Higher stability of the bulk and dynamic foam with polymer addition to the aqueous phase has been demonstrated experimentally. Recent experiments indicated that the efficacy of polymer enhanced foam (PEF) is dependent on polymer type and surfactant-polymer interaction. However, numerical modeling of PEF flow in porous media has been relatively less well understood due to the additional complexity. In this work, we propose modifications to the population-balance foam model for PEF modeling, and their successful use in matching the experimental results.
The population-balance model proposed by Chen and co-workers has been used as development platform. Upon reviewing various aspects in the physics of foam generation, coalescence and mobility reduction in porous media with the addition of polymer, a modified population-balance model was proposed with new parameters pertaining to the polymer effect on the net foam generation and the limiting capillary pressure. The new model was implemented and used to history match foam coreflood experiments with and without polymer.
In addition to the foam apparent viscosity increase due to higher viscosity of the aqueous phase, polymer also impacts foamability and foam stability of bulk foam as indicated in the literature. Our modified population-balance model introduce the viscosity terms in foam generation and coalescence coefficients to account for postulated positive impact on reducing liquid drainage and foam coalescence and negative impact on the characteristic time needed for bubble snap-off in porous media. Additionally, a modification in the limiting capillary pressure was proposed in the new model to include the polymer effect based on our analysis of the disjoining pressure. Two new model parameters are proposed and implemented accordingly. The new foam model succeeded in history-matching the anionic-surfactant-based and nonionic-surfactant-based PEF corefloods with different types of polymers through tuning the two new model parameters. The simulations also captured the transient increasing of the pressure drops induced by polymer transport and adsorption. The proposed model can be used to provide meaningful values of the model parameters that were able to explain the physical mechanisms behind the PEF floods and to guide future experimental design to further constraint the choices of model parameters.
This work provided new methodology to model PEF flow in porous media using the mechanistic population-balance approach for the first time. With proper calibrations of the parameters proposed in the model, the new model can therefore be used to simulate PEF EOR processes to describe the combined effect of foam and polymer on the mobility control of the injectants.
Jin, Luchao (University of Oklahoma) | Budhathoki, Mahesh (University of Oklahoma) | Jamili, Ahmad (University of Oklahoma) | Li, Zhitao (The University of Texas at Austin) | Luo, Haishan (The University of Texas at Austin) | Delshad, Mojdeh (The University of Texas at Austin) | Shiau, Ben (University of Oklahoma) | Harwell, Jeffrey H. (University of Oklahoma)
The surfactant screening process to develop an optimum formulation under reservoir conditions is typically time consuming and expensive. Theories and correlations like HLB, R-ratio and packing parameters have been developed. But none of them can quantitatively consider both the effect of oil type, salinity, hardness and temperature, and model microemulsion phase behavior.
This paper uses the physics based Hydrophilic Lipophilic Difference (HLD) Net Average Curvature (NAC) model, and comprehensively demonstrated its capabilities in predicting the optimum formulation and microemulsion phase behavior based on the ambient conditions and surfactant structures. By using HLD equation and quantitatively characterized parameters, four optimum surfactant formulations are designed for target reservoir with high accuracy compared to experimental results. The microemulsion phase behavior is further predicted, and well matched the measured equilibrium interfacial tension. Its predictability is then reinforced by comparing to the empirical Hand's rule phase behavior model. Surfactant flooding sandpack laboratory tests are also interpreted by UTCHEM chemical flooding simulator coupled with the HLD-NAC phase behavior model.
The results indicate the significance of HLD-NAC equation of state in not only shorten the surfactant screening processes for formulators, but also predicting microemulsion phase behavior based on surfactant structure. A compositional reservoir simulator with such an equation of state will increase its predictability and hence help with the design of surfactant formulation.
Luo, Haishan (The University of Texas at Austin) | Mohanty, Kishore K. (The University of Texas at Austin) | Delshad, Mojdeh (The University of Texas at Austin) | Pope, Gary A. (The University of Texas at Austin)
Upscaling of unstable immiscible flow remains an unsolved challenge for the oil industry. The absence of a reliable upscaling approach greatly hinders the effective reservoir simulation and optimization of heavy oil recoveries using waterflood, polymer flood and other chemical floods, which are inherently unstable processes. The difficulty in upscaling unstable flow lies in estimating the propagation of fingers smaller than the gridblock size. Using classical relative permeabilities obtained from stable flow analysis can lead to incorrect oil recovery and pressure drop in reservoir simulations.
In a recent study based on abundant experimental data, it is found that the heavy-oil recovery by waterfloods and polymer floods has a power-law correlation with a dimensionless number (named viscous finger number in this paper), which is a combination of viscosity ratio, capillary number, permeability, and the cross-section area of the core. Based upon this important finding as well as the features of unstable immiscible floods, an effective-finger model is developed in this paper. A porous medium domain is dynamically identified as three effective zones, which are two-phase flow zone, oil single-phase flow zone, and bypassed oil (isolated oil island) zone, respectively. Flow functions are derived according to effective flows in these zones. This new model is capable of history-matching a set of heavy-oil waterflood corefloods under different viscosity ratios and injection rates. Model parameters obtained from the history match also have a power-law correlation with the viscous finger number.
The build-up of this correlation contains reasonable physical meanings to quantitatively characterize the upscaled behavior of viscous fingering effects. Having such a correlation enables the estimation of model parameters in any gridblock of the reservoir by knowing the local viscous finger number in reservoir simulations. The model is applied to several heavy-oil field cases with waterfloods and polymer floods with different heterogeneities. Oil recovery in water flooding of viscous oils is overpredicted by classical simulation methods which do not incorporate viscous fingering properly. Simulation results indicate that the new model reasonably differentiates the oil recoveries at different viscous finger numbers, e.g., lower injection rate leads to higher oil recovery. In contrast, classical simulations obtain close oil recoveries under different injection rates or degrees of polymer shear-thinning, which is apparently incorrect for unstable floods. Moreover, coarse-grid simulations using the new model are able to obtain consistent saturation and pressure maps with fine-grid simulations when the correlation lengths are not smaller than the coarse gridblock size. Furthermore, it is well captured by the model that the shear-shinning polymer solution can strengthen the fingering in high-permeability regions due to increased capillary number and viscosity ratio, which is not observed in waterflood. As a whole, the new model shows encouraging capability to simulate unstable water and polymer floods in heavy oil reservoirs, and hence can facilitate the optimization of heavy-oil EOR projects.