Hybrid Machine Learning and Meta-Heuristic Optimization for Well Placement and Operating Conditions in Carbonate Rocks: Low-Salinity Water Injection
This study proposes a computationally efficient data-driven framework that couples artificial neural network surrogate models with multi-objective meta-heuristic algorithms to simultaneously optimize well placement and operating conditions for low-salinity water injection in carbonate reservoirs, achieving significant increases in net present value and oil recovery while reducing water production.