地震记录小波域高阶相关叠加技术
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摘要
水平叠加技术能够有效地压制随机噪声和多次波,但是对于由于相邻道的噪声表现出相关性和一致性而产生的某些相干干扰,常规的叠加技术容易产生假的同相轴,难以取得较高的信噪比.基于小波理论和高阶统计理论本文提出了小波域高阶相关叠加技术(HOCS),其基本原理是将经动静校正的CMP道集变换到小波域,然后在小波域求取高阶相关系数,进而加权叠加.数值实验和实际资料计算的结果表明,此方法比常规叠加更能够有效地提高信噪比,剔除常规加权叠加无法抑制的某些相关噪声.
The horizontal stacking plays an important role in processing seismic data digitally, due to its efficiency in suppressing random noise and multiplies. However,for some noise exhibiting coherence and correlation in adjacent traces, the weighted stacking based on the conventional correlative function always leads to false events and lower ratios of signal to noise(S/N). In this paper, a new method of higher_order correlative stacking (HOCS) is proposed in the light of the theory of wavelet and higher_order statistics. The main idea is to stack common midpoint gathers after the normal movemout, according to the weight that is calculated on the basis of the higher_order correlative function in the wavelet domain. The results of both synthetic and practical examples show the advantages in improving S/N and muting some correlative noise that the conventional stacking can not inhibit.
The horizontal stacking plays an important role in processing seismic data digitally, due to its efficiency in suppressing random noise and multiplies. However,for some noise exhibiting coherence and correlation in adjacent traces, the weighted stacking based on the conventional correlative function always leads to false events and lower ratios of signal to noise(S/N). In this paper, a new method of higher_order correlative stacking (HOCS) is proposed in the light of the theory of wavelet and higher_order statistics. The main idea is to stack common midpoint gathers after the normal movemout, according to the weight that is calculated on the basis of the higher_order correlative function in the wavelet domain. The results of both synthetic and practical examples show the advantages in improving S/N and muting some correlative noise that the conventional stacking can not inhibit.
引文
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[2]茅金根,刘雯林.非规则噪音地震记录的优化加权叠加.石油物探,2002,40(3):309～311MaoJG,LiuWL.Optimumweightedstackingofseismicrecord withirregularnoises.GeophysicalProspectingforPetroleum(in Chinese),2002,40(3):309～311
[3]王云专,高美娟,任晓乔.分频信噪比加权叠加.物探与化探,2003,27(2):139～141WangYZ,GaoMJ,RenXQ.Signaltonoiseratioweightedstack bydividingfrequencyband.GeophysicalandGeochemicalExploration(inChinese),2003,27(2):139～141
[4]赵玉梅,周兴元.自适应加权叠加.石油地球物理勘探,2003,38(增刊):31～33ZhaoYM,ZhouXY.Adaptiveweightedstacking.OilGeophysical Prospecting(inChinese),2003,38(Suppl.):31～33
[5]AvijitChakraborty,DavidOkaya.Frequency_timedecompositionof seismicdatausingwavelet_basedmethods.Geophysics,1995,60(6):1906～1916
[6]徐义贤,王家映.基于连续小波变换的大地电磁信号谱估计方法.地球物理学报,2000,43(5):677～783XuYX,WangJY.Powerspectrumestimationfor magnetotelluricuricsignalbasedoncontinuouswavelettransform.ChineseJ.Geophys.(inChinese),2000,43(5):677～783
[7]吴爱弟,牟永光.地震信号的小波包分解压噪方法.石油地球物理勘探,1998,33(47):558～562WuAD,MouYG.Seismicnoisesuppressionusingwaveletpackage method.OilGeophysicalProspecting(inChinese),1998,33(4):558～562
[8]张军华,陆基孟.小波变换方法在地震资料去噪和提高分辨率中的应用.石油大学学报(自然科学版),1997,21(1):18～21ZhangJH,LuJM.Applicationofthewavelettransforminremoving noiseandimprovingresolutionofseismicdata.Journalofthe UniversityofPetroleum(inChinese),1997,21(1):18～21
[9]徐义贤,王家映.大地电磁的多尺度反演.地球物理学报,1998,41(5):704～711XuYX,WangJY.Amultiresolutioninversionofmagnetotelluric data.ChineseJ.Geophys.(inChinese),1998,41(5):704～711
[10]LiXG,SachhiMD,UlrchyTJ.Wavelettransforminversionwithpriorscaleinformation.Geophysics,1996,61(5):1379～1385
[11]WuYF,GeorgeA,McMechan.Waveextrapolationinthespatial waveletdomainwithapplicationtopoststackreverse_timemigration.Geophysics,63(2):589～600
[12]陈凌,吴如山,陈.基于Gabor_Daubechies小波域波场外推的散射系数矩阵的计算及其应用.地球物理学报,2004,47(2):289～298ChenL,WuRS,ChenY.Constructionandapplicationoflocal scatteringmatrixbasedonwavefieldextrapolationintheGabor_Daubechiesbeamletdomain.ChineseJ.Geophys.(inChinese),2004,47(2):289～298
[13]Tae_KyungHong,KennettBLN.Awavelet_basedmethodfor simulationoftwo_dimensionalelasticpropagation.Geophys.J.Int.,2002,150:610～638
[14]唐斌,尹成.基于高阶统计的非最小相位地震子波恢复.地球物理学报,2001,44(3):404～410TangB,YinC.Non_minimumphaseseismicwaveletreconstruction basedonhigherorderstatistics.ChineseJ.Geophys.(inChinese),2001,44(3):404～410
[15]谢桂生,石玉梅,尹成.高阶统计量子波估计与处理.石油物探,2000,39(4):19～25XieGS,ShiYM,YinC.Waveletestimationandprocessingusing high_orderaccumulationmethod.GeophysicalExplorationfor Petroleum(inChinese),2000,39(4):19～25
[16]GeogryDL.Mixed_phasewaveletestimationusingfourth_order cumulants.Geophysics,1993,58(7):196～203
[17]熊小军,尹成,张白林等.高阶统计量油气检测方法研究.地球物理学报,2004,47(5):920～927XiongXJ,YinC,ZhangBL,etal.Methodresearchofforecasting oilandgasusinghigher_orderstatistics.ChineseJ.Geophys.(in Chinese),2004,47(5):920～927
[18]迟新刚,贺振华,贺锡雷等.应用双谱进行裂缝储层检测.石油地球物理勘探,2003,38(3):285～289ChiXG,HeZH,HeXL,etal.Fracturedreservoirdetectionby bispectrum.OilGeophysicalProspecting(inChinese),2003,38(3):285～289
[19]王书明,王家映.高阶统计量在大地电磁测深数据处理中的应用研究.地球物理学报,2004,47(5):928～934WangSM,WangJY.Applicationofhigher_orderstatisticsin magnetotelluricdataprocessing.ChineseJ.Geophys.(inChinese),2004,47(5):928～934
[20]DaubechiesI.Othonormalbasesofcompactlysupportedwavelets.Comm.PureAppl.Math.,1988,41:909～996
[21]张贤达.时间序列分析—高阶统计量方法.北京:清华大学出版社,1996ZhangXD.TimeSequenceAnalysis_Higher_orderstatisticsmethod(inChinese).Beijing:TsinghuaUniversityPress,1996
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