Predictive Modeling of subsurface CO2 Storage in Volpriehausen Sandstone beneath the German North Sea

Our study investigates the subsurface storage of CO₂ in saline aquifers, specifically in the Volpriehausen Sandstone beneath the German North Sea. We conduct numerical simulations using the TOUGH3 simulator with the ECO2N module. The reliable estimation of dynamic storage capacity for CO₂ storage is a challenge due to the lack of measurements for process parameters in the model area.

Therefore, we estimate some parameter ranges from literature and OpenData for Volpriehausen Sandstone from Denmark and the Netherlands. Based on these parameter ranges, sensitivity analyses are conducted to identify important rock parameters. A comprehensive dataset of parameters and corresponding simulation results is generated using Latin Hypercube Sampling.

This sample is used to perform sensitivity analyses and to train surrogate models using machine learning approaches. This allows us to identify relevant process parameters. At a constant injection rate, the injection pressure is affected by the permeability and pore compressibility of the reservoir rock, as well as the reservoir and injection temperature. The storage efficiency is affected by the relative permeability of the reservoir rock. The predictions of the surrogate models are illustrated with 3D simulations.

This research has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement “LEILAC2 - Low Emission Intensity Lime and Cement” GA 884170.