Validation of thermodynamic databases for hydro- geochemical modeling in geothermal environments
Creators: name: Trumpp, Michael
name: Yström, Lars
name: Kohl, Thomas
name: Nitschke, Fabian
Publisher: name: Karlsruher Institut für Technologie (KIT)
Year: 2023
Subjects: Geochemical Modeling
Scaling
Database
PHREEQC
Bubble Point

description: Advances in geochemistry in recent decades have been supported by an increasing number of geochemical models to help understanding brine behavior and scaling occurrence. Geochemical modeling is based on thermodynamic databases that are compiled from experimental and calculated thermodynamic data. The data gathered in these databases is subject to limitations that are subject to the experimental thermodynamic conditions present during the experiments. The key parameters for solubility problems are temperature and pressure, as well as pH and salinity. Therefore, the same model results can diverge when using different thermodynamic data or by applying data that is not valid for the chemical conditions and/or rely on interpolation from existing data. PHREEQC is one of the state-of-the-art modeling programs which is used in this work. Several new PHREEQC databases have recently become available for geochemical modeling, such as geothermal.dat by Zhang et al. (2020), carbfix.dat by Voigt et al. (2018), or the imported YMP and soltherm databases from TOUGHREACT by Alsemgeest et al. (2021), which are compiled specifically for geothermal modeling. In addition to the previously mentioned problems with inconsistent modeling results, there are two cases involving pressure in PHREEQC. The first one is a pressure correction for the solubility product based on the addition of the molar volume and the usage of the Redlich-type equation, however this is not integrated in every database. The second one is about the equation to calculate the gas pressure. Either the ideal gas law or the Peng-Robinson equation of state is used. The recently developed geothermal databases were compared with existing ones to evaluate the best suited thermodynamic data for degassing pressure and geothermal power plant modeling. The evaluated data will be compiled in a new PHREEQC thermodynamic database. In order to compare the databases, a set of scaling minerals was defined. This set includes the most abundant sulfides, sulfates, oxides, and carbonates regarding scalings in geothermal power plants. The molal concentrations of these minerals were modeled at solubility equilibrium over a temperature range from 0.1 to 300 °C, a pressure of 1 bar or less and in low salinity (&lt;0.1 MNaCl) solutions. The results were comparable to experimental data to determine the best-fitting database for each specific mineral. Additionally, the degassing pressure of brines with known chemical composition was evaluated for the different databases. The modeled gas phase consisted of CO2, CH4, N2 and H2S which were completely dissolved in solution at elevated temperature and pressure. The time at which a free gas phase began to form was determined by a controlled decrease in pressure. Furthermore, experiments are planned to compare the modeled results for the degassing pressure and the newly developed database at different geothermal power plants with the help of special power-plant-demonstrator facility. References Alsemgeest, J.; Auqué, L. F.; Gimeno, M. J. (2021): Verification and comparison of two thermodynamic databases through conversion to PHREEQC and multicomponent geothermometrical calculations. In: Geothermics 91, S. 102036. DOI: 10.1016/j.geothermics.2020.102036. Voigt, Martin; Marieni, Chiara; Clark, Deirdre E.; Gíslason, Sigurður R.; Oelkers, Eric H. (2018): Evaluation and refinement of thermodynamic databases for mineral carbonation. In: Energy Procedia 146, S. 81–91. DOI: 10.1016/j.egypro.2018.07.012. Zhang, Guanru; Lu, Peng; Zhang, Yilun; Tu, Kevin; Zhu, Chen (2020): SupPhreeqc: A program for generating customized Phreeqc thermodynamic datasets from Supcrtbl and extending calculations to elevated pressures and temperatures. In: Computers &amp; Geosciences 143, S. 104560. DOI: 10.1016/j.cageo.2020.104560.