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Automatic NMO correction and Full Common Depth Point NMO Velocity Field Estimation In Anisotropic and lateral heterogeneous Media

机译:各向异性和横向异质介质中的自动NMO校正和全公共深度点NMO速度场估算

摘要

#$%^&*AU2016202792A120171116.pdf#####ABSTRACT Although several anisotropic traveltime equations have been written by different researchers to perform normal moveout (NMO) correction of common depth point (CDP) seismic gathers, none has been able to address the problems associated with the far offset data. In this paper, we present a computational process that, not only accurately flattens and NMO-correct the far offsets data to zero-offset times no matter how far, but simultaneously provide full NMO velocity (Vnmo) fields and corresponding anisotropy field. The method is based on doing a predefined number of NMO velocity iterations using linear vertical interpolation of different NMO velocities at each seismic trace individually. At each iteration, we measure the semblance between the zero offset trace and the next seismic trace, then after all the iterations are done, the one with the maximum semblance value is chosen, which is assumed to be the most suitable NMO velocity trace that accurately flattens seismic reflection events. The other traces follow the same process, and a final velocity field is then extracted. Isotropic, anisotropic and lateral heterogenous synthetic geological models were built based on a ray tracing algorithm to test the method. A range of synthetic background noise, ranging from 10 to 30 %, was applied to the models. In addition, the method was tested on Hess's VTI (vertical transverse isotropy) model and Alaska (gas field) pre-stack seismic CDP field example. The results from the presented examples show an excellent NMO correction and extracted a reasonably accurate NMO velocity field.
机译:#$%^&* AU2016202792A120171116.pdf #####抽象尽管不同的人写了几个各向异性的旅行时间方程研究人员对普通深度点进行法向运动(NMO)校正(CDP)地震道,没有一个能够解决与远距数据。在本文中,我们提出了一个计算过程,不仅精确展平并NMO将远偏移数据校正为零偏移时间距离,但同时提供完整的NMO速度(Vnmo)场和相应的各向异性场。该方法基于执行预定义数量的使用不同NMO的线性垂直插值进行NMO速度迭代每个地震道上的速度分别。在每次迭代中,我们测量零偏移迹线和下一条地震迹线之间的相似度,然后完成迭代后,选择具有最大相似度值的迭代,即被认为是最精确地平展地震的NMO速度轨迹反思事件。其他迹线遵循相同的过程,并具有最终速度场然后提取。各向同性,各向异性和横向异质性综合地质基于光线跟踪算法构建模型以测试该方法。范围模型应用了10%至30%的合成背景噪声。在此外,该方法在Hess的VTI(垂直横向各向同性)模型上进行了测试和阿拉斯加(气田)叠前地震CDP油田实例。来自的结果给出的示例显示了出色的NMO校正并提取了合理的准确的NMO速度场。

著录项

  • 公开/公告号AU2016202792A1

    专利类型

  • 公开/公告日2017-11-16

    原文格式PDF

  • 申请/专利权人 MOHAMED ABDEL HAMED;

    申请/专利号AU20160202792

  • 发明设计人 ABDEL HAMED MOHAMED;

    申请日2016-04-30

  • 分类号G01V1/36;G01V1/28;

  • 国家 AU

  • 入库时间 2022-08-21 12:45:55

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