Data processing flow of the method combining Matched Filter Technique and Curvelet Transform

图1 匹配曲波结合法的数据处理流程
Fig.1 Data processing flow of the method combining Matched Filter Technique and Curvelet Transform

图2 连续曲波频域分块图(a)和离散曲波频域分块图(b)(据Emmanuel et al,2006)<br/>Fig.2 Continuous curvelet frequency domain block diagram(a)and discrete curvelet frequency domain block diagram(b)(based on Emmanuel et al,2006)

图2 连续曲波频域分块图(a)和离散曲波频域分块图(b)(据Emmanuel et al,2006)
Fig.2 Continuous curvelet frequency domain block diagram(a)and discrete curvelet frequency domain block diagram(b)(based on Emmanuel et al,2006)

图3 主动源气枪激发仿真信号<br/>Fig.3 The simulation signal of active source air gun activates

图3 主动源气枪激发仿真信号
Fig.3 The simulation signal of active source air gun activates

图4 匹配识别相关系数曲波处理前后对比<br/>Fig.4 Comparsion of match and identify correlation coefficients before and after wave processing

图4 匹配识别相关系数曲波处理前后对比
Fig.4 Comparsion of match and identify correlation coefficients before and after wave processing

图5 不同方法处理二维数据的结果对比<br/>Fig.5 Comparsion of the results of two-dimensional data processed by different methods

图5 不同方法处理二维数据的结果对比
Fig.5 Comparsion of the results of two-dimensional data processed by different methods

图6 不同方法处理后信号中某道与理论信号对比<br/>Fig.6 Comparision of theory signal and the channel in the signal processed by different methods

图6 不同方法处理后信号中某道与理论信号对比
Fig.6 Comparision of theory signal and the channel in the signal processed by different methods

图7 不同方法计算得到的波速相对变化<br/>Fig.7 Relative change of wave velocity calculated by different methods

图7 不同方法计算得到的波速相对变化
Fig.7 Relative change of wave velocity calculated by different methods

表1 -5 dB时不同去噪方法的评价结果对比<br/>Tab.1 The comparison of evaluation results of different denoising methods when -5 dB

表1 -5 dB时不同去噪方法的评价结果对比
Tab.1 The comparison of evaluation results of different denoising methods when -5 dB

图8 不同方法在不同信噪比下的Eva值比较<br/>Fig.8 The results of Eva-values at differentSNR by several different methods

图8 不同方法在不同信噪比下的Eva值比较
Fig.8 The results of Eva-values at differentSNR by several different methods

图9 53284台原始数据<br/>Fig.9 Raw data to be processed of 53284

图9 53284台原始数据
Fig.9 Raw data to be processed of 53284

图10 不同方法去噪后的二维数据信号(a)和信号中一道(b)的对比<br/>Fig.10 Two-dimensional data signals(a)denoised by different methods are compared with one another(b)

图10 不同方法去噪后的二维数据信号(a)和信号中一道(b)的对比
Fig.10 Two-dimensional data signals(a)denoised by different methods are compared with one another(b)

图11 不同方法得到的地下介质波速相对变化曲线(a)与该地水位变化曲线(b)对比<br/>Fig.11 Comparison between the rate curve of wave velocity(a)obtained by different methods and the water level curve(b)

图11 不同方法得到的地下介质波速相对变化曲线(a)与该地水位变化曲线(b)对比
Fig.11 Comparison between the rate curve of wave velocity(a)obtained by different methods and the water level curve(b)

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备注

引言

1 方法原理简介

2 仿真数据计算

3 实际数据处理

4 结论与讨论

期刊信息