Data-driven reservoir modeling

Data-driven reservoir modeling

Staff photo

PhD Candidate Cuthbert Shang Wui NG

Main Supervisor Ashkan Jahanbani Ghahfarokhi

Sponsor: NTNU 

Numerical reservoir simulations are widely applied to assist in decision-making related to reservoir management. However, more accurate models will need higher computation time. To mitigate this, a smart proxy model (SPM) has been developed. SPM applies a combination of advanced methods, such as optimization, statistics and data-driven techniques, which aim at significantly decreasing the run-time in any reservoir simulation task. The objective of this project is to improve the understanding of data-driven modelling and applying smart proxy modelling in reservoir simulations. The approach combines numerical simulations and data-driven techniques. Models are updated in realtime, creating realistic opportunities for real-time reservoir management in smart fields with uncertainty analysis.

BRU21 Conference 2022