Scaleup of laboratory data for surfactant-alternating-gas foam enhanced oil recovery

Foam increases sweep efficiency during gas injection in enhanced oil recovery processes. Surfactant alternating gas (SAG) is the preferred method to inject foam for both operational and injectivity reasons. Dynamic SAG corefloods are unreliable for direct scaleup to the field because of core-scale artifacts. In this study, we report fit and scaleup local-equilibrium (LE) data at very-low injected-liquid fractions in a Bentheimer core for different surfactant concentrations and total superficial velocities. We fit LE data to an implicit-texture foam model for scaleup to a dynamic foam process on the field scale using fractional-flow theory. We apply different parameter-fitting methods (least-squares fit to entire foam-quality scan and the method of Rossen and Boeije 2015) and compare their fits to data and predictions for scaleup. We also test the implications of complete foam collapse at irreducible water saturation for injectivity. Each set of data predicts a shock front with sufficient mobility control at the leading edge of the foam bank. Mobility control improves with increasing surfactant concentration. In every case, scaleup injectivity is much better than with coinjection of gas and liquid. The results also illustrate how the foam model without the constraint of foam collapse at irreducible water saturation (Namdar Zanganeh et al. 2014) can greatly underestimate injectivity for strong foams. For the first time, we examine how the method of fitting the parameters to coreflood data affects the resulting scaleup to field behavior. The method of Rossen and Boeije (2015) does not give a unique parameter fit, but the predicted mobility at the foam front is roughly the same in all cases. However, predicted injectivity does vary somewhat among the parameter fits. Gas injection in a SAG process depends especially on behavior at low injected-water fraction and whether foam collapses at the irreducible water saturation, which may not be apparent from a conventional scan of foam mobility as a function of gas fraction in the injected foam. In two of the five cases examined, this method of fitting the whole scan gives a poor fit for the shock in gas injection in SAG. We also test the sensitivity of the scaleup to the relative permeability k_rw(S_w) function assumed in the fit to data. There are many issues involved in scaleup of laboratory data to field performance: reservoir heterogeneity, gravity, interactions between foam and oil, and so on. This study addresses the best way to fit model parameters without oil for a given permeability, an essential first step in scaleup before considering these additional complications.