GEM-Selektor geochemical modeling package: revised algorithm and GEMS3K numerical kernel for coupled simulation codes

Reactive mass transport (RMT) simulation is a powerful numerical tool to advance our understanding of complex geochemical processes and their feedbacks in relevant subsurface systems. Thermodynamic equilibrium defines the baseline for solubility, chemical kinetics, and RMT in general. Efficient RMT simulations can be based on the operator-splitting approach, where the solver of chemical equilibria is called by the mass transport part for each control volume whose composition, temperature, or pressure has changed. Modeling of complex natural systems requires consideration of multiphase-multicomponent geochemical models that include nonideal solutions (aqueous electrolytes, fluids, gases, solid solutions, and melts). Direct Gibbs energy minimization (GEM) methods have numerous advantages for the realistic geochemical modeling of such fluid-rock systems. Substantial improvements and extensions to the revised GEM interior point method algorithm based on Karpov's convex programming approach are described, as implemented in the GEMS3K C/C+ + code, which is also the numerical kernel of GEM-Selektor v.3 package ( http://gems.web.psi.ch ). GEMS3K is presented in the context of the essential criteria of chemical plausibility, robustness of results, mass balance accuracy, numerical stability, speed, and portability to high-performance computing systems. The stand-alone GEMS3K code can treat very complex chemical systems with many nonideal solution phases accurately. It is fast, delivering chemically plausible and accurate results with the same or better mass balance precision as that of conventional speciation codes. GEMS3K is already used in several coupled RMT codes (e.g., OpenGeoSys-GEMS) capable of high-performance computin

Modeling cesium migration through Opalinus clay: a benchmark for single- and multi-species sorption-diffusion models

Sophisticated modeling of the migration of sorbing radionuclides in compacted claystones is needed for supporting the safety analysis of deep geological repositories for radioactive waste, which requires robust modeling tools/codes. Here, a benchmark related to a long term laboratory scale diffusion experiment of cesium, a moderately sorbing radionuclide, through Opalinus clay is presented. The benchmark was performed with the following codes: CORE$^{2D}$V5, Flotran, COMSOL Multiphysics, OpenGeoSys-GEM, MCOTAC and PHREEQC v.3. The migration setup was solved with two different conceptual models, i) a single-species model by using a look-up table for a cesium sorption isotherm and ii) a multi-species diffusion model including a complex mechanistic cesium sorption model. The calculations were performed for three different cesium boundary concentrations (10$^{-3}$, 10$^{-5}$, 10$^{-7}$ mol / L) to investigate the models/codes capabilities taking into account the nonlinear sorption behavior of cesium. Generally, good agreement for both single- and multi-species benchmark concepts could be achieved, however, some discrepancies have been identified, especially near the boundaries, where code specific spatial (and time) discretization had to be improved to achieve better agreement at the expense of longer computation times. In addition, the benchmark exercise yielded useful information on code performance, setup options, input and output data management, and post processing options. Finally, the comparison of single-species and multi-species model concepts showed that the single-species approach yielded generally earlier breakthrough, because this approach accounts neither for cation exchange of Cs$^{+}$ with K$^{+}$ and Na$^{+}$, nor K$^{+}$ and Na$^{+}$ diffusion in the pore water

Direct mineral content prediction from drill core images via transfer learning

Deep subsurface exploration is important for mining, oil and gas industries, as well as in the assessment of geological units for the disposal of chemical or nuclear waste, or the viability of geothermal energy systems. Typically, detailed examinations of subsurface formations or units are performed on cuttings or core materials extracted during drilling campaigns, as well as on geophysical borehole data, which provide detailed information about the petrophysical properties of the rocks. Depending on the volume of rock samples and the analytical program, the laboratory analysis and diagnostics can be very time-consuming. This study investigates the potential of utilizing machine learning, specifically convolutional neural networks (CNN), to assess the lithology and mineral content solely from analysis of drill core images, aiming to support and expedite the subsurface geological exploration. The paper outlines a comprehensive methodology, encompassing data preprocessing, machine learning methods, and transfer learning techniques. The outcome reveals a remarkable 96.7% accuracy in the classification of drill core segments into distinct formation classes. Furthermore, a CNN model was trained for the evaluation of mineral content using a learning data set from multidimensional log analysis data (silicate, total clay, carbonate). When benchmarked against laboratory XRD measurements on samples from the cores, both the advanced multidimensional log analysis model and the neural network approach developed here provide equally good performance. This work demonstrates that deep learning and particularly transfer learning can support extracting petrophysical properties, including mineral content and formation classification, from drill core images, thus offering a road map for enhancing model performance and data set quality in image-based analysis of drill cores

Reactive transport modelling of a low-pH concrete / clay interface

Versión aceptada de https://doi.org/10.1016/j.apgeochem.2020.104562[Abstract:] Cement-based materials are key components in the barrier system and structural support of repositories for disposal of nuclear waste. As such, increased understanding of their long-term performance under repository conditions is paramount for the safety assessment. Quantification of the impact that cement-based materials could have on the surrounding barriers and the host rock is essential to assess long-term safety of the repository system. This interaction can impact the physical properties of the system near the interface and needs to be assessed by means of numerical modelling. A reactive transport modelling study of the interaction between a newly-developed low-pH concrete and a clay host rock (i.e. Callovo Oxfordian) over 100,000 years is presented here. The main goal is to build confidence in the consistency of the different modelling approaches and in the application of different reactive transport codes (iCP, ORCHESTRA, OpenGeosys-GEM, CORE2D, and MIN3P) to analyse the performance of the recently developed low-pH concrete within the CEBAMA project. A common setup of a reference case was established, including precipitation/dissolution reactions, redox and cation exchange processes, building upon preliminary cases of increasing complexity. In addition, a set of sensitivity cases was simulated to test the effect of key geochemical and transport parameters on the results, including the impact of porosity changes on the diffusion coefficient and electrochemical couplings. Different reactive transport codes were used in the benchmark. Overall, the results show not only the high level of understanding of the governing processes but also the good agreement obtained with different codes, which is essential to demonstrate the applicability of reactive transport modelling to support safety assessment. The sensitivity and preliminary cases modelled show that the results obtained are much more sensitive to changes to transport parameters and couplings than to the different modelling tools used in each case. In addition, the impact of including or not the slow kinetics of dissolution of the claystone minerals is shown to be negligible in the studied scenarios.The research leading to these results has received funding from the European Union's European Atomic Energy Community's Horizon 2020 Programme (NFRP-2014/2015) under grant agreement, 662147 – CEBAMA. V. Montoya., J. Poonoosamy and G. Deissmann acknowledge the German Federal Ministry of Education and Research (Grant 02NUK053A) and the Initiative and Networking Fund of the Helmholtz Association (Grant SO-093) within the iCross project for partial funding. The authors would like to thank Barbara Lothenbach for fruitful discussions on modelling cement hydration of the low-pH cement system and the two reviewers for constructive and valuable comments that have helped to improve the manuscript.Alemania. German Federal Ministry of Education and Research; 02NUK053AAlemania. Initiative and Networking Fund of the Helmholtz Association; SO-09

Diffusion of Na and Cs in montmorillonite

The state and dynamics of water and cations in pure and mixed Na-Cs-montmorillonite as a function of the interlayer water content were investigated in the present study, using Monte Carlo and classical, molecular-dynamics methods. While highly idealized, the simulations showed that the swelling behavior of hetero-ionic Na-Cs-montmorillonite is comparable to the swelling of a homo-ionic Na- or Cs-montmorillonite. The mixed Na-Cs-montmorillonite is characterized by intermediate interlayer distances compared to homo-ionic Na- and Cs-montmorillonites. Dry, hetero-ionic Na-Cs-montmorillonite is characterized by a symmetric sheet configuration, as is homo-ionic Cs-montmorillonite. We found that at low degrees of hydration the absolute diffusion coefficient of Cs is less than for Na, whereas at greater hydration states the diffusion coefficient of Cs is greater than for Na. An analysis of the relative diffusion coefficients (the ratio between the diffusion coefficient of an ion in the interlayer and its diffusion coefficient in bulk water) revealed that water and Na are always less retarded than Cs. With large interlayer water contents, tetralayer or more, Na ions preferentially form outer-sphere complexes. The mobility perpendicular to the clay surface is limited and the diffusion is equivalent to two-dimensional diffusion in bulk water. In contrast, Cs ions preferentially form 'inner-sphere complexes' at all hydration states and their two-dimensional diffusion coefficient is less than in bulk water. The question remains unanswered as to why experimentally derived relative diffitsion coefficients of Cs in the interlayer of clays are about 20 times less than those we obtained by classical molecular dynamics studies

The essential role of cement-based materials in a radioactive waste repository

Abstract Cement-based materials are integral to radioactive waste repositories, providing versatile solutions for diverse disposal strategies. They are part of the multi-barrier system, and serve to immobilize waste materials, limit the release of radionuclides, contribute to an alkaline near-field to inhibit steel corrosion, reduce microbial activity, and slow down radionuclide transport in the repository near-field. This work delves into the adaptability of the multi-barrier systems for long-term safety, examining cases in clay and granite. Highlighting the disposal case in clay, the study emphasizes the role of cement in ensuring repository stability. The barrier system aims to minimize radionuclide release and demonstrate long-term isolation and containment of waste. The containment duration is relevant to the radionuclide’s half-life, with consideration for extended safety over extremely long periods. Cement evolves under geological conditions, undergoing a progressive process of degradation that is influenced by intricate aggregate-cement reactions and external factors, e.g., sulfates and chlorides in groundwater, the host rocks (including clays and granites), and the engineered barrier materials (including bentonite and steel), and in turn influencing mechanical stress generation and porosity. The very slow chemical alteration processes that take place at the concrete/granite interface underscore the repository stability. Corrosion of steel in the cement is expected to be slow, but its long-term structural and chemical changes remain quite unknown. Challenges remain in accurately predicting the long-term performance of the cement due to uncertainties in chemical reactivity, the impact of partial water saturation, and the kinetics of degradation processes. The manuscript advances the development of predictive modeling tools for assessing the long-term performance of cement-based barriers. The integration of experimental results with modeling efforts offers a robust framework for predicting the behavior of cementitious materials under various environmental conditions, thereby contributing to more reliable safety assessments of radioactive waste repositories. The role of cement phases in ensuring repository safety remains pivotal

Effects of solution supersaturation on barite precipitation in porous media and consequences on permeability: experiments and modelling

The understanding of porosity evolution in porous media due to mineral reactions and its impact on the transport of fluids and solutes is important, as this is a key factor in the long-term behaviour of underground engineered systems. The implementation of such coupled processes into numerical codes requires a mechanistic understanding of the relevant precipitation/dissolution processes in porous media and model validation with quantitative experiments. In this context, we conducted a series of flow-through column experiments to investigate the effect of supersaturation on barite precipitation mechanisms (e.g. nucleation) and consequential permeability changes. These experiments were modelled using the reactive transport code OpenGeoSys-GEM. Although the Kozeny-Carman equation is widely applied in numerical models describing porosity and permeability changes due to mineral dissolution and precipitation, it distinctively underestimated the permeability changes observed in the experiments. Instead, a porosity-permeability relationship involving a critical porosity at which the permeability decreases significantly had to be considered in the model. Post-mortem characterization (Scanning Electron Microscopy) highlighted the importance of including pore-scale information on passivation processes in order to get a better match between experimental and simulated results