The application of In Situ Leaching (ISL) has significantly boosted uranium production in countries like Kazakhstan. Given that hydrodynamic and chemical processes occur underground, mining enterprises worldwide have developed models of reactive transport. However, modeling these complex processes demands considerable computational resources. This issue is particularly significant in the context of numerical analyses of mining processes or when modeling production scenarios in uranium mining by the ISL technique, given that a substantial portion of computational resources is allocated to solving the hydraulic head equation. This work aims to explore the applicability of PINNs to accelerate hydrodynamic simulations of the ISL process. The solution of the Poisson equation is accelerated by generating an initial approximation for the iterative method through the application of the Inverse Distance Weighting (IDW) interpolation and PINNs. The impact of various factors, including the computational grid and the spacing between wells, on both the accuracy and efficiency of initial approximation and the overall solution of the elliptic equation are explored. Employing the hydraulic head distribution obtained through PINNs as the initial approximation led to a significant reduction in computation time and a decrease in the number of iterations by a factor of 2.8 to 7.10.

In situ leaching represents an efficient and safe method for uranium mining, where a suboptimal well flow rate distribution leads to solution imbalances between wells, forming stagnant zones that increase operational costs. This study examines a real technological block from the Budenovskoye deposit, applying reactive transport modeling to optimize well flow rates and reduce operational time and reagent consumption. A reactive transport model was developed based on mass conservation and Darcy’s laws coupled with chemical kinetics describing sulfuric acid interactions with uranium minerals ($U{O}_2$ and $U{O}_3$). The model simulated a technological block with 4 production and 18 injection wells arranged in hexagonal cells over 511–542 days to achieve 90% uranium recovery. Six approaches for well flow rate redistribution were compared, based on different weighting factor calculation methods: advanced traditional, linear distance, squared distance, quadrilateral area, and two streamline-based approaches utilizing the minimum and average time of flight. The squared distance method achieved the highest efficiency, reducing operational costs by 5.7% through improved flow redistribution. The streamline-based methods performed comparably and offer potential advantages for heterogeneous conditions by automatically identifying hydraulic connections. The reactive transport modeling approach successfully demonstrated that multi-criteria optimization methods can improve ISL efficiency by 3.9%–5.7% while reducing operational costs.

This study presents a comprehensive computational analysis of flow rate efficiency during uranium extraction via the In Situ Recovery method. Using field data from a deposit located in Southern Kazakhstan, a series of mathematical models were developed to evaluate the distribution and balance of leaching solution. A reactive transport model incorporating uranium dissolution kinetics and acid–rock interactions were utilized to assess the accuracy of both traditional and proposed methods. The results reveal a significant spatial imbalance in sulfuric acid distribution, with up to 239.1 tons of acid migrating beyond the block boundaries. To reduce computational demands while maintaining predictive accuracy, two alternative methods, a streamline-based and a trajectory-based approach were proposed and verified. The streamline method showed close agreement with reactive transport modeling and was able to effectively identify the presence of intra-block reagent imbalance. The trajectory-based method provided detailed insight into flow dynamics but tended to overestimate acid overflow outside the block. Both alternative methods outperformed the conventional approach in terms of accuracy by accounting for geological heterogeneity and well spacing. The proposed methods have significantly lower computational costs, as they do not require solving complex systems of partial differential equations involved in reactive transport simulations. The proposed approaches can be used to analyze the efficiency of mineral In Situ Recovery at both the design and operational stages, as well as to determine optimal production regimes for reducing economic expenditures in a timely manner.

Ground thermal energy storage are effective systems for building climate control, yet, their modeling is complicated by a sharp geometric disproportion, particularly the diameter of the heat exchanger is several orders of magnitude smaller than its depth. This makes full-scale 3D modeling practically unfeasible due to large computational costs. The situation is exacerbated by the multi-parametric nature of the problem. As a result, classical parametric studies and sensitivity analysis require high computational power, which hinders the process of rapid iterative design. To address this problem, this paper presents a novel integrated, full-stack software architecture that automates conjugate heat and mass transfer calculations, which traditionally require complex hydrodynamic computations. The methodology relies on an accessible application and a localized database combined with an optimized explicit finite-difference backend, utilizing vectorized numerical solvers to calculate 1D hydrodynamics and thermal processes within the borehole heat exchanger and 3D heat conduction in heterogeneous soil. The reliability of the software's calculations is validated by previously obtained results of field Thermal Response Tests. The proposed tool enabled the implementation of large-scale parametric studies and system sensitivity analysis to key physical factors. The model allows for a comprehensive assessment of the impact of the thermophysical characteristics of heterogeneous soil layers and the properties of the borehole grouting material on heat extraction efficiency. The inclusion of the influence of groundwater flows into the computational scheme potentially expands functionality, allowing for full-fledged dynamic modeling of the system under changing conditions. As a result, the developed software represents a scalable and cost-effective desktop tool for rapid, dynamic modeling of geothermal systems. By providing the capability for deep parametric optimization considering real soil properties, bentonite characteristics, and the impact of groundwater flows, the program successfully combines advanced theoretical thermodynamic principles with the needs of practical design.