The basic principle of in situ leaching is chemical mining. The process of in situ leaching is to inject leaching solution into the ore body, and the leaching solution is spread in the pores of the mountain. The process is completed by the coupling action of the liquid seepage field and ion exchange reactions. In the production process, only one injection of liquid can be carried out in a certain stope, so it is impossible to improve the injection process and leaching effect through field practice. By simulating the in situ leaching process of rare earth ions, this paper builds the test stope true three-dimensional numerical model and simulates the leaching process of rare earth ore under the coupling of seepage control, ion exchange, and dilute material transfer in porous media. The migration rule of RE³⁺ and Mg²⁺ in stopes was analyzed to evaluate the leaching effect. It is of great significance to increase the recovery rate of rare earth ore.

During the in situ leaching process of ion-adsorption rare earths, leaching solution needs to be constantly injected to the mine slopes. As a consequence, landslides are highly likely to occur due to the increasing water level of soil mass. To solve this problem, we conducted a mechanical analysis on the rising water level after solution injection, which shed light on the mechanical principle of slope instability brought about by rising water level. With water level variation as the major factor, we established an early warning system for landslide risks on the basis of the real-time monitoring of water level. Within the system, a self-designed landslide early warning model is embedded. In addition to monitoring the water level variation in slopes, this system can be employed for real-time data processing. With the integration of early warning model algorithm, the real-time graded early warning of slope landslide risks is achieved within the mining process of ion-adsorption rare earths. By discussing the real-time monitoring method, framework of landslide early warning system, FIFC landslide early warning model, optimization method of water level, and selection of landslide-inducing factors, this research provides an effective solution to the landslide early warning within the mining process of ion-adsorption rare earth minerals. Thus, it can be employed as a favorable reference for other types of early warning systems.

During the in-situ leaching process of ion-adsorption rare earth ore, the seepage velocity of the leaching solution is one of the core problems in studying the leaching efficiency. The determination of the saturated hydraulic conductivity is of great significance to reveal the leaching process. The classical Kozeny–Carman (KC) equation is widely employed to predict the hydraulic conductivity of sandy soils. However, in the equation, the effect of tortuosity on the hydraulic conductivity is not considered, and the specific surface area is difficult to determine in practice. In this study, the capillary model for predicting the saturated hydraulic conductivity of ion-adsorption rare earth ore was established. First, we assumed that all the pores in the ore body are a series of parallel and tortuous capillaries with equal diameters. Based on the assumption and Hagen–Poiseuille’s law, the KC equation was improved by introducing the tortuosity. Second, the constant head permeability tests were carried out to derive the seepage velocity and hydraulic head loss under the steady seepage state. According to the experimental results, the diameter of the capillary was calculated with Darcy's formula. Then we obtained a linear-fit relationship between capillary diameter and porosity to express the specific surface area variation with porosity. Third, by validating with experimental data, when the pore shape coefficient is 0.4, the saturated hydraulic conductivity calculated by the capillary model is in good agreement with the tested value. The proposed model can be considered to have a satisfactory capability to predict the saturated hydraulic conductivity of ion-adsorption rare earth ore.

In order to simulate and calculate the leaching process of ionic rare earths more realistically, a digital model of ionic rare earths with real size, shape, seepage channel, and pore ratio and distribution at the mesoscopic scale was constructed based on nuclear magnetic resonance imaging (NMRI) technology. And the in situ leaching mining process was simulated and calculated by using three control equations of solution seepage, ion exchange, and solute migration. The reliability of the NMRI model was verified by the results of the indoor column leaching experiment, and the influence of the injection intensity and leaching agent concentration on the leaching of rare earth ions was analyzed. The results show that there are dominant seepage channels in the ore body, and the rare earth ion exchange reaction and migration in the dominant channel area are completed first. By analyzing the leaching results of rare earth ions under the working conditions of different injection strengths and different concentrations of leaching agent, the results show that the injection strength and the concentration of leaching agent have an obvious promoting effect on the leaching of rare earth ions in a certain range. The injection strength of 0.5~1.0 mL/min and the concentration of 0.20~0.25 mol/L leaching agent are considered to be more economical in practical engineering.

The change of permeability coefficient of ionic rare earth ore is one of the most important factors causing the uncontrollable flow of leaching solution, and the variation of pore structure of the ore body has a great influence on the permeability coefficient. The research on the evolution of the relationship between pore structure and permeability coefficient of ionic rare earths is of great significance for controlling water and soil pollution and improving the leaching rate of rare earths. In this paper, the column leaching test of ionic rare earth was carried out to study the evolution of the relationship between pore structure and permeability coefficient. In the process of MgSO₄ solution and deionized water leaching, the spectrum and inversion image at each time were obtained by nuclear magnetic resonance (NMR). Based on the fractal theory, the pore structure change of the inversion image was quantitatively analysed, and the permeability coefficient of samples at each time of different leaching agents was calculated by using supercritical Dubinin-Redushckevich (SDR) model to analyse the nuclear magnetic resonance spectrum. The results show that in MgSO₄ solution, the permeability coefficient of the sample changes significantly, and the growth rate of pore fractal dimension remains large. By discussing the evolution law of pore fractal dimension and seepage characteristics of ionic rare earth, the mathematical relationship between permeability coefficient and pore fractal dimension of mineral soil samples at different depths is fitted by polynomial function.

In the in-situ leaching method of ionic rare earth, ion exchange reaction between rare earth ions and leaching agent ions is carried out, which allows the rare earth ions to be leached from the ore body as the leaching solution flows through the pores. This indicates that the leaching process of rare earth ions is closely related to the seepage field, ion exchange field, and ion migration process of the leaching solution. In this study, an ionic rare earth mine located in Longnan of Jiangxi Province was taken as the research object. By conducting nuclear magnetic resonance scanning on the ore samples of this mine and vectorizing the nuclear magnetic resonance images, a two-dimensional geometric model of pores was obtained. Then, COMSOL Multiphysics software was used to establish a coupled numerical model of seepage–exchange–migration of the ionic rare earth mine during the leaching process at the pore scale to study the seepage situation of leaching solution with different injection strengths and concentrations, as well as the exchange and migration process. The results show that increasing the concentration of magnesium ions can increase the difference of ion diffusion concentration, accelerate the forward exchange rate of ions, promote the forward exchange reaction, and improve the concentration gradient of rare earth ions in the leaching solution. The more significant the diffusion effect, the higher the ion migration rate, while at the same time inhibiting the reverse adsorption of rare earth ions, and accelerating the leaching efficiency of rare earth ions. In addition, increasing the strength of the injection solution allows rare earth ions to leach out of the ore body earlier, shortens the leaching cycle, and thus reduces the peak concentration of leached rare earth ions. By analyzing the effects of the strength of the injection solution and leaching concentration on ionic rare earth leaching, the influence of those two factors on engineering economy can be briefly evaluated, which can be provided as a reference for the optimization of ionic rare earth mining technology.