Optimizing Carbon Capture and Storage (CCS) Design Using Multi-objective Optimization and Dynamic IPR-OPR Nodal Analysis

Summary This study presents an integrated optimization framework for offshore Carbon Capture and Storage (CCS) system design, combining multi-objective optimization (MOO) and dynamic inflow performance relationship (IPR)–outflow performance relationship (OPR) nodal analysis. The methodology systematically analyzes facility specifications and operating conditions to balance CO2 storage capacity, safety, and economic feasibility. MOO is employed to identify Pareto-optimal solutions for key transport and injection parameters, including pipeline diameter, well tubing size, and injection pressures. These solutions are further refined using dynamic IPR-OPR nodal analysis, which evaluates real-time pressure and temperature variations during CO2 injection. A coupled surface–subsurface simulation using CMG’s CoFlow software is utilized to enhance the Front End Engineering Design (FEED) process. Results demonstrate that optimizing discharge pressure, pipeline diameter, and wellhead temperature improves injection stability while maintaining geomechanical integrity. The proposed framework ensures operational reliability and enables decision-makers to design CCS infrastructure with greater confidence. Future research will focus on integrating AI-driven predictive modeling and expanding field-scale validation to further enhance CCS system optimization. This methodology provides a structured, data-driven approach for advancing CCS projects, ensuring efficient CO2 transport and storage while mitigating operational risks.