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Abstract

Mineralogical and geochemical observations from laboratory CO2-exposure experiments on reservoir rocks are compared with predictions from geochemical modeling that was performed using PHREEQC software. The Pitzer-based Eq 3/6 thermodynamic database, provided by Quintessa Ltd., was applied. For kinetic modeling, a Lasaga-type rate equation was implemented and different models were parameterized taking kinetic rate law parameters from literature. Based on previous modeling studies a modified inverse modeling approach is presented here. This comprises several different Fe-proxies and improved statistical ranking preferences that were implemented in particular to better match modeled and measured concentrations of dissolved K+, Fe2+ and Al3+. Compared to the previous approach, the presented modeling results are in good (better) agreement with experimental data. Systematic discrepancies between modeling and observation still occur regarding K-bearing mineral phases and corresponding K+ brine concentrations. Despite missing correlation between K+ and Cl− concentrations, potential reasons for these discrepancies may be increased K+ brine concentrations during the experiments due to dissolution of K-rich salt(s), such as sylvite. Much better matches were generated for dissolved Fe2+ concentrations. Goethite mainly controls the chemical behavior of dissolved Fe2+ in kinetic simulations. Based on both the available equilibrium and kinetic modeling results, the ultimate fate of dissolved Al3+ and the analysis of Al-bearing mineral phases potentially controlling dissolved Al3+ brine concentrations cannot be conclusively determined. The overall best ranked kinetic model comprises anhydrite, dolomite, goethite, K-feldspar and kaolinite. Despite minor inconsistencies dissolved Fe2+, Al3+ and Si4+ were in particular much better reproduced by the best ranked kinetic models.