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.