In gas-injection enhanced oil recovery (EOR), gas can be injected alone, or in alternating slugs with water injection in a Water-Alternating-Gas process. Oil recovery depends on gas sweep efficiency, which can be reduced by gravity override and gas breakthrough in high-permeability zones. This can degrade the gas utilization factor, making the process uneconomical. Foam can improve sweep efficiency in gas-injection EOR. Surfactant-Alternating-Gas (SAG) is often the injection strategy used for injecting foam into a reservoir. However, liquid injectivity can be very poor in SAG, and fracturing of the well can occur. Core-flood studies of liquid mobility following foam injection have been reported. However, there is no consistent approach to model liquid injectivity in a SAG process. The Peaceman equation is employed in most conventional foam simulators for estimating the wellbore pressure and injectivity. In this work, we propose a simple modelling approach to liquid injectivity during SAG processes based directly on laboratory core-flood results. The results illustrate the errors in estimating liquid injectivity in a SAG process using conventional models based on the Peaceman equation.
We conducted a series of core-flood experiments to study liquid injectivity under conditions like those near an injection well in a SAG process in the field. Our experimental results suggest that the injectivity in a SAG process is determined by propagation of several banks. In this paper, we describe a modelling approach for gas and liquid injectivity in a SAG process based on our experimental findings. The model represents the propagation of various banks in gas and liquid injection. We first compare the model predictions for linear flow with the core-flood results, and obtain good agreement. We then develop a radial-flow model by scaling-up the core-scale behavior to the field. The comparison between the results of the radial-propagation model and the Peaceman equation shows that a conventional simulator based on the Peaceman equation greatly underestimates both gas and liquid injectivities in a SAG process. The conventional simulator cannot represent the effect of gas injection on subsequent liquid injectivity, especially the propagation of a relatively small region of collapsed-foam near an injection well. The conventional simulator's results can be brought closer to the radial-flow-model prediction by applying two constant skin factors, one for the gas-injection period, and one for the liquid-injection period.
The work-flow described in this study can be applied in future field applications. The model we propose is based on a number of simplifying assumptions. In addition, the model would need to be fitted to core-flood data for the particular surfactant formulation, porous medium and field conditions of a particular application. The adjustment of the simulator to better fit the radial-flow model could depend on grid resolution of the near-well region in the simulation as well.