Considering the distinct variations among different uranium deposits, it proves challenging to devise a universally applicable in situ leaching strategy for all scenarios. While experiences from similar deposits offer insights, personalized technological procedures and parameter adjustments tailored to the unique characteristics of each deposit are necessary to achieve maximum leaching efficiency. Therefore, recent technological innovations in in situ leaching have predominantly focused on customized approaches designed based on the specific features of individual uranium deposits.

In situ leaching relies on seepage of leaching solution in the porous media of uranium deposits [121]. As a result, a key element determining the usability of this mining method and a major barrier to its widespread adoption is the permeability of the uranium deposit [122]. In situ leaching techniques are typically considered unsuitable for uranium deposits with low inherent permeability (<0.5 m/d) [123]. To address this challenge, many scholars have concentrated their studies on permeability modification techniques for low-permeability uranium deposits, thereby broadening the application of in situ leaching [123,124,125,126]. While hydraulic fracturing, a widely used approach for enhancing permeability in oil and gas reservoirs [127,128], has been proven ineffective for uranium deposits [124], blasting-enhanced permeability (BEP) has emerged as a promising and effective technique for this specific context [125]. The schematic diagram in Figure 1 illustrates the underlying principle of the BEP technique for enhancing the permeability of uranium deposits. Experimental and simulation methods have substantiated that blasting can initiate well-connected fracture networks. The creation of sustainable and large-scale seepage channels within the networks is a crucial factor in improving the permeability of low-permeability uranium deposits. This enhancement enables subsequent applications of in situ leaching and facilitates the flow of leaching solution [125]. This application of BEP in in situ leaching for uranium mining is also referred to as in situ blasting leaching [126] or in situ fragmentation leaching [129].

When applying the BEP technique to low-permeability uranium deposits, a thorough assessment of the natural burial conditions of the uranium deposit is crucial. The appropriate blasting method should be selected based on the burial depth of the deposit [129]. For shallow deposits, either drilling-blasting [130] or chamber-blasting [131] methods can be employed. Usually, drilling blasting is preferable for shallow-buried thick deposits due to its more pronounced cost-effectiveness [132]. Conversely, deeper deposits often require chamber blasting to ensure the generation of a larger space for relieving underground pressure post-blasting. Subsequently, specific parameters for the blasting process are further determined based on the morphology, occurrence, and thickness of the ore body. Finally, the leaching solution is selected from the previously mentioned acid, alkaline, neutral, or bioleaching solutions, considering the actual mineral composition and properties of the ore rocks. The technique improves the permeability of uranium ore by pre-crushing the rock, allowing previously unsuitable deposits for in situ leaching to effectively utilize this method [123].

Significantly, the BEP technique enhances the permeability of the deposit and reduces the size of mineral particles [133], contributing to a notable improvement in subsequent in situ leaching effectiveness. Enhanced permeability in the deposit facilitates increased flow rates of the leaching solution through the pore spaces, enhancing uranium dissolution efficiency and leaching solution transfer efficiency [104,134,135,136,137,138]. Meanwhile, smaller mineral particles with larger surface areas favor the contact and reaction between the leaching solution and uranium minerals.

In addition to the intrinsic characteristics of the uranium deposit, the effectiveness of permeability modification by the BEP technique is influenced by blasting-related parameters such as shock wave [139,140], blasting stress [141,142], and water-decoupling coefficient [143,144]. Therefore, it is necessary to customize the blasting-related parameters according to the specific conditions of each uranium deposit. This entails conducting pre-simulation assessments of the in situ leaching effects of blasting using established numerical models [123,125] and making necessary adjustments to related parameters so as to achieve the optimal leaching effect.

The in situ leaching process of uranium deposits involves intricate fluid flow and geochemical reactions. The fluid flow within the porous media of the ore body, as well as the reactions between the leaching solution and uranium minerals within the ore body, undergo dynamic changes that significantly impact in situ leaching efficiency. To comprehend these dynamic changes more effectively, some scholars have proposed utilizing reactive transport models (RTMs) tailored to the specific characteristics of different uranium deposits to predict these dynamic variations accurately [145,146].

The reactive transport model plays a crucial role in studying the behavior of solutes in the subsurface environment [147,148,149]. Its wide application extends to predicting fluid behavior in porous media during petroleum and natural gas production [146,150], as well as in the sequestration of carbon dioxide in saline aquifers [151]. In recent years, this technique has progressively been applied to the in situ leaching of uranium deposits. When studying fluid flow and geochemical reactions in uranium deposits using reactive transport models, it is convenient to choose mature commercial and open-source software such as PHREEQC (version 3) [152,153], MT3DMS (version 5) [154], TOUGHREACT (version 4) [155], and Geochemist’s Workbench (version 6) [156] to directly establish and simulate research models. In cases where customized or advanced simulations are required, it is necessary to utilize programming languages such as Python (version 3), MATLAB (version 2010), and R (version 4) to write code for more flexible control over model implementation and simulation.

In laboratory research focused on in situ leaching for uranium mining, column experiments are commonly employed [157,158]. These experiments utilize tall column-like containers to hole uranium ore samples, simulating the actual in situ leaching process by injecting leaching solutions into the column. Such experiments help researchers assess the flow of leaching solutions and the migration of uranium-bearing pregnant solutions, providing valuable insights into the effectiveness of in situ leaching. In 2019, Laurent et al. proposed a one-dimensional reactive transport model for column experiments [111]. This approach thoroughly integrates the hydraulic properties of the leaching solution. Grounded in chemical reaction kinetics, this reactive transport model also considers the influence of grain size, providing nuanced insights into the dynamics of the leaching process. Although limited to 1D laboratory experiments, this methodology offers a deeper understanding of the hydrological and chemical processes occurring during in situ leaching. Afterward, Lagneau et al. exemplified the application of the reactive transport model in practical in situ leaching of uranium deposits [159]. By employing a reactive transport model, they precisely fitted historical data for 61 wells in one uranium block and subsequently assessed and predicted results for another block. This demonstration underscores the robustness of the model in real-world production scenarios. In 2022, Collet et al. developed a three-dimensional reactive transport model to comprehensively simulate coupled hydrodynamic and geochemical processes during in situ leaching [35], aiming to predict production outcomes. This 3D reactive transport model is based on the HYTEC program code [160,161]. It employs actual data from uranium deposits, incorporating deposit hydrodynamic parameters and mineral descriptions as a 3D geological model for hydrological processes. The simulation integrates geochemical processes and relevant mineralogical databases (including kinetic and mineral databases, along with underlying chemical processes) as a geochemical model. Finally, specific parameters of operational conditions (such as well placement, leaching solution composition, injection and extraction rates, etc.) serve as input parameters for coupled simulations of hydrodynamic and geochemical processes. This comprehensive reactive transport model facilitates fitting historical data and predicting future production in actual uranium mining scenarios. It accurately considers the details of practical in situ leaching, including realistic mineral balances, dissolution rates, and recovery rates. It has been successfully applied in large-scale, real-world, in situ uranium mining production, demonstrating precise predictive capabilities. Furthermore, reactive transport models are beneficial in the context of CO₂-O₂ leaching, which entails more complex mechanisms. They can serve to quantitatively elucidate site-specific geochemical processes during leaching and also aid in comprehending the storage of CO₂ as a gas phase due to capillary mechanisms in the permeable pores of uranium deposits [98]. This dual function enhances insights into the effectiveness of CO₂-O₂ leaching and its long-term environmental impact in the context of CO₂ utilization and storage.

Reactive transport models, in addition to their capability to predict production based on uranium deposit characteristics, are also employed for evaluating downgradient transport at in situ leaching sites. This aids in optimizing management decisions and facilitating groundwater remediation post-in situ leaching [162,163], contributing to maximizing returns and ensuring the sustainable development of uranium mining through in situ leaching.

In order to enhance the efficiency and sustainability of the entire in situ leaching process for uranium mining, a data-driven and intelligent information system with comprehensive analytical capabilities has become a notable innovation. The system offers thorough information on geological, technical, and economic elements to optimize the development and operation of mining sites. It is specifically developed to facilitate intelligent management and decision-making during the in situ leaching of uranium deposits.

The Seversk Technological Institute of the National Research Nuclear University (MEPhI) developed an informational support software package specifically designed to manage the in situ leaching process for uranium mining [164]. Operating on client–server technology, the software facilitates interaction between client programs and data storage through SQL queries, making it applicable at any stage of in situ leaching operations. There are seven interconnected information systems within the software package: (1) the mining–geological information system (MGIS) collects and processes raw geological data, generates 2D/3D mathematical models, calculates uranium reserves, and visually presents the production layer’s information status; (2) the technological information system constructs a model for the geological–technical mining complex, coordinates technical data processing, evaluates relationships, and generates operational reports to ensure data integrity; (3) the geo-technological modeling system simulates in situ leaching and pollutant migration using geological mathematical models of the uranium deposit and numerical models of the mining complex; (4) the geo-information expert analytical system (GEAS) visualizes all information in the entire mining operation process, analyzes hydrodynamic flow in the production layer, optimizes solutions, and reduces reagent usage in the in situ leaching process; (5) the techno-economic system employs economic mathematical models to calculate the economic performance of uranium mining units, including fundamental costs and other economic indicators related to unit development; (6) the computer-aided design system designs and optimizes mining development patterns based on initial data derived from geological and mathematical models of the deposit; and (7) the mining planning system predicts and formulates mining plans for operational units, ensuring planned uranium production levels based on multifactor statistical models of productivity. The software package offers advantages such as a modular architecture, scalability, and expandability. Its optimal database structure ensures both data integrity and consistency, complemented by seamless integration mechanisms with existing enterprise information systems. The collaborative utilization of the seven information systems within the package enhances the intelligence of geotechnical enterprise management through comprehensive analysis of geological and geotechnical data, multifaceted modeling of geotechnical processes, and intelligent decision support.

The collaboration between the Seversk Institute of Technology and ARMZ Uranium Holding Company has led to further enhancements of the software package, giving rise to the Smart ISL site digital mining system [24]. This system is currently capable of managing uranium production through informationization, utilizing automated data collection and remote control of wellfields. It comprehensively analyzes geological and operational data, as well as hydrogeological and technical simulations. In practical production scenarios, the system optimizes processes, enhances extraction efficiency, and reduces risks. This progression toward digitalization and intelligence in in situ leaching technology provides a sustainable and efficient intelligent solution for future uranium mining.