基于高阶统计复倒谱子波提取
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摘要
子波反褶积是提高地震资料分辨率的主要方法之一,其关键在于子波的准确性。常规处理方法通常假设子波是最小相位的,但这是不符合实际的,针对这一局限性,利用高阶统计量包含系统相位信息以及抑制高斯噪声的特性,研究了基于复倒谱子波提取方法,分别给出了复倒双谱和复倒三谱提取子波的原理,并构造了平滑窗函数来提高子波估计的准确性。该方法无需对子波相位作任何假设,可估计任意相位子波。针对混合相位子波,进行了理论试算,验证了该方法的有效性,最后对实际资料处理的结果也说明了该方法的实际应用价值。
Wavelet deconvolution is one of the main methods to improve the resolution of seismic data,and the key is the accuracy of the wavelet.Conventional methods usually presume that the wavelet is the minimum phase,but this may not be correct.To solve this problem,the authors utilized the property of the higher order statistic quantity that it includes phase information of the system and suppresses Gaussian noise to study the wavelet extraction method based on cepstrum and,as a result,gave the principles of extracted wavelet based on complex cepstrum,bispectrum and trispectra.In addition the authors constructed a smooth window function to improve the accuracy of wavelet.The method does not need to make any assumption about wavelet's phase,and it can extract wavelet of any phase.Tackling the mixed wavelet,the authors made theoretical experiments to verify the effectiveness of the method,and the results of actual data processing showed the effectiveness of the method.
Wavelet deconvolution is one of the main methods to improve the resolution of seismic data,and the key is the accuracy of the wavelet.Conventional methods usually presume that the wavelet is the minimum phase,but this may not be correct.To solve this problem,the authors utilized the property of the higher order statistic quantity that it includes phase information of the system and suppresses Gaussian noise to study the wavelet extraction method based on cepstrum and,as a result,gave the principles of extracted wavelet based on complex cepstrum,bispectrum and trispectra.In addition the authors constructed a smooth window function to improve the accuracy of wavelet.The method does not need to make any assumption about wavelet's phase,and it can extract wavelet of any phase.Tackling the mixed wavelet,the authors made theoretical experiments to verify the effectiveness of the method,and the results of actual data processing showed the effectiveness of the method.
引文
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[18]邢贞贞,韩立国,王宇.高阶统计量方法在地震信号分析中的应用[J].吉林大学学报:地球科学版,2007,37(增刊1):139-142.
[19]秦雪霏,韩立国,李巍.地震波多次散射波场的高阶谱统计分析[J].吉林大学学报:地球科学版,2007,37(增刊1):91-94.
[20]冯智慧,刘财,冯晅,等.基于高阶累积量一维切片的地震信号初至自动拾取方法[J].吉林大学学报:地球科学版,2011,41(2):559-571.
[21]Tribolet J M.Seismic applications of homomorphic signal processing[M].Englewood Cliffs,NJ:Prentice-Hall,1979.
[2]梁光河.地震子波提取方法研究[J].石油物探,1998,37(1):31-39.
[3]张贤达.时间序列分析—高阶统计量方法[M].北京:清华大学出版社,1996.
[4]尹成,伍志明,邓怀群.高阶统计量方法在地震勘探中的应用[J].地球物理学进展,2003,18(3):546-550.
[5]Lazear G D.Mixed-phase wavelet estimation using fourth-order cu-mulates[J].Geophysics,1993,58(7):1042-1051.
[6]Ulrych T J,Velis D,Sacchi M.Wavelet estimation revisited[J].The Leading Edge,1995,14(11):1139-1142.
[7]Velis D R,Ulrych T J.Simulated annealing wavelet estimation viafourth-order cumulant matching[J].Geophysics,1996,61(6):1939-194.
[8]戴永寿,王俊岭,王伟伟,等.基于高阶累积量ARMA模型线性非线性结合的地震子波提取方法研究[J].地球物理学报,2008,51(6):1851-1859.
[9]戴永寿,牛慧,彭星,等.基于自回归滑动平均模型和粒子群算法的地震子波提取[J].中国石油大学学报:自然科学版,2011,35(3):47-50.
[10]李大卫,尹成,熊晓军,等.高阶谱混合方法地震子波估计及处理[J].地球物理学进展,2005,20(1):29-33.
[11]李大卫,田继东,成竹,等.基于高阶统计的混合相位子波估计及其处理[J].勘探地球物理进展,2005,28(2):117-121.
[12]谢桂生,石玉梅,魏野.双谱地震子波估计[J].西南石油学院学报,2000,22(3):25-29.
[13]李亚峻,李月,高颖.基于双谱幅值和相位重构的地震子波提取[J].地球物理学进展,2007,22(3):947-952.
[14]PAN R L,Chrysostomos L N.The complex cepstrum of higher ordercumulants and nonminimum phase system identification[J].IEEEtransactions on acoustics,speech,and signal processing,1988,36(2):186-205.
[15]Polydoros A,Fam A.The differential cepstrum:Definition and prop-erties[J].Proc.IEEE Int.Symp.Circuits Syst,1981:77-80.
[16]Polydoros A,Au A,Fam A.Shift-invariant homomorphic filtering[J].Proc.22nd Midwest Symp.Circuits Syst.,Philadelphia,PA,1979:140-145.
[17]Nikias C L,Petropulu A P.Higher-order spectral analysis:a nonlin-ear signal processing framework[M].Englewood Cliffs,NJ:Pren-tice-Hall,1993.
[18]邢贞贞,韩立国,王宇.高阶统计量方法在地震信号分析中的应用[J].吉林大学学报:地球科学版,2007,37(增刊1):139-142.
[19]秦雪霏,韩立国,李巍.地震波多次散射波场的高阶谱统计分析[J].吉林大学学报:地球科学版,2007,37(增刊1):91-94.
[20]冯智慧,刘财,冯晅,等.基于高阶累积量一维切片的地震信号初至自动拾取方法[J].吉林大学学报:地球科学版,2011,41(2):559-571.
[21]Tribolet J M.Seismic applications of homomorphic signal processing[M].Englewood Cliffs,NJ:Prentice-Hall,1979.
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