AI-Driven Polymer Injection Optimization for Supporting Sustainability of Water Management

Energy-related industries are working hard to ensure that their operations are sustainable and to reduce their carbon footprint. Optimizing field operations to boost sustainability while maintaining output levels is one of these projects. The fourth industrial revolution is having a significant influence on the oil and gas industry, which also makes it feasible to more thoroughly examine possibilities for lowering carbon footprints. With the aid of contemporary production logging technology, the formation may be accurately described, and its production behavior quantified. Technologies that use polymer injection may significantly lower water cut, which helps lower carbon emissions and achieve net-zero objectives. We evaluated the effects of various polymer injection strategies on the Volve field using a variety of production and injection wells in order to predict the influence of injecting polymers on the fluid production rates. Lowering the reservoir’s water production rates is made possible by the injection of polymers. Consequently, managing produced water and water injection results in a reduced carbon footprint. Integrating properly log interpreted polymer amounts to maximize recovery is a crucial component of optimization. The total carbon footprint was determined using a probability-likelihood framework following the evaluation of many scenarios to determine their overall impact on carbon emissions. Although there are many factors that determine the optimal injection strategy, polymers have demonstrated the ability to significantly reduce overall carbon footprints while increasing hydrocarbon output.