Optimizing Transportation and Storage Design for CO₂ Geological Sequestration Using Multiobjective Optimization and Nodal Analysis: A Case Study From the Gunsan Basin, South Korea

This study presents a front-end engineering design (FEED) methodology for an integrated CO₂ transport–injection–storage system, utilizing multiobjective optimization (MOO) and nodal analysis. The methodology’s performance is validated through a carbon capture and storage (CCS) demonstration project in the Gunsan Basin (GB), South Korea. This approach employs the dynamic inflow performance relationship (IPR)−outflow performance relationship (OPR) technique, applying it to the FEED of the CO₂ transport–injection–storage system to enable CO₂ injection into a saline aquifer via a single injection well connected through an onshore hub terminal and a subsea pipeline. By adjusting decision variables (CO₂ discharge pressure at the onshore hub terminal, pipeline diameter, tubing diameter, and CO₂ temperature at the wellhead), three objectives (CO₂ storage capacity, safety, and economic benefit) are optimized through MOO, identifying the Pareto-optimal front (POF) among objective functions. These trade-off solutions provide reliable ranges for the four decision variables used in the nodal analysis, which considers real-time pressure and temperature variations in the system during CO₂ injection, along with the associated facility qualifications and operating conditions. This analysis determines the IPR−OPR at the bottom of the injection well and the corresponding pressure–flowrate, defining the practical FEED scope for the integrated CO₂ transport–injection–storage system. By integrating optimal solutions from both MOO and nodal analysis, the study identifies the final nondominated solutions for efficient and stable CO₂ geological storage. The proposed methodology offers decision-makers robust scenarios for facility qualifications and operating conditions, considering CO₂ storage capacity, safety, and economic efficiency at the FEED stage of a CCS demonstration project.