Your mission:

Seismic exploration is of great importance for future planetary missions: the planet’s subsurface structure can reveal a great deal of information about the planet’s past and present. We envision the use of a network of multiple agents – of a swarm – to autonomously and cooperatively reconstruct the subsurface structure. To compute an image of the subsurface typically several processing steps of seismic measurements are required. One of those steps is a so called normal moveout strategy that can be used to obtain velocity estimates of the subsurface. At present seismic exploration surveys such data processing is conducted in a centralized manner, where all seismic measurements are available at a single computing entity. However, for application in a network of multiple agents these computations need to be conducted in a distributed fashion.

In this thesis, the task of the potential candidate is to implement the normal moveout strategy in a distributed fashion for an estimation of the subsurface velocities and layer depths within a network of geophones. To this end, layered Earth models shall be simulated by solving a wave equation that generates synthetic measurements at the geophone locations. Based on the seismic measurements the objective is to reconstruct the velocities and depths of the layered Earth model in a distributed fashion. The developed scheme shall be tested via simulations with both synthetic and real measurements. If time allows, experiments in a real environment shall be conducted to validate the simulation results.

Your qualifications:

- Solid background in signal processing

- Good programming skills in Python or Matlab

- Independent and self-motivated working style

- Motivativation to solve complex tasks