Project description
Research obective
This project will leverage newly acquired onshore and offshore passive seismic data to image the crustal and upper mantle structure across much of Svalbard. This will help determine how the crust-mantle architecture (layering, Moho depth, etc.) varies according to terrane age and degree of deformation across Svalbard, and investigate whether there are relationships between lateral changes in crust-mantle architecture and earthquake distribution.
Data and methods
Data to be analyzed in this project are passive seismic recordings from both onshore and offshore broadband seismometers. These data are publicly available and archived at the UiB-NORSAR EIDA node, from which they can be downloaded via standard web services requests. These data will be used to compute Ps and Sp teleseismic receiver functions (RFs), which provide an estimate of the ground’s impulse response to sharp boundaries in elastic properties (e.g., the Moho and lithosphere-asthenosphere boundary). RFs will then be used to construct images and obtain models of crust and upper-mantle structures beneath the stations. Lastly, the images and models thus obtained will be interpreted in conjunction with local seismicity, obtained from the NNSN earthquake catalogue.
Work tasks
The work will comprise the following tasks:
- Background research on the geology, tectonics, and seismicity of Svalbard, as well as on RF methods.
- Familiarization with the Linux operating system.D
- ownload and quality control of seismic data from onshore and offshore (OBS) broadband data from Svalbard.
- Generation of Ps and Sp RFs using a modified version of the PyGLImER software to allow for the processing of OBS data.
- Imaging and modelling/inversion of RFs using the PyGLImER and community packages distributed through GitHub (e.g., RF_INV, PyRaysum)
- Joint interpretation of RF images/models and seismicity catalogue data through bespoke visualization tools.
These work tasks involve extensive writing, modification and application of computer programs mainly in MATLAB and Python, and possibly in Fortran 90. Candidates with a strong interest in computer programming and in developing their analytical skills are thus encouraged to apply.
The student starting this project should have a bachelor degree in geophysics or equivalent.