Inversion Method for Spectral Analysis of Surface Waves (SASW)
Orozco, M. Catalina (Maria Catalina)
MetadataShow full item record
This research focuses on estimating the shear wave velocity (Vs) profile based on the dispersion curve obtained from SASW field test data (i.e., inversion of SASW data). It is common for the person performing the inversion to assume the prior information required to constrain the problem based on his/her own judgment. Additionally, the Vs profile is usually shown as unique without giving a range of possible solutions. For these reasons, this work focuses on: (i) studying the non-uniqueness of the solution to the inverse problem; (ii) implementing an inversion procedure that presents the estimated model parameters in a way that reflects their uncertainties; and (iii) evaluating tools that help choose the appropriate prior information. One global and one local search procedures were chosen to accomplish these purposes: a pure Monte Carlo method and the maximum likelihood method, respectively. The pure Monte Carlo method was chosen to study the non-uniqueness by looking at the range of acceptable solutions (i.e., Vs profiles) obtained with as few constraints as possible. The maximum likelihood method was chosen because it is a statistical approach, which enables us to estimate the uncertainties of the resulting model parameters and to apply tools such as the Bayesian criterion to help select the prior information objectively. The above inversion methods were implemented for synthetic data, which was produced with the same forward algorithm used during inversion. This implies that all uncertainties were caused by the nature of the SASW inversion problem (i.e., there were no uncertainties added by experimental errors in data collection, analysis of the data to create the dispersion curve, layered model to represent a real 3-D soil stratification, or wave propagation theory). At the end of the research, the maximum likelihood method of inversion and the tools for the selection of prior information were successfully used with real experimental data obtained in Memphis, Tennessee.