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Real-time oil Reservoir Characterization by Assimilation of Production Data
, Ph.D. Dissertation Sharif University of Technology ; Pishvaie, Mahmoud Reza (Supervisor) ; Bozorgmehry Boozarjomehry, Ramin (Supervisor)
Abstract
Hydrocarbon reservoirs development and management is based on their dynamic models. To encounter various types of error during model building, model parameters are adjusted to produce reservoir historical data by assimilation (history matching) of reservoir production or 4D seismic data. Among the existing sequential methods for automatic history matching, ensemble Kalman filter and its variants have displayed promising results. The innovations of this thesis for ensemble Kalman filter (EnKF) are presented into three major orients; these includes adaptive localization/regularization, characterization of original PUNQ test model and characterization of channelized reservoir.
To mitigate...
To mitigate...
Intelligent and Sequential Reservoir Model Updating and Uncertainty Assessment during EOR Process
, Ph.D. Dissertation Sharif University of Technology ; Pishvaie, Mahmoud Reza (Supervisor) ; Bozorgmehry Boozarjomehry, Ramin (Supervisor)
Abstract
Hydrocarbon reservoir management and development as well as planning of enhanced oil recovery (EOR) processes are based on the reservoir dynamic model. Thus, successful implementation of EOR scenarios greatly depends on the quality of the dynamic model and accuracy of the associated parameters in order to correctly describe fluid flow through porous media. First, a dynamic model is constructed based on the prior knowledge. However, because of the various types of error during model building, the prior model is not so accurate and perfect. Accordingly, new observation data, such as production and 4D seismic data, are utilized to calibrate the prior model and characterize the reservoir under a...