Synthetic seismic surveys on glaciers

Simulating a glacier seismic survey to analyse the influence of crystal anisotropy on seismic data

Thesis details
Synthetic seismic surveys on glaciers
  • 6 months
  • M.Sc.
  • 90% Programming
  • 80% Field work
  • 10% Lab work
  • 60% Theory
  • 70% Processing
  • 60% Interpretation
  • 50% Geology
Contact person
Marc S. Boxberg's profile picture's profile picture
Dr. rer. nat.
Marc S. Boxberg
Postdoctoral researcher and deputy director
+49 241 / 80 99755

The study of ice-sheet dynamics is a crucial part of glaciological research and of utmost importance for contributing to reliable predictions of the global climate and sea level rise. The deformation of glacial ice is governed by friction at the base and shear margins, and by internal deformation which can be broken down to principal physical processes on the scale of crystals. The deformation is mainly controlled by how stress is accommodated by the polycrystal. As natural ice has a high mechanical anisotropy, the strain response is very heterogeneous on different length scales and the cause for many observable structures in ice bodies (e.g., Bons et al., 2016). In turn, crystal-preferred orientation (CPO), which is observed in ice core samples, can provide evidence of small- to large-scale structures in a glacier that have developed as a result of the deformation.

Information on the CPO is largely and in high resolution obtained from ice cores, that is, the information is restricted to a 1D profile in a 3D glacier. Recently, new efforts are concentrated on developing novel techniques (e.g., Booth et al., 2020) which employ geophysical methods to reconstruct 2D or even 3D structures in the ice by making use of the crystal anisotropy, as ice is also optically anisotropic, that is, a seismic wave front will be slower or faster depending on the CPO of the polycrystal (maximum difference of about 280m/s). Ideally, the collected data with seismics is anchored with the laboratory-measured CPO from an ice core. The connection between the techniques can be made via seismic velocities, but it is to date not understood exactly how a “seismic signature” due to a specific CPO can be expected to look like.

Your tasks:

In this project, synthetic seismic data will be computed using the numerical wave propagation solver SPECFEM and afterwards be processed (e.g., using Seismic Unix or Reflexw). The model will be based on CPO data measured on an ice core from Colle Gnifetti and the corresponding theoretic seismic velocities that were computed for the polycrystal material (Kerch et al., 2018). Central questions of this study are: (1) How is the observed small-scale variability in CPO affecting seismic measurements with different wave lengths and (2) how do these synthetic seismic data relate to internal reflections observed in previous seismic surveys on this glacier (Diez et al., 2013, 2014, data available).

Supplementary Documents

Bons, P.D., Jansen, D., Mundel, F., Bauer, C.C., Binder, T., Eisen, O., Jessell, M.W., Llorens, M.-G., Steinbach, F., Steinhage, D., and Weikusat, I. (2016). Converging flow and anisotropy cause large-scale folding in Greenland’s ice sheet. Nat. Commun., 7:11427.

Booth, A., Christoffersen, P., Schoonman, C., Clarke, A., Hubbard, B., Law, R., Doyle, S., Chudley, T., and Chalari, A. (2020). Detecting anisotropy using Distributed Acoustic Sensing and fibre-optic seismology in a fast-flowing glacier in Greenland.

Diez, A., Eisen, O., Hofstede, C., Bohleber, P., and Polom, U. (2013). Joint interpretation of explosive- and vibro-seismic surveys on cold firn for the investigation of ice properties. Ann. Glaciol., 54(64):201–210.

Diez, A., Eisen, O., Weikusat, I., Eichler, J., Hofstede, C., Bohleber, P., Bohlen, T., and Polom, U. (2014). In uence of ice crystal anisotropy on seismic velocity analysis. Ann. Glaciol., 55(67):97–106.

Kerch, J., Diez, A., Weikusat, I., and Eisen, O. (2018). Deriving micro- to macro-scale seismic velocities from ice-core c axis orientations. The Cryosphere, 12(5):1715–1734.

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