Optimum salinity surfactant concentration

Since partitioning is altered by the total concentration of surfactant [44], the optimum formulation for three-phase behavior or for minimum interfacial tension is likely to change with concentration [8,48]. Thus, optimum salinity, optimum ACN, or optimum EON change with the concentration of surfactant if it is a mixture, whereas it is independent of the concentration for an isomerically pure surfactant, as shown in Fig. 10 left and center plots. 

If we input Cjjmaxi = 0.03, Cjs axo = C33max2 = 0.06, and injected salinity C(M,KC,L) = Cii X Cse = 0.99 x 0.36S = 0.3614 meq/mL solution (not water), the effective salinity in. SALT is then exactly equal to 0.355 meq/mL water. Here, C, = 1 - C31 = 1 - 0.01 = 0.99 because the surfactant concentration is 1%. In C(M,KC,L), M denotes the well number, which is 1 for the injector in this simulation model KC denotes the component number, which is 5 for anion and L denotes the phase number, which is 1 for the injected aqueous phase. The solubilization ratios C23/C33 and C13/C33 from the simulation are the same—1 5.2. This solubilization ratio is lower than the experimental data—15.8. To improve this ratio, we reduce C33maxi to 0.03 X 15.2/1 5.8 = 0.0289 and keep the other parameters unchanged. Then we have the solubilization ratios equal to 1 5.8. Thus, we have matched the point at the optimum salinity. 

By the preceding definition, will be independent of WOR and depend only on salinity, as we would expect. According to Eq. 7.74, when Si (i.e., WOR) increases, C31, the surfactant concentration in the water phase, will decrease so that the total amount of surfactant in the water phase, V31, is independent of WOR but dependent on the salinity. At the optimum salinity, V32 = V31, the surfactant has equal partition in the aqueous and oleic phases. However, Eq. 7.74 has not been tested using experimental data. 

This section reviews information in the literature about optimum phase types, the relationship between optimum salinity and surfactant concentration, and optimum salinity gradients. 

Healy et al. (1976) and Reed and Healy (1977) reported that the dependence of optimum salinity on surfactant concentration was moderate, except for low concentration (<3%), where optimum salinity decreased as surfactant concentration increased. They also found that optimum salinity decreased with WOR. 

Because alkalis provide an additional somce of electrolytes, their presence in a surfactant solntion will reduce the optimum salinity. When Martin and Oxley (1985) investigated the effects of alkalis on surfactant phase behavior, they fonnd that for petrolenm sulfonate, alkali anion had little or no effect on the phase behavior, whereas cations were effective for decreasing the optimum salinity in this order potassinm > sodium ammonium (see Figure 8.4). For the solutions with and withont alkali, the optimum salinity decreased with the snrfactant concentration. In the presence of alkaline chemicals, Martin and... 

FIGURE 8.4 Effect of surfactant concentration on optimum salinity for 1 wt.% alkaline chemicals, brine, n-tetradecane, and surfactant Exxon 914-22. Source Martin and Oxley (1985). 

Oxley observed that the alkaline chemicals lowered the optimum salinity, which decreased with increasing petrolenm snlfonate mixtures. In an NaCi20XS/ DN253S/1PA system, dilntion led to a decrease in optimum salinity. Martin and Oxley attributed this to divalent cation snlfonate equilibria. In the second system, when only NaCl (without divalent) was in the brine, dependence of optimum salinity on surfactant concentration was much less, and the optimum salinity was higher. Martin and Oxley (1985) further discussed this interaction between divalent and sulfonate systems. 

Clearly, the relationship between the optimum salinity and surfactant concentration is complex (Salager et al., 1979b) and requires further investigation. The possibility of a shifting optimum salinity has to be taken into account to predict phase behavior during the oil recovery process. 

To the best of our knowledge, the work by Gupta and Trushenski (1979) and experimental data from Nelson (1982) are the only data published so far to support the concept of a negative salinity gradient. Gupta and Trushenski, and Nelson used the same kind of surfactant with a special phase behavior. My explanation to their observation on salinity effect is that for the surfactant they used, the IFTs for both microemulsion/oil and microemulsion/water in the type III system were high. Therefore, when a lower salinity was in the drive water, low IFT was obtained because the lower salinity matched the lower optimum salinity of surfactant as the surfactant concentration was diluted. 

The relationship between optimum salinity and surfactant concentration was system-dependent. In other words, the optimum salinity could decrease or increase with surfactant concentration, depending on surfactant, cosolvent, salinity, divalent contents, and so on. 

This section further discusses the effects of k, curves, optimum phase type, and phase viscosity. The effect of negative salinity gradient is further discussed under conditions where different relationships between optimum salinity and surfactant concentrations occur. 

Martin and Oxley (1985) studied the effect of different alkalis on surfactant systems. They showed that the presence of any alkali lowered the optimum salinity of the surfactant system. This phenomenon is caused by two facts (1) alkali can provide electrolytes and (2) alkali reacts with crude oil to generate soap, and soap has lower optimum salinity (see the next section). Martin and Oxley found a linear relationship between the optimum salinity and sodium concentration. The addition of any alkali agents results in a decrease in the optimum salinity of the system. However, alkali anions have very little effect on the phase behavior. 

FIGURE 12.1 Optimum salinity of an alkaline-surfactant system as a function of WOR and surfactant concentration. Source Zhang et al. (2006). 

Figure 12.2 shows that the optimum salinity increases as the soap/surfactant ratio decreases. During ASP flooding, oil saturation decreases from the downstream (the displacing front) to the upstream. Because soap concentration is proportional to oil saturation, the soap/surfactant ratio would likely decrease. The soap generated in situ is a surfactant different from the injected synthetic surfactant. These two surfactants have different properties. Generally, the injected surfactant is more hydrophilic than the soap. Thus, the optimum salinity of soap is lower than that of the synthetic surfactant. As the soap/surfactant ratio decreases, the optimum salinity would increase. Consequently, the salinity upstream would likely be lower than the optimum salinity, resulting in a local Winsor 1 environment. Such a microemulsion environment is desirable. 

Zhao et al. (2008) used an activity map like the one in Figure 12.5 showing the sodium carbonate concentrations as a function of the ratio of oil concentration in vol.% to surfactant concentration in wt.%. They assumed that this ratio corresponds to the ratio of soap to surfactant because the amount of soap generated by the alkali is proportional to the oil concentration. They used the concentration ratio of oil to surfactant based on the finding shown in Figure 12.2 that the optimum salinity is independent of WOR when the ratio is used. They used oil concentration instead of soap concentration for convenience (without any calculation in the laboratory). As the ratio decreases, the more hydrophilic mixture causes the phase behavior to change from Winsor 111 to Winsor 1. 

Based on Eq. 12.1, optimum salinity follows the logarithmic mixing rule. Mohammadi et al. (2008) replaced the ratio of oil to surfactant concentration shown in Figure 12.5 by soap molar fraction and used the more generally effective salinity in the vertical axis. They did so because they could get these values from UTCHEM simulation models. Based on the logarithmic mixing rule, both axes in such activity maps are in logarithmic scales, and the upper and lower boundaries should be linear. 

At the concentrations of alkali above that required for minimum interfacial tension, the systems become overoptimum. The excess alkali plays the same role as excess salt. When synthetic surfactants are added, the salinity requirement of alkaline flooding system is increased. NEODOL 25-3S is such a synthetic surfactant used by Nelson et al. (1984). Figure 12.4, shown earlier, is a composite of three activity maps for 0, 0.1, and 0.2% of NEODOL 25-3S as a synthetic surfactant for 1.55% sodium metasilicate with Oil G at 30.2°C. We can see in the figure that without the synthetic surfactant, the active region of this system is below the sodium ion concentration supplied by the alkali. However, with 0.1 and 0.2% of NEODOL 25-3S (60% active) present, the active region is above the sodium ion concentration supplied by the alkali, so additional sodium ions must be added to reach optimum salinity. 

Salinity was found to decrease foam stability. The surfactant concentrations in which foaming ability increased with concentration were 0 to 0.5%. The optimum polymer molecular weight for foaming ability was around 17 million. Core flood tests showed that ASPF incremental oil recovery factor over ASP was above 10% because the ASPF sweep efficiency was higher than the ASP efficiency. 

The characteristic parameter of the surfactant can be estimated by the use of the corresponding correlations (Eqs. (3.3) and (3.4)). For anionic surfactants for instance, salinity scans with a given oil, alcohol type and concentration and temperature, would allow to determine the optimum salinity (S in wt.% NaCl) for each tested surfactant, and thus estimate the value of the surfactant characteristic parameter a from Eq. (3.3). Another way to characterise a surfactant is by using the double-scan technique (see Fig. 3.7). A first scan, e.g. a salinity scan, is carried out with a given set of (not-to-be changed) variables such as oil phase, alcohol type and concentration and temperature. With the first (known) surfactant (subscript 1), the optimum salinity Sj is such that... 

The effect of surfactants Figure 6 shows that the microemulsion volume is proportional to the surfactant concentration as reported previously (8,10). However, in some cases it appears that the optimum salinity in a given system varies with this concentration when the surfactant used is not an isomerically pure product. It has been pointed out, for instance, by interfacial tension measurements that by increasing the petroleum sulfonate (TRS 10-80 supplied by Witco Chemical Company) concentration, the preferred alkane molecular weight is decreased. This shift occurs apparently because there is a dependence of the mean micellar and monomeric molecular weights on the total surfactant concentration (9,11). 

Figure 2 shows the test tube aspect of a salinity scan with an anionic surfactant at a concentration about 1 wt. % and for WOR = 1. hi all test tubes the surfactant, oil, alcohol, and temperature are the same, i.e., in Eq. 4 all values are set but sahnity. The test tube that exhibits three-phase behavior corresponds to the salinity S = 2.2% NaCl, so-called optimum sahnity in this case, which satisfies HLD = 0 according to Eq. 4. 

The temperature (or salinity) at which optimal temperature (or optimal salinity), because at that temperature (or salinity) the oil—water interfacial tension is a minimum, which is optimum for oil recovery. For historical reasons, the optimal temperature is also known as the HLB (hydrophilic—lipophilic balance) temperature (42,43) or phase inversion temperature (PIT) (44). For most systems, all three tensions are very low for Tlc < T < Tuc, and the tensions of the middle-phase microemulsion with the other two phases can be in the range 10 5—10 7 N/m. These values are about three orders of magnitude smaller than the interfacial tensions produced by nonmicroemulsion surfactant solutions near the critical micelle concentration. Indeed, it is this huge reduction of interfacial tension which makes micellar-polymer EOR and its SEAR counterpart physically possible. 

Surfactant Mixing Rules. The petroleum soaps produced in alkaline flooding have an extremely low optimal salinity. For instance, most acidic crude oils will have optimal phase behavior at a sodium hydroxide concentration of approximately 0.05 wt% in distilled water. At that concentration (about pH 12) essentially all of the acidic components in the oil have reacted, and type HI phase behavior occurs. An increase in sodium hydroxide concentration increases the ionic strength and is equivalent to an increase in salinity because more petroleum soap is not produced. As salinity increases, the petroleum soaps become much less soluble in the aqueous phase than in the oil phase, and a shift to over-optimum or type H(+) behavior occurs. The water in most oil reservoirs contains significant quantities of dissolved solids, resulting in increased IFT. Interfacial tension is also increased because high concentrations of alkali are required to counter the effect of losses due to alkali-rock interactions. 

In this relation. T is the temperature at optimum formulation where R = t, i.e.. [he PIT according to Shinoda s prcmi.se, an expression that deserves the latter label HLB-temperature. This relationship is very close to the one deduced b some re.searchers (78) who used the surfactant HLB instead EON-a to arrive to u similar result as far as the combined effects of temperature, salinity, and oil ACN are concerned. The above formula indicates how the PIT increases with the number of ethylene oxide groups in the surfactant molecule, increases with oil chain length, and decreases with electrolyte concentraiion and surfactant tail length (proportionally to a). It also predicts a variation with the alcohol type and concentration, a decrease with lipophilic. species. 

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