Repeatability of Surface Wave Velocity Estimates from Distributed Acoustic Sensing (DAS) Data

Abstract:

The repeatability of surface wave velocity estimates from local ambient noise hinges on the stability of the crosscorrelation function for the receiver pair in the presence of a variable noise field, assuming near-surface soil properties are invariant over the duration of the surveys. Distributed acoustic sensing (DAS) data recorded on a linear trenched fiber optic cable sensor can accurately sample surface waves in a near continuous fashion (>1 kHz) with high spatial resolution (>1 receiver/m) and long range (10’s of km). DAS recordings of ambient noise represent a unique means to explore the practical reliability of field-scale seismic property estimation from seismic interferometry. We test this hypothesis using continuous DAS field recordings from a shallow trench experiment near a busy road with diurnally-variable traffic patterns. Continuous records are processed using a modified ambient noise workflow consisting of receiver pair crosscorrelation, signal stacking, dispersion analysis, and a Monte Carlo search procedure to determine a best-fitting Vs model. The same processing flow is also applied to campaign data acquired with geophones to determine the repeatability benefit of trenched DAS deployment.