Robust Value Quantification of Enhanced Oil Recovery Methods Using Ensemble-Based Optimization

Abstract

Summary Over the last decades, the development of different oil reservoirs with gas or chemical enhanced oil recovery (EOR) methods have been studied, and the EOR effects of the recovery methods are found to be sensitive to fluid and rock properties in the reservoirs. The use of a single reservoir model with the assumption of known reservoir parameters is not enough to guarantee an accurate prediction of EOR effects. The best decision related to the injection strategies of EOR methods can be appropriately found using an optimization setup that accounts for the uncertainty quantification in the reservoir. In this paper, we present mathematical tools for optimizing and ranking the value of the commonly used EOR methods. The methodology is demonstrated with Smartwater, carbon dioxide (CO2), and polymer EOR methods on synthetic 2D and 3D oil reservoirs. To capture the uncertainties in the reservoirs, we use an ensemble of geological realizations obtained by engineering upscaling of the initial model. The usefulness of this study is to improve the understanding of the actual benefit of EOR methods and to provide a methodology that quickly allows users to appropriately predict EOR injection strategies that maximize the annually discounted economic values of the injected and production data. The control variables of optimization problems include EOR gas rate or chemical concentration, water rates, oil rate, or bottomhole pressures. An ensemble-based optimization method with covariance adaptation is used to solve the optimization problem. For the different reservoirs considered, we find the optimal well controls for EOR methods. A comparative study of the economic benefits of the optimal solutions of EOR methods using optimized waterflooding as a reference point is presented. CO2 is found to rank high compared with other EOR methods in both cases. Finally, we investigate the effect of different injection costs of CO2 on the optimization results of CO2 EOR methods for the 3D reservoir field.