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时频域零炮检距地震道拟合技术在高分辨率资料处理中的应用
引用本文:温书亮,王焕弟,苑益军,何汉漪,刘永江.时频域零炮检距地震道拟合技术在高分辨率资料处理中的应用[J].石油地球物理勘探,2003,38(5):512-516.
作者姓名:温书亮  王焕弟  苑益军  何汉漪  刘永江
作者单位:[1]中国地质大学,北京 [2]中海石油研究中心
摘    要:在地震资料处理中,水平叠加的作用是压制随机噪声和消除多次波,但伴随的缺点是降低了地震资料分辨率,且模糊了振幅特征。为了提高地震资料分辨率和振幅保真,许多学者提出了多种拟合方法代替水平叠加。然而,这些拟合方法也有其自身的弱点,如在提高信噪比方面的能力较弱等。本文从应用角度出发,讨论了时频域零炮检距拟合方法的特点及在海上高分辨率地震资料处理中应用叠前消除各种线性干扰和多次波的必要性。实际资料处理结果表明,只要在叠前做好去噪工作,应用时频域零炮检距地震道拟合方法代替水平叠加有利于改善地震资料的分辨率和振幅保真。

关 键 词:时频域  零炮检距  地震道拟合技术  高分辨率  地震资料处理  水平叠加  振幅保真  聚束滤波  均值加权

Application of zero-offset seismic trace fitting in time-frequency domain to m arine high-resolution seismic data processing.
Wen Shuliang,Wang Huandi,Yuan Yij un,He Hanyi and Liu Yongjiang..Application of zero-offset seismic trace fitting in time-frequency domain to m arine high-resolution seismic data processing.[J].Oil Geophysical Prospecting,2003,38(5):512-516.
Authors:Wen Shuliang  Wang Huandi  Yuan Yij un  He Hanyi and Liu Yongjiang
Abstract:The function of CMP stack in seismic data processing is to suppress r andom noise and eliminate multiple,but associated disadvantages are decreasing the res olution of seismic data and smearing the amplitude character.In order to impro ve the resolution of seismic data and the hi-fi of amplitude,many researchers have presented variety of fitting methods to replace CMP stack,but each fittin g method has his own shortcomings,such as poor ability of improving S/N.Star ting from application aspect,the paper discussed the characters of zero-offset fitting in time-frequency and necessity of application of prestack elimination of different linear interference and multiple to marine high-resolution seismic data processing.The real data processing showed so long as the prestack noise- elimination well-done,application of zero-offset seismic trace fitting in time -frequency domain to replace CMP stack is favorable to improve seismic resoluti on and hi-fi of amplitude.
Keywords:seismic data processing  fitting method  time-frequency domai n  CMP stack  high-resolution  hi-fi of amplitude  beam-focusing filtering  mean  value weighting
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