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.
Although geochemical reactions are the fundamental basis of the alkaline/surfactant/polymer (ASP) flooding, their importance is commonly overlooked and not fully assessed. Common assumptions made when modeling geochemical reactions in ASP floods include: 1) ideal solution (i.e., using molalities rather than ion activities) for the water and aqueous geochemical species 2) limiting the number of reactions (i.e., oil/alkali and alkali consumptions) rather than including the entire thermodynamically-equilibrated system 3) ignoring the effect of temperature and pressure on reactions 4) local equilibrium ignoring the kinetics. To the best of our knowledge, the significance of these assumptions has never been discussed in the literature. In this paper we investigate the importance of geochemical reactions during alkaline/surfactant/polymer floods using a comprehensive tool in the sense of surfactant/soap phase behavior as well as geochemistry.
We coupled the United States Geological Survey (USGS) state-of-the-art geochemical tool, with 3D flow and transport chemical flooding module of UTCHEM. This geochemical module includes several thermodynamic databases with various geochemical reactions, such as ion speciation by applying several ion-association aqueous models, mineral, solid-solution, surface-complexation, and ion-exchange reaction. It has capabilities of saturation index calculation, reversible and irreversible reactions, kinetic reaction, mixing solutions, inverse modeling and includes impacts of temperature and pressure on reaction constants and solubility products. The chemical flood simulator has a three phase (water, oil, microemulsion) phase behavior package for the mixture of surfactant/soap, oil, and water as a function of surfactant/soap, salinity, temperature, and co-solvent concentration. Hence, the coupled software package provides a comprehensive tool to assess the significance of geochemical assumptions typically imposed in modeling ASP floods. Moreover, this integrated tool enables modeling of variations in mineralogy present in reservoir rocks. We parallelized the geochemistry module of this coupled simulator for large-scale reservoir simulations.
Our simulation results show that the assumption of ideal solution overestimates ASP oil recovery. Assuming only a subset of reactions for a coupled system is not recommended, particularly when a large number of geochemical species is involved, as is the case in realistic applications of ASP. Reservoir pressure has a negligible effect but temperature has a significant impact on geochemical calculations. Although mineral reaction kinetics is largely a function of the temperature and in-situ water composition, some general conclusions can be drawn as follows: to a good approximation, minerals with slow rate kinetic reaction (e.g., quartz) can be excluded when modeling ASP laboratory floods. However, minerals with fast rate kinetic reactions (e.g., calcite) must be included when modeling lab results. On the other hand, in modeling field-scale applications, local equilibrium assumption (LEA) can be applied for fast rate kinetic minerals, whereas kinetics should be used for slow rate kinetic minerals.
Imqam, Abdulmhsin (Missouri University of Science and Technology) | Wang, Ze (Missouri University of Science and Technology) | Bai, Baojun (Missouri University of Science and Technology) | Delshad, Mojdeh (The University of Texas at Austin)
Preformed particle gels (PPG) have been successfully applied as a plugging agent to solve the conformance problem in fractured reservoirs. They are injected to plug fractures and then divert displacing fluid into poorly swept zones and areas. However, PPG propagation and plugging mechanisms through open fractures have not been studied thoroughly. This paper investigated the influence of some factors (particle size, brine concentration, heterogeneity, injection flow rate, and brine salinity) on gel injectivity and plugging performance for water flow through opening fractures. Five-foot tubes were used to mimic opening fractures. Three models were designed to gain understanding on how fracture geometry and PPG properties affect gel injection and plugging efficiency, including (1) single fracture with uniform fracture width, (2) single fracture with different widths, and (3) two parallel fractures with different width ratios between each other. Results from single uniform fracture experiments showed that PPG injection pressure was more sensitive to gel strength than gel particle size. When large PPG size and high gel strength were used, high injection pressure and large injection pore volume were required for PPG and brine to reach fracture outlets. Results from single heterogeneous fracture model experiments showed PPG injection pressure increased as the fracture heterogeneity in sections increased. Particle gel accumulated at the choke point within each fracture and caused injection pressure to increase accordingly. Furthermore, results showed that having a lower salinity within a fracture, which was less than the brine salinity that was used to prepare PPG, would improve the PPG plugging efficiency for water flow. Parallel fracture models results showed that when weak PPG was used, a large volume of PPG flowed into a large fracture width and a small portion of the gel particle volume flowed into small fracture width. However, with increased gel strength and fracture width ratio, PPG only flowed through larger fracture widths. This paper demonstrates important impact elements of gel propagation and water flow for different opening fracture situations.
In this paper, we estimate foam parameters and investigate foam behavior for a given range of water saturation using two local equilibrium foam models: the population balance and the Pc*. Our method uses an optimization algorithm to estimate foam model parameters by matching foam measured pressure gradient from steady-state coreflood experiments. We calculate the effective foam viscosity and the water fractional flow using experimental data and we then compare lab data against results obtained with the matched foam models to verify the foam parameters. Other variables, such as the foam texture and foam relative permeability are used to further investigate the behavior of the foam during each experiment. We propose an improvement to the Pc* model with a better match in high quality regime by assuming resistance factor and critical water saturation is a linear function of pressure gradient. Results show that the parameter estimation method coupled with an optimization algorithm successfully matches the experimental data using both foam models. In the population balance, we observe different values of the foam effective viscosity for each pressure gradient due to variations of the foam texture and shear thinning viscosity effect. The Pc* model presents a constant effective viscosity for each pressure gradient; we propose the use of resistance factor and critical water saturation as a linear function of pressure to improve the match in the high quality regime, when applicable. Foam has been successfully used in the oil industry for conformance and mobility control in gas injection processes. The efficiency of a foam injection project must be assessed by means of numerical models. Although there are several foam flow models in the literature, the prediction of foam behavior is an important issue that needs further investigation.
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.