Maximizing Production and Storage in CO2 Injection Supported by a Physics Embedded Machine Learning

References

1. Calad, C., Gutiérrez, F., Pastor, P., Sarma, P., [2020] - Combining Machine Learning with Traditional Reservoir Physics for Predictive Modeling and Optimization of a Large Mature Waterflood Projectin the Gulf of San Jorge Basin in Argentina. SPE-199048-MS, presented at SPE Latin America and Caribbean Petroleum Engineering Conference, Bogota, Colombia, July 2020.
   [Google Scholar]
2. Sarma, P., Kyriacou, S., Henning, M., Orland, P., Thakur, G., Sloss, D., [2017] – Redistribution of Steam Injection in Heavy Oil Reservoir Management to Improve EOR Economics, Powered by a Unique Integration of Reservoir Physics and Machine Learning. SPE-185507-MS, presented at SPE Latin America and Caribbean Petroleum Engineering Conference, Buenos Aires, Argentina, May 2017.
   [Google Scholar]
3. Todd, M.R., and W.J.Longstaff. “The Development, Testing, and Application Of a Numerical Simulator for Predicting Miscible Flood Performance.” J Pet Technol24 (1972): 874–882.
   [Google Scholar]