Large amounts of subsurface data are available, but current workflows and programs for subsurface understanding are not optimal, resulting in inadequate utilization of datasets.
To build a Sustainable Subsurface Value Chain and make more informed decisions, digitalization and ML are necessary to integrate the knowledge and competence building from different WPs.
A digital infrastructure, Subsurface Knowledge Cloud (SKC), will be established to provide readily usable data and high-performance computing power and visualization tools.
- How can we effectively utilize all available data from available data sources across multiple sites?
- How can we develop automated workflows allowing for more robust forecasts from subsurface models with feasible computational cost?
- How can important uncertainties be accounted for quantifying uncertainties in model forecasts?
- How can ML extract relevant information for decision-making and quantifying data value?