Multiple reflection and transmission phases in complex layered media using a multistage fast marching method
Multiple reflection and transmission phases in complex layered media using a multistage fast marching method
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DOI：
10.1190/1.1801950
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发表时间：
2004-09-01
期刊：
影响因子：
3.3
通讯作者：
Sambridge, M
中科院分区：
文献类型：
--
作者：
Rawlinson, N;Sambridge, M
计算旅行时间的传统基于网格的eikonal方案通常只局限于获得第一个到达点。然而，较晚到达的地震可能数量众多，振幅更大，这使它们成为地震成像等实际应用的潜在宝贵资源。本文的目的是介绍一种基于网格的方法来跟踪分层介质中由任意数量的反射和折射分支组成的多值波前。一种称为快速推进法（FMM）的有限差分对角求解器用于将波前从一个界面传播到下一个界面。通过将波前进入的每一层作为单独的计算域处理，通过在相邻层中重新初始化FMM得到折射分支，通过在入射层中重新初始化FMM得到反射分支。为了提高精度，在波前曲率较大的源附近采用局部网格细化方案。算例表明该方法在高度复杂的分层介质中是可行的。即使在速度变化大至8:1和高曲率界面的情况下，由许多反射和透射事件组成的波前也能快速准确地跟踪。这是因为该方案保留了单级FMM的两个理想特性：计算速度和稳定性。关于源的局部网格细化也可以在计算成本增加很少的情况下将精度提高一个数量级。
Traditional grid-based eikonal schemes for computing traveltimes are usually confined to obtaining first arrivals only. However, later arrivals can be numerous and of greater amplitude, making them a potentially valuable resource for practical applications such as seismic imaging. The aim of this paper is to introduce a grid-based method for tracking multivalued wavefronts composed of any number of reflection and refraction branches in layered media. A finite-difference eikonal solver, known as the fast marching method (FMM) is used to propagate wavefronts from one interface to the next. By treating each layer that the wavefront enters as a separate computational domain, one obtains a refracted branch by reinitializing FMM in the adjacent layer and a reflected branch by reinitializing FMM in the incident layer.To improve accuracy, a local grid refinement scheme is used in the vicinity of the source where wavefront curvature is high. Several examples are presented which demonstrate the viability of the new method in highly complex layered media. Even in the presence of velocity variations as large as 8:1 and interfaces of high curvature, wavefronts composed of many reflection and transmission events are tracked rapidly and accurately. This is because the scheme retains the two desirable properties of a single-stage FMM: computational speed and stability. Local grid refinement about the source also can increase accuracy by an order of magnitude with little increase in computational cost.