小波变换域K-L变换及其去噪效果分析
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摘要
K-L变换利用相邻地震道的相关性来去除随机噪声,但对于倾斜和弯曲同相轴反射去噪效果不佳。采用改进的时变倾角扫描叠加K-L变换能够较好地去除随机噪声,但由于在时间域进行,没有考虑有效信号和随机噪声在频率域的特点,高频有效信号易受压制。小波变换具有较强的时频分析能力,在小波变换域进行K-L变换,可以实现分时分频K-L变换去噪。介绍了小波变换域K-L变换压制随机噪声的基本原理,即先将地震信号进行小波分解形成分时分频的小波包剖面,然后用K-L变换对小波包剖面进行去噪,再将去噪后的小波包剖面重构回地震剖面,从而达到消除随机噪声的目的。理论模型计算和实际资料处理表明,小波变换域K-L变换去噪方法在有效去除随机噪声的同时能够保护高频有效信号。
The K-L transformation uses the coherence of adjacent seismic traces to remove the random noise. But the de-noise effect is not good for sloping and bending event reflection. Although the advanced time-variation dip sweep stack K-L transformation can remove random noises, the characteristics of effective signals and random noises in frequency domain is not taken into consideration, making the high-frequency effective signals lost. Because the wavelet transformation has a good ability in time-frequency analysis, the K-L transformation in wavelet domain can remove noises in time and frequency domain separately. The principles of suppressing random noises with K-L transformation in wavelet conversion domain are that 1) wavelet decomposition is carried out on seismic signals to form wavelet packet sections in time sharing and frequency division, 2) K-L transformation is utilized to remove noises on sections, and 3) the de-noise wavelet packet sections are reconstituted into seismic sections to remove random noises. The theoretical model computation and actual data processing show that the K-L transformation in wavelet conversion domain can remove random noises effectively and preserve the effective high-frequency signals simultaneously.
The K-L transformation uses the coherence of adjacent seismic traces to remove the random noise. But the de-noise effect is not good for sloping and bending event reflection. Although the advanced time-variation dip sweep stack K-L transformation can remove random noises, the characteristics of effective signals and random noises in frequency domain is not taken into consideration, making the high-frequency effective signals lost. Because the wavelet transformation has a good ability in time-frequency analysis, the K-L transformation in wavelet domain can remove noises in time and frequency domain separately. The principles of suppressing random noises with K-L transformation in wavelet conversion domain are that 1) wavelet decomposition is carried out on seismic signals to form wavelet packet sections in time sharing and frequency division, 2) K-L transformation is utilized to remove noises on sections, and 3) the de-noise wavelet packet sections are reconstituted into seismic sections to remove random noises. The theoretical model computation and actual data processing show that the K-L transformation in wavelet conversion domain can remove random noises effectively and preserve the effective high-frequency signals simultaneously.
引文
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8王振国,汪恩华．小波包相关阀值去噪[J]．石油物探, 2002,41(4):400～405
9周洁玲．利用K-L变换提高地震记录的信噪比[J]．西南石油学院学报,2003,25(3):5～11
10张广智,印兴耀．一种提高K-L变换速度和精度的方法[J]．石油物探,1997,36(增刊):112～115
2 Al-Yahya K M.部分卡南一洛伊夫变换用于压制地震剖面的随机噪声[J]．石油物探译丛,1992,15(2):28-41
3李小红,汪晓兵．中值滤波在地震资料处理中的应用[J]．石油物探,2004,43(3):248～250
4王润秋,胡天跃．用聚束滤波方法消除地震资料中规则噪音[J]．勘探地球物理进展,2003,26(4): 268～272
5吕景贵,刘振彪．压制叠前相干噪音的速度变换域滤波方法[J]．石油物探,2001,40(1):94～112
6胡大跃．地震资料叠前去噪技术的现状与未来[J]．地球物理学进展,2002,24(2):218～222
7朱仕军,杜志敏,沈昭国等．储层定量建模[M]．北京:石油工业出版社,2005．6～13
8王振国,汪恩华．小波包相关阀值去噪[J]．石油物探, 2002,41(4):400～405
9周洁玲．利用K-L变换提高地震记录的信噪比[J]．西南石油学院学报,2003,25(3):5～11
10张广智,印兴耀．一种提高K-L变换速度和精度的方法[J]．石油物探,1997,36(增刊):112～115
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