@article{HennigStockmannKuehn2020,
  author    = {Hennig, Theresa and Stockmann, Madlen and K{\"u}hn, Michael},
  title     = {Simulation of diffusive uranium transport and sorption processes in the Opalinus Clay},
  series = {Applied geochemistry : journal of the International Association of Geochemistry and Cosmochemistry},
  volume    = {123},
  journal   = {Applied geochemistry : journal of the International Association of Geochemistry and Cosmochemistry},
  publisher = {Elsevier},
  address   = {Oxford},
  issn      = {0883-2927},
  doi       = {10.1016/j.apgeochem.2020.104777},
  pages     = {9},
  year      = {2020},
  abstract  = {Diffusive transport and sorption processes of uranium in the Swiss Opalinus Clay were investigated as a function of partial pressure of carbon dioxide pCO(2), varying mineralogy in the facies and associated changes in porewater composition. Simulations were conducted in one-dimensional diffusion models on the 100 m-scale for a time of one million years using a bottom-up approach based on mechanistic surface complexation models as well as cation exchange to quantify sorption. Speciation calculations have shown, uranium is mainly present as U(VI) and must therefore be considered as mobile for in-situ conditions. Uranium migrated up to 26 m in both, the sandy and the carbonate-rich facies, whereas in the shaly facies 16 m was the maximum. The main species was the anionic complex CaUO2(CO3)(3)(2-) . Hence, anion exclusion was taken into account and further reduced the migration distances by 30 \%. The concentrations of calcium and carbonates reflected by the set pCO(2) determine speciation and activity of uranium and consequently the sorption behaviour. Our simulation results allow for the first time to prioritize on the far-field scale the governing parameters for diffusion and sorption of uranium and hence outline the sensitivity of the system. Sorption processes are controlled in descending priority by the carbonate and calcium concentrations, pH, pe and the clay mineral content. Therefore, the variation in porewater composition resulting from the heterogeneity of the facies in the Opalinus Clay formation needs to be considered in the assessment of uranium migration in the far field of a potential repository.},
  language  = {en}
}
@article{TranterDeLuciaWolfgrammetal.2020,
  author    = {Tranter, Morgan Alan and De Lucia, Marco and Wolfgramm, Markus and K{\"u}hn, Michael},
  title     = {Barite scale formation and injectivity loss models for geothermal systems},
  series = {Water},
  volume    = {12},
  journal   = {Water},
  number    = {11},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2073-4441},
  doi       = {10.3390/w12113078},
  pages     = {24},
  year      = {2020},
  abstract  = {Barite scales in geothermal installations are a highly unwanted effect of circulating deep saline fluids. They build up in the reservoir if supersaturated fluids are re-injected, leading to irreversible loss of injectivity. A model is presented for calculating the total expected barite precipitation. To determine the related injectivity decline over time, the spatial precipitation distribution in the subsurface near the injection well is assessed by modelling barite growth kinetics in a radially diverging Darcy flow domain. Flow and reservoir properties as well as fluid chemistry are chosen to represent reservoirs subject to geothermal exploration located in the North German Basin (NGB) and the Upper Rhine Graben (URG) in Germany. Fluids encountered at similar depths are hotter in the URG, while they are more saline in the NGB. The associated scaling amount normalised to flow rate is similar for both regions. The predicted injectivity decline after 10 years, on the other hand, is far greater for the NGB (64\%) compared to the URG (24\%), due to the temperature- and salinity-dependent precipitation rate. The systems in the NGB are at higher risk. Finally, a lightweight score is developed for approximating the injectivity loss using the Damkohler number, flow rate and total barite scaling potential. This formula can be easily applied to geothermal installations without running complex reactive transport simulations.},
  language  = {en}
}