Abstract
Summary Forecasts of production with associated uncertainties must be based on a stochastic model of the reservoir variables and a fluid-flow simulator. The latter is usually very computationally demanding to activate. Approximate fluid-flow simulators based on upscaling of the reservoir variables are frequently used to assess the forecasts with uncertainties. The upscaling introduces biases and changes the error structures in the production forecasts, however. A production forecast model that accounts for these biases and changed error structures is defined, and estimators for the model parameters are specified. Forecasts both at the appraisal stage and the production stage including history matching are discussed. The so-called "ranking problem" is formalized and solved as a part of the study. The results are demonstrated and verified on a large case study inspired by the Troll field in the North Sea.
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