In recent years, much effort has been spent in integration of the hydrocarbon E&P business processes. The new challenge lies in the use of the generated data for decision-making. In particular, in hydrocarbon assets, where large uncertainties occur, it is important to include the formal quantification of these uncertainties in the integrated workflow and allow for a decision framework based on a full characterization of these uncertainties.
For quantification of uncertainties two classes of approach are currently in use –the probabilistic approach based on the description of a stochastic model for capturing all uncertainty and the scenario approach based on a definition of a number of conceptually different models expressing the uncertainty. Some hybrid versions of the approaches exist as well. The pros and cons of these approaches are discussed. Following this, an extended statistical framework is presented in which the previous approaches to subsurface uncertainty modelling have been combined. The framework is not limited to subsurface uncertainties, but can also be applied to the other uncertainties and decisions in the asset model. In the integrated framework several scenarios may be identified for the static earth model, the dynamic earth model, the drilling model, the surface facilities model and the economic model. A scenario tree can represent the combination of all these scenarios.
Within each scenario a stochastic model can be applied to capture the within-scenario uncertainty. Calculation rules for the integration of the stochastic and scenario uncertainties are presented. Finally, decision rules are given that allow for decision-making based on the full uncertainty span in the integrated asset framework.