Research at CGRE

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Computational Geoscience and Reservoir Engineering addresses scientific and engineering questions related to
subsurface flow and transport problems with numerical methods. While classical applications in this field are often related to hydrocarbon and groundwater extraction and contamination problems, more recent questions include, for example, carbon sequestration and geothermal systems as a sustainable energy source.

By extension, many of the methods that were originally developed in the preceding context are now also applied to investigate dynamic interactions between the geological system and the climate system, with important applications in large-scale climate simulations.

Numerical Reservoir Engineering is a profoundly interdisciplinary topic: solving problems in this context requires an understanding of multiple scientific disciplines, from geology (e.g. to determine likely property distributions due to the sedimentological history, or the position of main structures and faults), over geophysics (e.g. to constrain the position of main structures or to monitor fluid movement and fracture behaviour), to fundamental fluid and solid mechanics and chemistry (e.g. to understand and model the relevant physical processes and fluid behaviour).

Further, a robust comprehension of the mathematical and numerical methods to solve these problems is required—and finally, as all of these aspects contain elements of uncertainty, we need to understand how robust the numerical predictions are, and how we can integrate all information in the best possible way to understand and reduce uncertainties in the entire process.

The field of Numerical Reservoir Engineering therefore provides a wide range of opportunities for scientific investigations with a high relevance to society and industry. In my research group, we have been focussing on methods to characterise the spatial distribution of rock properties and relevant geological features, as well as the link to subsequent process simulations. Of specific interest to me is the investigation of uncertainties in the diverse aspects of this link between geological models and process simulations, as our knowledge about the
subsurface is incomplete and often limited to sparse observations and inference on the basis of geophysical measurements. On a high level, my scientific interests can be described in the following fields:

  • Data and knowledge: what do we actually know about geological structures, rock properties and physical processes in the subsurface, and which data and information can help to improve this knowledge?
  • Methods: what are suitable theoretical and computational methods to analyse and quantify uncertainties, and finally to reduce uncertainties with additional observations and information?
  • Processes: how do uncertainties in geological models influence the subsequent process simulations and how sensitive are the simulated systems to these uncertainties?


Applications of the work in my group have mainly been in the field of geothermal systems, but also in groundwater hydrogeology and mineral exploration. However, the investigation of uncertainties in geological models has, in itself, shown to be a highly diverse and interesting topic, arguably with profound applications beyond the field of Numerical Reservoir Engineering itself: apart from their use in many other parts of industry, 3-D geological models are becoming increasingly relevant in various scientific investigations and in the work of geological surveys.