改进的矢量分解法压噪研究
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摘要
去噪处理是地震勘探领域的重要方法,对地震资料的品质有较大的影响。矢量分解法是利用噪音偏离信号的夹角来实现随机噪音的压制,属于角度滤波。该方法适用于叠前和叠后资料处理,且不受地层倾角限制,但仍存在信噪分离不彻底的问题。改进的矢量分解法使用高维矢量函数、样条函数提高了矢量夹角的计算精度,并针对常规压噪后相邻道夹角不连续的缺陷,提出进一步的夹角平滑处理的改进方法,使信噪分离更为有效、准确,也能更好地滤除随机噪音、部分多次波和斜干扰等。实际资料处理结果表明,与常规的矢量分解法相比,该方法信噪分离更有效、准确,具有较好的压噪效果。
Denoising is an important method in seismic prospecting and has a great impact on the quality of seismic data. Vector decomposition method is to use the angle of noise deviation from the signal to realize suppression of the random noises, belonging to a kind of angle filtering. This method is suitable for prestack and poststack data processing, not restricted by the formation dip, but there is still the problem that noise is not completely separated. This paper proposes a method for further smoothing of the angles by using improved vector decomposition approach based on high dimensional vector function and spline function to improve the accuracy of the vector angle calculation, in view of the shortage of the discontinuous angles between adjacent tracts after conventional noise suppression. The real seismic data processing shows that this method can be used to get more efficient and more accurate separation between signal and noise, and to filter out random noises, part of multiple and oblique interferences, The case study indicates that this method has good effect of suppressing noise, compared with conventional vector decomposition method.
Denoising is an important method in seismic prospecting and has a great impact on the quality of seismic data. Vector decomposition method is to use the angle of noise deviation from the signal to realize suppression of the random noises, belonging to a kind of angle filtering. This method is suitable for prestack and poststack data processing, not restricted by the formation dip, but there is still the problem that noise is not completely separated. This paper proposes a method for further smoothing of the angles by using improved vector decomposition approach based on high dimensional vector function and spline function to improve the accuracy of the vector angle calculation, in view of the shortage of the discontinuous angles between adjacent tracts after conventional noise suppression. The real seismic data processing shows that this method can be used to get more efficient and more accurate separation between signal and noise, and to filter out random noises, part of multiple and oblique interferences, The case study indicates that this method has good effect of suppressing noise, compared with conventional vector decomposition method.
引文
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[11]李月,杨宝俊,郭华,等.微弱方波信号检测模型混沌解的判定[J].地球物理学进展,2002,17(1):36-42.
[12]仇苏江,黄坚,程慧.多分量地震勘探技术在准噶尔盆地西北缘的应用[J].新疆石油地质,2012,33(4):483-485.
[13]能冉,赵继龙,厚刚福.用频谱分解和地震峰值属性分析预测薄砂岩储集层[J].新疆石油地质,2013,34(2):225-227.
[2]Thorson R,Claerbout J.Velocity?stack and slant?stack stochastic inversion[J].Geophysics,1985,50(12):2 727-2 741.
[3]Hampson D.Inverse velocity stacking for multiples estima?tion[J].Journal of Canadian Society of Exploration Geophys?icists,1986,22(1):44-55.
[4]Foster D J,Mosher C C.Suppression of multiple reflectors using the Radon trans form[J].Geophysics,1992,57(3):386-395.
[5]Kabir M M N,Marfurt K J.Toward true amplitude multi?ples remova[lJ].The Leading Edge,1999,18(1):66-73.
[6]Hu T,White R E.Robust multiple suppression using adaptive beamforming[J].Geophysical Prospecting,1998,46(1):227-248.
[7]Ozbek A.Adaptive beamforming with generalized linear constraints[C].The 70th SEG Annual Meeting,Expanded Abstracts,2000,32(3):2 081-2 084.
[8]Zhou B,Greenhalgh S A.Multiple suppression by 2D filtering in the parabolicτ-p domain:a wave?equation?based method[J].Geophysical Prospecting,1996,44(1):375-401.
[9]王宏伟.矢量分解法压噪[J].石油地球物理勘探,1989,24(1):9-16.
[10]夏洪瑞,陈德钢,周开明,等.中值约束下的矢量分解去噪[J].石油物探,2001,40(3):3-10.
[11]李月,杨宝俊,郭华,等.微弱方波信号检测模型混沌解的判定[J].地球物理学进展,2002,17(1):36-42.
[12]仇苏江,黄坚,程慧.多分量地震勘探技术在准噶尔盆地西北缘的应用[J].新疆石油地质,2012,33(4):483-485.
[13]能冉,赵继龙,厚刚福.用频谱分解和地震峰值属性分析预测薄砂岩储集层[J].新疆石油地质,2013,34(2):225-227.