Surfactant flooding models

Set up a base model like batch.txt for surfactant flooding with injection compositions (water/oil ratio, surfactant concentration, and so on) being the same as the phase behavior tests. The initial lower and upper salinities, Csei and Cseu, may be the same as those in the pipette tests. 

The main objective of surfactant flooding is to reduce residual oil saturation, which is closely related to capillary number. Therefore, the concept of capillary number is discussed first. Analysis of the pore-doublet model yields the following dimensionless grouping of parameters (Moore and Slobod 1955), which is a ratio of the viscous-to-capillary force ... 

A new dimensionless number called the trapping number has been defined it includes both gravity and viscous forces (UTCHEM-9.0, 2000). The dependence of residual saturations on interfacial tension is modeled in UTCHEM as a function of the trapping number. This is a formulation necessary to model the combined effect of viscous and buoyancy forces in three dimensions. Buoyancy forces are much less important under enhanced oil recovery conditions than under typical surfactant-enhanced aquifer remediation (SEAR) conditions therefore, it had not been carefully considered under three-dimensional surfactant flooding held conditions. 

Relative permeability is probably one of the least-defined parameters in chemical flooding processes. The classical relative permeability curves represent a situation in which the fluid distribution in the system is controlled by capillary forces. When capillary forces become small compared to viscous forces, the whole concept of relative permeability becomes weak. This area has not been adequately researched, and theoretical understanding is rather inadequate (Brij Maini, University of Calgary in Canada, personal communication, 2007). This section discusses relative permeability models related to surfactant flooding and the IFT effect on relative permeabilities. 

A hne core-scale model is used to study the optimum phase type and optimum salinity prohle in surfactant flooding. 

In this section, simulation results are compared with the information from the literature for different polymer and surfactant-polymer injection schemes. We expect that UTCHEM simulation of a core-scale chemical process is the best simulation approach to study mechanisms. In this study, we use a ID core flood model with 100 blocks to represent a 1-foot-long core. The permeability is 2000 md, and the water and oil viscosities are 1 and 2 mPa s, respectively. To optimize injection schemes, we compare the incremental oil recovery factors over waterflooding and chemical costs. Chemical costs are evaluated using the amounts of chemicals injected per barrel of incremental oil (Ib/bbl oil). 

Hirasaki, G.J. 1981. Application of the theory of multicomponent, multiphase displacement to three component, two phase surfactant flooding. Soc. Pet. Eng. J. 21 191-198. HOrst, J., W.H. Holl, and S.H. Eberle. 1990. Application of surface complex formation model... 

Several micellar-polymer flooding models as applied to the EOR are discussed in [237]. It is noted that the co-solvent ordinarily used in this process considerably influences not only the microemulsion stabilisation, but also the removal of impurities in the pores of the medium. The idea of using an alkali in micellar-polymer flooding is discussed in [238] in detail. The alkali effect on the main oil components was studied aromatic hydrocarbons, saturated and unsaturated compounds, light and heavy resin compounds and asphaltenes. It is demonstrated that at pH 12 surfactants formed from resins allow to achieve an interfacial tension value close to zero. For asphaltenes, such results are achieved at pH 14. In the system alkali solution (concentration between 1300 to 9000 ppm)/crude oil at 1 1 volume ratio a zone of spontaneous emulsification appears, which is only possible at ultra-low interfacial tensions. 

Larson (139) also carried out a detailed analysis of the influence of phase behavior on surfactant flooding. He constructed mathematical models to account for phase behavior, low interfacial tension, dispersion and other mechanisms to determine conditions under which good oil recovery can be obtained. He also found that the best recovery should come from Type II+, that is an expanding oil phase with the plait point on the left. Larson goes even further in his analysis to claim that good recovery can be achieved from phase behavior alone without the requirement for low interfacial tensions. However, without the aid of low interfacial tension, the good recovery is delayed according to Larson (139). 

Mathematical Modelling of Oil Recovery by Polymer/Surfactant Flooding... 

Abstract. This article describes a hydrodynamic model of collaborative flnids (oil, water) flow in porons media for enhanced oil recovery, which takes into account the influence of temperature, polymer and surfactant concentration changes on water and oil viscosity. For the mathematical description of oil displacement process by polymer and surfactant injection in a porous medium, we used the balance equations for the oil and water phase, the transport equation of the polymer/surfactant/salt and heat transfer equation. Also, consider the change of permeabihty for an aqueous phase, depending on the polymer adsorption and residual resistance factor. Results of the numerical investigation on three-dimensional domain are presented in this article and distributions of pressure, saturation, concentrations of poly mer/surfactant/salt and temperature are determined. The results of polymer/surfactant flooding are verified by comparing with the results obtained from ECLIPSE 100 (Black Oil). The aim of this work is to study the mathematical model of non-isothermal oil displacement by polymer/surfactant flooding, and to show the efficiency of the combined method for oil-recovery. 

The Optimal Surfactant Formulation model can be considered as an extension of the PIT concept for complex surfactant mixtures. In 1973, the oil embargo caused a considerable amount of research aimed at enhanced oil recovery. Among the proposed methods were low-tension surfactant flooding processes, in which a surfactant solution was injected into the oil reservoir to produce a low interfacial tension between the crude oil and water, in order to reduce the capillary pressure resistance. The researchers were aiming at an optimal surfactant formulation , at which the interfacial tension has a minimum, i.e. at the balanced surfactant composition. The systems studied represented very complex mixtures, containing polydisperse surfactants, alcohols, salts, hydrocarbons, and water. Elaborate em-... 

Formation damage caused by clay migration may be observed when the injected brine replaces the connate water during operations such as water-flooding, chemical flooding including alkaline, and surfactant and polymer processes. These effects can be predicted by a physicochemical flow model based on cationic exchange reactions when the salinity decreases [1665]. Other models have also been presented [345,1245]. 

The assessment of surfactant structures and optimal mixtures for potential use in tertiary flooding strategies in North Sea fields has been examined from fundamental investigations using pure oils. The present study furthermore addresses the physico-chemical problems associated with reservoir oils and how the phase performance of these systems may be correlated with model oils, including the use of toluene and cyclohexane in stock tank oils to produce synthetic live reservoir crudes. Any dependence of surfactant molecular structure on the observed phase properties of proposed oils of equivalent alkane carbon number (EACN) would render simulated live oils as unrepresentative. 

Mobility control, issues in, 18 626 Mobility control agents polyacrylamides as, 18 625 in polymer flooding, 18 622 Mobility control surfactants, in enhanced oil recovery, 18 625-628 Mobilizable vectors, for genetic manipulation, 12 471 Mobilization, of ascorbic acid, 25 771 Modacryhc fibers, 9 192 11 188, 189, 190 dyesite content of, 11 195 flame resistance of, 11 214 flammability of, 11 194 pigmented, 11 213 U.S. production of, 11 220t Mode conversion phenomenon, 17 422 Model agreements, 24 373-374 Model-based methods, for reliability, 26 1044... 

The chapter by Fulton and Smith (Chapter 5) shows that ionic surfactants can form microemulsions with ethane and water under conditions that might be encountered in miscible floods with light hydrocarbons. These microemulsions correspond to the single-phase regions of the model diagrams in Figure 11. 

One natural core was used to compare the performance of waterflood (W), AP flood, and ASP flood. The recovery factors for W, AP, and ASP were 50%, 69.7%, and 86.4%, respectively. These core flood tests were history matched, and the history-matched model was extended to a real field model including alkaline consumption and chemical adsorption mechanisms. A layered heterogeneous model was set up by taking into account the pilot geological characteristics. The predicted performance is shown in Table 11.3. In the table, Ca, Cs, and Cp denote alkaline, surfactant, and polymer concentrations, respectively. After the designed PV of chemical slug was injected, water was injected until almost no oil was produced. The total injection PV for each case is shown in the table as well. The cost is the chemical cost per barrel of incremental oil produced. An exchange rate of 7 Chinese yuan per U.S. dollar was used. From... 

In chemical flooding, the most challenging tasks are the quantification of surfactant phase behavior and alkahne reactions. Simulation of phase behavior of an alkaline-surfactant system that combines these two tasks in a single model may be the most challenging one. This section uses EQBATCH and UTCHEM to investigate several aspects of the phase behavior of alkaline-surfactant systems. 

A core-flood for adsorption determination consists of injecting a measured volume of surfactant solution containing a nonadsorbing tracer into a brine-saturated core and collecting effluent fractions at the core outlet. Chemical analysis of the effluent samples allows the calculation of an adsorption level based on material balance considerations and also results in a set of effluent profiles for the surfactant and the tracer. In addition to the material balance, adsorption is evaluated by matching experimental effluent concentrations from the core-floods with a convection—dispersion—adsorption numerical model. The model parameters then allow calculation of a complete adsorption isotherm. 

Figure 10. Example of experimental and simulated effluent concentrations from a core-flood and the surfactant adsorption isotherm calculated from the best-fit adsorption model parameters.

Effluent profiles obtained from a core-flood performed with a mixture of two surface-active components (C12 and C18) separated from a commercially available sulfobetaine are shown in Figure 24 (115). The points represent experimental data, and the lines were obtained by simulating the core-flood with a convection—dispersion—adsorption model that is based on the surface excess concept and takes into account monomer—micelle equilibrium (115). Because the mixture contains different homologues of the same surfactant, the ideal mixed micelle model... 

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