Bandwidth enhancement: Inverse Q filtering or time-varying Wiener deconvolution?
Bandwidth enhancement: Inverse Q filtering or time-varying Wiener deconvolution?
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DOI：
10.1190/geo2011-0500.1
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发表时间：
2012-06
期刊：
影响因子：
3.3
通讯作者：
M. Baan
中科院分区：
文献类型：
--
作者：
M. Baan
摘要色散和衰减校正可以提高地震数据的分辨率。这极大地方便了解释。原则上，逆Q滤波和时变维纳反卷积可以实现这一点。逆 Q 滤波是一个确定性过程，需要了解品质因数 Q，而时变维纳反卷积是一种基于非平稳传播小波估计的统计方法。基于纯相位逆 Q 滤波的色散校正是一种本质上稳定的方法，在存在噪声的情况下也具有鲁棒性。另一方面，通过仅幅度逆 Q 滤波进行的衰减校正可能会导致噪声放大以及带宽增强。通过时变维纳反卷积进行色散校正具有挑战性，因为这需要估计非平稳、频率相关、非最小相位小波。幸运的是，通过维纳反卷积进行衰减校正只需要估计......
ABSTRACTDispersion and attenuation corrections can improve the resolution of seismic data. This significantly facilitates interpretation. In principle, inverse Q filtering and the time-varying Wiener deconvolution can achieve this. Inverse Q filtering is a deterministic process that requires knowledge of the quality factor Q, whereas the time-varying Wiener deconvolution is a statistical approach based on the estimation of the nonstationary propagating wavelet. Dispersion corrections based on phase-only inverse Q filtering is an inherently stable method that is robust in the presence of noise. Attenuation corrections via amplitude-only inverse Q filtering, on the other hand, is likely to lead to noise amplification as well as bandwidth enhancement. Dispersion corrections via the time-varying Wiener deconvolution are challenging because these require estimation of a nonstationary, frequency-dependent, nonminimum-phase wavelet. Fortunately, attenuation corrections via the Wiener deconvolution need only esti...