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

Samara Garvey, Matthew Siegfried, Jeffrey Shragge, Lucas Zoet, Dougal Hansen, Nathan Stevens

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.