The Hydrothermal Synthesis of Zeolites: History and Development from the Earliest Days to the Present Time

https://cyberleninka.org/article/n/22310.pdf

Pore-scale imaging and modelling

This paper presents a polynomial dimensional decomposition (PDD) method for global sensitivity analysis of stochastic systems subject to independent random input following arbitrary probability distributions. The method involves Fourier-polynomial expansions of lower-variate component functions of a stochastic response by measure-consistent orthonormal polynomial bases, analytical formulae for calculating the global sensitivity indices in terms of the expansion coefficients, and dimension-reduction integration for estimating the expansion coefficients. Due to identical dimensional structures of PDD and analysis-of-variance decomposition, the proposed method facilitates simple and direct calculation of the global sensitivity indices. Numerical results of the global sensitivity indices computed for smooth systems reveal significantly higher convergence rates of the PDD approximation than those from existing methods, including polynomial chaos expansion, random balance design, state-dependent parameter, improved Sobol’s method, and sampling-based methods. However, for non-smooth functions, the convergence properties of the PDD solution deteriorate to a great extent, warranting further improvements. The computational complexity of the PDD method is polynomial, as opposed to exponential, thereby alleviating the curse of dimensionality to some extent. Mathematical modeling of complex systems often requires sensitivity analysis to determine how an output variable of interest is influenced by individual or subsets of input variables. A traditional local sensitivity analysis entails gradients or derivatives, often invoked in design optimization, describing changes in the model response due to the local variation of input. Depending on the model output, obtaining gradients or derivatives, if they exist, can be simple or difficult. In contrast, a global sensitivity analysis (GSA), increasingly becoming mainstream, characterizes how the global variation of input, due to its uncertainty, impacts the overall uncertain behavior of the model. In other words, GSA constitutes the study of how the output uncertainty from a mathematical model is divvied up, qualitatively or quantitatively, to distinct sources of input variation in the model [1].

Reliability Engineering and System Safety

CO2 storage capacity estimation: Methodology and gaps

CO2 storage in geological media: Role, means, status and barriers to deployment

Numerical simulation of CO2 disposal by mineral trapping in deep aquifers

https://escholarship.org/content/qt9jx243hn/qt9jx243hn.pdf

Mineral sequestration of carbon dioxide in a sandstone–shale system

https://digital.library.unt.edu/ark:/67531/metadc895656/m2/1/high_res_d/929005.pdf

Numerical modeling of injection and mineral trapping of CO2 with H2S and SO2 in a sandstone formation

[1] A reactive fluid flow and geochemical transport numerical model for evaluating long-term CO2 disposal in deep geologic formations has been developed. The numerical model is needed because alteration of the predominant host rock aluminosilicate minerals is very slow and is not amenable to laboratory experiment under ambient deep-formation conditions. Using this model, we performed numerical simulations for a commonly encountered Gulf Coast sediment under natural and CO2 injection conditions in order to analyze the impact of CO2 immobilization through carbonate precipitation. Under conditions considered in our simulations, CO2 trapping by secondary carbonate minerals such as calcite (CaCO3), dolomite (CaMg(CO3)2), siderite (FeCO3), and dawsonite (NaAlCO3(OH)2) could occur in the presence of high pressure CO2. Variations in the precipitation of secondary carbonate minerals strongly depend on rock mineral composition and their kinetic reaction rates. Using the data presented in this paper, the CO2 mineral-trapping capability after 10,000 years is comparable to CO2 dissolution in pore waters (2–5 kg CO2 per cubic meter of formation). The addition of CO2 mass as secondary carbonates to the solid matrix decreases porosity. A small porosity decrease can result in a significant decrease in permeability. Despite simplifications in the current model, a comparison between initial model results and field observations for natural diagenesis of Gulf Coast sediments is instructive. Most of the simulated mineral alteration pattern is consistent with the observations. Some inconsistencies are noted, which can help identify issues, limitations, and areas where the conceptual model requires improvement. The numerical simulations described here provide useful insight into potential sequestration processes, and their controlling conditions and parameters.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2002JB001979

Reactive geochemical transport simulation to study mineral trapping for CO2 disposal in deep arenaceous formations

Approximately 300 kg/day of food-grade CO2 was injected through a perforated pipe placed horizontally 2–2.3 m deep during July 9–August 7, 2008 at the MSU-ZERT field test to evaluate atmospheric and near-surface monitoring and detection techniques applicable to the subsurface storage and potential leakage of CO2. As part of this multidisciplinary research project, 80 samples of water were collected from 10 shallow monitoring wells (1.5 or 3.0 m deep) installed 1–6 m from the injection pipe, at the southwestern end of the slotted section (zone VI), and from two distant monitoring wells. The samples were collected before, during, and following CO2 injection. The main objective of study was to investigate changes in the concentrations of major, minor, and trace inorganic and organic compounds during and following CO2 injection. The ultimate goals were (1) to better understand the potential of groundwater quality impacts related to CO2 leakage from deep storage operations, (2) to develop geochemical tools that could provide early detection of CO2 intrusion into underground sources of drinking water (USDW), and (3) to test the predictive capabilities of geochemical codes against field data. Field determinations showed rapid and systematic changes in pH (7.0–5.6), alkalinity (400–1,330 mg/l as HCO3), and electrical conductance (600–1,800 μS/cm) following CO2 injection in samples collected from the 1.5 m-deep wells. Laboratory results show major increases in the concentrations of Ca (90–240 mg/l), Mg (25–70 mg/l), Fe (5–1,200 ppb), and Mn (5–1,400 ppb) following CO2 injection. These chemical changes could provide early detection of CO2 leakage into shallow groundwater from deep storage operations. Dissolution of observed carbonate minerals and desorption-ion exchange resulting from lowered pH values following CO2 injection are the likely geochemical processes responsible for the observed increases in the concentrations of solutes; concentrations generally decreased temporarily following four significant precipitation events. The DOC values obtained are 5 ± 2 mg/l, and the variations do not correlate with CO2 injection. CO2 injection, however, is responsible for detection of BTEX (e.g. benzene, 0–0.8 ppb), mobilization of metals, the lowered pH values, and increases in the concentrations of other solutes in groundwater. The trace metal and BTEX concentrations are all significantly below the maximum contaminant levels (MCLs). Sequential leaching of core samples is being carried out to investigate the source of metals and other solutes.

/pdf/changes-in-the-chemistry-of-shallow-groundwater-related-to-1imiubk2ua.pdf

John A. Apps

Papers

Numerical simulation of CO2 disposal by mineral trapping in deep aquifers

Mineral sequestration of carbon dioxide in a sandstone–shale system

Numerical modeling of injection and mineral trapping of CO2 with H2S and SO2 in a sandstone formation

Reactive geochemical transport simulation to study mineral trapping for CO2 disposal in deep arenaceous formations

Changes in the chemistry of shallow groundwater related to the 2008 injection of CO2 at the ZERT field site, Bozeman, Montana