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频率域奇异值分解压制随机噪声方法
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科技导报 | 研究论文 2013,31(21): 58-63
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科技导报 | 研究论文 2013, 31(21): 58-63
频率域奇异值分解压制随机噪声方法
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鲍伟1, 马继涛2
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    1. 中石化江苏油田物探技术研究院, 南京 210046;2. 中国石油大学(北京)地球物理与信息工程学院;油气资源与探测国家重点实验室, 北京 102249
Seismic Random Noise Suppression by Using Frequency-domain Singular Value Decomposition
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出版时间: 2013-07-28 doi: 10.3981/j.issn.1000-7857.2013.21.010
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奇异值分解(SVD)是提高信噪比的一种较新的有效手段之一。本文从数学角度阐述了奇异值分解SVD滤波技术增强地震资料信噪比的原理,对比了时间域和频率域SVD技术压制随机噪声的处理效果。结果表明,时间域SVD技术只能对水平或接近水平的同相轴进行信号增强,对倾斜同相轴的处理效果较差;而频率域SVD技术既可以处理水平同相轴,也可以处理倾斜同相轴,对提高地震剖面信噪比具有很好的效果。本文用3个简单的合成地震记录和1个实际地震资料检验了SVD两种方法的应用效果。结果表明,本文方法可以达到随机噪声压制的效果。
奇异值分解  /  随机噪声  /  时间域  /  频率域
Singular Value Decomposition (SVD) is a new and effective method for random noise suppression. The principle of the SVD filtering technique, which enhances the signal to noise ratio of seismic data, is illustrated. Then, by applying time-domain and frequency- domain SVD techniques to suppress random noise generated from a variety of seismic model data, their processing results are compared with each other. The results indicate that the time-domain SVD technique is only able to enhance flat or near flat events. Whenencountering dip events, it is less effective. However, the frequency-domain SVD technique is able to enhance both flat and dip events, and improve the signal to noise ratio of seismic profile. Three simple synthetic seismograms and one real seismic data are used, and the practical effects of these two SVD methods are verified. The results show that the frequency-domain SVD is effective for suppressing the random noise.
SVD  /  random noise  /  time-domain  /  frequency-domain
鲍伟;马继涛. 频率域奇异值分解压制随机噪声方法. 科技导报, 2013 , 31 (21) : 58 -63 . DOI: 10.3981/j.issn.1000-7857.2013.21.010
BAO Wei;MA Jitao. Seismic Random Noise Suppression by Using Frequency-domain Singular Value Decomposition[J]. Science & Technology Review, 2013 , 31 (21) : 58 -63 . DOI: 10.3981/j.issn.1000-7857.2013.21.010
2013年第31卷第21期
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doi: 10.3981/j.issn.1000-7857.2013.21.010
  • 接收时间:2012-12-14
  • 首发时间:2013-07-28
  • 出版时间:2013-07-28
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  • 收稿日期:2012-12-14
  • 修回日期:2013-03-15
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
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Genus
种数
Number of
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占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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