The conventional approach used to account for geomechanical effects when modeling steam injection operations is based on dilation/compaction tables. These tables are mostly empirical and are usually employed as a history-matching parameter to calibrate simulation models to observed injection/production rates and pressures. In this study, we use a more rigorous workflow that couples a geomechanical simulator to more accurately model the changes in permeability and pore volume that occur during high-pressure steam injection.
This paper demonstrates a new approach for incorporating and modeling the geomechanical effects observed while injecting steam for heavy oil recovery, specifically during SAGD (Steam-Assisted Gravity Drainage) operations. This workflow does not need an explicit, empirical table relating pressure to permeability and porosity; instead it uses a mechanical simulator to determine the evolution of the reservoir's stresses and strains to calculate a new property distribution that is updated in the reservoir simulator to account for dilation and compaction phenomena.
To model the complex thermo-poro-mechanical coupling that prevails during thermal stimulation processes, we use a numerical workflow that integrates finite-difference reservoir and finite-element geomechanical simulators. This coupling technique enables a more rigorous modeling of the fluid and heat flows while predicting their influence on the reservoir deformation and stresses. Consequently, a direct link between stress/strain and porosity/permeability can be used to model the geomechanical changes that occur in the reservoir during high-pressure steam injection. We also compare the predicted behavior of SAGD models using the coupled approach against the use of empirical dilation/compaction pressure tables.
A comparison of the simulation results obtained using the proposed coupled approach versus those obtained using empirical tables (uncoupled) showed significant differences in steam injectivity and distribution as well as oil and water production.