CCS Reservoir Simulation using Graph Neural Networks: Building ML solutions for efficient CO2 subsurface modelling

Reducing cost and improving computability of reservoir simulation is an important goal in the process of enabling CCS (Carbon Capture \& Storage) as a large-scale technology for mitigating CO2 emissions. In terms of computation time data-driven approaches have potential to outweigh the performance of numerical reservoir simulators, learning...

Who Cares About Fairness: How Background Influences the Way Practitioners Consider Machine Learning Harms

The increasing dangers of unfairness in machine learning (ML) are becoming a frequent subject of discussion, both, in academia and popular media. Recent literature focused on introducing and assessing algorithmic solutions to bias in ML. However, there is a disconnect between these solutions and practitioners' needs. By interviewing 30 ML...