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.