Qing Li

Integrated energy companies operate vast and complex supply chains encompassing exploration, refining, distribution, logistics, storage, and trading. These supply chains are significant contributors to global carbon dioxide emissions. In 2023, oil and gas production and transport generated approximately 5.81 billion tons of CO₂-equivalent emissions. In light of increasingly stringent carbon neutrality commitments, optimizing these networks more than operational efficiency—it calls for intelligent, low-carbon strategies grounded in advanced optimization, intelligent planning, and system-level coordination. This study presents a comprehensive supply chain optimization framework tailored for large-scale petroleum enterprises, with a focus on final petrochemical product planning. The framework spans the entire supply chain and integrates multiple geographically distributed refineries processing crude from diverse oil fields and transfer to different markets. A mathematical programming model is developed to maximize system-wide economic returns while explicitly incorporating carbon emissions as operational constraints. To assess the robustness and flexibility of the proposed model, sensitivity analysis and Monte Carlo simulations are conducted, quantifying the impact of carbon constraints on supply chain decisions. Results indicate that different final product types and amount combinations lead to varying benefits while simultaneously resulting in distinct emissions. The carbon emissions resulting from the production of chemical products, such as ethylene, are estimated 1.3 to 1.9 times higher than those from producing refinery products like gasoline and diesel. Under dynamic market conditions, by adjusting crude oil allocation, optimizing product yields, and enhancing inter-refinery resource coordination, it is possible to reduce emissions without incurring profit loss. When maintaining constant crude throughput and overall supply chain capacity, such internal optimizations can achieve carbon reductions ranging from 3.7% to 7.8%. This work highlights the practical potential of integrating digital tools and mathematical planning into the operational core of oil supply chains, offering a viable pathway for traditional energy producers to advance toward global decarbonization targets while sustaining economic competitiveness.