Foam-Assisted-Water-Alternating-Gas (FAWAG) injection has been proposed to improve the inherent unfavorable mobility ratio of gas and liquid in WAG process. The foam reduces gravity override and gas channeling as to improve volumetric sweep efficiency and thus oil recovery. There are still a lot of uncertainties yet to be understood in foam dynamics, surfactant adsorption, and foam stability when contacting oil, which impact the actual foam propagation into the reservoir. Although some insights are gained from laboratory and field experiments, the performance, and design of the injection strategy and facilities as part of the field development of FAWAG is not trivial and field data is sparse.
Extensive laboratory experiments and simulation studies are necessary to de-risk enhanced oil recovery (EOR) application, but these processes are time consuming and expensive. For this reason, a screening study is normally conducted to increase the possibility of selecting high potential candidates prior to embarking on the detailed feasibility studies. Unfortunately for FAWAG, the screening criteria are not readily established nor commonly available in commercial screening tools unlike for other matured EOR methods, largely contributed by the limited database on FAWAG field implementations worldwide.
This paper presents a robust FAWAG screening tool which accounts for important reservoir properties, uncertainties in foam model parameters, as well as various reservoir conditions of oil and gas production and injection plans. The FAWAG process is modelled from the assumption of local equilibrium of foam creation and coalescence using an Implicit Texture model. Relevant foam scan experiments/steady state coreflood data were analyzed to derive parameters that characterize foam dynamics.
The sensitivity study in this paper ranks and identifies the main risks and opportunities for the FAWAG process, quantifies the reliability of the model and increases the understanding of the effective dynamic behaviour. The sensitivity study was the basis for the development and validation of a proxy model by design of experiments. The screening tool employs this proxy model to generate immediate screening results without the need to run additional simulations. The screening tool was further validated with upscaled experimental data. A set of prediction results on the range of oil recovery for numerous plausible field scenarios was established; these screening criteria will be used as the basis for high-level decision making.