The research is planed as part of  the RUBADO project (BMWE, FKZ 03EE4076A), which is led by KIT, and will focus on developments within the DeepStor research infrastructure. DeepStor investigates the implementation of an HT-ATES (High Temperature Aquifer Thermal Energy Storage) system at the KIT Campus North, using former hydrocarbon reservoirs in deep sedimentary rocks. The exploration phase includes the drilling of a well to ~1.5 km. During this phase, a dense seismic network of more than 90 3C-seismic nodes will be installed in a radius of 2 km around DeepStor. In addition to the nodes, Distributed Acoustic Sensing (DAS) will also be applied along the telecommunication fiber-optic infrastructure of KIT. The objective of these networks is to record and process the noise generated by the drill-bit during drilling of the exploration well, which will be also recorded by a 3C-accelerometer from the bottom-hole-assembly, in order to obtain an image of the elastic properties of the underground around the well trajectory. This survey can be compared to a passive reverse 3D Vertical Seismic Profile (VSP), the source (the drill-bit) moving in depth and the receivers being fixed at surface. The goal of the research work is to develop and to apply a signal processing methodology of the drill-bit induced noise recorded by the surface networks to derive a reliable velocity model for P- and S-waves and, potentially, to obtain a seismic image of the geological structures. Independent data acquired at DeepStor will enable to assess the quality of the results. Particular attention is also given to the comparative assessment of DAS and geophone data in the workflow. If the approach is validated, this would show that an alternative to post-drilling active well surveys may exist.

In this framework, the following tasks are expected:

• Data acquisition and pre-processing
  • Preparation, installation and maintenance of the acquisition campaign in the field.
  • Forward synthetic model of the 3C-seismic nodes and DAS geometry responses to the drill-bit sources to better understand acquisition biases and limitations.
  • Collect and organize datasets.
  • Quality control and pre-processing of downhole accelerometer, geophone and DAS data.
• Signal analysis of drill-bit noise
  • Characterize the spectral and temporal properties of drilling-induced signals.
  • Apply cross-correlation and well-seismic processing techniques between the source(s) and the receivers.
• Velocity model inversion and seismic imaging
  • Travel-time tomography to derive initial P- and S-wave velocity models.
  • Full-waveform inversion (FWI) to refine velocity models and enhance structural resolution.
• Comparative assessment of DAS and Geophones
  • Quantify differences in sensitivity, frequency content, and noise levels.
  • Evaluate spatial coverage, resolution and inversion quality for each technology.
  • Explore hybrid approaches that combine DAS and geophone datasets forimproved imaging.

• Master’s degree in Geophysics, Physics, Computational Earth Sciences, or related field.
• Strong background in seismology, seismics, numerical modelling.
• Experience with programming (e.g. Matlab, C/C++).
• Interest in geothermal applications.
• Enthusiasm for fieldwork in addition to office work, and for interdisciplinary collaboration.