Lashgari, Hamid R. (The University of Texas) | Pope, Gary A. (The University of Texas) | Tagavifar, Mohsen (The University of Texas) | Luo, Haishan (The University of Texas) | Sepehrnoori, Kamy (The University of Texas) | Li, Zhitao (Ultimate EOR Services) | Delshad, Mojdeh (Ultimate EOR Services)
This paper presents a new three-phase relative permeability model for use in chemical flooding simulators. Numerical simulation test cases are presented to illustrate the continuity of the new relative permeability model. Comparisons are made with a three-phase relative permeability model that has been widely used in chemical flooding simulators for decades. These comparisons show the old model has numerical discontinuities that are not physical in nature and that can lead to oscillations in the numerical simulations. The proposed model is simpler, has fewer parameters and requires less experimental data to determine the relative permeability parameters compared to the original model. Simulations using the new model showed excellent agreement with ASP coreflood data.
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. In this paper, we estimate foam parameters and investigate foam behavior for a given range of water saturation by use of two local equilibrium foam models: the population balance assuming local equilibrium (LE) model and the University of Texas (UT) model. Our method uses an optimization algorithm to estimate foam-model parameters by matching the measured pressure gradient from steady-state foam-coreflood experiments. We calculate the effective foam viscosity and the water fractional flow by use of experimental data, and we then compare laboratory 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 UT model that provides a better match in the high-quality regime by assuming resistance factor and critical water saturation as a linear function of the pressure gradient. Results show that the parameter-estimation method coupled with an optimization algorithm successfully matches the experimental data by use of both foam models. In the LE model, we observe different values of the foam effective viscosity for each pressure gradient caused by variations of foam texture and the shear-thinning viscosity effect. The UT 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 the pressure gradient to improve the match in the high-quality regime, when applicable.
Jin, Luchao (University of Oklahoma) | Li, Zhitao (Ultimate EOR Services) | Jamili, Ahmad (University of Oklahoma) | Kadhum, Mohannad (University of Oklahoma) | Lu, Jun (University of Tulsa) | Shiau, Bor-Jier (University of Oklahoma) | Harwell, Jeffrey H. (University of Oklahoma) | Delshad, Mojdeh (University of Tulsa and University of Texas at Austin)
Microemulsion phase behavior is crucial to surfactant flooding performance and design. In previous studies, analytical/numerical solutions for surfactant flooding were developed dependent on the classical theory of multicomponent/multiphase displacement and empirical microemulsion phase-behavior models. These phase-behavior models were derived from empirical correlations for component-partition coefficients or from the Hand-rule model (Hand 1930), which empirically represents the ternary-phase diagram. These models may lack accuracy or predictive abilities, which may lead to improper formulation design or unreliable recovery predictions.
To provide a more-insightful understanding of the mechanisms of surfactant flooding, we introduced a novel microemulsion phase-behavior equation of state (EOS) dependent on the hydrophilic/lipophilic-difference (HLD) equation and the net-average curvature (NAC) model, which is called HLD-NAC EOS hereafter. An analytical model for surfactant flooding was developed dependent on coherence theory and this novel HLD-NAC EOS for two-phase three-component displacement. Composition routes, component profile along the core, and oil recovery can be determined from the analytical solution.
The analytical solution was validated against numerical simulation as well as experimental study. This HLD-NAC EOS based analytical solution enables a systematic study of the effects of phase-behavior-dependent variables on surfactant-flooding performance. The effects of solution gas and pressure on microemulsion phase behavior were investigated. It was found that an increase of solution gas and pressure would lead to enlarged microemulsion bank and narrowed oil bank. For a surfactant formulation designed at standard conditions, the analytical solution was able to quantitatively predict its performance under reservoir conditions.
Fortenberry, Robert (Ultimate EOR Services) | Li, Zhitao (Ultimate EOR Services) | Huh, Chun (Ultimate EOR Services) | Delshad, Mojdeh (Ultimate EOR Services) | Lu, Jun (University of Tulsa) | Chen, Mai (University of Tulsa)
Degradation of EOR polymers, including thermal and mechanical degradation and in-situ hydrolysis, has been a long-neglected topic in simulation of polymer flooding. Recent field studies and increasing application of polymer to challenging conditions of temperature and salinity highlight the importance of proper modeling of these phenomena. This paper describes implementation of multimodal degradation models in the University of Texas Chemical Flooding reservoir simulator (UTCHEM) and simulation studies of the effects of thermal degradation on polymer flooding in a viscous oil reservoir.
Dynamic changes of polyacrylamide viscosity are of great concern during polymer flooding as it directly impacts oil recovery performance. Degradation can include losses to due to mechanical shearing in wellbores and chokes as well as instability at the reservoir condition. Hydrolysis can increase viscosity of polymer solutions with time as amide moieties are replaced with hydroxyls. To properly account for the effects of degradation and hydrolysis, existing models have been improved and new ones implemented in UTCHEM. This includes a global degradation model assuming reduction in apparent concentration of polymer, a thermal decomposition model using a fictive reacting tracer to trace the weight-average polymer molecular weight, and an in-situ hydrolysis model using another fictive reacting tracer to trace the process of hydrolysis, and a molecular weight loss model to represent mechanical degradation.
Results of this work show that mechanical and physical degradation as well as polymer hydrolysis can be measured in laboratory experiments and modeled in reservoir simulations. We show how these models can be used to represent viscosity losses which could occur during a polymer flood.
This work describes the first holistic approach to polymer degradation modeling including hydrolysis, mechanical degradation and thermal degradation completed in the literature. This approach is useful in many ways - it can provide more accurate predictions of polymer flooding performance in situations where polymer stability isn't guaranteed. The models can be implemented in commercial and in-house reservoir simulators to correctly represent laboratory data, which we also provide for others to calibrate their own models. Finally, it serves to increase industry modeling sophistication of this important, mature and economical EOR process which is growing rapidly in the Middle East.
Luo, Haishan (The University of Texas at Austin) | Delshad, Mojdeh (The University of Texas at Austin) | Pope, Gary A. (The University of Texas at Austin) | Mohanty, Kishore K. (The University of Texas at Austin)
Unstable floods and resulting viscous fingers remain a big challenge for reservoir simulation as the gridblock size is usually many orders larger than the viscous finger wavelength. This problem becomes especially pronounced with increasing applications of polymer and other chemical floods in the development of heavy oil reservoirs. Traditional reservoir simulators do not consider sub-grid viscous fingering effects and tend to overestimate the waterflood oil recovery. Using extremely fine grid models with centimeters size is unrealistic for field-scale simulations.
While some researchers disregard viscous fingering by claiming that channeling dominates at the large scale for heterogeneous reservoirs, they miss the existence of viscous fingering at the small scale, which affects the displacement efficiency. To overcome this limitation, an effective-fingering model was developed to upscale fingering effects. The model divides each gridblock into three dynamic regions: two-phase flow, single phase oil flow, and bypassed-oil regions. Model parameters represent the maximum fraction of viscous fingering and the growth rates of different regions, which are used to modify flow functions. Model parameters from history match of a set of laboratory experiments show clear power-law correlations with a dimensionless viscous finger number, a function of viscosity ratio, velocity, permeability, interfacial tension, and core cross-sectional area.
The correlation was achieved in the lab scale by considering homogeneous cores, and we extended it further to the field scale by performing high-order spatial accuracy numerical simulations at the intermediate scale using fine gridblock sizes roughly the same as that of the core. Geostatistical realizations of the permeability field were generated with various variances and correlation lengths. In a statistical way, we were able to quantify the viscous finger number valid for a gridblock at the field scale affected by various heterogeneities using the effective-fingering model. We also observed that channelized permeability distributions increase the viscous finger number drastically, showing the important role of channeling in such cases. This new model was applied to a field case with high heterogeneity undergoing water/polymer floods. We observed that the oil recovery was improved by the polymer slug because of the enhancement in both local displacement efficiency and sweep efficiency.
In summary, we developed an upscaling model that provides a fresh-new insight on how to simulate unstable water/polymer floods at the field scale, which effectively accounts for the interplay of viscous fingering and channeling.
Luo, Haishan (The University of Texas at Austin) | Li, Zhitao (Ultimate EOR Services LLC) | Tagavifar, Mohsen (The University of Texas at Austin) | Lashgari, HamidReza (The University of Texas at Austin) | Zhao, Bochao (The University of Texas at Austin) | Delshad, Mojdeh (The University of Texas at Austin) | Pope, Gary A. (The University of Texas at Austin) | Mohanty, Kishore K. (The University of Texas at Austin)
Polymer flooding has been commercially applied to a number of viscous oil fields in the past decade and gradually gained more popularity. Due to limited injectivity in viscous-oil reservoirs, a relatively low polymer viscosity is usually used to avoid excessive injection pressure. In such a case, mobility ratio of polymer solution to oil is much greater than one, which implies unstable flow and strong viscous fingering. Existing reservoir simulators lack the capability of modeling such a physical phenomenon. Since many viscous-oil reservoirs have high permeability contrast between layers, we are motivated to study, for the first time, the impact of crossflow between different layers considering the presence of viscous fingering.
Numerical modeling polymer floods with crossflow in a layered viscous-oil reservoir is difficult due to two major challenges: first is how to correctly allocate flow rates from the wellbore to multiple layers; and second is how to capture the viscous fingering effect without using excessively fine grids. To address the first issue, we developed an implicit well-rate-allocation model based on the potential method, which fully couples all the wellbore segments of each well with reservoir gridblocks to ensure a physical wellbore pressure. To deal with the second challenge, we implemented the effective fingering model, which is an upscaling model that lumps all the viscous fingers in a coarse grid block into one fictitious finger to allow for accurate estimation of fingering strength and growth during unstable flows. Both models were validated individually against the analytical solution or experimental data.
The integrative module including the two new capabilities was used to simulate a polymer flood following a waterflood in a layer-cake reservoir in North America with moderate oil viscosity. We observed the fast propagation of water fronts and small fingering fraction in high permeability layers during the waterflooding phase, indicating active channeling and viscous fingering. The subsequent polymer flooding minimized both factors of oil bypassing and led to stable flow and high sweep efficiency. Without the implicit well-rate-allocation model, crossflow was overestimated and wellbore pressures of different well blocks were not consistent. Without the effective-fingering model, oil recovery was overestimated due to the lack of accounting for viscous fingering. The simulation results indicated that polymer flooding improved both displacement and sweep efficiencies.
The model has shown comprehensive capabilities in reservoir simulations of polymer floods including unstable floods and crossflows between layers. This is a major significance to optimization of non-thermal viscous-oil EOR projects and also making more informed operational decisions for field developments.
Conventional fractional flow theories such as the Buckley-Leverett analysis have benefited reservoir engineers greatly for many decades. Although being simple, these analyses provide prompt and decent estimations of water breakthrough and oil bank height/duration in the experiments and the fields. However, their intrinsic inaccuracy in estimating unstable immiscible floods due to the existence of viscous fingering has long been ignored. With increasing non-thermal immiscible floods developed for heavy oil reservoirs, an essential improvement for such a theory is desirable.
The intrinsic residual oil saturation can never be achieved for strong unstable immiscible floods within a finite time. The fraction of the bypassed oil at a time is highly dependent on the viscosity ratio, flow velocity, interfacial tension, wettability, permeability and the geometry of the rock. Extensive experimental data and numerical studies have indicated that the strength and growth rate of viscous fingering are correlated to a dimensionless number, i.e., the viscous finger number, which is an integration of those factors aforementioned. Such a discovery enables a quantitative establishment of two-phase pseudo relative permeabilities, which are functions of fluid saturations and the viscous finger number. The fractional flow for unstable floods can hence be obtained by use of such pseudo relative permeabilities.
The new fractional flow theory extended from the Buckley-Leverett analysis was applied to several groups of heavy-oil water coreflood experiments under various conditions. The new fractional flow analysis was able to predict very well the breakthrough time and oil recovery of these experiments. We further applied the new fractional flow analysis to a slab experiment of viscous oil with a waterflood followed by a polymer flood, and achieved a very good agreement with the oil recovery data. The analysis reproduced that the water cut increased very rapidly and the remaining oil saturation was much larger than the intrinsic residual oil saturation after several pore volumes of waterflood. The subsequent polymer flood altered the pseudo relative permeability curves due to the change of viscosity ratio and brought in a considerable amount of mobile oil to be displaced. This process happens to be similar to the fractional flow of low-tension immiscible flow. Such a scenario is different from what the conventional fractional flow analysis suggests, which neglects the fact that the subsequent polymer flood is able to greatly improve the oil cut by mitigating the viscous fingers originally created by waterflood.
The new theory has extended the original fractional flow theories to unstable immiscible floods, a major progress. It can also serve as a critical guideline to estimate and predict the water/polymer breakthrough and the oil production in viscous-oil benchscale experiments and field projects.
The interest in low-salinity-water injection (LSWI) compared with seawater injection or high-salinity-produced-brine injection is increasing in both laboratory and field tests. The single-well chemical-tracer test (SWCTT) is also becoming increasingly popular as an in-situ test to assess the reduction in oil saturation caused by an enhanced-oil-recovery (EOR) process. Hence, accurate modeling of SWCTTs is essential. In this paper, modeling and simulation of the SWCTT of LSWI in a carbonate reservoir is investigated by use of the UTCHEM reservoir simulator, a nonisothermal, 3D, multiphase, multicomponent, chemical compositional simulator developed at the University of Texas at Austin (UTCHEM 2011). Both radial- and Cartesian-grid models are set up for a field-scale pilot by use of measured rock and fluid data of a Middle Eastern reservoir. Tracer reactions and the empirical LSWI model implemented in UTCHEM are used to estimate residual oil saturation (ROS) as a result of LSWI. Two approaches are used to estimate ROS to LSWI, including analytical and numerical methods. Results show that both approaches give consistent values for ROS for homogeneous radial- and Cartesian-grid models. The two approaches were inconsistent for the multilayer radial model, which highlights the necessity of the use of numerical approaches for layered reservoirs. The Cartesian-grid model was used to investigate the effect of heterogeneity on SWCTT results, where a new numerical approach is proposed for estimating ROS. This finding validates the approach used and the implementation of both tracer reactions and the LSWI model in UTCHEM. The proposed approach can now be used to estimate ROS of the SWCTT for reservoirs with different degrees of heterogeneity, which provides a clear insight into reservoir performance before planning multiwell demonstration pilots.
The upscaling of unstable immiscible flow remains an unsolved challenge for the oil industry. The absence of a reliable upscaling approach hinders effective reservoir simulation and optimization of heavy-oil recoveries by use of waterflood, polymer flood, and other chemical floods, which are inherently unstable processes. The difficulty in scaling up 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.
Extensive experimental data in water-wet cores indicate 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), a combination of viscosity ratio, capillary number, permeability, and the cross-sectional area of the core. On the basis of the features of unstable immiscible floods, an effective-fingering model is developed in this paper. A porous-medium domain is dynamically identified as three effective regions, which are two-phase flow, oil single-phase flow, and bypassed-oil region, respectively. Flow functions are derived according to effective flows in these regions. Model parameters represent viscous-fingering strength and growth rates. The new model is capable of history matching a set of heavy-oil waterflood corefloods under different conditions. Model parameters obtained from the history match also have power-law correlations with the viscous-finger number. This model is applicable to water-wet reservoirs; it has not been tested for mixed-wet and oil-wet systems, low-interfacial-tension (IFT) environments, low permeability, and heavy-oil reservoirs with free gas cap.
In reservoir simulations, having such a correlation enables the estimation of model parameters in any gridblock of the reservoir by knowing the local viscous-finger number. The model was first applied to a heavy-oil field case with channelized permeability by waterfloods. Simulation results with the new model indicated that viscous fingering strengthened the channeling. Also, the new model shows that a lower injection rate leads to a higher oil recovery. In contrast, oil recovery in waterflooding of viscous oils is overpredicted by classical simulation methods that do not incorporate viscous fingering properly. We further showed that coarse grid simulations with the new model were able to obtain saturation and pressure maps consistent with fine-grid simulations. The new model was then used to model a real field case in the Pelican Lake heavy-oil field. It was able to match the field-production data without major adjustment of reservoir/fluid properties from the literature, showing its competence in capturing subgrid viscous-fingering effects. Overall, 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 enhanced-oil-recovery (EOR) projects.
Jin, Luchao (University of Oklahoma) | Li, Zhitao (Ultimate EOR Services LLC) | Jamili, Ahmad (University of Oklahoma) | Luo, Haishan (The University of Texas at Austin) | Delshad, Mojdeh (The University of Texas at Austin) | Lu, Jun (The University of Tulsa) | Shiau, Ben (University of Oklahoma) | Harwell, Jeffrey H. (University of Oklahoma) | Rui, Zhenhua (Independent Project Analysis, Inc.)
Chemical flood reservoir simulators developed based on component partitioning model or empirical phase behavior model lack the effects of physical properties such as surfactant structure and oil properties i.e. equivalent alkane carbon number (EACN) on microemulsion phase behavior. Hence, these simulators have limited function in helping formulation design. A typical empirical microemulsion phase behavior model is the Hand's model that is used in UTCHEM, a benchmark chemical flood compositional simulator. However, it needs several matching parameters to fit phase behavior experiments and requires iterative calculations to solve phase compositions. Therefore, it is desirable to develop a chemical flood simulator with a more efficient and physics-based phase behavior model.
This work incorporates a physics based HLD-NAC equation of state (EOS) into UTCHEM. A non-iterative flash calculation algorithm based on HLD-NAC microemulsion EOS is developed, which uses simple equations to represent plait point, binodal curve, and tie-lines. Input model parameters include quantitatively characterized physical properties, such as oil EACN, reservoir temperature, surfactant structure properties (head area and tail length), and optimum solubilization ratio. Therefore, the effects of these parameters on oil recovery can be systemically studied. Coreflood simulation results are validated against the Hand's model.
Compared to the Hand's model which requires at least 5 matching parameters and with limited predictability, the HLD-NAC EOS can reproduce microemulsion phase behavior with surfactant tail length as the only fitting parameter. Comparing coreflood simulations using the HLD-NAC model and the Hand's model shows that the same oil recovery curves are obtained when slug at optimum salinity is injected. However, for corefloods using a salinity gradient design, HLD-NAC model predicts higher oil recovery than the Hand's model. The reasons for the differences are analyzed by examining the simulated solubilization ratios and ternary phase diagrams at different salinities. Moreover, numerical experiments show that the HLD-NAC model improves the phase behavior computational efficiency by approximately 65%. The effect of live oil at reservoir pressure is also investigated. Results indicate shifted optimal salinity and solubilization ratio due to solution gas and pressure lead to larger microemulsion bank.
Owing to the physical significance, simplicity, and computational efficiency of the HLD-NAC EOS, this novel chemical flooding simulator proves to be a fast and promising tool to speed up surfactant screening process and helping chemical formulation development and injection designs.