论文标题
从表面波分散数据反转开发不确定性一致性与轮廓的过程
A Procedure for Developing Uncertainty-Consistent Vs Profiles from Inversion of Surface Wave Dispersion Data
论文作者
论文摘要
非侵入性的表面波方法已成为推断位点地下剪切波速度（VS）结构的传统侵入性现场特征化形式的流行替代方法。表面波方法比传统形式的场地表征的优点在于，仅在地面上进行的测量可以定期和经济地使用，以推断位置的地下结构，以在某些特殊情况下，在工程感兴趣的深度（20-50 m）以及更大的深度（> 1 km）。但是，从表面波测量到随后的工程分析中使用的VS轮廓的不确定性的定量和传播仍然具有挑战性。尽管这一直是近年来很多工作的重点，尽管已经取得了很大的进步，但没有被广泛接受的方法，导致分析师以自己的专业方式解决不确定性的传播，或者更糟的是完全忽略这些不确定性。作为回应，本文提出了一种易于实施，有效且可验证的方法，用于从表面波分散数据反转开发不确定性一致性与轮廓。首先，我们研究了文献中提出的四种方法，以开发旨在说明测量分散数据中存在的不确定性的套件。这些方法显示出三种特定方式缺陷。首先，所有方法均显示对其许多用户定义的反转输入参数高度敏感，这使得它们很难/不可能由不同的分析师反复执行。其次，当根据其隐含的理论分散数据来查看倒置与轮廓的套件，显示出显着低估了实验分散数据中存在的不确定性，尽管当纯粹有限地观看时，有些人可能会令人满意...
Non-invasive surface wave methods have become a popular alternative to traditional invasive forms of site-characterization for inferring a site's subsurface shear wave velocity (Vs) structure. The advantage of surface wave methods over traditional forms of site characterization is that measurements made solely at the ground surface can be used routinely and economically to infer the subsurface structure of a site to depths of engineering interest (20-50 m), and much greater depths (>1 km) in some special cases. However, the quantification and propagation of uncertainties from surface wave measurements into the Vs profiles used in subsequent engineering analyses remains challenging. While this has been the focus of much work in recent years, and while considerable progress has been made, no approach for doing so has been widely accepted, leading analysts to either address the propagation of uncertainties in their own specialized manner or, worse, to ignore these uncertainties entirely. In response, this paper presents an easy-to-implement, effective, and verifiable method for developing uncertainty-consistent Vs profiles from inversion of surface wave dispersion data. We begin by examining four approaches presented in the literature for developing suites of Vs profiles meant to account for uncertainty present in the measured dispersion data. These methods are shown to be deficient in three specific ways. First, all approaches are shown to be highly sensitive to their many user-defined inversion input parameters, making it difficult/impossible for them to be performed repeatedly by different analysts. Second, the suites of inverted Vs profiles, when viewed in terms of their implied theoretical dispersion data, are shown to significantly underestimate the uncertainty present in the experimental dispersion data, though some may appear satisfactory when viewed purely qualitatively...
