On the development of uncertainty-consistent one-dimensional shear wave velocity profiles from inversion of surface wave dispersion data
Creators: name: Vantassel, Joseph Philip
name: 0000-0002-1601-3354
Publisher: name: The University of Texas at Austin
Year: 2021
Subjects: Uncertainty
Surface waves
Shear wave velocity
Inversion
Site characterization

description: Characterization of a site’s subsurface shear stiffness is of critical importance to many areas of geotechnical engineering, such as site characterization and seismic hazard analysis. The site’s subsurface shear stiffness, more specifically referred to as the site’s small-strain shear modulus (G₀), is most commonly determined through measurements of the site’s shear wave velocity (Vs), as G₀ and the square of Vs are linearly related through mass density (ρ) (i.e., G₀=ρ Vs²). Due to their advantages in terms of speed of acquisition and versatility in challenging geologic environments, non-invasive characterization methods are increasingly being preferred over invasive methods for assessing a site’s Vs. Of the non-invasive techniques, surface wave methods are becoming the technique of choice for near-surface characterization due to their ability to be used to characterize arbitrary subsurface conditions, even those which are challenging to other non-invasive techniques (e.g., soft layers beneath stiff layers), and their ability to accurately infer Vs at both the near-surface as well as at depth through the combined use of active-source and passive-wavefield approaches to measuring surface wave propagation. However, surface wave methods, as with all site characterization techniques (invasive and non-invasive), contain uncertainties that need to be quantified and propagated through the data acquisition and processing into the resulting Vs measurements. Non-invasive techniques, such as surface wave methods, are particularly challenging due to the ill-posedness of the inverse problem and the non-uniqueness that it implies. The presence of non-uniqueness in the solution of the inverse problem results in a compounding of the apparent uncertainties. As a result, it is imperative that uncertainties in surface wave testing be quantified not only in regard to the acquisition and processing of the data but in the inversion process itself. This dissertation presents a comprehensive approach that documents the process of quantifying experimental dispersion data uncertainty, stemming from aleatory and epistemic sources, and the rigorous propagation of that uncertainty through the inversion process and into suites of Vs profiles that more realistically quantify the expected distribution of Vs. Because the resulting suites of Vs profiles propagate both epistemic and aleatory uncertainty, as well as the uncertainty associated with the inverse problem’s ill-posedness, the profiles are referred to as uncertainty-consistent. The development of uncertainty-consistent Vs profiles has been the interest of much research over the past two decades, however, the approach detailed in this dissertation is the first to quantitatively show that such profiles could be obtained from experimental surface wave dispersion data.