Optimization of coupled carbon dioxide sequestration and enhanced oil recovery

Sequestration of carbon dioxide (CO2) in depleted or partially depleted oil reservoirs is a plausible option to reduce CO2 emissions into the atmosphere. Carbon dioxide has been used as the injection fluid in Enhanced Oil Recovery (EOR) operations. The goal of such projects is to improve the profitability by maximizing the oil production (to increase the revenue) and minimizing the CO2 injection (to decrease the costs). However, in sequestration projects, subsurface storage of the injected CO2 needs to be maximized.;The objective of this study is to develop a framework to co-optimize oil extraction and CO2 sequestration. In the proposed framework, the net present value (NPV) of the project is selected as the optimization objective function. In my work, factors such as the cost of capturing the produced CO2, CO2 transportation and recycling are taken into account. A number of simulations are studied to achieve comprehensive understanding of the financial performance of the coupled CO2 sequestration and EOR projects. The simulations show that the projects would be unprofitable for immiscible cases when using current typical costs of CO2 capture from power plants unless there is some form of credit for storage. In contrast, in miscible cases, the projects may be profitable even without considering any CO2 credits, and their profitability is further enhanced with possible carbon credits.;With the advances in smart well technology, maximizing net present value of oil recovery and CO2 storage can be achieved substantially by managing the operation intelligently in a closed-loop optimization framework. Closed-loop optimization consists of two parts: data assimilation and NPV optimization. Data assimilation adjusts the reservoir geological model to honor the production data and reduces the uncertainty of the estimate of reservoir geological properties. NPV optimization modifies the operational strategy based on the updated geological model.;The Ensemble-based Optimization (EnOpt) algorithm has been selected as the optimization algorithm and the well-injection patterns and rates as the controlling variables. EnOpt can be easily combined with the ensemble-based data-assimilation methods to form an ensemble-based closed-loop optimization framework. The production rate data are assimilated in real-time by an ensemble Kalman filter for characterization of the reservoir. Simultaneously, EnOpt optimizes the expectation of net present value based on the up-to-date reservoir models. Several cases are used to demonstrate the applicability of the developed technique. Our results show that the oil recovery and the NPV can be increased significantly. The proposed methodology is fairly robust, does not require adjoint programming and can be readily used with any reservoir simulator. The workflow presented in this work can be used to design and co-optimize the coupled CO2 sequestration and EOR projects.