Full Waveform Inversion to Determine the Seismic Structure of Firn

The compaction of firn (the transition of snow to ice) is a process in glaciology that is difficult to constrain without the use of intrusive geophysical techniques. Full Waveform Inversion (FWI) is a seismic imaging technique used to obtain high-resolution images of the subsurface. This research introduces FWI to glaciological modelling and shows that FWI can improve upon the Herglotz-Wiechert travel time tomography method that’s use is currently widespread. Using synthetic firn velocity models, acoustic FWI was shown to recover the compressional (P) wave velocity gradient of the firn column and could correct a velocity model that was a poor representation of the subsurface structure (up to a 5% velocity error). Additionally, FWI was able to detect ice layers of a minimum thickness of 10 m (half the minimum wavelength) within the firn column and provide constraints on their depth providing the ice slab did not occur in the shallow surface (20 m or less), where the steepest velocity gradient occurs.

FWI is applied to two datasets. Firstly, legacy data acquired by the British Antarctic Survey on Pine Island Glacier were problematic, owing to an inconsistent, high-frequency source waveform that made FWI vulnerable to cycle skipping. Consequently, no improvement was observed to the seismic structure. Secondly, a dataset acquired specifically for this research was collected on Norway’s Hardangerjøkulen Ice Cap. With this dataset a combination of Travel Time and Least-Squares FWI can be successful due to the use of a repeatable seismic source with lower frequency content (10 Hz), A VSP survey used to provide near-surface velocity constraints and near offset small receiver spacing (1 m). FWI provided a 6% change to the starting velocity model and improved the data match by 47%. The results showed that acoustic FWI must be considered from the seismic acquisition stage for the technique to be successful in characterising firn velocity structure. In this case, FWI can improve the model of the subsurface velocity structure from the HW technique and increase the match of the modelled seismic data.