Improved Production Forecasts and History Matching Using Approximate Fluid-Flow Simulators
Wednesday, January 9, 2002 - 9:30am - 10:30am
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 computer demanding to activate. In order to assess the forecasts with uncertainties approximate fluid flow simulator based on upscaling are frequently used. This introduces biases and other error structures in the production forecasts, however. A production forecasting model that accounts for these biases and error structures is defined, and estimators for the model parameters are specified. The socalled '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. The study is a part of the URE - Uncertainty in Reservoir Evaluation - activity at NTNU.