A reactive transport model designed to predict the environmental footprint of an 'in-situ recovery' uranium exploitation.

Worldwide, most uranium production relies on the 'in situ recovery' (ISR) extraction technique. This consists of dissolving the ore using a leaching solution (acid or alkaline) directly within the deposit through a series of injection and extraction wells. Due to the nature of the injected ISR solutions, the water quality of the aquifer could be affected. Reactive transport modeling is a powerful tool for predicting fluid flow and geochemical reactions in ISR reservoirs. In this study we present a coupled 3D environmental geochemical model (EGM) (based on the HYTEC reactive transport software), capable of predicting the physico-chemical conditions in an acid-leaching ISR uranium mine and its environmental footprint on the aquifer in the years following the closure of the production block. The model was validated at the KATCO mine (Kazakhstan) on two different and independent production blocks, over 10 years after their closure. The model shows that incorporating two main geochemical processes, (1) cationic sorption on clay surfaces (smectite-beidellite) and (2) precipitation of gypsum (CaSO4.2H2O), successfully reproduces the measured well data (pH, acidity and SO4) over short- and long-term time scales. Clay surface sites remain mostly saturated in protons during the production phase. Simulations show that sorbed protons on the clay surfaces maintains the acid conditions for a longer period of time. The environmental impact model was also compared to a pre-existing model specifically developed for production simulation purposes: differences are observed as expected for the uranium production, but also for the impact distances, due to differences in the considered reactive mineralogical paragenesis. Thus, the choice of geochemical model should be made with due regard for the desired objectives. This work will assist the mine operator by providing a tool capable of assessing both the short- and long-term environmental footprints of the ISR production operation conditions and of identifying the best remediation strategy.

Modeling uranium and 226Ra mobility during and after an acidic in situ recovery test (Dulaan Uul, Mongolia).

This article presents the results of groundwater monitoring over a period of six years and the interpretation of these results by a reactive transport model, following an In Situ Recovery (ISR) test on the Dulaan Uul uranium deposit in Mongolia. An environmental monitoring survey was set up using 17 piezometers, from which it has been possible to describe the changes in the water composition before, during and after the ISR test. The water quality before the start of mining activities rendered it unfit for human consumption. During and after the test, a descent of the saline plume was observed, resulting in a dilution of the injection solutions. After a rapid decrease to pH = 1.13 during the production phase of the ISR test, the pH stabilized at around 4 in the production area and 5.5 below the production cell one year after the end of the test. Uranium and radium were being naturally attenuated. Uranium returned to background concentrations (0.3 mg/L) after two years and the measured 226Ra concentrations represent no more than 10% of the expected concentrations during production (75 Bq/L). The modeling of the contaminants of concern mobility, namely pH and concentrations of sulfate, uranium and 226Ra, is based on several key complementary mechanisms: density flow, cation exchange with clay minerals and co-precipitation of 226Ra in the barite. The modeling results show that the observed plume descent and sulfate dilution can only be predicted if consideration of a high-density flow is included. Similarly, the changes in pH and 226Ra concentration are only correctly predicted when the cationic exchanges with the clays and the co-precipitation reaction within the barite using the solid solution theory are integrated into the models. Finally, the proper representation of the changes in water composition at the scale of the test requires the use of a sufficiently fine mesh (1 m × 1 m cell) to take into account the spatial variability of hydrogeological (permeability distribution in particular) and geological (reduced, oxidized and mineralized facies distributions) parameters.