Near-surface imaging of urban environments using distributed acoustic sensing (DAS) and finite element method (FEM) modelling

SUMMARY Shear-wave velocity imaging is key for near-surface geotechnical characterization of foundation soils, for subsurface anomaly detection, and for process monitoring in urban environments. In this study, we propose a workflow for characterizing metropolitan areas using ambient and anthropogenic noise records from distributed acoustic sensing (DAS) data collected on telecommunications fibre. We developed a finite-element model that computes shear-wave dispersion curves for fundamental and higher-order surface-wave modes from a layered velocity profile. The model parameters allow intralayer linear and power-law variations of velocity with depth to provide realistic near-surface soil behaviour. The forward model is coupled with an inversion algorithm that minimizes the model’s misfit to dispersion curves derived from the DAS data. We demonstrate the workflow using DAS data collected on the University of Wisconsin–Madison’s campus network. The results are compared with the multichannel analysis of surface waves method using a line of geophones colocated with one of the DAS sites and a nearby borehole log. Both solutions indicated a sharp change in shear-wave velocity at approximately 20 m, corresponding to the depth of a sandstone formation at the site, and that a physically based, power-law function better fits the velocity profiles of unconsolidated sediments. These results demonstrate that our method provides reliable near-surface imaging while suggesting likely soil types. The proposed measurements and modelling techniques can be extended to image the near surface wherever telecommunications fibre is available.