Geostatistical Modeling and Numerical Simulation of the SAGD Process
Xia BaoLogin to View Article
Overlying top water and gas thief zones have a detrimental effect on the Steam-Assisted Gravity Drainage (SAGD) recovery process since steam penetrates into these zones which results in great heat loss. Due to the presence of these top thief zones, recovering bitumen by the SAGD process has become challenging in the Surmont lease of an Athabasca oil sand reservoir.
Previous numerical simulations, laboratory experiments and field production data have demonstrated that oil production and steam-oil ratios tend to decrease as the depletion of top gas continues; also, heat loss to the overlying thief zone will be more significant when a top water zone is present. However, an optimal operating strategy for the full field scale SAGD process with both top gas and top water remains uncertain.
The objective of this paper is to construct a 3D geostatistical model for a Surmont pilot and implement sensitivity study in SAGD simulation aiming at investigating the impact of the top thief zones on bitumen recovery. The major steps involved in the 3D geostatistical modeling process consist of structural, facies and property modeling and uncertainty analysis. Facies-based log-derived porosity, permeability and water saturation are populated into a grid block by Sequential Gaussian Simulation (SGS) in the petrophysical modeling process. Then a static model is further downscaled to finer simulation grids, and a submodel for each single well pair is extracted for the purpose of history match in the STARSTM simulator.
Reasonable history match of oil and water rates has been achieved by calibrating this static model with field production data. The steam chamber pressure and temperature profiles from the numerical model have been conformed to the field data from the observation wells. Sensitivity analysis of the thief zones pressure, thickness and area extension has been conducted to simulate the impact of the top thief zones. Optimization of cumulative steam oil ratios (cSOR) and recovery factors by varying the steam trap control and injection pressure with the top thief zones has been investigated in great detail. Finally, integrated optimization strategies have been developed and tested on a full field-based heterogeneous simulation model.