Data-driven models are an attractive alternative to reservoir simulation in workflows where full field-scale simulations may be computationally prohibitive [3,4]. One example is the forecasting and schedule optimization of waterflooding scenarios, where numerous function evaluations that correspond...

Optimizing placement and trajectory of wells is a computationally demanding, and hence time-consuming task due to the high number of simulations typically required to achieve a local optimum. In this work, we combine three remedies for speeding up the workflow; firstly, we employ a flow-diagnostics...

Ensembles of geomodels provide an opportunity to investigate the range of parameters and possible operational outcomes for a reservoir of interest. Full-featured dynamic modelling of all ensemble members is often computationally unfeasible, however some form of dynamic modelling, allowing us to...

The Monte Carlo (MC) method is an appealing candidate for uncertainty quantification in reservoir simulation for three reasons: (i) It is the preferred approach for systematic reduction in variance for cases with high-dimensional uncertainty with a strongly nonlinear effect (robustness); (ii) it is...