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Love, A. J., Shand, P., Karlstrom, K., Crossey, L., Rousseau-Gueutin, P., Priestley, S., et al. (2013). Geochemistry and Travertine Dating Provide New Insights into the Hydrogeology of the Great Artesian Basin, South Australia. Procedia Earth and Planetary Science, 7, 521–524.
Abstract: While of great national and societal significance, and importance in its own right, the Great Artesian Basin of Australia is an iconic example of a continental scale artesian groundwater system. New geochemical, hydrological, and neo-tectonic data suggests that existing models that involve recharge in eastern Australia, relatively simple flowpaths and discharge in springs in the western margin require modification. New geochemical data indicate a small volume flux of deeply derived (endogenic) fluids mixing into the aquifer system at a continental scale. Neo- tectonic data indicates active tectonism today that provides a fluid pathway through faults for the deeply sourced endogenic fluids to discharge in GAB travertine depositing springs.
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Lach, P., Cathelineau, M., Brouand, M., & Fiet, N. (2015). In-situ Isotopic and Chemical Study of Pyrite from Chu-Sarysu (Kazakhstan) Roll-front Uranium Deposit. Procedia Earth and Planetary Science, 13, 207–210.
Abstract: Pyrite is common in roll-front type uranium deposit in Chu-sarysu basin, Kazakhstan. Combined in-situ microstructural, isotopic and chemical analysis of pyrite indicates variation in precipitation conditions and in fluid composition. Broad-scale δ34S heterogeneity indicates a complex multi-facet evolution. First generation authigenic framboïdal aggregates are biogenic as demonstrated by the lowest δ34S values of -48‰ to -28‰. The latest generation pyrites are probably hydrothermal with greater δ34S variation (-30‰ to +12‰). This hydrothermal pyrite commonly displays variable enrichment of several trace elements especially As, Co and Ni. Strong variation in δ34S values and variable trace element enrichment is interpreted in terms of continuous variations in fluid composition.
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Hu, K., Wang, Q., Tao, G., Wang, A., & Ding, D. (2011). Experimental Study on Restoration of Polluted Groundwater from in Situ Leaching Uranium Mining with Sulfate Reducing Bacteria and ZVI-SRB. Procedia Earth and Planetary Science, 2, 150–155.
Abstract: In the case of in situ leaching of uranium, the primitive geochemical environment for groundwater is changed since leachant is injected into the water beaving uranium deposit. This increases the concentration of uranium and results in the groundwater contamination.Microbial reduction technology by Sulfate reducing bacteria and Zero Valent Iron were employed to treat uranium wastewater. The experiments were conducted to evaluate the influence of anion (sulfate and nitrate) on dealing with uranium wastewater. Experimental results show that the utilization of both SRB system and ZVI – SRB system to process uranium wastewater is affected by sulfate ion and nitrate ion. As the concentration of sulfate radical is lower than 4000mg/L, sulfate-reducing bacteria has no influence on precipitated uranium. However, as the concentration of sulfate is more than 6,000mg/L, uranium removal rate decreases significantly, from 80% to 14.1%. When adding sulfate radical on ZVI – SRB system to process uranium wastewater, its uranium removal rate is higher than SRB system. Low concentration of nitrate contributes to reduction metabolism of SRB. High concentration of nitrate inhibits the growth and metabolism of SRB and affects the treatment efficiency of uranium wastewater. When the concentration of nitrate reaches 1500mg/L, uranium removal rate is less than 0.1%. Nevertheless, as the concentration of nitrate is lower than 1000mg/L, uranium removal rate could reach more than 75%. As existence of nitrate radical, uranium removal rate of SRB by adding ZVI is higher than that without adding.
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Merembayev, T., Yunussov, R., & Yedilkhan, A. (2019). Machine Learning Algorithms for Stratigraphy Classification on Uranium Deposits. Procedia Computer Science, 150, 46–52.
Abstract: Machine learning today becomes more and more effective instrument to solve many particular problems, where there are difficulties to apply well known and described math model. In other words – it is a great tool to describe non-linear phenomena. We tried to use this technique to improve existing process of stratigraphy, and reduce costs on site by applying computer leaded predictions on the basis of existing on-field collected data. Article describes usage of machine learning algorithms for stratigraphy boundaries classification based on geophysics logging data for uranium deposit in Kazakhstan. Correct marking of stratigraphy from geophysics logging data is complex non-linear task. To solve this task we applied several algorithms of machine learning: random forest, logistic regression, gradient boosting, k nearest neighbour and XGBoost.
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Liu, Z., Tan, K., Li, C., Li, Y., Zhang, C., Song, J., et al. (2023). Geochemical and S isotopic studies of pollutant evolution in groundwater after acid in situ leaching in a uranium mine area in Xinjiang. Nuclear Engineering and Technology, 55(4), 1476–1484.
Abstract: Laboratory experiments and point monitoring of reservoir sediments have proven that stable sulfate reduction (SSR) can lower the concentrations of toxic metals and sulfate in acidic groundwater for a long time. Here, we hypothesize that SSR occurred during in situ leaching after uranium mining, which can impact the fate of acid groundwater in an entire region. To test this, we applied a sulfur isotope fractionation method to analyze the mechanism for natural attenuation of contaminated groundwater produced by acid in situ leaching of uranium (Xinjiang, China). The results showed that δ34S increased over time after the cessation of uranium mining, and natural attenuation caused considerable, area-scale immobilization of sulfur corresponding to retention levels of 5.3%–48.3% while simultaneously decreasing the concentration of uranium. Isotopic evidence for SSR in the area, together with evidence for changes of pollutant concentrations, suggest that area-scale SSR is most likely also important at other acid mining sites for uranium, where retention of acid groundwater may be strengthened through natural attenuation. To recapitulate, the sulfur isotope fractionation method constitutes a relatively accurate tool for quantification of spatiotemporal trends for groundwater during migration and transformation resulting from acid in situ leaching of uranium in northern China.
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