Injection well site optimization of carbon geological sequestration based on dynamic programming

Geological storage of carbon dioxide (CO₂) is one of the most effective methods for reducing carbon emissions and mitigating the greenhouse effect, critical challenges in combating climate change. This earth science technology involves capturing CO₂ emissions from industrial processes and safely injecting them into deep underground geological formations for long-term storage. A key factor for its success is selecting appropriate injection well locations, which play a crucial role in determining storage capacity and the overall effectiveness of the geological storage system. Choosing injection well locations is a complex optimization problem; it involves assessing geological conditions at the target site and addressing technical and logistical constraints of well construction. Key geological factors include stratigraphic traps that prevent CO₂ from migrating upward, potential spill paths that could allow CO₂ leakage, and spill points where CO₂ could escape from the reservoir. Poorly chosen injection sites can reduce storage capacity, increase risks of CO₂ leakage, or lead to system failure. Therefore, optimizing well placement is critical for enhancing the viability and scalability of CO₂ geological storage. This study developed a comprehensive CO₂ geological storage model that integrates geometric methods and seepage theory to estimate the storage capacity of geological formations; it evaluates essential geological conditions, including stratigraphic traps, spill paths, and spill points. Building upon this model, the optimization problem of well placement was transformed into a dynamic programming framework. Dynamic programming, a mathematical optimization approach, is well-suited for solving problems that can be broken down into smaller subproblems with overlapping solutions. In this context, the optimization process defines an optimal substructure and a state transition equation to determine the best injection well location that maximizes CO₂ storage capacity while minimizing potential risks. The dynamic programming method was applied to the Utsira formation, a prominent saline aquifer in the North Sea near Norway, widely studied as a potential site for large-scale CO₂ storage. Using the model, the storage capacity of the Utsira formation was estimated, and optimal locations were identified. This approach not only maximized storage capacity but also offered practical insights into the technical and logistical aspects of well placement. The study underscores the importance of integrating advanced optimization techniques with geological models to address CO₂ storage challenges. The methodology offers a systematic approach for selecting injection well locations and serves as a valuable tool for developing efficient, secure CO₂ storage systems worldwide. As the demand for sustainable carbon management solutions grows, this work contributes valuable theoretical and practical guidance to the emerging field of CO₂ geological storage.