Multi-objective joint inversion of Love-wave dispersion curves and SH-wave first-arrival traveltimes

In near-surface seismic characterization, first-arrival traveltime tomography and surface-wave methods are the most commonly used approaches, and their joint inversion can further improve the reliability of the inversion results. In traditional joint inversion methods, assigning weights to surface-wave and first-arrival traveltime misfits introduces subjectivity, as different weightings result in different inversion outcomes. This study proposes a novel joint inversion approach that employs a multi-objective optimization algorithm to invert Love-wave dispersion curves and SH-wave first-arrival traveltimes simultaneously. This method does not require assigning weights to the objective functions, thereby alleviating conflicts between the two wave types. It improves the accuracy and reliability of the reconstructed near-surface model, and additionally, allows for uncertainty estimation of the inversion results. Both synthetic and field tests demonstrate that our proposed method reconstructs more accurate results compared with individual inversions and traditional joint inversion. Furthermore, we found that the uncertainty estimation derived from Pareto solutions in the field example serves as a reliable indicator for the lateral heterogeneity in the near-surface model.