Abstract: The promotion of carbon capture, utilization and storage (CCUS) technologies is of great significance for mitigating global warming. As a fundamental component of CCUS technologies, source-sink matching can effectively identify the optimal carbon dioxide transportation route and improve the efficiency and economic performance of CCUS systems. Aiming to address the challenges of high economic cost and substantial technical risk facing offshore CCUS technologies, this study conducted research on offshore CCUS source-sink matching modeling and economic evaluation. Based on the mixed integer linear programming method, a multi-period source-sink matching model for offshore CO₂ storage and utilization was established. With the objective of minimizing the overall process cost, a cost model for parallel ship-pipeline transportation specifically designed for offshore scenarios and a levelized cost function for offshore storage were developed within this framework. CO2 utilization revenues were directly incorporated into the objective function, realizing the dual driving mechanism of "emission reduction and efficiency improvement". A hypothetical planning area was selected as a case study for a 20-year multi-period dynamic planning analysis. The results of economic evaluation showed that the capture cost accounted for the largest proportion of the total cost of the offshore CCUS process, at approximately 83%, while transportation cost, utilization cost and storage cost accounted for approximately 8.6%, 4.3% and 2.7%, respectively. Sensitivity analysis indicated that the system cost was the most sensitive to capture efficiency, followed by transportation distance, and the improvement of capture efficiency was significantly constrained by physical limitations such as space, load and energy supply in the offshore platform environment. Under multi-period conditions, the model exhibited strong robustness in source-sink matching. The scalable quantitative analysis tool and decision support framework developed in this study can provide a scientific basis for cluster planning, technical route selection and large-scale application of offshore CCUS projects.