Full-field Proxy Development Using Neural Operator-based Machine Learning Approach for Reservoir Simulation

Summary A workflow combining a GPU-based full physics reservoir simulator with a FNO-based machine learning model on the cloud performed 50 times faster. ML model demonstrated reasonable agreement with HPC full physics simulation in both the well placement optimization and scenarios with geological uncertainties. The developed workflow provides a foundation for building advanced subsurface applications aided by machine learning and AI approaches.