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基于变时窗Gabor变换的高分辨率处理技术研究与应用 被引量:4

Research and application of high resolution technique based on Gabor transform with variable time window
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摘要 为了克服时变谱白化等方法中窗长难以确定和等幅效应的问题,以及反Q滤波等方法中Q值难以求准的问题,在反射地震记录变子波模型的基础上,基于Gabor变换,提出了高分辨率处理技术,即在地震数据地层结构的约束下构造一组自适应于地震记录的分析时窗,对地震记录进行自适应非均匀划分;在时频域利用非线性压缩映射提取时变子波;对非平稳地震记录做频谱拓宽和振幅校正,估计补偿因子,对不同时窗之间由吸收引起的能量衰减进行补偿;反变换回时间域得到相对保幅的高分辨率处理结果。理论分析与实际应用表明,该技术的适用条件更接近地下实际情况,是一种相对保幅的提高地震资料分辨率的方法,可以显著提高地震资料的分辨率,能够在波阻抗反演、层序检测等领域发挥重要作用。 To solve such difficult problems as window length determining and constant amplitude effect of TVSW method, and accurate evaluation of Q in the inverse Q filtering method, a high resolution method using Gabor transform is proposed based on changing wavelet mode of reflection seismic signal. Firstly, a set of Gabor time windows adaptive to the seismic signal are constructed constrained by stratum structure and the signal is divided into proper segments of different lengths; Secondly, the time-varying wavelet spectrums in each window are extracted using nonlinear contraction mapping in time-frequency domain; Thirdly, the compensation factors are evaluated and the attenuation caused by absorption in each window is compensated to widen the spectrum and correct the amplitude of the non-stationary seismic signal; Finally, the time-frequency spectrum is transformed back to time domain to obtain the high resolution signal with relative amplitude-preservation. Theoretical analysis and application indicate that the applicable condition of the technique is more close to the actual underground. The proposed technique is a high resolution method with relative amplitude-preservation, can dramatically enhance the seismic resolution, and plays an important role in other fields such as impedance inversion and sequence detection.
机构地区 中海油研究总院
出处 《中国海上油气》 CAS CSCD 北大核心 2015年第6期19-26,共8页 China Offshore Oil and Gas
基金 "十二五"国家科技重大专项"近海大中型油气田地震勘探技术(编号:2011ZX05023-005)"部分研究成果
关键词 变子波模型 GABOR变换 自适应时窗分解 时变子波提取 高分辨率处理 changing wavelet model Gabor transform adaptive time window decomposition time-varying wavelet extraction high resolution processing
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参考文献16

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