The study focuses on evaluating the efficiency of digital twins of oil treatment units (OTU) as a tool for reducing water consumption and industrial effluents under freshwater scarcity conditions caused by a high proportion of associated formation water and the resource load of upstream operations. The problem is justified by the scale of the industry's water turnover and the limitations of traditional reactive control, which lead to suboptimal reagent consumption, excessive energy use, and the formation of effluents requiring costly post-treatment for reuse. As a solution, a digital twin is proposed as a dynamic mathematical model integrated with the process control system (PCS) for real-time data flow analysis, predictive forecasting, and issuance of control recommendations on separation modes and reagent dosing. The case study focuses on a typical OTU with a capacity of 4.5 million tons per year in a water-scarce region, featuring a process scheme of preliminary settling, three-phase separators, electro-dehydrators, and a demulsifier dosing unit; retrospective and operational data over 36 months were used. The model relied on an interdisciplinary descriptive core of mass and heat transfer and more than 200 online process parameters, including flow rate, water cut, temperature, pressure, reagent dosage, and quality indicators of separated water. Ensemble gradient boosting algorithms were applied for calibration and adaptation, achieving a root mean square forecast error of no more than 3.5% over the validation period. In industrial trials in “advisor” mode, the digital twin dynamically adjusted temperature and demulsifier dosage, maintaining residual oil content in water below 40 mg/L, which enabled expansion of internal water recirculation. Quantitative improvements achieved include: a 41.72% reduction in freshwater consumption, a 279.64% increase in reused water volume, a 34.22% reduction in effluents, and a decrease in specific water consumption from 0.148 to 0.086 m³/t (−41.89%). Correlation analysis revealed key control levers: water cut (+0.915), temperature (−0.683), demulsifier dosage (−0.541), and a weak effect of pressure (−0.112). The economic and environmental effects were confirmed by significant reductions in costs for water intake, treatment, and disposal, as well as a decrease in indirect CO₂ emissions by 2150.6 tons per year due to energy savings. The conclusions highlight the transition to proactive multi-criteria optimization and the closure of water cycles at the OTU while maintaining product quality and reducing environmental impact. The technology is scalable and promising for integration into a unified digital water circuit of an oil field together with reservoir pressure maintenance and water treatment models.