Modified interferometric imaging condition for reverse-time migration
Modified interferometric imaging condition for reverse-time migration
复制标题
逆时偏移的改进干涉成像条件
DOI：
10.1071/eg16116
复制
发表时间：
2017-01
影响因子：
0.9
通讯作者：
Ying Shi
中科院分区：
文献类型：
--
作者：
Xue-Bao Guo;Hong Liu;Ying Shi
对于逆时偏移，高分辨率成像主要取决于速度模型的精度和成像条件。然而，在实践中，速度模型的小尺度分量不能通过层析成像方法来估计;因此，波场不能从背景速度准确地重建，并且成像过程将产生伪影。一些噪声是由于不相关的地震事件的互相关。干涉成像条件能有效地抑制成像噪声，尤其是小尺度部分的未知随机干扰。本文对传统的干涉成像条件进行了扩展，提出了一种基于伪维格纳分布函数的干涉成像条件。数值算例表明，改进后的干涉成像条件提高了成像精度。背景速度模型中的随机波动所引起的伪影会污染最终图像，这使得逆时偏移的解释工作难以实现。本文提出的成像条件利用伪维格纳分布函数，可以降低这种噪声，也有助于改善复杂层的连续性。
For reverse-time migration, high-resolution imaging mainly depends on the accuracy of the velocity model and the imaging condition. In practice, however, the small-scale components of the velocity model cannot be estimated by tomographical methods; therefore, the wavefields are not accurately reconstructed from the background velocity, and the imaging process will generate artefacts. Some of the noise is due to cross-correlation of unrelated seismic events. Interferometric imaging condition suppresses imaging noise very effectively, especially the unknown random disturbance of the small-scale part. The conventional interferometric imaging condition is extended in this study to obtain a new imaging condition based on the pseudo-Wigner distribution function (WDF). Numerical examples show that the modified interferometric imaging condition improves imaging precision. The artefacts caused by random fluctuations in the background velocity model will contaminate the final image, which makes the work of interpretation difficult to implement in reverse-time migration. The imaging condition proposed in this paper, which exploits the pseudo-Wigner distribution function, can reduce this noise, and also help improve the continuity of complex layers.
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DOI：
10.1190/1.3059164
发表时间：
2008
期刊：
Seg Technical Program Expanded Abstracts
影响因子：
--
作者：
P. Sava
通讯作者：
P. Sava
影响因子：
3.3
作者：
P. Sava;O. Poliannikov
通讯作者：
P. Sava;O. Poliannikov
DOI：
10.1137/050633524
发表时间：
2006-07
期刊：
Multiscale Model. Simul.
影响因子：
--
作者：
L. Borcea;G. Papanicolaou;C. Tsogka
通讯作者：
L. Borcea;G. Papanicolaou;C. Tsogka
影响因子：
3.3
作者：
Yu Zhang;Guanquan Zhang
通讯作者：
Yu Zhang;Guanquan Zhang
影响因子：
4.4
作者：
J. Mayer;W. Band
通讯作者：
J. Mayer;W. Band