This article presents research on hydrolithospheric processes using groundwater inflow testing results. The study develops a mathematical model of hydrolithospheric processes that accounts for the skin effect, a phenomenon influencing groundwater flow. The methodology involves using groundwater inflow testing data to determine parameters of approximating models that consider skin effects. The study also addresses the challenges of modeling hydrodynamic processes with random factors and develops a statistical analysis method for well monitoring data. An algorithm for studying these processes is created, and a procedure for selecting the optimal number of production wells is developed based on the results of groundwater inflow testing. The research aims to determine the prospects for developing and utilizing new aquifers. The study analyzes the impact of random factors on hydrogeological processes and develops a mathematical model of aquifers that accounts for these factors. The model is verified using field experiments and shows good agreement with real-world data. The research also explores the problems of modeling hydrolithospheric processes under random influences and develops methods for managing these processes. The study finds that the optimal number of production wells for maximizing profit is six, as increasing the number beyond this leads to no increase in profit and may even decrease it. The research highlights the importance of considering environmental factors and the need for careful planning to ensure the sustainability of groundwater resources. The study contributes to the development of mathematical models for hydrogeological entities and provides insights into the optimization of production well numbers for efficient and environmentally safe mineral water extraction.This article presents research on hydrolithospheric processes using groundwater inflow testing results. The study develops a mathematical model of hydrolithospheric processes that accounts for the skin effect, a phenomenon influencing groundwater flow. The methodology involves using groundwater inflow testing data to determine parameters of approximating models that consider skin effects. The study also addresses the challenges of modeling hydrodynamic processes with random factors and develops a statistical analysis method for well monitoring data. An algorithm for studying these processes is created, and a procedure for selecting the optimal number of production wells is developed based on the results of groundwater inflow testing. The research aims to determine the prospects for developing and utilizing new aquifers. The study analyzes the impact of random factors on hydrogeological processes and develops a mathematical model of aquifers that accounts for these factors. The model is verified using field experiments and shows good agreement with real-world data. The research also explores the problems of modeling hydrolithospheric processes under random influences and develops methods for managing these processes. The study finds that the optimal number of production wells for maximizing profit is six, as increasing the number beyond this leads to no increase in profit and may even decrease it. The research highlights the importance of considering environmental factors and the need for careful planning to ensure the sustainability of groundwater resources. The study contributes to the development of mathematical models for hydrogeological entities and provides insights into the optimization of production well numbers for efficient and environmentally safe mineral water extraction.