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Skip to Search Results- 2Ensemble Kalman Filter
- 2History Matching
- 1Artificial Neural Networks
- 1Characterisation
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Spring 2017
In reservoir simulation studies, history matching is extensively used for uncertainty reduction and reservoir management. History matching using Ensemble Kalman Filter (EnKF) is a promising approach due to its non-iterative nature and ability to assimilate a large number of model parameters....
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Re-Sampling the Ensemble Kalman Filter for Improved History Matching and Characterizations of Non-Gaussian and Non-Linear Reservoir Models
DownloadSpring 2015
Reservoir simulation models play an important role in the production forecasting and field development planning. To enhance their predictive capabilities and capture the uncertainties in model parameters, stochastic reservoir models should be calibrated to both geologic and flow observations. The...