Contourlet域相关和阈值衰减联合去噪方法及其在地震资料处理中的应用
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摘要
针对常规方法不能很好地压制复杂地质条件下的低信噪比地震记录中的随机噪声的问题,提出了Contourlet域相关和阈值衰减联合去噪方法(CTCT)。首先,采用Contourlet分解地震资料,对得到的尺度-方向分量进行倾角扫描,通过相关叠加压制随机噪声;然后,对相干加强处理后的剩余随机噪声采用非线性阈值进一步衰减。模型算例及实例结果表明,此方法压制随机干扰的效果要优于传统方法,一定程度上改善了常规滤波方法在压制噪声时对有效波的影响。
For the question that traditional methods can not perfectly denoise for the low signal to noise ratio of seismic records in complex geological conditions,we propose the joint denoising method based on correlation and thresholding in Contourlet domain.Contourlet transform(CT) is firstly applied to decompose seismic data.We do dip scanning for every scale-orientation component,suppress random noise by correlative stacking.Besides,we apply non-linear thresholding for the residual random noise to eliminate it thoroughly.Applications to both synthetic data and actual seismic data from Dabashan,South China,show that the new method eliminates the noise portion more efficiently and retains a greater amount of geologic data.
For the question that traditional methods can not perfectly denoise for the low signal to noise ratio of seismic records in complex geological conditions,we propose the joint denoising method based on correlation and thresholding in Contourlet domain.Contourlet transform(CT) is firstly applied to decompose seismic data.We do dip scanning for every scale-orientation component,suppress random noise by correlative stacking.Besides,we apply non-linear thresholding for the residual random noise to eliminate it thoroughly.Applications to both synthetic data and actual seismic data from Dabashan,South China,show that the new method eliminates the noise portion more efficiently and retains a greater amount of geologic data.
引文
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[11]Do M N,Vetterli M.The Contourlet Transform:an Effcient Directional Multiresolution Image Repre-sentation[J].IEEE Transactions on Image Process-ing,2005,14(12):2 091-2 106
[12]Feng Peng,Pan Yingjun,Wei Biao,et al.Enhan-cing Retinal Image by the Contourlet Transform[J].Pattern Recognition Letters,2007,28(4):516-552
[13]Chen G Y,Kegl B.Invariant Pattern RecognitionUsing Contourlets and AdaBoost[J].Pattern Rec-ognition,2010,43(3):579-583
[14]张恒磊,张云翠,刘天佑,等.基于Curvelet域的叠前地震资料去噪方法[J].石油地球物理勘探,2008,43(5):508-513
[2]安勇,杨长春.一种改进的频率-波数域倾角扫描去噪方法[J].石油地球物理勘探,2008,43(2):210-212
[3]杨海涛,朱仕军,杨爱国,等.S变换时变滤波在去噪处理中的应用研究[J].西南石油大学学报(自然科学版),2009,31(6):56-58
[4]高静怀,毛剑,满蔚仕,等.叠前地震资料噪声衰减的小波域方法研究[J].地球物理学报,2006,49(4):1 155-1 163
[5]夏洪瑞,葛川庆,彭涛.小波时空变阈值去噪方法在可控震源资料处理中的应用[J].石油地球物理勘探,2010,45(1):23-27
[6]王黎,孙云莲.二维小波变换及ICA消除图像混合噪声[J].武汉大学学报.信息科学版,2008,33(2):136-139
[7]王文波,费浦生,羿旭明,等.基于提升格式小波包变换的SAR图像去噪[J].武汉大学学报.信息科学版,2007,32(7):585-588
[8]安勇.利用地震波组特征的精细相干扫描方法[J].石油地球物理勘探,2009,44(4):406-408
[9]樊计昌,王夫运,刘明军,等.小波尺度域和空间域倾角扫描高阶相关去噪技术[J].石油地球物理勘探,2008,43(5):514-517
[10]樊计昌,刘明军,王夫运,等.小波包节点域和空间域倾角扫描高阶相关去噪技术[J].石油地球物理勘探,2009,44(6):695-699
[11]Do M N,Vetterli M.The Contourlet Transform:an Effcient Directional Multiresolution Image Repre-sentation[J].IEEE Transactions on Image Process-ing,2005,14(12):2 091-2 106
[12]Feng Peng,Pan Yingjun,Wei Biao,et al.Enhan-cing Retinal Image by the Contourlet Transform[J].Pattern Recognition Letters,2007,28(4):516-552
[13]Chen G Y,Kegl B.Invariant Pattern RecognitionUsing Contourlets and AdaBoost[J].Pattern Rec-ognition,2010,43(3):579-583
[14]张恒磊,张云翠,刘天佑,等.基于Curvelet域的叠前地震资料去噪方法[J].石油地球物理勘探,2008,43(5):508-513
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