Multi-objective Optimization of WAG Injection in Fractured Carbonate Reservoirs under Geological Uncertainty

Water-Alternating-Gas injection could be an efficient way to improve recovery factors in fractured carbonate reservoirs. However, the complex geology of fractured carbonate reservoirs and the complexity of the WAG process itself create uncertainties when predicting the efficiency of WAG. It is hence challenging to identify engineering controls that allow us to optimize recovery during WAG while accounting for geological uncertainties. To overcome this challenge, we use Latin Hypercube and Box-Behnken experimental designs to set up multiple screened simulations of WAG injection in a fractured carbonate reservoir model that contains multiple geological uncertainties. From these simulations we construct surrogate response surfaces using polynomial chaos expansion. The response surface allow us to predict recovery factor, gas cumulative production, water cumulative production and NPV for different geological scenarios and engineering controls. Finally, we run the Non-dominated Sorting Genetic Algorithm-II on the response surface to obtain an optimal engineering design that not only accounts for geological uncertainties but also competing objectives. Our results show that only such a comprehensive simulation approach, which nevertheless can still be carried out on modern desktop PCs, is capably of analysing the complex interactions between geological and physical uncertainties and engineering controls to identify the most suitable WAG implementation.