Near-Surface Site Characterization Using Surface Waves
Modern surface wave testing methods rely on advanced signal processing and inversion algorithms to extract information about the shear wave velocity profile from observations of Rayleigh wave propagation at the free surface. Extensive use is made of temporal and spatial Fourier transforms to measure Rayleigh wave dispersion. In this context, it is important to understand the influence of finite temporal and spatial sampling on frequency and wavenumber resolution and aliasing. The aperture smoothing function is shown to be a valuable tool to understand these characteristics for a particular receiver array. Four commonly used methods for calculating dispersion curves — Spectral Analysis of Surface Waves (SASW), Multi-Offset Phase Analysis (MOPA), Spatial Autocorrelation (SPAC), and conventional frequency-domain beamforming — are presented and discussed for both active and passive tests.
Surface wave inversion, like most geophysical inverse problems, is ill posed due to finite, uncertain data and modelling errors. To overcome these difficulties, it is possible employ one or more of several strategies that conceptually involve introducing additional information about the inverse problem. Candidates include introducing information about uncertainty in the experimental dispersion data, a priori values of shear wave velocity, and/or desired characteristics of the shear wave velocity profile such as smoothness. Several least squares inversion algorithms are presented that allow the user to incorporate this type of information.
KeywordsSurface Wave Dispersion Curve Shear Wave Velocity Wavenumber Spectrum Shear Wave Velocity Profile
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