In light of the urgent need to mitigate the atmospheric consequences of carbon dioxide (CO2) emissions while safeguarding the planet and its inhabitants, carbon capture, utilization, and storage (CCUS) emerges as a viable solution. The co-optimization of CO2 sequestration and CO2-enhanced oil recovery (CO2-EOR) has become a decisive strategy to simultaneously enhance oil recovery and long-term CO2 trapping in depleted oil reservoirs.
This study presents efficient techniques for predicting oil recovery and the CO2 solubility trapping across over 800 experimental designs using Computer Modelling Optimization and Sensitivity Tool- Artificial Intelligence (CMOST-AI).
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