Multi-component Rayleigh wave dispersion analysis for Vs-depth profiling of Glaciers

Seismic ice velocity estimates provide quantitative constraints on glacial systems including ice thickness, englacial structure, and bedrock topography. Detailed velocity modeling using active-source seismic surveys on glaciers, however, is often challenged by sub-optimal survey acquisition design due to complex field logistics. This study explores new potential of such surveys for characterizing potentially heterogeneous seismic ice velocities by leveraging dispersive Rayleigh-wave responses recorded on three-component (3-C) receivers. We use synthetic models to study survey design, data conditioning, and improvements provided by multi-component data for dispersion analysis that inform estimates of vertical velocity profiles. We employ these learnings to optimize the accuracy of dispersion curves derived from a limited aperture, 3-C dataset acquired on the Saskatchewan Glacier in the Canadian Rocky Mountains. Our experiments suggest that when working with a limited number of geophones practitioners should: prioritize array length over finer receiver spacing; use shot points to infill receiver gaps; preprocess shot gather data to emphasize Rayleigh waves; and use supergathers to enhance signal-to-noise ratio and extend effective array aperture prior to building dispersion panels. Finally, we extract novel value from 3-C dispersion analysis by combining vertical- and horizontal-displacement data to reduce uncertainty and improve picked dispersion curve accuracy.