Disposal of nuclear waste in host rock formations featuring high-saline solutions – Implementation of a thermodynamic reference database (THEREDA)

Moog, Helge C.; Bok, Frank; Marquardt, Christian; Brendler, Vinzenz

doi:10.1016/j.apgeochem.2014.12.016

Cited by 41 publications

(25 citation statements)

References 11 publications

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“…In view of the practical requirements necessary to create internally consistent and quality assured parameter files, we propose the following definition: a "database" is a technical framework which ensures that dependent and independent data are stored in a manner which maintains internal consistency when independent data are modified. Examples for databases in this sense are THERMOCHIMIE (Giffaut et al 2014) or THEREDA (Moog et al 2015). They constitute secured sources for thermodynamic data from which parameter files can be exported.…”

Section: Definitionmentioning

confidence: 99%

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Validation of hydrogeochemical databases for problems in deep geothermal energy

Hörbrand

Baumann

Moog³

2018

Geotherm Energy

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Background Geothermal energy has acquired a key position in the mix of renewable energies due to its very effective heat supply and the ability to provide base load electrical energy. Many current model concepts addressing deep geothermal exploration focus on thermal, mechanical, and hydraulic interactions (e.g. Gholizadeh Doonechaly et al. 2016; Magnenet et al. 2014; Major et al. 2018; Yoon et al. 2014; Zhao et al. 2015), while neglecting hydrogeochemical effects. This is partly due to a lack of experimental data for short-term hydrogeochemical processes in the vicinity of production and injection wells (Baumann Abstract Hydrogeochemical modelling has become an important tool for the exploration and optimisation of deep hydrogeothermal energy resources. However, well-established software and model concepts are often run outside of its temperature, pressure, and salinity ranges. The core of the model codes are thermodynamic databases which contain a more or less complete subset of mineral phases, dissolved species, and gases occurring in geothermal systems. Although very carefully compiled, they should not be taken for granted at extreme conditions but checked prior to application. This study compares the performance of four commonly used geochemical databases, phreeqc. dat, llnl.dat, pitzer.dat, and slop16.dat. The parameter files phreeqc.dat, pitzer.dat, and llnl.dat are distributed with PHREEQC and implement extended Debye-Hückel and Pitzer equations. Thermodynamic data in slop16.dat represent an implementation of the revised Helgeson-Kirkham-Flowers formalism and were converted to be used with the Gibbs Energy Minimizer ChemApp for this work. Test calculations focussed on the solubility for some of the most common scale-forming mineral phases (barite, celestite, calcite, siderite, and dolomite). The databases provided with PHREEQC performed comparatively well, as long as the range of validity was respected for which the corresponding database was developed. While it is obvious to use pitzer.dat at high salinities instead of phreeqc.dat, the range of validity for high temperature is usually not given in the database and has to be checked manually. The results also revealed outdated equilibrium constants for celestite in slop16.dat and llnl.dat and the lack of adequate temperature functions for the solubility constants of siderite and dolomite in all databases. For those two minerals, new thermodynamic data are available. There is, however, a lack of experimental thermodynamic data for scale-forming minerals in low-enthalpy geothermal settings, which has to be addressed for successful modelling.

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Section: Definitionmentioning

confidence: 99%

“…Baumann et al 2017;Fritz et al 2010;Nitschke et al 2017;Reed 1989;Regenspurg et al 2015). These geochemical model concepts rest on four foundations (Moog et al 2015):…”

mentioning

confidence: 99%

Validation of hydrogeochemical databases for problems in deep geothermal energy

Hörbrand

Baumann

Moog³

2018

Geotherm Energy

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“…This modeling strategy was first implemented by Harvie, Möller, and Weare for the oceanic system Na + ‐K + ‐Mg 2+ ‐Ca 2+ ‐H + ‐OH − //Cl − ‐SO 4 2− ‐HCO 3 − , CO 3 2− /H 2 O at 25 °C. Within the framework of the THEREDA project, the polytherm model for the ion combinations Na + ‐K + ‐Mg 2+ ‐Ca 2+ //Cl − ‐SO 4 2− /H 2 O was extended to a temperature range of 0 to 110 °C . The inclusion of lithium into this system has so far only succeded at 25 °C, based on the work of Song et al .…”

Section: Lithium Recovery From Salt Lakesmentioning

confidence: 99%

Lithium Recovery from Challenging Deposits: Zinnwaldite and Magnesium‐Rich Salt Lake Brines

et al. 2017

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Lithium can be found in its bound form in silicatic rocks and dissolved in salt lake brines. Both types of lithium resources, whose amounts exceed the expected demand for lithium by several times, are used for lithium recovery. The known lithium resources and their geochemical characteristics are reviewed together with the presently applied recovery processes which are still very similar to the historically early techniques. New processes for direct carbonization of zinnwaldite, hydrochloric and oxalic acid leaching as well as a new method for the recovery of lithium from magnesium‐rich brines are presented.

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“…Furthermore, large uncertainties affect the phenomenological model itself. Kinetics rates in natural media span over orders of magnitude (Marty et al, 2015); activity models for the brines usually encountered in the subsurface lack parameterization for higher temperature, salinity, or for many elements (Dethlefsen et al, 2011;Appelo et al, 2013;Moog et al, 2015); and even larger uncertainty concerns the parameterization of the subsurface, regarding, for example, the heterogeneity of rock mineralogy, which is mostly unknown and hence often disregarded (De Lucia et al, 2011;Nissan and Berkowitz, 2019). It may thus appear unjustified to allocate large computational resources to solve very expensive yet still actually oversimplified or uncertain problems.…”

Section: Introductionmentioning

confidence: 99%

DecTree v1.0 – chemistry speedup in reactive transport simulations: purely data-driven and physics-based surrogates

Lucia

Kühn

2021

Geosci. Model Dev.

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Abstract. The computational costs associated with coupled reactive transport simulations are mostly due to the chemical subsystem: replacing it with a pre-trained statistical surrogate is a promising strategy to achieve decisive speedups at the price of small accuracy losses and thus to extend the scale of problems which can be handled. We introduce a hierarchical coupling scheme in which “full-physics” equation-based geochemical simulations are partially replaced by surrogates. Errors in mass balance resulting from multivariate surrogate predictions effectively assess the accuracy of multivariate regressions at runtime: inaccurate surrogate predictions are rejected and the more expensive equation-based simulations are run instead. Gradient boosting regressors such as XGBoost, not requiring data standardization and being able to handle Tweedie distributions, proved to be a suitable emulator. Finally, we devise a surrogate approach based on geochemical knowledge, which overcomes the issue of robustness when encountering previously unseen data and which can serve as a basis for further development of hybrid physics–AI modelling.

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Disposal of nuclear waste in host rock formations featuring high-saline solutions – Implementation of a thermodynamic reference database (THEREDA)

Cited by 41 publications

References 11 publications

Validation of hydrogeochemical databases for problems in deep geothermal energy

Validation of hydrogeochemical databases for problems in deep geothermal energy

Lithium Recovery from Challenging Deposits: Zinnwaldite and Magnesium‐Rich Salt Lake Brines

DecTree v1.0 – chemistry speedup in reactive transport simulations: purely data-driven and physics-based surrogates

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