With the global growth in demand for clean energy, the development of uranium ore resources and its environmental impact increasingly have raised concerns. Uranium tailings (slag), as the main by-product of uranium mining and processing, are an urgent environmental concern requiring safe disposal. This study systematically summarized the research progress of uranium tailings backfilling and safe disposal technology, and focuses on the paste filling process optimization and nano material solidification mechanism, in order to provide theoretical support for the green development of uranium resources and the safe disposal of radioactive waste.

In order to cope with the rising cost of truck haulage due to the rising price of diesel fuel, this thesis focuses on the existing trolley line in the Husab uranium mine in Namibia, the “Field two-time refueling method” was designed to measure the oil consumption and power consumption on the slope under the condition of pure oil and the auxiliary condition of trolley line. By disassembling the cost and benefit factors related to the operation of trolley line, this thesis put forward the reasonable value method of each factor, constructed the economic analysis frame and completed the economic feasibility calculation of the operation of trolley line. The results show that the truck with 330 t rated load in Husab is driven up the slope by trolley line at a speed of 550 m, consumes 62.65 kW·h of electricity, saves 11.25 liters of fuel consumption than the truck with pure oil, and the climbing speed is 24 km/h, which is twice as fast as that of the truck with pure oil. According to the calculation, the total dynamic income of the test section in Husab is 70.47 million N$\$$ during its whole life, and the static payback period of the technical renovation investment is less than 2 years. The static payback period of the investment is less than 5 years considering the construction cost. The investment sensitivity analysis shows that the project is most sensitive to the oil price, followed by electricity price and operating cost, and the project is least sensitive to the capital input, but even when the oil price is reduced by 50%, the dynamic income of the whole life of the project can still reach 22.09 million N$\$$, indicating that the project has strong risk resistance.

With the growing global demand for nuclear energy, the evaluation of the quality of uranium resource distribution and the precise measurement of reserves have become increasingly important. The uranium fission prompt neutron logging technology, as a critical tool for uranium ore logging exploration, offers the advantage of providing quantitative results unaffected by radioactive equilibrium. However, the measurement accuracy is influenced by the pulse width and yield of the neutron source. This study utilizes a uranium logging instrument equipped with an associated particle sealed-tube neutron generator, which enables time and spatial statistics of the companion α particles emitted by the outgoing neutrons. This approach helps to eliminate interference from the source neutrons and enhances the accuracy of the logging results. In the simulation process, to obtain information on neutron emissions during logging and the timing signal responses of both the companion α detector and the epithermal neutron detector, we propose a response time simulation method that combines Monte Carlo simulation software with MATLAB. By appropriately setting the pre-delay time and gate width, a relationship curve between the count rate and uranium content in formations with uranium levels ranging from 0 to 1.00% was established. The results from validation samples indicate that the calculated uranium content show a deviation of less than 0.1% from the actual values. When the uranium content in the formation exceeds 0.5%, the relative deviation is within 10%. This method meets the exploration requirements and demonstrates significant application value for uranium ore logging.

Machine learning algorithms can automatically learn and extract features from a large amount of geological data to achieve fast and accurate lithology identification. In this paper, the logging data of several wells in a sandstone-type uranium deposit in Inner Mongolia were randomly divided into training sets and verification sets according to the ratio of 7∶2. The model structure was adjusted and the hyperparameters were optimized for training. BC1401, BC2802, BC4603 and BC7206 well were used for testing to realize the comparative analysis of 5 kinds of models, such as random forest, XGBoost, K value proximity algorithm, BP neural network and SMOTE-LSTM algorithm. The results show that SMOTE-LSTM model has the most superior stability and accuracy, with an accuracy of 84.6%.

In order to clarify the leaching effect of horizontal well technology on in-situ leaching of uranium, a numerical simulation method was used to study the influence of different parameters on "Horizontal Well Injection-Vertical Well Pumping" and conventional "Vertical Well Injection and Pumping". The results show that compared with "Vertical Well Injection and Pumping", the length of horizontal wells is proportional to the leaching range, the vertical leaching range of "Horizontal Well Injection-Vertical Well Pumping" is small, the plane sweep efficiency is high, the dead corner of leaching is small, and the effective utilization rate of leaching solution is high; it has a wide coverage in the horizontal direction and have significant advantages in the treatment of thin uranium ore deposits. The ratio of horizontal permeability to vertical permeability has a greater impact on the leaching of "Vertical Well Injection and Pumping". When the vertical permeability is low, the leaching effect of horizontal well sections is better than that of vertical well sections; the amount of pumping and injection fluid is positively correlated with the leaching range. As the amount of pumping and injection fluid increases, the dead corners of leaching of both "Horizontal Well Injection-Vertical Well Pumping" and "Vertical Well Injection and Pumping" decrease. The increase in the amount of pumping and injection fluid has a greater impact on the leaching effect of "Horizontal Well Injection-Vertical Well Pumping". When the flow rate reaches 210 m³/d, the leaching range of the ore layer of "Horizontal Well Injection-Vertical Well Pumping" is higher than that of generalized "Vertical Well Injection and Pumping".

In the in-situ leaching of uranium, uranium migration is influenced by both groundwater flow and solute diffusion, and this process can be effectively modeled using the advection-diffusion equation. Accurately modeling the variation of uranium concentration over time and space is crucial for predicting uranium migration in groundwater during in-situ leaching of uranium. Traditional numerical methods, such as the finite difference method, are computationally intensive and prone to errors while dealing with high-dimensional, complex problems. Therefore, this research aims to explore the applicability and accuracy of physics-informed neural networks (PINN) in solving the advection-diffusion equation. Through numerical simulations of the one-dimensional advection-diffusion equation, and by comparing the PINN solutions with numerical and analytical solutions. The results show that PINN provide higher accuracy and better alignment with the analytical solution over long-term simulations compared to numerical methods. Furthermore, PINN exhibit certain extrapolation capabilities. Additionally, the introduction of dropout enhances the generalization ability and convergence speed of the PINN model, confirming the potential of PINN in solving complex physical problems.

As the mining depth of a uranium mine continues to increase, the ore body shows a trend of decreasing thickness and increasing inclination angle. This paper focuses on the steeply inclined thin ore veins of the uranium mine, utilizing the AHP-TOPSIS method for comparative analysis of different mining methods, and proposes a high-segment continuous efficient collaborative mining method suitable for the thin ore veins in this mine. Based on this, the numerical analysis is conducted using FLAC3D to examine different structural parameter schemes of the stope, analyzing the stress field, displacement field, and distribution characteristics of the plastic zone during the mining process, ultimately acquiring the optimal stope structural parameters. The results indicate that: no tensile stress was observed in the top and intermediary pillars in scheme 1 to 4, while a small amount of tensile stress occurred in schemes 5 and 6; the proportion of the plastic zone varies from 22.52% to 27.98% across scheme 1 to 6, with scheme 3 demonstrating better stability. Considering both safety and economic factors, the optimal stope structural parameters are determined to be a top pillar height of 5 m and an intermediary pillar width of 8 m (scheme 3).

The accuracy of hydraulic conductivity holds great significance for the subsequnce research and exploitation of the in-situ leaching sandstone-type uranium deposit. Taking the in-situ leaching technology of sandstone-type uranium deposit as the research object, based on the current research status of hydrogeological well completion technology and hydraulic conductivity calculation methods at home and abroad, this paper analyzes the influencing factors of hydrogeological well completion quality on hydraulic conductivity calculation. Through VB visual programming software, the loopholes of human error in calculation and curve drawing are made up, and the calculation of hydrogeological parameters of deposit is more concise, efficient and accurate.

The "CO₂+O₂" leaching process is an artificially intensified water-rock interaction process that leads to the dissolution of non-uranium minerals, which enter the leaching solution system and cause changes in the dissolution and precipitation state of the minerals in the leachate. Geochemical simulation methods were used to simulate ion species in the leachate and the mineral leaching equilibrium studying the dissolution, migration, and precipitation of minerals during the in-situ leaching mining process. For the first time, the conditions and influencing factors for the precipitation of manganese minerals were studied, targeting the characteristics of strong groundwater reducibility and high carbonate content in the target deposit.The results show that under neutral leaching conditions, uranium in the leachate mainly exists in the form of UO₂(CO₃${)}_{3}^{4-}$ followed by UO₂(CO₃${)}_{2}^{2-}$, and the proportions of the two are affected by pH. The saturation indices of carbonate minerals in the neutral leaching leachate of the study area are all greater than zero, indicating a supersaturated state, and pH is the main factor controlling the precipitation of carbonates, with the critical pH for calcium carbonate precipitation being 6.7 and for calcium magnesium carbonate precipitation being 6.5. The saturation indices of sulfate minerals are all less than zero, and no precipitation of calcium sulfate will occur in the formation, and the precipitation of calcium sulfate is mainly controlled by the content of calcium ions and sulfate ions. Under neutral leaching conditions, iron mineral precipitation is likely to occur and is greatly affected by pH conditions; at the same time, manganese-containing minerals will precipitate in the leachate, and the redox conditions are the main factors affecting their dissolution and precipitation; some silicon-containing minerals in the leachate are in a supersaturated state, and their dissolution and precipitation are greatly affected by pH The research results are of great significance for the prevention of precipitation in in-situ leaching mining.

A sandstone-type uranium deposit in Xinjiang belongs to auspicious prospecting stage with exploration line of 200 m×200 m, low exploration degree, thin ore bed and low uranium content. In addition, there are complex hydrogeological conditions with poor permeability (permeability coefficient is only 0.045 m/d) and high pressure head. No leaching test work has been carried out in this deposit area. In order to study the leaching of uranium resources in the deposit, field leaching test was carried out by adopting neutral leaching and improving the pressure leaching technology, the results show that the average extraction volume of single hole is 1.7 m³/h, the average mass concentration of uranium in leaching solution is 40.37 mg/L, the maximum mass concentration of uranium in single hole is 390.22 mg/L, and the annual leaching recovery is 13.39%, it provides technical support for the exploitation of uranium resources in the deposit.