Zeng, S., Shen, Y., Sun, B., Tan, K., Zhang, S., & Ye, W. (2022). Fractal kinetic characteristics of uranium leaching from low permeability uranium-bearing sandstone. Nuclear Engineering and Technology, 54(4), 1175–1184.
Abstract: The pore structure of uranium-bearing sandstone is one of the critical factors that affect the uranium leaching performance. In this article, uranium-bearing sandstone from the Yili Basin, Xinjiang, China, was taken as the research object. The fractal characteristics of the pore structure of the uranium-bearing sandstone were studied using mercury intrusion experiments and fractal theory, and the fractal dimension of the uranium-bearing sandstone was calculated. In addition, the effect of the fractal characteristics of the pore structure of the uranium-bearing sandstone on the uranium leaching kinetics was studied. Then, the kinetics was analyzed using a shrinking nuclear model, and it was determined that the rate of uranium leaching is mainly controlled by the diffusion reaction, and the dissolution rate constant (K) is linearly related to the pore specific surface fractal dimension (DS) and the pore volume fractal dimension (DV). Eventually, fractal kinetic models for predicting the in-situ leaching kinetics were established using the unreacted shrinking core model, and the linear relationship between the fractal dimension of the sample’s pore structure and the dissolution rate during the leaching was fitted.
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Zeng, S., Song, J., Sun, B., Wang, F., Ye, W., Shen, Y., et al. (2023). Seepage characteristics of the leaching solution during in situ leaching of uranium. Nuclear Engineering and Technology, 55(2), 566–574.
Abstract: Investigating the seepage characteristics of the leaching solution in the ore-bearing layer during the in situ leaching process can be useful for designing the process parameters for the uranium mining well. We prepared leaching solutions of four different viscosities and conducted experiments using a self-developed multifunctional uranium ore seepage test device. The effects of different viscosities of leaching solutions on the seepage characteristics of uranium-bearing sandstones were examined using seepage mechanics, physicochemical seepage theory, and dissolution erosion mechanism. Results indicated that while the seepage characteristics of various viscosities of leaching solutions were the same in rock samples with similar internal pore architectures, there were regular differences between the saturated and the unsaturated stages. In addition, the time required for the specimen to reach saturation varied with the viscosity of the leaching solution. The higher the viscosity of the solution, the slower the seepage flow from the unsaturated stage to the saturated stage. Furthermore, during the saturation stage, the seepage pressure of a leaching solution with a high viscosity was greater than that of a leaching solution with a low viscosity. However, the permeability coefficient of the high viscosity leaching solution was less than that of a low viscosity leaching solution.
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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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Wang, W., Liang, X., Niu, Q., Wang, Q., Zhuo, J., Su, X., et al. (2023). Reformability evaluation of blasting-enhanced permeability in in situ leaching mining of low-permeability sandstone-type uranium deposits. Nuclear Engineering and Technology, 55(8), 2773–2784.
Abstract: It is essential to evaluate the blasting-enhanced permeability (BEP) feasibility of a low-permeability sandstone-type uranium deposit. In this work, the mineral composition, reservoir physical properties and rock mechanical properties of samples from sandstone-type uranium deposits were first measured. Then, the reformability evaluation method was established by the analytic hierarchy process-entropy weight method (AHP-EWM) and the fuzzy mathematics method. Finally, evaluation results were verified by the split Hopkinson Pressure Bar (SHPB) experiment and permeability test. Results show that medium sandstone, argillaceous sandstone and siltstone exhibit excellent reformability, followed by coarse sandstone and fine sandstone, while the reformability of sandy mudstone is poor and is not able to accept BEP reservoir stimulation. The permeability improvement and the distribution of damage fractures before and after the SHPB experiment confirm the correctness of evaluation results. This research provides a reformability evaluation method for the BEP of the low-permeability sandstone-type uranium deposit, which contributes to the selection of the appropriate regional and stratigraphic horizon of the BEP and the enhanced ISL of the low-permeability sandstone-type uranium deposit.
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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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