A Bayesian Approach to Microtremor Array Methods for Estimating Shallow S‐wave Velocity Structures: Identifying Structural Singularities
A Bayesian Approach to Microtremor Array Methods for Estimating Shallow S‐wave Velocity Structures: Identifying Structural Singularities
复制标题
用于估计浅 S 波速度结构的微震阵列方法的贝叶斯方法：识别结构奇点
DOI：
10.1029/2018jb015831
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Iwata Takaki
中科院分区：
文献类型：
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作者：
Cho Ikuo.;Iwata Takaki
本文提出将贝叶斯推理应用于估计浅波速度结构的问题，特别是那些包含结构奇点的结构（夹在高速层之间的低速层或低速层之间的高速层），方法是使用微震勘测中获得的瑞利波相速度。这里提出的方法使用经验贝叶斯方法，其中使用现场测量数据来构建先验分布。基于贝叶斯因子，从具有不同层厚度参数值的多个候选模型中选择最佳速度结构模型。使用所提出的方法可以客观地确定一维速度结构模型中的层厚度参数值，以解释观测到的瑞利波相速度色散曲线。它还通过使用先验分布来稳定反演过程，并通过使用多种瑞利波模式来加强对未知参数或每层中的波速的约束。该方法的这些特点允许对高度变化的浅层地下结构进行灵活且稳定的反分析。本研究进行了数值实验，以表明我们的方法允许重现假设的结构奇点。然后，来自三个地点的现场测量数据表明，该方法可以正确识别浅层结构奇点（深度 5-30 m）。
This paper proposes applying Bayesian inference to the problem of estimating shallowSwave velocity structures—in particular, those containing a structural singularity (a low‐velocity layer sandwiched between high‐velocity layers or a high‐velocity layer between low‐velocity layers)—by using Rayleigh‐wave phase velocities obtained in a microtremor survey. The method proposed here uses the empirical Bayesian approach, whereby field measurement data are used to build the prior distribution. An optimal velocity structure model is selected, from among multiple candidate models with different layer thickness parameter values, on the basis of a Bayes factor. The use of the proposed method allows the layer thickness parameter values in a one‐dimensional velocity structure model to be determined objectively for explaining an observed Rayleigh‐wave phase velocity dispersion curve. It also stabilizes the inversion process by the use of the prior distribution and strengthens constraints on the unknown parameter, orSwave velocity in each layer, by using multiple Rayleigh‐wave modes. These characteristics of the proposed method allow flexible and stable inverse analysis of highly variable shallow subsurface structures. The present study conducts numerical experiments to show that our method allows the assumed structural singularities are reproduced. Then field measurement data from three sites are used to show that the method has allowed shallow structural singularities (depths 5–30 m) to be identified appropriately.