Open-source and open data: combining both worlds for optimised decision making in geological subsurface modelsFlorian Wellmann , Miguel de la Varga & Alexander Jüstel
Computational Geoscience and Reservoir Engineering (CGRE), RWTH Aachen University, Aachen, Germany(1);Terranigma Solutions GmbH, Aachen, Germany(2);Fraunhofer IEG, Fraunhofer Research Institution for Energy Infrastructures and Geothermal Systems, Am Hochschulcampus 1, 44801 Bochum, Germany(3);
A Heat Demand Map of North-West Europe - its impact on supply areas and identification of potential production areas for deep geothermal energyEileen Herbst , Elias Khashfe , Alexander Jüstel , Frank Strozyk & Peter Kukla
To achieve the Paris Agreement's goal of maximum global warming by 2 degrees, CO2 reduction is indispensable. Space heating for residential, service and industrial buildings amounts to 26% of EU's final energy consumption with about 3347 TWh/a. Approximately 75% of the heat produced is generated by fossil fuels with high CO2 emissions. Those Emissions can be reduced by implementation of renewable energy sources, such as deep geothermal energy. As Part of the Interreg NWE project...
Bias evaluated structural and probabilistic subsurface modelling: a case study of the Münsterland Basin, NW GermanyMarius Pischke , Alexander Magnus Jüstel , Frank Strozyk, Peter Kukla & Florian Wellmann
The analysis of uncertainties in the description of the subsurface is an important aspect for resource exploration and material storage. Because of the complexity of the subsurface and an often inhomogeneous data situation, models exhibit several aspects of uncertainties. These may be caused by the interpolation of locally sparse data and must be considered when constraining a structural geological model. Further, these interpolations may be subject to errors caused by psychological biases, which need to...