Low-salinity water flooding by a novel hybrid of nano γ-Al2O3/SiO2 modified with a green surfactant for enhanced oil recovery

This paper introduces a hybrid enhanced oil recovery (HEOR) method that combines a low-salinity water flooding (LSWF) and nanoparticles (NPs) stabilized with a green surfactant. We experimentally investigated the use of combinations of silica (SiO2) and gamma alumina (γ-Al2O3) nanohybrids stabilized with Gum Arabic (GA) at different water salinities. Nanofluids (NFs) were prepared by dispersing γ-Al2O3 and SiO2 NPs (0.1 wt%) in deionized water (DW), synthetic seawater (SSW), 2, 5, and 10 times diluted samples of synthetic seawater (in short 2-DSSW, 5-DSSW and 10-DSSW, respectively). The challenge is that NPs become unstable in the presence of cations in saline water. Moreover, an attempt was made to introduce NFs with high stability for a long period of time as the optimal NFs. The effects of temperature on the behaviour of optimal NFs in the presence of different base fluids, distinct mass ratios of γ-Al2O3/SiO2 and various concentrations of surfactant were analysed via interfacial tension (IFT) and viscosity measurements. The results of the viscosity measurement showed that with increasing temperature, the NPs dispersed in DW had lower viscosity than NPs dispersed in various salinities. However, the IFT measurement for NPs dispersed in different base-fluids revealed that with increasing temperature and presence of cations in saline water, IFT values decreases. Although, the minimum IFT for hybrid nanofluid (HNF) γ-Al2O3/SiO2 modified with GA and dispersed in 10-DSSW was reported 0.99 mN/m. Finally, according to the micromodel flooding results, in oil-wet conditions, the highest oil recovery for combination γ-Al2O3/SiO2 modified with GA and dispersed in 2-DSSW was reported 60.34%. It was concluded that NFs modified with GA could enhanced applicability of LSWF via delay in breakthrough time and improving sweep efficiency.

of 54.18 lb/ft 3  (31.47°API) and a viscosity of 25.93 CST was used from the Gachsaran oilfield in Iran for the IFT and flooding experiments (Table 2).
Table 3 lists the properties of the brine compositions used in this paper.Hexamethyldisilane, Si 2 (CH 3 ) 6 was utilized to change the wettability of the micromodel from water-wet to oil-wet.Toluene (C 7 H 8 ) and methanol (CH 3 OH) were used as wettability-changing agents and washing, respectively, both of which afforded 99% purity.
GA was used as a surfactant to aid in dispersing the NPs and improving the stability of the suspensions; It was purchased from Merck.GA is a natural polysaccharide obtained from the tree Acacia Senegalese.GA is a multicomponent substance, the majority of which consists of approximately 98 wt% polysaccharide and the smallest fraction consists of 2 wt% protein-polysaccharide.Peptides form the hydrophobic part and polysaccharides form the hydrophilic part of GA.Peptides are adsorbed on the oil surface.However, polysaccharides as the most hydrophilic component, stabilize oil droplets with a negative charge on carboxylates 41,42

Experimental equipment
A 2D glass micromodel was used as the porous medium and images were obtained from a CT scan of the core 44 .
The micromodel was a 2D glass sheet with narrow pores etched on its surface.A piece of engraved glass was placed on the other part of the glass.Then, both parts of the glass were placed in the furnace and fused at 730 °C.
The glass sheets bond at high temperatures to form a single piece.Thus, only the engraved pattern and drilled holes are open for flow 14 .The inlet and outlet channels of the micromodel for fluid injection and production are shown in Fig. 1.Additionally, one of the advantages of the glass micromodel is its chemical inertness and its substrate is easily visible 4 .It consists of a 5 × 5 cm 2 matrix and an etch depth of 460 µm corresponding to a porous media with 41.13% porosity and a 0.51 cm 3 pore volume (PV).Measured IFT between crude oil and NFs dispersed in aqueous phases (DW, SSW, 2-DSSW, 5-DSSW and 10-DSSW) at 25 °C and 60 °C.The system was equipped with a CCD camera and a computerized macro lens.The formed droplets were analysed by professional drop shape analysis software (Apex DSA) based on pendant drop methods.A photo of the IFT device is shown in Fig. 2.After each test, the IFT measurement chambers for crude oil and NFs were washed with distilled water and toluene.www.nature.com/scientificreports/A Brookfield DV3T digital viscometer was used at different temperatures to measure the viscosity of the NFs.The temperature was continuously measured and controlled by a sensor.The spindle ULA was utilized for measuring low viscosity.After selecting the optimal NFs, 16 ml of the 0.1 wt% solution was added to the container with a thermal jacket connected to the rheometer at a constant shear rate of 73 (1⁄S).Before the viscosity of the NFs was measured, distilled water was used to calibrate the device and reduce error.

Methodology Designing experiments
The Taguchi method was used to determine the stability of the nanosolutions in response to low-salinity water (ppm), the mass fraction of γ-Al 2 O 3 /SiO 2 (wt%) and the surfactant concentration (ppm) as operating variables.The Taguchi method is based on three factors and five levels and was used to determine the optimal process characteristics that minimize the sensitivity 45 .In this research, the first factor was the salinity of the water, the second was the mass fraction of γ-Al 2 O 3 /SiO 2 and the third was the concentration of GA.According to the factors and their levels in Table 4, an L-25 orthogonal arrangement was used to design the experiments.Since most of the stability was used in the response, a larger qualitative characteristic was chosen as the better criterion.The average values of the two generated responses were considered the original response.
The stability test results were analysed with a signal-to-noise diagram.In this way, if the quality characteristic is large or better, the signal-to-noise ratio (S/N) is calculated as follows: The signal-to-noise ratio is calculated from the mean square of the standard deviation (MSD), where Y i is the result of N repeated experiments 46,47 .

Preparation of NFs and selection of optimal NFs (screening)
The preparation of hybrid nanofluids (HNFs) involves different steps.Each step has different results.There has been no consensus among researchers about predicting HNFs 18 .In the first step, the solutions were prepared by adding NPs and GA to base fluids with various salinities.Next, the solutions were homogenized by a magnetic stirrer at 500 rpm for 15 min.Finally, to ensure the complete dispersion of the NPs in the base fluids, the mixture was sonicated for 1 h.Due to the instability of NFs in saline water and rapid aggregation, screening was performed.On an operational scale, the aggregation of NPs causes leakage around the injection well, which ultimately causes damage to the formation in the areas around the injection well 48 .

Micromodel test
In the first step, the micromodel was washed with sodium hydroxide solution and saturated for 30 min.Next, the vacuum pump evacuated the micromodel from any trapped fluid or air.To ensure that no fluid was trapped in the micromodel, the micromodel was washed with DW and dried in an oven at 200 °C.The micromodel was saturated with 2% hexamethyldisilane and 98% toluene for 30 min, as shown in Fig. 3, after which the glass surfaces became completely oil wet.Toluene and methanol were used to clean the micromodel.Finally, the micromodel was dried in an oven at 100 °C.All flooding tests were performed at atmospheric pressure and ambient temperature.The micromodel was placed horizontally to remove the effects of gravity 14 .
(1) Flooding of the micromodel took place in three steps: 1.The micromodel was saturated with formation water.2. The micromodel was saturated with oil.
All analyses performed on the micromodel were based on photographs taken.Micromodel photographs were taken every 0.2 PV for all the tests.Figure 4 shows that a syringe pump was used to injection the fluids.A digital microscope camera (digimicro1/3) that located above the micromodel was used for imaging.Finally, the images were analysed using image processing software to calculate the oil recovery factor.The oil recovery factor is calculated by Eq. 3, where the initial oil saturation (S oi ) and the residual oil saturation (S or ).

Stability evaluation of the nanosolutions
Among the 25 NFs prepared, 15 had longer stability times.These nanosolutions with longer stability times were selected as the optimal NFs.In Table 5, the optimal NFs are shown with (*).The stability test was performed visually, similar to the methods of other researchers 21,28,48 .Sediment formation was observed at intervals of time on day one (1) and day sixty-third (63).In Fig. 5, photos of the stabilities of the different NFs are shown.(a) Two hours after preparation (b) 48 h after preparation.The NFs were considered stable when their dispersity remained constant in various base fluids, indicating that no sedimentation had formed.The interval time when sedimentation occurred at the end of the test tube and phase separation occurred at the top of the laboratory tube was considered the instability of the NFs.
In rows 10, 14, 18, and 22 of Table 5, NFs for which GA was not used as a surfactant are shown.The duration of their stability was reported to be less than 2 h.However, the addition of different surfactants, such as ionic sodium dodecyl benzene sulfonate (SDBS) and CTAB, nonionic surfactants (Span 80, Tween 20) and polymers polyvinyl alcohol (PVA) and GA during NF preparation can also control particle aggregation 49 .This finding could indicate that the increase in stability with surfactant coating on NPs leads to the dominance of electrostatic repulsion over van der Waals attraction and thus prevents the accumulation of NPs.
According to the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory, two forces cause the dispersion of particles: the van der Waals force of attraction and the electrostatic repulsion force of the double layer.The aggregation of NPs leads to their instability and in the case of nonaggregation their stability is maintained.
Salinity causes the instability of nanosuspensions 50 .In the rows 21-25 of Table 5, the NFs dispersed in SSW had the lowest stability.However, the NFs dispersed in DW had the highest stability compared to that of all the prepared nanosolutions.The first row of Table 5 shows that the SiO 2 NPs were stable in DW without surfactant for 63 days.Additionally, according to the results of Zulkeflee and Mamat 51 the addition of GA surfactant to silica NPs dispersed in DW improves the stability time compared to dodecylbenzene sulfonic acid (DBSA) and Chinese ink (CI) surfactants.In the 21st row of Table 5, silica NPs were dispersed in SSW with 1000 ppm GA and were stable for 65 h.According to the results of Hamdi et al. 52 the functional groups of GA modify the surface of www.nature.com/scientificreports/NPs and reduce the effect of van der Waals forces between nanosheets.As a result, more stable NFs were created even in high-salinity environments for a longer time.In row 5 of Table 5, the maximum stability time was 16 h for γ-Al 2 O 3 NPs dispersed in DW with 1000 ppm GA.Divalent cations such as Ca 2+ can effectively neutralize the negative charge of SiO 2 NPs.Therefore, when the van der Waals force of attraction between particles is greater than the electrostatic repulsion force, the accumulation and instability of the solution occur 53 .HNFs exhibit different behaviours when dispersed in DWs and brines.They are completely hydrophilic when dispersed in DW and have good stability, while they tend to cause  sedimentation in brine.However, adding surfactants to HNFs results in a smaller aggregation size than in the absence of a surfactant 54 .The presence of monovalent cations such as Na + in brine reduces the negative surface charge on silica NPs.Because silica NPs absorb monovalent cations such as Na + present in brine, the stability of the solution decreases 17 .The dispersion of divalent ions such as Ca 2+ and Mg 2+ in brine results in amphoteric properties in HNFs 6 .Three factors, the base-fluid salt concentration, mass fraction of nanosolutions and GA concentration, were studied to investigate the duration of stability, as shown in Fig. 6.The slope of the salinity graph could indicate an increase in the concentration of polyvalent ions.The results showed that the stability of HNFs with different mass fractions decreased with increasing amounts of alumina NPs, which could be due to the tendency of alumina to aggregate.Therefore, it is necessary to use stabilizers for the dispersion of alumina NPs 12 .Throughout the stability evaluation of the nanosolutions dispersed in the base fluid types, the highest stabilities were as follows: SiO 2 NPs > combination of γ-Al 2 O 3 /SiO 2 with a mass fraction of 10:90 > combination of γ-Al 2 O 3 /SiO 2 with a mass fraction of 30:70 > γ-Al 2 O 3 NPs > combination of γ-Al 2 O 3 /SiO 2 with a mass fraction of 50:50.According to the results shown in Fig. 6, the most suitable concentration for GA was reported 250 ppm.At low surfactant concentrations, due to the Gibbs adsorption effect, surfactant molecules are absorbed at the fluid-solid interface, which causes a decrease in the surface energy between the fluid and NPs, ultimately leading to a decrease in the aggregation of NPs 54 .

IFT measurement
Any change in water composition (ionic or nonionic) could change the IFT.All IFT tests were performed at constant pressure.To ensure the reproducibility of the results and to determine the standard error, IFT measurements were performed at least seven times for the optimized NFs.According to the results of Afzalitabar et al. 55 adding HNFs reduces the IFT. Figure 7 shows the IFT of NFs at 25 °C.HNFs γ-Al 2 O 3 /SiO 2 with different mass fractions have lower IFT than SiO 2 NPs; however, their IFT is greater than that of γ-Al 2 O 3 NPs.Figure 7 shows that the IFT of NFs decreases as the temperature increases from 25 to 60 °C.At high temperatures, the IFT decreases, which could be due to an increase in the brownian motion of NPs or the weak interaction between molecules, ultimately leading to improved oil recovery 56 .Figure 7 shows that with increasing temperature from 25 to 60 °C, the IFT for SiO 2 NPs decreased from 9.97 (mN/m) to 6.66 (mN/m) and that for γ-Al 2 O 3 decreased to 1.57 (mN/m) and 1.07 (mN/m), respectively.In another attempt, Nowerouzi et al. 57 reported that among the NPs of TiO 2 and MgO and γ-Al 2 O 3 , the most successful at reducing the IFT was related to γ-Al 2 O 3 .Figure 7 shows the IFT with increasing temperature from 25 to 60 °C for HNFs with mass fractions of 10:90, 30:70 and 50:50 and GA concentrations of 250, 500 and 750 ppm, from 5.71, 2.44 and 1.85 (mN/m) to 2.32, 1.7 and 1.47 (mN/m), respectively.The presence of NPs modified with GA could reduce the IFT between crude oil and displacing nanofluid.Adsorption of modified NPs with GA at the interface between oil and brine occurs due to the hydrophilic and hydrophobic functional groups of the modified NPs, which cause the modified NPs to act as amphiphilic surfactants.Finally, the functional groups of the modified NPs create an additional layer at the interface between brine and oil to reduce the IFT 52 .
The effect of salt on IFT values in oil-salt water-containing systems is complex.A water-in-oil emulsion is formed in the presence of surfactants at low salt concentrations.In this system, increasing the amount of salt causes a further decrease in IFT.An oil-in-water emulsion is formed at high salt concentrations and the IFT www.nature.com/scientificreports/increases with increasing salt concentration 58,59 .Adsorption of cations at the interface occurs due to the interaction between cations and the hydrocarbon phase.The interface concentration increases or becomes positive due to the placement of cations at the interface.As a result, the IFT decreases with decreasing salinity.However, at high brine concentrations, the cations are surrounded by water molecules, so the cations are less inclined to transfer to the interface.Separation of cations from the interface could reduce the positive charge of the interface.As a result, the IFT increases at high brine concentrations 59 .
Figure 8a shows the IFT of the NFs dispersed in 10-DSSW at ambient temperature and 60 °C.As shown, the NFs dispersed in 10-DSSW at 25 °C had a lower IFT than did the NFs dispersed in DW.This could be due to the reduction in IFT at low salt concentrations.The combination of HNF γ-Al 2 O 3 /SiO 2 with a mass fraction of 50:50 modified with GA dispersed in 10-DSSW had the minimum IFT of 0.99 (mN/m) in 60 °C compared to that of the other NFs.However, Khaksar et al. 60 reported the lowest IFT for silica-bentonite nanocomposite treated with anethum graveolens surfactant dispersed in 10,000 ppm NaCl at 1.73 (mN/m).
By increasing temperature, SiO 2 NPs and HNFs with mass ratios of 10:90 and 30:70 were modified with GA (250, 500 and 750 ppm) respectively, their IFT decreased 1.57, 1.7 and 1.08 (mN/m).However, the results showed that the NFs dispersed in 10-DSSW had the lowest IFT.
Figure 8c shows that with increasing salinity of the base fluid, the IFT of the SiO 2 NPs and HNF γ-Al 2 O 3 / SiO 2 dispersed in 2-DSSW increased at ambient temperature compared to that of the NPs dispersed in 5-DSSW.This increase in the IFT of the NFs dispersed in 2-DSSW could be due to the high concentration of salt.As mentioned, increasing the salt concentration could reduce the separation of cations from the interface.Therefore, the silica NPs and HNF γ-Al 2 O 3 /SiO 2 dispersed in 2-DSSW at ambient temperature had an IFT of 2.7 and 4.7 (mN/m) respectively.On the other hand, with increasing temperature, the IFT of the NFs dispersed in 2-DSSW decreased.However, in Fig. 8d, the IFT for SiO 2 NPs dispersed in SSW modified with 1,000 ppm GA at ambient temperature and 60°C was reported 2.1 and 1.52 (mN/m), respectively.

Viscosity measurement
The dynamic viscosities of the optimal nanosolutions were measured at temperatures of 25 °C, 35 °C, 45 °C and 55 °C.As shown in Fig. 9, the NFs dispersed in DW had lower viscosities than the NFs dispersed in various salinities.The results of Hashemzadeh and Hormozi 34 showed that γ-Al 2 O 3 and SiO 2 NPs dispersed in DW have relatively the same viscosity in the temperature range 10-55 °C.However, Fig. 9 shows that γ-Al 2 O 3 NPs have a higher viscosity than SiO 2 NPs.However, with increasing temperature, the viscosity of γ-Al 2 O 3 decreases significantly compared to that of silica.The reason for this difference could be the presence of GA, which was applied together with the γ-Al 2 O 3 NPs dispersed in DW at a mass ratio of 1:1.However, no surfactant was used with SiO 2 NPs.As the temperature increases, the viscosity of the NFs decreases 61,62 .As inferred by Ma et al. 54 adding surfactant improves nanofluid viscosity.According to the results of Buckley and Leverett 63 , decreasing mobility of the displacing fluid delays the breakthrough time.Additionally, the brownian motion of NPs induces interactions with surface-active compounds at the water-oil interface by attracting natural surfactants at the interface, thus reducing the IFT and improving oil recovery 14 .The reduction in nanocolloidal viscosity largely depends on the NPs and base fluids used.HNFs have a higher viscosity than do normal fluids and nanofluids.However, the viscosity of HNFs depends on the selected NPs and their composition 62 .
HNFs with mass ratios of 10:90 and 30:70 had lower viscosities than SiO 2 and γ-Al 2 O 3 NPs at low temperatures.However, with increasing temperature, the viscosity of these NFs increased compared to that of mono NFs.However, for HNFs a mass ratio of 50:50 was reported to result in a lower viscosity than that of mono nanofluids and this trend was observed at all the measured temperatures.In general, the viscosity of HNFs is greater than that of base fluids and single NPs 34,62 .
Figure 10a shows the viscosity as a function of temperature for SiO 2 NPs and HNFs with mass ratios of 10:90, 30:70 and 50:50 modified with 250, 500, 750 and 1,000 ppm GA dispersed in 10-DSSW.The results show that HNFs with different mass ratios at different temperatures (25, 35, 45 and 55 °C) have higher viscosities than silica NPs and the lowest viscosity is obtained for SiO 2 NPs at 55 °C.However, the combination of γ-Al 2 O 3 /SiO 2 dispersed in 10-DSSW with a mass fraction of 50:50 has a higher viscosity than other nanosolutions at 25 °C.Although, by increasing temperature the combination of γ-Al 2 O 3 /SiO 2 with a mass fraction of 50:50 the measured viscosity difference between 25 and 55 °C was reported 0.29 cp, which was observed greater than that of another HNFs with mass ratios of 10:90 and 30:70.
Figure 10b shows that the silica NPs dispersed in the 5-DSSW modified with 500 ppm GA at 25 °C had a greater viscosity than did the HNFs with mass ratios of 10:90 and 30:70 that, modified with 750 and 1000 ppm GA.However, with increasing temperature to 35 °C, the viscosities of the silica NPs and HNFs are somewhat equal.At high temperatures, the viscosity of HNFs was greater than the viscosity of silica NPs.The results showed that silica NPs and HNFs with a mass ratio of 10:90 exhibited a decreasing trend with increasing temperature, while the lowest viscosity was reported for the combination of HNF γ-Al 2 O 3 /SiO 2 with a mass fraction of 30:70 at 45 °C.
Figure 10c shows that the HNF with a mass ratio of 10:90 and 1,000 ppm GA dispersed in 2-DSSW, compared to the viscosity of the SSW at 25 °C and 55 °C, has a lower viscosity than the silica NPs with 750 ppm GA.At 45 °C, the viscosities of the combinations of HNF γ-Al 2 O 3 /SiO 2 with a mass fraction of 10:90 and silica NPs  were equal.Moreover, the viscosity of the optimal NFs dispersed in 2-DSSW decreased.As shown in Fig. 10d, the viscosity of the silica NPs dispersed in SSW decreased with increasing temperature.

Flooding tests
Figure 11 shows that when NFs were dispersed in DW, breakthrough occurred after 0.4 PV.According to the results of the micromodel flooding, the minimum oil recovery was 34.4% when SiO 2 NPs were injected into DW.Additionally, oil recovery was reported during the injection of γ-Al 2 O 3 NPs (35.82%).According to the results of Nowrouzi et al. 57 γ-Al 2 O 3 NPs improve oil recovery by reducing the IFT and viscosity.However, during the injection of HNFs γ-Al 2 O 3 /SiO 2 with mass fractions of 10:90, 30:70 and 50:50 and concentrations of 250, 500 and 750 ppm GA, oil recoveries of 38.92%, 43.2% and 45.85%, respectively, were obtained.In all the flooding tests, the synergistic effect of injecting HNFs was evident, and the oil recovery was greater than that of mono NFs.In similar studies, Khaksar et al. 60 showed that SiO 2 /bentonite nanocomposites modified dill and hop surfactants can improve the oil recovery.The modified nanocomposite with 4000ppm dill extract can improve oil recovery by 14% of original oil in place.Their results confirmed the effectiveness of the formulated green nano-solution as a sustainable and consistent method with the environment in the EOR process.HNFs increase oil recovery by transporting more residual oil.However, compared with water flooding, GA flooding improved the oil recovery factor on average by 4.6%.GA can reduce the IFT between brine and oil through its migration to the oil-water interface, where the hydrophobic polypeptide chain of GA reacts with oil and the hydrophilic arabinogalactan unit of GA reacts with water.Additionally, adding GA to silica and alumina NPs improved the oil recovery factor by 14.4% and 20.9%, respectively 64 .
Figure 12 shows that breakthrough occurs at 0.5 PV when the NFs are dispersed in 10-DSSW.The oil recoveries during the injection of SiO 2 NPs and HNFs with mass fractions of 10:90, 30:70 and 50:50 along with different concentrations of GA were reported as 45, 45.75, 46.28 and 57.75%, respectively.We observed that, among the optimized NFs that were stably dispersed in 10-DSSW, HNF γ-Al 2 O 3 /SiO 2, with a mass fraction of 50:50 and modified with 1,000 ppm GA, initially had lower oil recovery than the other NFs.However, after 0.8 PV, the oil recovery of the HNF γ-Al 2 O 3 /SiO 2 composite increased significantly.
As evident in Fig. 13, a delayed breakthrough occurred when the NFs dispersed in 5-DSSW were injected in comparison to the NFs dispersed in 10-DSSW, and the breakthrough time occurred at 0.6 PV.The oil recovery during the injection of SiO 2 NPs and HNFs with mass fraction 10:90 and 30:70 and modified with 500, 750 and 1000 ppm GA were reported 43.8, 46.77 and 49.68%, respectively.We observed in micromodel flooding tests that increasing the concentration of brine can improve oil recovery.According to the results of Rostami et al. 4 , NPs dispersed in brines have a better performance in improving the oil recovery compared to NPs dispersed in deionized water.NPs flooding modified with GA compared with water flooding, has a greater ability to sweep out oil.The ability of the modified NPs to reduce the IFT between the crude oil and nanofluid solutions ultimately reduced the capillary pressure inside the pores.Additionally, the modified nanofluids alter the wettability of the pores surface to strong water wetting 52 .
Figure 14a shows that, for NFs dispersed in 2-DSSW breakthrough occurs delayed at 0.8 PV compared to NFs dispersed in 5-DSSW.We observed a maximum oil recovery of 60.34% when the combination of γ-Al 2 O 3 /SiO 2 was injected with a mass fraction of 10:90 dispersed in 2-DSSW.On the other hand, Khaksar et al. were achieved the maximum oil recovery factor for KCl-SiO 2 -xanthan nanocomposite treated with the aloe vera biopolymer surfactant at 73.35%.They also attributed the increase in oil recovery to the reduction of IFT, wettability alteration and mobility improvement mechanisms 65 .Figure 14b shows that by injecting 0.1 wt% SiO 2 nanofluid dispersed in SSW into the micromodel, 51.53% oil recovery was obtained.

Conclusions
In this experimental study, the effects of mono/hybrid γ-Al 2 O 3 /SiO 2 nanofluids dispersed at various salinities and modified with GA surfactant on the stability, viscosity, IFT and oil recovery were investigated.The results showed that the NFs became highly unstable with increasing salt concentration to 40,710 ppm and quickly accumulated at the end of the test tube.However, the NFs that were not modified with GA became unstable after approximately 2 h.The stability of NPs in base fluid is essential for the long-term utilization of NFs, particularly for EOR applications.
In addition, the effects of temperature, various salinities of base fluid and mass fractions of γ-Al 2 O 3 /SiO 2 on the viscosity and IFT of long-term stable NFs were evaluated.The results of the IFT evaluation showed that increasing temperature had a greater effect on the dispersal of NFs at various salinities than on the dispersion of NFs in DW.However, the results clearly showed that with increasing salinity to 20,400 ppm the IFT increased.
Also, the evaluation of viscosity results shows that with increasing temperature, NFs dispersed in DW have lower viscosity than NFs dispersed in various salinities.According to results of experimental viscosity data nanohybrids with different mass fractions by increasing temperature show different action in the presence of cations in salt water and deionized water.The lowest viscosity was observed at 55 °C for the nanohybrid γ-Al 2 O 3 / SiO 2 with a mass fraction of 50:50 dispersed in deionized water.
The results of the micromodel flooding test showed that increasing the salinity of the base fluid leads to a delay in breakthrough.In this way, NFs dispersed in DW were observed at 0.4 PV breakthrough time; however, NFs dispersed in 2-DSSW were reported at 0.8 PV breakthrough time.

Figure 1 .
Figure 1.Schematic of the 2D glass micromodel based on the image obtained from the core CT scan 42 .The pore bodies are black and the rocks are white.

Figure 2 .
Figure 2. The photo of the IFT measurement device was used for optimal NFs.

Figure 3 .
Figure 3. Water droplet contacting the oil-wet glass surface.

Figure 4 .
Figure 4. Schematic of the flooding setup.

Figure 6 .
Figure 6.Results obtained from the taguchi method and the quality characteristic was selected large-the better.To investigation the salinity, the mass ratio of γ-Al 2 O 3 to SiO 2 and concentration of GA in NFs.

Figure 7 .
Figure 7.The effect of temperature on IFT of optimal NFs dispersed in DW.At ambient and 60 °C.

Figure 14 .
Figure 14.Oil recovery during injection of different NFs in to the oil-wet micromodel.(a) SiO 2 NPs and HNFs γ-Al 2 O 3 /SiO 2 with mass fractions 10:90 modified with GA dispersed in 2-DSSW.(b) SiO 2 NPs modified with GA dispersed in SSW.

Figure 15
Figure15shows micromodel images used for sweep efficiency calculations.The images show the injection of some NFs after the injection of 1 PV into the treated to oil-wet micromodel.From these images, it could be concluded that the injection of HNF γ-Al 2 O 3 /SiO 2 in combination with a mass fraction of 10:90 dispersed in 2-DSSW with 1,000 ppm GA into the micromodel had the highest areal sweep efficiency.Figure15eshows the synergistic effect of HMF γ-Al 2 O 3 /SiO 2 modified with GA dispersed in 2-DSSW, which increased the displacement efficiency of the oil mixture among the other injection scenarios.Figure15aalso shows that the silica NPs dispersed in DW without GA had the lowest oil recovery among the other optimal NFs.

Table 1 .
. The results Review of some research performed using the HEOR methods.
39Nanocomposites silica and alumina based on polyacrylamide (NCSAP), surfactant (CTAB) and polyacrylamide (PAM)IFT, contact angle and oil recoveryThe most effective mechanism in oil recovery for light oil and heavy oil were reported IFT reduction and mobility control, respectively40

Table 2 .
The composition of crude oil.

Table 3 .
Composition of various synthetic water.

Table 5 .
The results were obtained from the duration of stability.