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Abstract As Malaysia pushes toward its national net-zero emissions goal, carbon capture and storage (CCS) is emerging as a key decarbonization strategy for the oil and gas sector. Depleted hydrocarbon reservoirs, with their well-understood geology and existing infrastructure, offer promising sites for permanent CO2 storage. This study introduces a decision-support framework designed to optimize CO2 injection site selection across Malaysian reservoirs, aiming to maximize storage potential while maintaining pressure safety and reducing logistical hurdles. The framework is specifically tailored for early-stage CCS project screening and planning. We developed a mixed-integer linear programming (MILP) model to identify the best reservoirs for CO2 injection. Each candidate reservoir was evaluated based on storage capacity, distance to CO2 compression platforms, and pressure response under injection. A simplified gas tank model estimates pressure buildup from CO2 injection, with constraints to avoid exceeding fracture pressure or operational safety limits. The model balances CO2 storage volume against transport costs linked to source-to-sink distance, maximizing net storage utility. Additionally, we also explored and compared alternative nature-inspired optimization algorithms as part of the study. When applied to real-world Malaysian reservoir data, the framework revealed that pressure constraints and location-based costs heavily influence injection site selection. Some high-capacity reservoirs were deprioritized due to pressure risks or unfavorable distances. The MILP model allows rapid scenario testing and sensitivity analysis, highlighting the need for early pressure screening to prevent costly CO2 allocation mistakes in later project stages. This study presents a practical optimization approach for Malaysia’s regional CCS planning, supporting industry efforts to achieve net-zero targets. By integrating reservoir capacity, geographic logistics, and pressure safety constraints, the framework offers a scalable and efficient alternative to traditional screening methods. The inclusion of a gas-law-based pressure model at the pre-screening stage ensures realistic and safe site evaluations without extensive simulations.