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About Topic 8


The mission of Topic 8 is to provide a scientific basis for accessing safe, clean energy and the raw materials needed for our 21st-century infrastructure, enabling the energy transition and supporting a growing circular economy. To this end, Topic 8 will address two key challenges related to georesources for the energy transition and a high-tech society: where to find the resources that we need today and in the future, and how to access those resources in the most sustainable way.

Our focus:

More people than ever live in urban centres and use sophisticated technologies. Topic 8 will address one of the most fundamental challenges facing society: securing the future supply of energy and raw materials needed to sustain our 21st century infrastructure, to enable the transition from fossil and nuclear energy to renewables. In doing so, we want to achieve the targeted reduction of CO2 emissions and also to support a growing circular economy. During this transition, geoscience solutions to sustainable energy, raw materials supply, and subsurface storage of waste will be required, with a growing emphasis on the deep subsurface.

Our research foci include:

  • development and application of new technologies for georesources
  • accessing clean geothermal energy as an integral part of the energy supply
  • constraining the key processes that form high value ore deposits
  • developing knowledge-based approaches for the safe disposal of waste from energy production
  • designing new observational, experimental and simulation platforms to assess the coupled thermal, hydraulic, mechanical, chemical, and biological controls on resources
  • integrating geodynamics as a fundamental control on the occurrence of resources and a defining boundary condition for safe subsurface utilization
  • the role of biological-solid-fluid interactions and the deep biosphere in georesource systems

Recent Highlights

Machine Learning in Georesources

3D seismic interpretation with deep learning

Topic 8 Researchers demonstrate how to automate and accelerate the analysis of large seismic data sets with machine learning. Using deep convolutional neural networks, the researchers were able to perform typical seismic interpretation tasks such as mapping tectonic faults, salt bodies, and sedimentary horizons at high accuracy. Once trained, the models can analyze large volumes of data within seconds, opening a new pathway to study the processes shaping the internal structure of our planet.


Graphic Representation of Subtopics

Subtopics in detail

Cross-Cutting Activities (distinguished as CARFs and CTAs*) serve the overall objectives of the Helmholtz Association to bridge Research Fields, to promote thematic profiling and networking in the Research Fields and to strengthen and organize links with the German scientific community.

*CARFs = Cooperations across Research Fields, CTAs = Cross-Topic Activities

Links to CARFS/CCA

CARF Nuclear Repository Research (with RF Energy)

CARF Geoenergy (with RF Energy)

Participating Centers