小波
反褶积
偏斜
峰度
振幅
算法
计算机科学
小波变换
连贯性(哲学赌博策略)
数学
模式识别(心理学)
统计
人工智能
物理
光学
作者
Wei Feng,Teng Hu,Y. Zhang,Fuqi Yao
出处
期刊:Proceedings
日期:2015-05-26
被引量:1
标识
DOI:10.3997/2214-4609.201413421
摘要
Summary Seismic wavelet estimation is an important part of seismic data processing and interpretation, whose preciseness is directly related to the results of deconvolution and inversion. The methods for seismic wavelet estimation can be classified into two basic types: deterministic and statistical. By combining the two types of methods, spectral coherence method ( Walden & White, 1998 ) of deterministic method and skewness attribute method ( Fomel & Van der Baan, 2014 ) of statistical method, the amplitude and phase of the time-varying wavelet are estimated separately. The skewness attribute is used to estimate time-varying phase of propagating wavelet instead of locally observed wavelet. Phase-only corrections can then be applied by means of a time-varying phase rotation. Alternatively, amplitude and phase deconvolution can be achieved to enhance the resolution. We illustrate the method on both synthetic and real data examples.
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