Fast screening of geostatistical realizations for SAGD reservoir simulation

Abstract Identifying the range of dynamic reservoir performance responses requires conducting numerical flow modeling on geostatistical realizations. The extent of steam-assisted gravity drainage (SAGD) models, multiple horizontal well-pairs, and simultaneous flow of heat and fluids make a single SAGD simulation computationally burdensome. Therefore, it is impractical to simulate all hundreds of SAGD realizations. We have introduced a static measure based on average harmonic permeability called the ( k H ) A method to help rank realizations for their SAGD performance. The high correlation between the ( k H ) A method and the thermal simulation results shows that the ( k H ) A method is a useful ranking tool and helps to select a few realizations exhibiting distinct responses for detailed flow modeling. By testing the method against several datasets, it is shown to be easy to apply, fast to run, reliable and robust compared to other methods.