Groundwater mapping in Denmark is internationally acknowledged and regarded as a benchmark approach. Huge amounts of data (well logs, geophysical, geo- and hydro-logical data) have been collected. Today these data are combined in a deterministic sequential workflow, where, typically, a single final model represents all available information. While successful, this workflow has some limitations: There is no way to ensure the final model consistency with all information at hand, and there is no way to ensure correct uncertainty quantification. To remedy this, we propose to develop a probabilistic data integration workflow that allows consistent integration of well-log, geophysical and geological data. The results will be a probabilistic geological model that: a) will be consistent with all data, and b) allow detailed uncertainty analysis. The resulting probabilistic geo-model can be efficiently used by the end-users for informed, data-driven, decision- making and for risk assessment.
The Project is partly financed by The Independent Research Fund Denmark and is a 3 year project running from May 2018 including University of Copenhagen, Aarhus University, United States Geological Survey (USGS), University of Cagliari, and I•GIS
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