首页> 外文学位 >Elastic and acoustic wavefield decompositions and application to reverse time migrations.
【24h】

Elastic and acoustic wavefield decompositions and application to reverse time migrations.

机译:弹性和声波场分解及其在逆向时间偏移中的应用。

获取原文
获取原文并翻译 | 示例

摘要

P- and S-waves coexist in elastic wavefields, and separation between them is an essential step in elastic reverse-time migrations (RTMs). Unlike the traditional separation methods that use curl and divergence operators, which do not preserve the wavefield vector component information, we propose and compare two vector decomposition methods, which preserve the same vector components that exist in the input elastic wavefield. The amplitude and phase information is automatically preserved, so no amplitude or phase corrections are required. The decoupled propagation method is extended from elastic to viscoelastic wavefields.;To use the decomposed P and S vector wavefields and generate PP and PS images, we create a new 2D migration context for isotropic, elastic RTM which includes PS vector decomposition; the propagation directions of both incident and reflected P- and S-waves are calculated directly from the stress and particle velocity definitions of the decomposed P- and S-wave Poynting vectors. Then an excitation-amplitude image condition that scales the receiver wavelet by the source vector magnitude produces angle-dependent images of PP and PS reflection coefficients with the correct polarities, polarization, and amplitudes. It thus simplifies the process of obtaining PP and PS angle-domain common-image gathers (ADCIGs); it is less effort to generate ADCIGs from vector data than from scalar data.;Besides P- and S-waves decomposition, separations of up- and down-going waves are also a part of processing of multi-component recorded data and propagating wavefields. A complex trace based up/down separation approach is extended from acoustic to elastic, and combined with P- and S-wave decomposition by decoupled propagation. This eliminates the need for a Fourier transform over time, thereby significantly reducing the storage cost and improving computational efficiency. Wavefield decomposition is applied to both synthetic elastic VSP data and propagating wavefield snapshots. Poynting vectors obtained from the particle-velocity and stress fields after P/S and up/down decompositions are much more accurate than those without.;The up/down separation algorithm is also applicable in acoustic RTMs, where both (forward-time extrapolated) source and (reverse-time extrapolated) receiver wavefields are decomposed into up-going and down-going parts. Together with the crosscorrelation imaging condition, four images (down-up, up-down, up-up and down-down) are generated, which facilitate the analysis of artifacts and the imaging ability of the four images. Artifacts may exist in all the decomposed images, but their positions and types are different. The causes of artifacts in different images are explained and illustrated with sketches and numerical tests.
机译:P波和S波共存于弹性波场中,它们之间的分离是弹性逆时偏移(RTM)的重要步骤。与不使用保留卷曲度和散度运算符的传统分离方法(该方法不保留波场矢量分量信息)不同,我们提出并比较了两种矢量分解方法,它们保留了输入弹性波场中存在​​的相同矢量分量。幅度和相位信息会自动保存,因此不需要幅度或相位校正。解耦传播方法从弹性波场扩展到粘弹性波场。要使用分解后的P和S向量波场并生成PP和PS图像,我们为各向同性弹性RTM创建了一个新的2D迁移上下文,其中包括PS向量分解。直接从分解的P波和S波Poynting向量的应力和粒子速度定义中直接计算入射P波和反射波和反射波的传播方向。然后,以源矢量幅度缩放接收器小波的激励幅度图像条件会生成具有正确极性,偏振和幅度的PP和PS反射系数的角度相关图像。因此,它简化了获得PP和PS角域公共图像集(ADCIG)的过程;从矢量数据生成ADCIG的工作要比从标量数据生成的工作少。;除了P波和S波分解之外,上行波和下行波的分离也是处理多分量记录数据和传播波场的一部分。一种复杂的基于迹线的上/下分离方法从声学扩展到弹性,并通过解耦传播与P波和S波分解相结合。这消除了随时间进行傅立叶变换的需要,从而大大降低了存储成本并提高了计算效率。波场分解适用于合成弹性VSP数据和传播的波场快照。从P / S和上/下分解后的粒子速度和应力场获得的Poynting向量比没有P / S时更精确源和(逆时外推)接收器波场被分解为上行和下行部分。与互相关成像条件一起,生成了四个图像(上下,上下,上下和上下),这有助于分析伪影和四张图像的成像能力。伪像可能存在于所有分解图像中,但它们的位置和类型不同。通过草图和数值测试来解释和说明不同图像中伪影的原因。

著录项

  • 作者

    Wang, Wenlong.;

  • 作者单位

    The University of Texas at Dallas.;

  • 授予单位 The University of Texas at Dallas.;
  • 学科 Geophysics.
  • 学位 Ph.D.
  • 年度 2016
  • 页码 165 p.
  • 总页数 165
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 康复医学;
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号