Partition-Coefficient Relations for Improved Equation-of-State Description of Microemulsion-Phase Behavior

SPE Journal ◽  
2018 ◽  
Vol 23 (05) ◽  
pp. 1899-1908 ◽  
Author(s):  
V. A. Torrealba ◽  
R. T. Johns
Keyword(s):  
Equation Of State ◽  
Phase Behavior ◽  
Oil Recovery ◽  
Partition Coefficients ◽  
Behavior Modeling ◽  
Surfactant Partition Coefficients ◽  
Partitioning Coefficients ◽  
Excess Phases ◽  
Affinity Quantification ◽  
Behavior Models

Summary Surfactant-mediated enhanced-oil-recovery (EOR) techniques, such as surfactant/polymer (SP) flooding, have received increased attention because of their ability to reduce capillary forces at the pore-scale to ultralow values and mobilize trapped oil. Recently, there have been increased efforts in microemulsion-phase-behavior modeling capabilities by relying on the hydrophilic/lipophilic-difference (HLD) measure for surfactant-affinity quantification. One common assumption of most microemulsion-phase-behavior models is the assumption of pure excess phases, which states that the surfactant component is only present in the microemulsion phase. This assumption can lead to significant errors for some surfactant systems, especially when applied to chemical simulations in which discontinuities may arise. The main novelty of this paper is to allow for surfactant partitioning into both the water and oil excess phases by use of a simple approach, and then relate relevant surfactant-partitioning coefficients (i.e., K-values) to HLD. Surfactant screening that is based on surfactant-structure parameters is also considered based on estimated K-values. Key dimensionless groups are identified as a function of activity coefficients, which allow for a simplified description of the surfactant-partition coefficients. These surfactant-partition coefficients are combined with the chemical-potentials (CP) equation-of-state (EoS) model to describe and predict the phase behavior when the excess phases are not pure. Further, the developed surfactant-partitioning model can be used in other microemulsion-phase-behavior models to allow for impure excess phases.

scholarly journals Curvature-Based Equation of State for Microemulsion-Phase Behavior

SPE Journal ◽  
2018 ◽  
Vol 24 (02) ◽  
pp. 647-659 ◽  
Author(s):  
V. A. Torrealba ◽  
R. T. Johns ◽  
H.. Hoteit
Keyword(s):  
Equation Of State ◽  
Phase Behavior ◽  
Oil Recovery ◽  
Industrial Applications ◽  
Data Availability ◽  
Behavior Modeling ◽  
Average Curvature ◽  
Wide Range ◽  
Definition Of ◽  
Spheroidal Geometry

Summary An accurate description of the microemulsion-phase behavior is critical for many industrial applications, including surfactant flooding in enhanced oil recovery (EOR). Recent phase-behavior models have assumed constant-shaped micelles, typically spherical, using net-average curvature (NAC), which is not consistent with scattering and microscopy experiments that suggest changes in shapes of the continuous and discontinuous domains. On the basis of the strong evidence of varying micellar shape, principal micellar curves were used recently to model interfacial tensions (IFTs). Huh's scaling equation (Huh 1979) also was coupled to this IFT model to generate phase-behavior estimates, but without accounting for the micellar shape. In this paper, we present a novel microemulsion-phase-behavior equation of state (EoS) that accounts for changing micellar curvatures under the assumption of a general-prolate spheroidal geometry, instead of through Huh's equation. This new EoS improves phase-behavior-modeling capabilities and eliminates the use of NAC in favor of a more-physical definition of characteristic length. Our new EoS can be used to fit and predict microemulsion-phase behavior irrespective of IFT-data availability. For the cases considered, the new EoS agrees well with experimental data for scans in both salinity and composition. The model also predicts phase-behavior data for a wide range of temperature and pressure, and it is validated against dynamic scattering experiments to show the physical significance of the approach.

A Modified HLD-NAC Equation of State To Predict Alkali/Surfactant/Oil/Brine Phase Behavior

SPE Journal ◽  
2018 ◽  
Vol 23 (02) ◽  
pp. 550-566 ◽  
Author(s):  
Soumyadeep Ghosh ◽  
Russell T. Johns
Keyword(s):  
Equation Of State ◽  
Phase Behavior ◽  
Oil Recovery ◽  
Naphthenic Acids ◽  
Phase Region ◽  
Measured Data ◽  
Synthetic Surfactant ◽  
Chemical Flooding ◽  
Mineral Surfaces ◽  
Dimensionless Equation

Summary Reservoir crudes often contain acidic components (primarily naphthenic acids), which undergo neutralization to form soaps in the presence of alkali. The generated soaps perform synergistically with injected synthetic surfactants to mobilize waterflood residual oil in what is termed alkali/surfactant/polymer (ASP) flooding. The two main advantages of using alkali in enhanced oil recovery (EOR) are to lower cost by injecting a lesser amount of expensive synthetic surfactant and to reduce adsorption of the surfactant on the mineral surfaces. The addition of alkali, however, complicates the measurement and prediction of the microemulsion phase behavior that forms with acidic crudes. For a robust chemical-flood design, a comprehensive understanding of the microemulsion phase behavior in such processes is critical. Chemical-flooding simulators currently use Hand's method to fit a limited amount of measured data, but that approach likely does not adequately predict the phase behavior outside the range of the measured data. In this paper, we present a novel and practical alternative. In this paper, we extend a dimensionless equation of state (EOS) (Ghosh and Johns 2016b) to model ASP phase behavior for potential use in reservoir simulators. We use an empirical equation to calculate the acid-distribution coefficient from the molecular structure of the soap. Key phase-behavior parameters such as optimum salinities and optimum solubilization ratios are calculated from soap-mole-fraction-weighted equations. The model is tuned to data from phase-behavior experiments with real crudes to demonstrate the procedure. We also examine the ability of the new model to predict fish plots and activity charts that show the evolution of the three-phase region. The predictions of the model are in good agreement with measured data.

Microemulsion Phase-Behavior Equation-of-State Model Using Empirical Trends in Chemical Potentials

SPE Journal ◽  
2017 ◽  
Vol 23 (03) ◽  
pp. 819-830 ◽  
Author(s):  
V. A. Torrealba ◽  
R. T. Johns
Keyword(s):  
Experimental Data ◽  
Equation Of State ◽  
Phase Behavior ◽  
Correlation Length ◽  
Phase Correlation ◽  
Petroleum Engineering ◽  
Average Curvature ◽  
Three Phase ◽  
Spherical Micelles ◽  
Excess Phases

Summary Surfactant-based enhanced oil recovery (EOR) is a promising technique because of surfactant's ability to mobilize previously trapped oil by significantly reducing capillary forces at the pore scale. However, the field-implementation of these techniques is challenged by the high cost of chemicals, which makes the margin of error for the deployment of such methods increasingly narrow. Some commonly recognized issues are surfactant adsorption, surfactant partitioning to the excess phases, thermal and physical degradation, and scale-representative phase behavior. Recent contributions to the petroleum-engineering literature have used the hydrophilic/lipophilic-difference net-average-curvature (HLD-NAC) model to develop a phase-behavior equation of state (EoS) to fit experimental data and predict phase behavior away from tuned data. The model currently assumes spherical micelles and constant three-phase correlation length, which may yield errors in the bicontinuous region where micelles transition into cylindrical and planar shapes. In this paper, we introduce a new empirical phase-behavior model that is based on chemical-potential (CP) trends and HLD that eliminates NAC so that spherical micelles and the constant three-phase correlation length are no longer assumed. The model is able to describe all two-phase regions, and is shown to represent accurately experimental data at fixed composition and changing HLD (e.g., a salinity scan) as well as variable-composition data at fixed HLD. Further, the model is extended to account for surfactant partitioning into the excess phases. The model is benchmarked against experimental data (considering both pure-alkane and crude-oil cases), showing excellent fits and predictions for a wide variety of experiments, and is compared to the recently developed HLD-NAC EoS model for reference.

Application of the Theory of Multicomponent, Multiphase Displacement to Three-Component, Two-Phase Surfactant Flooding

1981 ◽  
Vol 21 (02) ◽  
pp. 191-204 ◽  
Author(s):  
George J. Hirasaki
Keyword(s):  
Partition Coefficient ◽  
Phase Behavior ◽  
Oil Recovery ◽  
Chromatographic Separation ◽  
Partition Coefficients ◽  
Phase System ◽  
Surfactant Flooding ◽  
Two Phase ◽  
Optimal Salinity ◽  
Interfacial Tensions

Abstract The theory presented in a companion paper is illustrated for the case of three-component, two-phase (i.e., constant-salinity) surfactant flooding. The utility of this method is that, in addition to computation of specific cases, it provides a general qualitative understanding of the displacement behavior for different phase diagrams and different injection compositions. The phase behavior can be classified as to whether the partition coefficient is less than or greater than unity. The injection composition of the slug can be classified as to whether it is aqueous or oleic and whether it is inside or outside the region of tieline extensions.The theory provides an understanding of the displacement mechanisms for the three-component, two-phase system as a function of phase behavior and injection composition. This understanding aids the interpretation of phenomena such as the effects of dispersion, salinity gradient, chromatographic separation, and polymer/surfactant interaction. Introduction The phase behavior of surfactant with oil and brine is the underlying phenomenon of most surfactant-flood design philosophies. The surfactant slugs have been formulated either as (1) surfactant in water, (2) surfactant in oil, or (3) microemulsions containing both water and oil. Recovery of oil is thought to occur by solubilization, oil swelling, miscible displacement, and/or low interfacial tensions. The low interfacial tensions occur in a salinity environment such that three phases can coexist. At higher salinities the surfactant is in the oleic phase, and at lower salinities it is in the aqueous phase.Some recent investigators have preferred designing their process at a constant salinity even though their experiments indicated better oil recovery with a salinity contrast. Glover et al. point out that the optimal salinity is not constant in brines containing divalent ions and that phase trapping can result in large retention of surfactant in a system that was at optimal salinity at injected conditions. Nelson and Pope have demonstrated that good oil recovery is possible in systems containing formation brine with 120,000 ppm TDS and 3,000 ppm divalent cations if the drive salinity is sufficiently low such that the surfactant partitions into the aqueous phase. Moreover, the peak surfactant concentration in the effluent occurred in the three-phase environment where the lowest interfacial tension usually occurs.The purpose of this work is to understand better the mechanism of multiphase, multicomponent displacement so that the phase behavior can be used to advantage. The approach used is to examine in detail the displacement mechanism and behavior of a two-phase, three-component system. This understanding will build a foundation for examining more complex systems.Earlier, Larson and Hirasaki showed effects of oil swelling and the retardation of the surfactant front due to the surfactant partitioning into the oleic phase. Recently, Larson extended the work to finite slugs including oleic slugs. He showed the conditions necessary to have miscible or piston-like displacement. His work showed that systems with large partition coefficients are more tolerant to dispersive mixing. We show in this paper that his observation was probably the consequence of having a phase diagram with a constant partition coefficient. Todd et al. show the effect of the partition coefficients on the chromatographic separation and retention for a two-component surfactant system. Pope et al. evaluated the sensitivity of the performance of a surfactant flood to a number of factors. SPEJ P. 191^

An Analytical Solution for Three-Component, Two-Phase Surfactant Flooding Dependent on the Hydrophilic/Lipophilic-Difference Equation and the Net-Average-Curvature Equation of State

SPE Journal ◽  
2017 ◽  
Vol 22 (05) ◽  
pp. 1424-1436 ◽  
Author(s):  
Luchao Jin ◽  
Zhitao Li ◽  
Ahmad Jamili ◽  
Mohannad Kadhum ◽  
Jun Lu ◽  
...  
Keyword(s):  
Equation Of State ◽  
Analytical Solution ◽  
Phase Behavior ◽  
Numerical Solutions ◽  
Surfactant Flooding ◽  
Two Phase ◽  
Average Curvature ◽  
Component Displacement ◽  
Behavior Models ◽  
Solution Gas

Summary 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.

Phase Behavior Modeling of Alkyl Amine + Hydrocarbon and Alkyl Amine + Alcohol Systems Using a Group Contribution Associating Equation of State

2009 ◽  
Vol 48 (16) ◽  
pp. 7705-7712 ◽  
Author(s):  
Francisco A. Sánchez ◽  
Amir H. Mohammadi ◽  
Alfonsina Andreatta ◽  
Selva Pereda ◽  
Esteban Brignole ◽  
...  
Keyword(s):  
Equation Of State ◽  
Phase Behavior ◽  
Group Contribution ◽  
Behavior Modeling ◽  
Alkyl Amine

An Equation-of-State Model To Predict Surfactant/Oil/Brine-Phase Behavior

SPE Journal ◽  
2016 ◽  
Vol 21 (04) ◽  
pp. 1106-1125 ◽  
Author(s):  
S.. Ghosh ◽  
R. T. Johns
Keyword(s):  
Experimental Data ◽  
Equation Of State ◽  
Phase Behavior ◽  
Oil Recovery ◽  
Atmospheric Pressure ◽  
Carbon Number ◽  
Oil Reservoirs ◽  
Potential Candidate ◽  
Average Curvature ◽  
Formulation Variables

Summary Surfactant/polymer (SP) floods have significant potential to recover waterflood residual oil in shallow oil reservoirs. A thorough understanding of surfactant/oil/brine-phase behavior is critical to design SP-flood processes. Current practices involve repetitive laboratory experiments of dead crude at atmospheric pressure in a salinity scan that aims at finding an “optimum formulation” of chemicals for targeted oil reservoirs. Although considerable progress has been made in developing surfactants and polymers that increase the potential of a chemical enhanced-oil-recovery (EOR) project, very little progress has been made to predict phase behavior as a function of formulation variables such as pressure, temperature, and oil equivalent alkane carbon number (EACN). The empirical Hand (1930) plot is still used today to model the microemulsion-phase behavior with little predictive capability because these and other formulation variables change. Such models could lead to incorrect recovery predictions and improper SP-flood designs. In this research, we develop a new predictive-phase-behavior model and introduce a new factor β to account for pressure changes in the HLD equation. This new HLD equation is coupled with the net-average-curvature (NAC) model to predict phase volumes, solubilization ratios, and microemulsion-phase transitions (Winsor II–, Winsor III, and Winsor II+). The predictions of key parameters are compared with experimental data and are within relative errors of 4% (average 2.35%) for measured optimum salinities and 17% (average 10.55%) for optimum solubilization ratios. This paper is the first to use the HLD/NAC model to predict microemulsion-phase behavior for live crudes, including optimal solubilization ratio and the salinity width of the three-phase Winsor III region at different temperatures and pressures. Although the effect of pressure variations on microemulsion-phase behavior is generally thought to be small compared with temperature-induced changes, we show here that this is not necessarily the case. The predictive approach relies on tuning the model to limited experimental data (such as at atmospheric pressure) similar to what is performed for equation-of-state (EOS) modeling of miscible gasfloods. This new EOS-like model could significantly aid the design of chemical floods where key variables change dynamically, and in screening of potential candidate reservoirs for chemical EOR.

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