The assessment of a geographic region for its geothermal energy potential typically comes with high upfront costs for exploratory drilling projects and financial as well as environmental risks. In the DEGREE project we are developing a virtual laboratory with the goal to provide visualization, analysis and decision making tools that can be used to plan exploration projects and increase their probability for success. The laboratory is developed with data from the East Eifel region in Germany and consists of three main parts: (a) a repository to collect data and models along with their associated metadata, (b) workflows and infrastructure for automatic processing and numerical modeling steps, and (c) an interface for visualization of and interaction with the results. As a final product we obtain two-dimensional maps derived from three-dimensional process simulations of physical quantities by fixing some of the parameters (e.g. temperature at a given depth), slicing and thresholding. The modeling steps often require user input by an expert, e.g. in order to assign thresholds or weights. This is typically an iterative process in which a fast user feedback is crucial, therefore workflows are required to execute quickly, if necessary even on remote infrastructure. Fast coupling of the entire modeling chain also helps to address the often large and unknown uncertainties in subsurface data as it enables us to automatically produce ensembles of models with different parameter values that can be analyzed statistically. The project is currently in the design and prototyping phase. We are developing the first prototype in JupyterLab using ParaView/trame and anywidget for visualization and interaction tools that can later be extracted into a standalone application. In addition to the prototype, we present a plan for the overall architecture of the laboratory, the requirements that shape it and point out some of the many challenges that we are facing.
Volk et al. (Thu,) studied this question.