Development of Composite Materials Based on the Interaction

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Materials and Interfaces

Development of Composite Materials Based on the Interaction between Nanoparticles and Surfactants for Application on Chemical Enhanced Oil Recovery Stefania Betancur, Francisco Carrasco-Marín, Camilo A. Franco, and Farid B. Cortés Ind. Eng. Chem. Res., Just Accepted Manuscript • DOI: 10.1021/acs.iecr.8b02200 • Publication Date (Web): 21 Aug 2018 Downloaded from http://pubs.acs.org on August 25, 2018

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Industrial & Engineering Chemistry Research

Development of Composite Materials Based on the Interaction between Nanoparticles and Surfactants for Application on Chemical Enhanced Oil Recovery Stefanía Betancur1, 2, *, Francisco Carrasco-Marín2, Camilo A. Franco1, Farid B. Cortés1 1

Grupo de Investigación en Fenómenos de Superficie – Michael Polanyi, Facultad de Minas, Universidad Nacional de Colombia Sede Medellín, Kra 80 No. 65-223, Medellín, Colombia.

2

Grupo de Investigación en Materiales de Carbón, Departamento de Química Inorgánica, Facultad de Ciencias, Universidad de Granada, 18071, Granada, Spain. * Corresponding authors: [email protected]

ABSTRACT The main objective of this work is to develop a nanofluid based on the adsorption/desorption process of cationic, anionic and nonionic surfactants onto nanoparticles and its application in enhancing the process of oil recovery. The development of the nanofluids was divided into two experimental routes for understanding the adsorption phenomena of the surfactants (Cetyltrimethylammonium Bromide “CTAB”, Sodium Dodecyl Sulphate “SDS” and Polyoxyethylenesorbitan Monolaurate “Tween 20”) onto silica nanoparticles (SiO2) by i) simultaneous addition of nanoparticles and surfactant before micelles formation and ii) the addition of nanoparticles after micelles formation. The adsorption/desorption isotherms for determining the ability of nanoparticles to adsorb surfactants were obtained at 25, 50 and 70 °C using batch-mode experiments. The experimental adsorption isotherms were Type I and III depending on the route and the chemical nature of the surfactant and were adequately described by the Solid-Liquid Equilibrium (SLE) model. The amount adsorbed of surfactant onto nanoparticles decreased in the following order CTAB >

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Tween 20 > SDS and was higher for Route II than Route I. Meanwhile, the desorption percentages obtained were below of 2.0, 5.3 and 9.1 % for CTAB, Tween 20 and SDS, respectively. The thermodynamic behavior of surfactant adsorption onto SiO2 nanoparticles suggested that the adsorption was a spontaneous and an exothermic process. From the adsorption/desorption isotherms, a composite nanomaterial for enhancing oil recovery was obtained and was evaluated through interfacial tension (IFT) measurements and displacement tests using a micromodel. The composite material based on nanoparticles-surfactant did not generate a significant effect on interfacial tension compared to the surfactant solution. However, the nanofluid increased the oil recovery up to 240 % regarding surfactant flooding.

KEYWORDS: Surfactant, Nanoparticles, Adsorption, Chemical Enhanced Oil Recovery (CEOR).


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1. INTRODUCTION The recovery factor of mature oil fields worldwide ranges between 20 and 40 % and, at the current production oil rates, reserves will last about 50 years.1 This situation accompanied by the falling of the oil price experienced for the global economy since 20142 has made necessary the expansion of the supply of hydrocarbons through innovative methods that allow the improvement of the oil recovery. In the production history of a reservoir, various stages of recovery are identified, namely: primary, secondary and tertiary stage. The primary recovery process depends on the natural energy of reservoir. The secondary recovery results from increased natural energy by injecting water or gas to displace oil towards producing wells.3 Commonly, the waterflooding is the most used secondary recovery method. However, its application is limited in porous media where there is high horizontal and vertical heterogeneity, and those where the oil viscosity is high. In these cases, the tertiary oil recovery, also called enhanced oil recovery (EOR), has been used as an alternative process. The EOR methods imply a reduction in oil saturation below the residual oil saturation4 through of chemical methods, heat injection to the reservoir, miscible gas and biological processes.5, 6 Among these methods, chemical flooding takes particular importance due to the surface facilities where heat generation or gas availability are not available. Chemical EOR (CEOR) processes employ different chemical formulations composed mainly of polymer, surfactants and/or alkali to increase the capillary number, as well as decrease the mobility ratio.4, 7 Surfactant flooding is applied to recover the residual oil of reservoir after primary recovery or water injection by means of reduction of interfacial tension between water and oil.8, 9 It is estimated that the oil recovery in surfactant flooding processes is around 17 %. However, the efficiency of the surfactant injection is affected mainly by the ACS Paragon Plus Environment


adsorption of the chemical in the porous medium10, 11 which increases the amount of surfactant needed (due to its spending onto the rock) for obtaining additional oil and therefore leads to increased operational costs. Hence, due to the exceptional properties of nanoparticles,12 several researchers have studied the effect of the simultaneous application of nanoparticles and surfactants on enhanced oil recovery.13-17 These authors focused their work on the evaluation of surfactant-nanoparticles mixtures for reducing the adsorption of surfactant over the porous medium and improving the recovery of oil. For the experiments, the researchers employed different types of surfactants such as sodium dodecyl sulfate (SDS)18-20 and cetyltrimethylammonium bromide (CTAB), as well as nanoparticles of zirconium oxide (ZrO2)13 and silica gel (SiO2).13, 18-20 Further, it has been concluded that with the use of nanoparticles in the surfactants solutions, the adsorption onto the rock can decrease up to 13.6 %

18

and the oil recovery can be

increased up to 51 %.21 It is worth to mention that these applications have been achieved mainly through nanoparticle-surfactant mixtures without considering the interaction between both components for the nanofluid design. Only Wu et al.19 showed that trace amounts of surfactant molecules adsorbed onto silica nanoparticles surface leads to the reduction of the adsorption or spending of surfactant onto the rock. However, the authors in their work ignored the nanoparticle-surfactant interaction.22 The interaction between surfactant-nanoparticle based on the adsorption phenomena could be an essential factor for avoiding the synthesis process of a complex nanomaterial23 such as synthesis of surfactant on the surface of the nanoparticle, which can increase the operating costs. Therefore, the main objective of this study is to evaluate the adsorption/desorption process of cationic, anionic and nonionic surfactants onto SiO2 nanoparticles for the development of a nanofluid based on a composite


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material of nanoparticles-surfactant as an alternative CEOR method. For understanding the nanoparticles-surfactant interactions, the experiments were divided into two experimental routes: I) simultaneous addition of nanoparticles and surfactant before micelles formation and II) addition of nanoparticles after micelles formation. Batch experiments were performed to investigate the adsorption and desorption of surfactants of different chemical nature onto SiO2 nanoparticles. The experimental data was described by the Solid-Liquid Equilibrium (SLE) model. Likewise, adsorption potential and thermodynamic properties were determined. Additionally, the effect of nanoparticles-surfactant on interfacial tension and the recovery of crude oil was evaluated.

2. EXPERIMENTAL SECTION 2.1.Materials Sodium chloride (99%, PanReac, Spain) and deionized water were used to prepare brine for all experiments. A cationic surfactant, Cetyltrimethylammonium Bromide “CTAB” (98%, PanReac, Spain), an anionic surfactant Sodium Dodecyl Sulfate “SDS” (85%, PanReac, Spain), and a nonionic surfactant named Polyoxyethylenesorbitan Monolaurate “Tween 20” (≥ 40%, Sigma-Aldrich, United States) were used for sorption experiments. Silica (SiO2) nanoparticles were purchased from Sigma-Aldrich (United States). The estimated value of Brunauer, Emmett and Teller (BET) surface area and particle size of SiO2 nanoparticles were 389.1 m2 ⋅ g-1 and 7 nm, respectively, as described in previous works.24 A light crude oil with 33.2°API obtained from a reservoir in Colombia was used for interfacial tension experiments and displacement tests in micromodel. The average content of saturated, aromatics, resins and asphaltenes (SARA) of crude oil was determined using an Iatroscan MK-6 thin layer chromatograph ACS Paragon Plus Environment


following the IP 469 method.25 Ottawa sand (Minercol S.A., Colombia) of 50/60 sieve was used for the displacement tests in a micromodel. 2.2.Methods 2.2.1. Determination of Critical Micelle Concentration (CMC) The critical micelle concentration (CMC) of cationic, anionic and nonionic surfactants was determined by dynamic light scattering (DLS) at 25 and 70 °C. The surfactant solutions were magnetically stirred for 2 hours at 600 rpm and left to stand for 24 hours to allow interaction between the surfactant molecules. UV-Vis spectrophotometry measurements were performed with a GENESYS 10S UV-Vis spectrophotometer (Thermo Scientific, Waltham, MA) at a wavelength between 190 and 205 nm for the different surfactants. DLS measurements were performed on a Nanoplus-3 particle analyzer (Micromeritics, Norcross, ATL). Surfactant concentrations between 100 and 10000 mg·L-1 were considered for the experiments. Plots of average particle size versus each surfactant concentration were generated, and the CMC was determined by a trend change in each scenario. 2.2.2. Sorption experiments Adsorption isotherms of surfactants over SiO2 nanoparticles Two different routes were employed for the adsorption isotherms due to the interactions between the surfactants and the nanoparticles can be affected by the micellization of the surfactant. In this way, the sorption experiments were divided into two routes for understanding the surfactant-nanoparticle behavior and thus determining the formulation of the injection fluid. The two routes used are the following: I) the simultaneous addition of nanoparticles and surfactant, and II) addition of nanoparticles after micelles formation. The adsorption experiments for the two routes between the


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adsorbates (surfactant such as CTAB, SDS and Tween 20) and SiO2 nanoparticles were performed in a GENESYS 10S UV-Vis spectrophotometer (Thermo Scientific, Waltham, MA) with a ± 0.001 a.u. of uncertainty in the absorbance measurement. For the experiments, a calibration curve of absorbance versus surfactant concentrations was constructed. The sorption experiments were carried out at 25, 50 and 70 °C. It is worth to mention that the CMC for all surfactants used was considered for determining and understanding the behavior described by adsorption isotherms. For the route, I, the nanoparticles and the surfactant are added at the same time to a brine with a NaCl concentration of 10000 mg·L-1. The solutions of surfactant in the brine are stirred for 2 hours and left to stand for 24 hours to ensure the interaction between the surfactant molecules and the nanoparticles. Surfactant concentrations ranged between 100 and 8000 mg·L-1. The dosage of the nanoparticles regarding the solution volume is 10 g·L-1 for allowing the decantation of the particles and thus to take accurate absorbance measurements, minimizing the noise that can generate the suspended nanoparticles. The adsorbed amount ( q ) in units of mg of surfactant/g of nanoparticles was determined according to equation (1):

q=

Co − C E V W

(1)

where, Co (mg·L-1) and CE (mg·L-1) are the initial and equilibrium concentrations, respectively, V (L) is the solution volume and W (g) is the amount of nanoparticles added to the solutions. In the route II, the surfactant is added to a brine with 10000 mg·L-1 of NaCl at concentrations between 100 and 8000 mg·L-1. The solutions are stirred for 2 hours and left to stand for 24 hours to ensure interaction between the surfactant molecules. Then, nanoparticles are added at a dosage of 10 g·L-1. Similarly, to ensure the interaction ACS Paragon Plus Environment


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between surfactant molecules/micelles with the nanoparticles, the solutions are stirred for 2 hours and are left to stand for 24 hours. In both routes I and II, each measurement was performed in triplicate. The isotherms obtained by UV-vis spectrophotometry were corroborated through thermogravimetric analyses with a TGA analyzer (Q50, TA Instruments, Inc., New Castle, DE). The SiO2 nanoparticles containing adsorbed surfactant were heated in air from 30 °C to 900 °C at 20 °C·min-1 and a constant airflow rate of 100 cm3·min-1 throughout the experiment. The uncertainties between the UV-vis and TGA techniques are presented as error bars in the adsorption isotherms. Surfactant desorption from nanoparticles The percentages of desorption of surfactant from the nanoparticles were evaluated using the batch-mode method26 at 25, 50 and 70 ºC. In desorption experiments, the nanoparticles with surfactant adsorbed obtained from the adsorption isotherms were added to a brine with 10000 mg·L-1 of NaCl at a dosage of 10 g·L-1. Then, the solution was stirred for 2 hours and left to stand for 24 hours. An aliquot of each solution was taken from the supernatant to determine the percentages of desorption. Each measurement was performed in triplicate. The percentages of desorption ( %des ) were calculated according to equation (2):

% des =

M des × 100 M ads

(2)

where M ads (mg) is the adsorbed mass of surfactant before the desorption process onto nanoparticles surface and M des (mg) is the desorbed mass of surfactant from nanoparticles. 2.2.3. Interfacial Tension Measurements


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The interfacial tension (IFT) experiments were performed using the surfactant with the best performance in the sorption tests at 25, 50 and 70 °C. The IFT measurements between crude oil-brine, crude oil-surfactant, and crude oil-nanoparticles-surfactant solutions were determined by the Wilhelmy plate method27 using a force tensiometer – K11 (Krüss, Germany). This device measures the IFT based on the force which acts on a wettable plate when is immersed vertically in the lower phase. The nanoparticlessurfactant solutions were prepared at concentrations between 0 and 8000 mg·L-1. Each measurement was performed three times. The uncertainties are presented as error bars in the interfacial tension curves. 2.2.4. Displacement test in micromodel The micromodel was used to evaluate the performance of a surfactant solution and the designed nanofluid (a nanoparticles-surfactant dispersion) for enhancing the oil recovery. The displacement tests were performed in a radial flow cell, packed with 50/60 sieve Ottawa sand. The sand was washed with deionized water and placed under vacuum at 60 °C for 12 h. The dimensions of the cell are 25 cm × 12 cm × 2 cm. Displacement tests were performed at a temperature of 25 °C. The injecting well and producing well were located on the diagonal line of the micromodel, which resembling a quarter five-spot well pattern as showed in Figure 1. The configuration is composed of the packed Ottawa sand, an injection pump (Eldex, United States), stainless steel displacement cylinders and a pressure sensor. The surfactant solutions were prepared at concentrations of 10 and 100 mg·L-1 in a brine with 10000 mg·L-1 of NaCl. The nanoparticles dosage was 10 mg·L-1 for both systems. First, the absolute permeability of the system is measured by the injection of brine at a flow rate of 5 mL·min-1. Then, oil is injected at 5 mL·min-1 until residual water saturation (Swr) conditions. At this point, oil recovery by water injection is performed, ACS Paragon Plus Environment


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and fluid production is monitored. Water injection stops after 5 pore volumes injected (PVI) when residual oil saturation (Sor) conditions are reached. Later, the surfactant or nanoparticles-surfactant solution is injected until the oil recovery is stabilized, emulating an enhancing oil recovery process. Subsequently, water is injected again to ensure that the oil production rate is zero.

5 6

1

4

8

2

7

3

Figure 1. Experimental setup of a quarter five-spot pattern micromodel: (1) Ottawa Sand packing, (2) injection pump, (3) displacement cylinder, (4) injection point, (5) production point, (6) test tube, (7) pressure sensor and (9) data acquisition.

3. MODELING 3.1. Solid-Liquid Equilibrium (SLE) model Within the specialized literature, there are several models for describing the adsorption phenomena.28,

29

However, there are few models that represent the complexity of the

interaction of between the surfactant molecules due to their self-associative properties. In this way, the Solid-Liquid Equilibrium (SLE) model was considered for understanding the adsorption of the auto-associative molecules such as the surfactants


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on the surface of the nanoparticles due to its phenomenological structure.30 The SLE model is related to the adsorption of self-associative molecules on the solid surfaces and has been applied conventionally for adsorption of asphaltenes in nanoparticles and microparticles of different chemical nature.31-33 In this work, this model has been extended for being used for the first time to describe surfactant adsorption onto nanoparticles surface, taking into account that surfactants also tend to self-associate.34, 35 Briefly, the equation of the SLE model is described as follows: ψ  ψ KH exp   1 + Kψ  qm 

(3)

−1 + 1 + 4 K ξ 2K

(4)

CE =

ψ =

 qm ⋅ q    qm − q 

ξ =

(5)

where, q (g·g-1) is the amount of surfactant adsorbed onto nanoparticles, qm (g·g-1) is the maximum adsorption capacity, and CE (mg·g-1) is the equilibrium concentration of surfactant in the solution. K (g·g-1) is the reaction constant related to the degree of selfassociation of surfactant onto nanoparticles surface and K H (mg·g-1) is the measured Henry’s law constant, which is an indicator of the adsorption affinity of surfactant onto a solid surface.31-33 High values of K indicate that the degree of self-association of the surfactant molecules is high. On the other hand, low values of K H suggest that the surfactant could have a high affinity towards adsorption over the nanoparticles surface. 3.2. Thermodynamic properties of adsorption The SLE model can be used to determine the thermodynamic properties, which are an estimate to describe the adsorption behavior of surfactant and the spontaneity of the



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process. The Henry’s law constant is exponentially related to the inverse of temperature and is expressed according to equation (6):

K   K H = exp  K H ,0 + H ,1  T  

(6)

Likewise, K is expressed as follows:

K   K = exp  K 0 + 1  T  

(7)

where, K0 is related to reaction entropy and K1 is associated with reaction enthalpy of surfactant onto surface.32 The K0 and K1 parameters were estimated using the experimental data of the adsorption isotherms at 25, 50 and 70°C for the surfactants ° ° studied. The change in standard entropy ∆ S ads and standard enthalpy ∆H ads is

determined as described in equations (8) and (9), respectively: ° ∆S ads = K0 R

(8)

° ∆H ads = K1 R

(9)

On the other hand, the change in the standard Gibbs free energy can be expressed as follows: ° ∆Gads = − RT ln K

(10)

3.3. Polanyi’s adsorption potential With the aim of understanding the adsorption phenomena, the adsorption potential or Polanyi’s theory was used.36 In Polanyi’s theory, the adsorbed layer is considered as a thick film of decreasing density with increase in distance from the surface.37 The model


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is expected to apply to surfactant adsorption. The adsorption potential is expressed as follows:  1  A = RTln  1 +   CE 

(11)

where CE (g·g-1) is the equilibrium concentration of surfactant in the solution. The error definition used was the root-mean-square error (RSM %), determined by equation (12). The calculated error values were tabulated. The RSM % and R2 were determined using the Microsoft Excel software package. The Cexp erimental corresponds to the concentration obtained through experimental measurements and Ccalculated is the concentration calculated using a determined model. m

RSM % =

∑ (C

exp erimental ,i

− Ccalculated ,i ) 2 × 100

i =1

m

(12)

4. RESULTS AND DISCUSSION 4.1. Crude oil Characterization A light crude oil of 33.2 °API from a Colombian field was used in this work. The SARA (Saturated, Aromatic, Resins and Asphaltenes) analysis of the crude oil indicated a percentage of saturated of 70.42 %, and 21.33, 8.16 and 0.01 % for aromatic, resins and asphaltenes, respectively. As observed, the crude oil is composed of a higher percentage of saturated and presents a lower content of asphaltenes. Also, when handling the crude oil, it has a paraffinic behavior at temperatures below 25 °C which agrees to the reported SARA analysis.38 4.2. Critical Micelle Concentration (CMC)



The average size of micelle as a function of surfactant concentration was obtained by DLS measurements at 25 °C based on a trend change of the curve as showed in Figure S1 of the Supporting Information document. The CMC of CTAB occurred at surfactant concentration close to 4000 mg·L-1. Likewise, the CMC obtained for Tween 20 occurred at a surfactant concentration near 600 mg·L-1, and for SDS at a concentration close to 2000 mg·L-1. The CMC of cationic and anionic surfactants (CTAB and SDS) is higher than the CMC of nonionic surfactant (Tween 20). The cationic and anionic surfactants form micelles much more difficult than the nonionic surfactants due to the repulsion between the hydrophilic parts of the associated surfactant molecules in the micelles.39 The CMC at 70 °C for each surfactant was also measured, showing an increase in all systems as the temperature increases. This behavior is due to the increase in temperature produces an increase in the disorganization of the water molecules that are close to the non-polar group (the compatibility increases), which hinders the formation of micelles.18, 39 Consequently, the CMC tends to occur at higher concentrations when the temperature increases. 4.3. Adsorption experiments 4.3.1. Effect of surfactant micellization Figure 2 shows the comparison of the adsorption isotherms of surfactants of different chemical nature onto SiO2 nanoparticles obtained from Route I and II. For CTAB and Tween 20, Type III isotherms were also observed. Similarly, SDS presented Type I (a) isotherms, according to the IUPAC classification scheme.40 For all surfactants evaluated, the adsorption amount is higher for Route II than Route I. This behavior occurs because, in the case of Route II, the nanoparticles are added to solutions of


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surfactant after the micelles formation and thus, after to the CMC, the micelles of surfactant are adsorbed onto nanoparticles surface. In contrast, on Route I, the nanoparticles and surfactant are added simultaneously to the brine solution, leading to a possible competition between the formation of surfactant micelles and the adsorption of surfactant onto the nanoparticles surface. In this way, surfactant micelles could have a smaller size, and thus the adsorption amount is lower. The observed behavior was corroborated through DLS measurements in which CTAB micelle size values close to 1 nm were obtained in the presence of nanoparticles. This value is lower than the average size of CTAB micelle, which was 2.3 nm. The results suggest that a formulation of injection fluid for surfactant flooding application must be performed following the Route II.

a 800

b 800

Route I Route II SLE Model

400

400

200

200

0

0 0

Route I Route II SLE Model

600 q (mg·g-1)

600 q (mg·g-1)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


10 20 CE (mg·L-1)

30

0


100 CE (mg·L-1)

200


c

q (mg·g-1)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

300

200

100

Route I Route II

0 0

2000 4000 CE (mg·L-1)

6000

Figure 2. Adsorption isotherms for a) CTAB, b) Tween 20 and c) SDS onto SiO2 nanoparticles from Route I and II at 25 °C. The two routes used are the following: I) the simultaneous addition of nanoparticles and surfactant, and II) addition of nanoparticles after micelles formation. The symbols are experimental data, and the continuous lines are from the SLE model.

4.3.2. Effect of chemical nature of the surfactant Figure 3 shows the adsorption isotherms for CTAB, Tween 20 and SDS onto SiO2 nanoparticles from Route II at 25 °C. It is observed that CTAB and Tween 20 showed Type III isotherms and SDS presented Type I (a) isotherm, according to the International Union of Pure and Applied Chemistry (IUPAC) classification scheme.40 The Type III isotherms are characterized by the adsorption of adsorbate in multilayers on the adsorbent surface.28 Meanwhile the Type I isotherm indicates that the adsorption phenomena occurs in monolayer.28 For all isotherms, the adsorbed amount of surfactant on nanoparticles increased with increasing surfactant concentration.41 Figure 3 shows that the amount adsorbed of surfactant decreased in the order: CTAB > Tween 20 >


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SDS for CE > 100 mg·L-1. In Henry’s region (i.e., CE < 100 mg·L-1), associated with the affinity of surfactant and nanoparticles surface,31 the slope of the isotherm corresponding to CTAB is the highest compared to adsorption isotherms of Tween 20 and SDS. However, as observed in Figure 3, SDS showed a higher slope than Tween 20 in CE values below 65 mg·L-1, in which SDS and Tween 20 are found as molecules ( CE values below CMC). Taking into account that the size of Tween 20 molecule is bigger than the SDS molecule, Tween 20 molecules occupy more space on the SiO2 surface, thus, at CE below 65 mg·L-1, the adsorbed amount is less regarding the amount adsorbed from the SDS. For CE above 65 mg·L-1, Tween 20 presents a higher adsorbed amount of surfactant onto nanoparticles than SDS. In all cases of this work, the theoretical value of the point of zero charge (pHPZC) was lower than the solution pH of 7.08. For pure SiO2 nanoparticles, pHPZC is close to a pH of 2.42 This suggests that silica nanoparticles in a solution of a pH higher than the pHPZC are negatively charged. In this way, the similar negative electrical charges of SiO2 nanoparticles and the dodecyl sulfate anion of SDS results in an electrostatic repulsive interaction, which makes it difficult for the surfactant molecules or micelles to get adsorbed onto the surface of the nanoparticles, possibly leading to adsorption of SDS surfactant occurring in monolayer. This behavior could be due to the Na+ cation of NaCl brine neutralizes the negative charges on the surface of nanoparticles, and consequently, the SDS surfactant can be adsorbed on the nanoparticles surface. Meanwhile, Tween 20 is adsorbed in multilayers on the nanoparticles surface. The negative charges of SiO2 nanoparticles could interact with the negative charges of hydroxyl and acyl functional groups of Tween 20 through dipole-dipole interactions. In this case, there are not repulsive electrostatic forces that difficult the adsorption of



surfactant on nanoparticles, resulting in a higher adsorbed amount for Tween 20 than SDS. On the other hand, the adsorption of CTAB onto nanoparticles can be related mainly due to the silanol functional groups of SiO2 nanoparticles are attracted by net electrostatic forces with CTAB cation. When comparing the adsorptive behavior of CTAB and SDS, the adsorption of SDS is lower than obtained with CTAB due to the negative charges of the dodecyl sulfate anions of SDS repel with SiO2 surface giving place to adsorption in monolayer. By contrast, the CTAB cations are attracted to the SiO2 surface in multilayer, and it is obtained, therefore, higher adsorption.

800 q (mg·g-1)

200

600 q (mg·g-1)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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150 100 50

Zoom for CE < 500 mg·L-1

0 0

400

100

200 300 400 CE (mg·L-1)

500

CTAB Tween 20 SDS SLE Model

200

0 0

2000

4000 CE

6000

(mg·L-1)

Figure 3. Adsorption isotherms for CTAB, Tween 20 and SDS onto SiO2 nanoparticles from Route II at 25 °C. The two routes used are the following: I) the simultaneous addition of nanoparticles and surfactant, and II) addition of nanoparticles after micelles formation. The symbols are experimental data, and the continuous lines are from the SLE model. Tables S1, S2, and S3 presented in Supporting Information, summarize the estimated SLE parameters for CTAB, Tween 20 and SDS, respectively. The SLE model is applied


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to surfactant adsorption onto nanoparticles surface, and as observed in Figures 2 and 3, this model presents an excellent fit to the experimental data with RSM < 5.8 %. For all surfactants evaluated, the maximum adsorption capacity qm estimated for the model was higher for Route II than for Route I, which corroborates that the formulation of injection fluid should be done following the Route II. As shown in Tables S1, S2 and S3, K H parameter increases (i.e., adsorption affinity decreases) in the order: CTAB = SDS < Tween 20 at 25 °C. The K parameter, related with self-association of surfactant molecules, increases in the order: CTAB > Tween 20 > SDS for Route I. For Route II, the trend is Tween 20 > CTAB > SDS. In the SLE model, the maximum adsorption capacity of CTAB, Tween 20 and SDS for Route II, were 1935.50, 1050.62 and 346.48 mg·g-1, respectively. These results are in agreement with the adsorbed amount obtained in Figure 3. More details of the parameters estimated from the SLE model for all surfactants can be found in the Supporting Information document. 4.3.3. Effect of temperature Figure 4 shows the adsorption isotherms for CTAB, Tween 20 and SDS from Route I and II at 50 and 70 °C. These temperatures are selected based on the surfactant flooding is conventionally applied to reservoir temperatures below 80 °C.3 As observed in all cases, the adsorption of surfactant decreases when increasing the temperature. This result indicates that the adsorption of all surfactants onto nanoparticles surface is an exothermic process.41 Similarly to that observed for adsorption isotherms at 25 °C for Route I and Route II presented in Figure 4, the adsorbed amount of surfactant onto nanoparticles is higher for Route II than for the Route I. Additionally, the CMC of each surfactant evaluated increased with temperature. Thus, the formation of surfactant micelles is disfavored, which in turn decreases the adsorption of these structures onto



nanoparticles. Likewise, CTAB and Tween 20 presented Type III isotherms, while for SDS, Type I (a) isotherm is observed, suggesting that the behavior of the adsorptive process remains independently of the system temperature. Tables S1, S2 and S3 included in the Supporting Information document showed the estimated SLE parameters for CTAB, Tween 20 and SDS at 25, 50 and 70 °C. As observed, the K H parameter of the SLE model increases when the temperature increases, which suggests that the adsorption affinity is lowered by increasing the temperature. Additionally, qm agrees with the adsorbed amount of each surfactant on nanoparticles. For example, for the case of CTAB for Route I, qm at 50 °C was 1700.08 mg·g-1 while at 70 °C was lower with a value of 1650.11 mg·g-1. Detailed information related with the estimated parameters of the SLE model can be found in the Supporting Information document.

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Figure 4. Adsorption isotherms for CTAB from a) Route I and b) Route II, Tween 20 from c) Route I and d) Route II, and SDS from e) Route I and f) Route II onto SiO2 nanoparticles at 25, 50 and 70 °C. The two routes used are the following: I) the simultaneous addition of nanoparticles and surfactant, and II) addition of nanoparticles after micelles formation. The symbols are experimental data, and the continuous lines are from the SLE model. 4.4. Desorption experiments



Figure 5 shows the percentages of desorption for CTAB, Tween 20 and SDS, respectively, from SiO2 nanoparticles for Route I and II at 25 °C. The selection of surfactant concentrations for experiments considered the CMC of each surfactant. As observed in Figure 5, CTAB presented percentages of desorption below of 1.6 % for Route I and values below of 0.5 % for Route II even for the surfactant concentration of 8000 mg·L-1. Also, the percentages of desorption of CTAB from the nanoparticles surface were obtained at temperatures of conventional application of surfactant flooding. Due to the CTAB showed the lowest percentages of desorption at 25 ºC, the desorption experiments were performed at 50 and 70 °C, showing desorption percentages values below of 0.71 %. These results indicate that the interactions of CTAB and nanoparticles surface are strong enough to prevent desorption of the surfactant. Meanwhile, it is observed that the percentages of desorption of Tween 20 from silica nanoparticles are higher than obtained with CTAB. In this case, the percentages of desorption were below 5.3 % for both Routes. However, SDS reached the percentages of desorption close to 90 %. Thus SDS cannot be used as an effective chemical material for CEOR applications. These percentages of desorption as well as the amount adsorbed, are significantly related to the strength of intermolecular forces between nanoparticles and surfactant. Hence, the attractive ion-dipole interactions between cetyltrimethylammonium cation of CTAB and nanoparticles can be stronger than the dipole-dipole between Tween 20 and nanoparticles, and these at the same time are stronger than the electrostatic repulsion forces between the SDS-nanoparticles couple. This result indicates that CTAB and Tween 20 showed an irreversible process, due to desorption was almost null. Further, the adsorption of CTAB onto nanoparticles surface could be converted in a process more effective and straightforward for the


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synthesis of composite materials which can be used in CEOR process, avoiding complex processes or equipment for the development of nanofluids.

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Route II 87.0 85.9 86.1 86.1

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Figure 5. Percentages of desorption (%) for different initial concentrations (Co) of a) CTAB, b) Tween 20 and c) SDS from SiO2 nanoparticles for Route I and II at 25 °C. The two routes used are the following: I) the simultaneous addition of nanoparticles and surfactant, and II) addition of nanoparticles after micelles formation. 4.5. Adsorption potential Figure 6-a, b and c, show the characteristic curves for the adsorption of CTAB, Tween 20 and SDS from Routes I and II at 25 °C, respectively. The characteristic curve



presents a simple relation between the adsorption potential and the distance of solid surface.36, 43 As observed in Figure 6, in all cases the adsorption potential of Route II is higher than Route I. This behavior indicates that the work required to transfer a surfactant molecule from the bulk phase to the nanoparticles surface is higher for Route II than Route I. When comparing CTAB and Tween 20, which showed Type III isotherm, it is observed that the adsorption potential values are higher for CTAB than Tween 20. This behavior also suggests that the interactions adsorbate-adsorbent in the case of CTAB-nanoparticles is stronger than the interactions between the pair Tween 20-nanoparticles. Consequently, it is more difficult to transfer a molecule of CTAB from bulk phase to nanoparticles surface than a molecule of Tween 20, which can impact the efficiency of the nanofluid preparation. Similarly, the adsorption potential values for SDS are lower than Tween 20 and CTAB cases. The desorption potential for CTAB, Tween 20 and SDS were calculated from Route II at 25 °C for an initial concentration of surfactant of 8000 mg·L-1. Hence, the desorption potential was estimated in 27.27, 22.59 and 15.48 kJ·mol-1 for CTAB, Tween 20 and SDS, respectively. This behavior indicates that the work required to transfer a surfactant molecule from the surface to a given distance is higher for a CTAB molecule than an SDS molecule. These results are in agreement with the percentages of desorption of all surfactants, where it is observed that the CTAB showed the lowest desorption values while the SDS showed a percentage of desorption close to 90 %.


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Route II

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Figure 6. Characteristic curves for a) CTAB, b) Tween 20 and c) SDS adsorption on SiO2 nanoparticles from Route I and II at 25 °C. The two routes used are the following: I) the simultaneous addition of nanoparticles and surfactant, and II) addition of nanoparticles after micelles formation. Due to the surfactant flooding is conventionally applied at temperatures below of 80 °C, the characteristic curves for all surfactants were constructed at 70 °C. As observed in Figure 7, the characteristic curves follow the order: CTAB > Tween 20 > SDS. This behavior is similar to obtained at a temperature of 25 °C, which indicates that the



composite material based on nanoparticles-surfactant can be applied at reservoir temperature without significant variations in the adsorptive behavior. Also, the characteristic curves at 70 °C confirm that the percentages of desorption for each surfactant do not present considerable changes even at reservoir temperatures.

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SDS

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Figure 7. Characteristic curves for CTAB, Tween 20 and SDS adsorption on SiO2 nanoparticles for the addition of nanoparticles after micelles formation (Route II) at 70 °C. 4.6. Thermodynamic properties Table S4 included in the Supporting Information summarizes the estimated thermodynamic parameters for CTAB, Tween 20 and SDS adsorption onto ° nanoparticles from Route I and II. As observed in all cases, the negative ∆Gads values

indicate that the adsorption process is spontaneous and thermodynamically favorable. Further, no additional energy needs to be included for promoting the nanoparticle° surfactant interaction. The negative values of ∆H ads suggest that the adsorption of

surfactant onto nanoparticles surface is an exothermic process, which is in agreement


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with the results showed in Figure 4 where the adsorption decreased with increasing ° temperature. Likewise, ∆S ads showed positive values that could be due to, in the bulk

phase, the molecules or micelles of the surfactant are in equilibrium according to the concept of CMC. However, when nanoparticles are added to the medium, the surfactant is adsorbed over the nanoparticles surface and then self-associates over the active sites in different extent according to the chemical nature of the adsorbate (Please see K parameter of the SLE model in Tables S1, S2, and S3 of the Supporting Information document). This behavior could lead to an increase in the randomness of the molecules or micelles of the surfactant during the adsorption process.37,

44

These results are in

agreement with those reported by Nassar et al.45 and Franco et al.,44 who studied the adsorption process of self-associative heavy hydrocarbons onto nanoparticles. 4.7. Interfacial Tension Measurements One of the most important effects of surfactants as EOR method is the reduction of the interfacial tension (IFT) between crude oil and an aqueous phase, and for this study was a tool for determining the best concentration of surfactant and the nanoparticles/CTAB ratio for the displacement tests. The aqueous phase is a brine with 10000 mg·L-1 of NaCl. Figure 8-a shows the IFT values obtained with different CTAB concentrations between 0 and 1000 mg·L-1 at 25, 50 and 70 °C. As observed, the IFT increases slightly when the temperature is increased. These results are in agreement with those reported by Kamal et al.,46 who indicate that the IFT typically increases with temperature for most of the reported surfactant systems. The effect of temperature on the IFT depends on the type of crude oil.46 As it can be seen, the IFT between crude oil and brine in the absence of surfactant showed no considerable changes due paraffinic nature of the evaluated crude oil.47



The molecular structure of surfactant also influences the IFT. More hydrophilic surfactants have less ability for reducing the IFT as compared to the lipophilic surfactants.46 As observed in Figure 8-a, CTAB surfactant was able to reduce the IFT to values between 3 and 5 mN·m-1, due to the CTAB is a hydrophilic surfactant with a hydrophilic-lipophilic balance (HLB) value of 10.48 In Figure 8-b, IFT values obtained with nanoparticles-surfactant systems at 25 °C are presented. It is observed that the presence of nanoparticles in CTAB surfactant solutions does not lead to significant changes in IFT. However, it is observed that the values of IFT obtained in the system with 100 mg·L-1 of nanoparticles are lower than those obtained with 1000 mg·L-1 of nanoparticles. At low concentrations of nanoparticles, they are attached to the interface, and then the IFT decreases. In contrast, in high concentrations such as 1000 mg·L-1, the nanoparticles can remove the surfactant of the bulk phase and thus the IFT does not decrease significantly.49 For example, for the point of 1000 mg·L-1 of nanoparticles and 1000 mg·L-1 of surfactant, a higher IFT was obtained (3.77 mN·m-1) than the one for 100 mg·L-1 of nanoparticles and 1000 mg·L-1 of surfactant (2.88 mN·m-1).


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Figure 8. Interfacial tension of crude oil/CTAB surfactant solution in a) absence of SiO2 nanoparticles at 25, 50 and 70 °C and b) presence of SiO2 nanoparticles at concentrations between 10, 100 and 1000 mg·L-1 and a fixed temperature of 25 °C.



4.8. Displacement test in micromodel Displacement tests in a quarter five-spot pattern micromodel were performed for evaluating two fluids based on the CTAB surfactant and SiO2 nanoparticles interaction. The nanoparticles dosage for displacement tests was fixed at 10 mg·L-1, due to the nanoparticles dosage does not present a significant effect on IFT. Likewise, CTAB surfactant concentrations of 10 and 100 mg·L-1 were selected for the displacement tests. Each displacement test was conducted in three steps: waterflooding emulating a secondary recovery, surfactant flooding, and nanoparticles-surfactant flooding. For all displacements tests, the fluid was injected until the oil production becomes zero. First, brine with 10000 mg·L-1 of NaCl was injected up to 5 PVI, when no more crude oil production was observed. Figure 9 shows oil recovery curves in a quarter five-spot pattern micromodel for waterflooding, followed by a) CTAB surfactant flooding at 10 mg·L-1 in the absence and presence of SiO2 nanoparticles at 10 mg·L-1, and b) CTAB surfactant flooding at 100 mg·L-1 in the absence and presence of SiO2 nanoparticles at 10 mg·L-1 for a fixed temperature of 25 °C. The inclusion of SiO2 nanoparticles in the absence of surfactant at a fixed dosage of 100 mg·L-1 did not have a significant effect on the oil recovered, showing an incremental recovery of less than 2%. In both cases of Figure 9, the oil recovered obtained with waterflooding was close to 47 %. In Figure 9-a, it is observed that oil recovered with 10 mg·L-1 of CTAB surfactant was about 50 %. Then, when the fluid with 10 mg·L-1 of CTAB surfactant and 10 mg·L1

of nanoparticles was injected, the oil recovered increased up to 130 % after 2 PVI

regarding the CTAB injection in the absence of nanoparticles. In Figure 9-b, it is observed that surfactant flooding with 100 mg·L-1 of CTAB reached an oil recovery of 60 % after 7 PVI and increased to 92 % when 100 mg·L-1 of CTAB surfactant and 10 mg·L-1 of nanoparticles were injected. This increase in the oil ACS Paragon Plus Environment

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recovery represents about 240 % more than that obtained with the injection of 100 mg·L-1 of CTAB in the absence of nanoparticles. This effect in the oil recovery with nanoparticles-surfactant flooding could be related to the inhibition of adsorption of surfactant onto the rock surface. As it can be seen in Figure 8-b, the nanoparticles do not reduce the IFT crude oil/surfactant solutions. This behavior indicates that the increase in oil recovery could be due to nanoparticles inhibit the adsorption and loss of surfactant in porous media. On the other hand, as observed in Figure 9, the oil recovery with 100 mg·L-1 of CTAB surfactant and 10 mg·L-1 of nanoparticles is much higher than obtained with 10 mg·L-1 of CTAB surfactant and 10 mg·L-1 of nanoparticles. This behavior can be associated with the CTAB/nanoparticles ratio. In the case of 10 mg·L-1 of CTAB surfactant and 10 mg·L-1 of nanoparticles, the ratio is 1:1. The nanoparticles can adsorb the surfactant onto their surface. In this way, the nanoparticles remove the surfactant from the bulk phase and thus, the IFT is not reduced enough to increase the oil recovery significantly. In contrast, in a surfactant/nanoparticles ratio of 10:1, there is free surfactant in the bulk phase. The increase in oil recovery could be due to the joint action of free surfactant and nanoparticles with adsorbed surfactant in their surface. In addition, the low concentration of the composite material based on nanoparticles-surfactant used to obtain the nanofluid corroborates that this material can be cost-effective for an industrial application and is significantly lower than the surfactant dosage used in other studies.13, 19, 20

It is worth to mention that the composite material described in this work was

designed for application in light or medium crude oils. However, due to the advantages of the nanotechnology, the application of surfactants can be extended to crude oils with lower API gravity as it has been shown that for other types of crude oil, the addition of



nanoparticles, additives, and solvents can alter the oil microstructure and thus may enhance the oil recovery.50-52

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Figure 9. Oil recovered in a quarter five-spot pattern micromodel for waterflooding, followed by a) CTAB surfactant flooding at 10 mg·L-1 in absence and presence of SiO2 nanoparticles at 10 mg·L-1 and b) CTAB surfactant flooding at 100 mg·L-1 in absence and presence of SiO2 nanoparticles at 10 mg·L-1 for a fixed temperature of 25 °C.

5. CONCLUSIONS Adsorption isotherms were successfully constructed for evaluated the interactions between cationic, anionic and nonionic surfactants onto SiO2 nanoparticles. Cationic and nonionic surfactants (CTAB and Tween 20, respectively) showed isotherms Type III, while anionic surfactant (SDS) presented isotherm Type I (a) according to the IUPAC scheme. CTAB showed the highest adsorptive capacity and the highest affinity adsorbate-adsorbent among the surfactants. Meanwhile, SDS presented the lowest adsorbed amount. This behavior can be related mainly due to the silanol functional groups of SiO2 nanoparticles presents attractive net electrostatic interactions with the cetyltrimethylammonium cation of CTAB, which can be stronger than the interactions of dipole-dipole showed by Tween 20 and the repulsive charges that are generated between SDS and SiO2 nanoparticles. Route II showed the higher adsorbed amount of surfactant onto nanoparticles than Route I, which suggests that the formulation of injection fluid for surfactant flooding application should be performed following the Route II. In this work, the SLE model was evaluated for the first time for adsorption of surfactant onto nanoparticles and presented a good fit to experimental data. Adsorption isotherms of surfactant onto nanoparticles were constructed at 25, 50 and 70 °C. The adsorbed amount of surfactant decreased as temperature increased, which indicates that the adsorption is an exothermic process. This behavior is in agreement



° with negative values of ∆H ads obtained for all surfactants. Also, the negative values of ° suggested that the adsorption is a spontaneous and thermodynamically favorable ∆Gads

process. CTAB showed percentages of desorption from nanoparticles surface below 1.6 % at 25 °C and values below of 0.71 % at 50 and 70 °C. The percentages of desorption of Tween 20 were lower than 5.3 %. In contrast, SDS desorbed about 90 %, which indicates that CTAB and Tween 20 adsorption is an irreversible process while SDS showed a reversible adsorption process. Additionally, the adsorption potential was higher for CTAB than Tween 20, which corroborates the strongest interactions between CTAB-nanoparticles. Thus, CTAB is the surfactant with the highest adsorbed amount and the lowest percentage of desorption, which could be a better alternative for nanoparticles- surfactant flooding for CEOR. The IFT between crude oil and brine in the absence of surfactant showed no considerable changes due to the paraffinic nature of the evaluated crude oil. The simultaneous use of surfactant and SiO2 nanoparticles does not have a significant effect on the interfacial tension between crude oil and brine. On the other hand, the nanoparticles-surfactant flooding increased the oil recovery up to 240 % regarding surfactant flooding. These results are associated with the ability of nanoparticles for inhibiting the surfactant adsorption onto the surface rock. From the adsorption process of cationic, anionic and nonionic surfactants onto SiO2 nanoparticles evaluated in this research, a new and alternative composite nanomaterial for enhanced oil recovery applications was obtained. In this way, a synthesis of a complex material that requires more costs and equipment can be avoided.


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6. SUPPORTING INFORMATION Supporting information includes Figure S1 shows the average size of micelle as a function of surfactant concentration obtained by DLS measurements at 25 °C. Tables S1, S2 and S3, which describe the model parameters obtained from Solid-Liquid Equilibrium (SLE) model for CTAB, Tween 20 and SDS onto SiO2 nanoparticles from Route I and Route II at 25, 50 and 70 °C. Also, the Table S4 shows the estimated thermodynamic parameters for CTAB, Tween 20 and SDS surfactants adsorption onto SiO2 nanoparticles from Route I and Route II.

ACKNOWLEDGMENTS Stefanía Betancur wants to acknowledge to the Departamento Administrativo de Ciencia, Tecnología e Innovación de Colombia (COLCIENCIAS) for the scholarship received from call 727-2015. The authors also acknowledge Universidad Nacional de Colombia, Universidad de Granada, FEDER, Spanish projects CTQ2013-44789-R (MINECO) and P12-RNM-2892 (Junta de Andalucía) for the support provided.

7. REFERENCES 1. Petroleum, B. BP Statistical Review of World Energy. Available at www.bp. com/statisticalreview, 2016. 2. Cornell, B. Information and the Oil Price Collapse. Available at SSRN 2584796, 2015. 3. De Ferrer, M. P. Inyección de agua y gas en yacimientos petrolíferos; Ediciones Astro Data SA: Maracaibo, 2001. 4. Thomas, S. Enhanced oil recovery-an overview. Oil & Gas Science and Technology-Revue de l'IFP 2008, 63, (1), 9-19. 5. Stosur, G. J.; Hite, J. R.; Carnahan, N. F.; Miller, K. The alphabet soup of IOR, EOR and AOR: effective communication requires a definition of terms. SPE International Improved Oil Recovery Conference in Asia Pacific, 2003.



6. Manrique, E. J.; Thomas, C. P.; Ravikiran, R.; Izadi Kamouei, M.; Lantz, M.; Romero, J. L.; Alvarado, V. EOR: current status and opportunities. SPE improved oil recovery symposium, 2010. 7. Thomas, S.; Ali, S. F. Status and assessment of chemical oil recovery methods. Energy sources 1999, 21, (1-2), 177-189. 8. Erik, S., Surfactant injection process. In Google Patents: 1970. 9. Sheng, J. J. Status of surfactant EOR technology. Petroleum 2015, 1, (2), 97105. 10. Shah, D. O. Improved oil recovery by surfactant and polymer flooding; Elsevier: New York, 2012. 11. Schramm, L. L.; Stasiuk, E. N.; Marangoni, D. G. Surfactants and their applications. Annual Reports Section" C"(Physical Chemistry) 2003, 99, 3-48. 12. Franco, C. A.; Zabala, R.; Cortés, F. B. Nanotechnology applied to the enhancement of oil and gas productivity and recovery of Colombian fields. Journal of Petroleum Science and Engineering 2017, 157, 39-55. 13. Mohajeri, M.; Hemmati, M.; Shekarabi, A. S. An experimental study on using a nanosurfactant in an EOR process of heavy oil in a fractured micromodel. Journal of Petroleum Science and Engineering 2015, 126, 162-173. 14. Amin, B. M.; Peyman, P. Improvement of surfactant flooding performance by application of nanoparticles in sandstone reservoirs. Journal of the Japan Petroleum Institute 2015, 58, (2), 97-102. 15. Zargartalebi, M.; Kharrat, R.; Barati, N. Enhancement of surfactant flooding performance by the use of silica nanoparticles. Fuel 2015, 143, 21-27. 16. Zargartalebi, M.; Barati, N.; Kharrat, R. Influences of hydrophilic and hydrophobic silica nanoparticles on anionic surfactant properties: Interfacial and adsorption behaviors. Journal of Petroleum Science and Engineering 2014, 119, 36-43. 17. Moghadam, T. F.; Azizian, S.; Wettig, S. Synergistic behaviour of ZnO nanoparticles and gemini surfactants on the dynamic and equilibrium oil/water interfacial tension. Physical Chemistry Chemical Physics 2015, 17, (11), 7122-7129. 18. Bagrezaie, M. A.; Pourafshary, P. Improvement of Surfactant Flooding Performance by Application of Nanoparticles in Sandstone Reservoirs. Journal of the Japan Petroleum Institute 2015, 58, (2), 97-102. 19. Wu, Y.; Chen, W.; Dai, C.; Huang, Y.; Li, H.; Zhao, M.; He, L.; Jiao, B. Reducing surfactant adsorption on rock by silica nanoparticles for enhanced oil recovery. Journal of Petroleum Science and Engineering 2017, 153, 283-287. 20. Cheraghian, G.; Kiani, S.; Nassar, N. N.; Alexander, S.; Barron, A. R. Silica Nanoparticle Enhancement in the Efficiency of Surfactant Flooding of Heavy Oil in a Glass Micromodel. Industrial & Engineering Chemistry Research 2017, 56, (30), 85288534. 21. Suleimanov, B.; Ismailov, F.; Veliyev, E. Nanofluid for enhanced oil recovery. Journal of Petroleum Science and Engineering 2011, 78, (2), 431-437. 22. Ahmadi, M.-A.; Ahmad, Z.; Phung, L. T. K.; Kashiwao, T.; Bahadori, A. Experimental investigation the effect of nanoparticles on micellization behavior of a surfactant: Application to EOR. Petroleum Science and Technology 2016, 34, (11-12), 1055-1061. 23. Giraldo, L. J.; Giraldo, M. A.; Llanos, S.; Maya, G.; Zabala, R. D.; Nassar, N. N.; Franco, C. A.; Alvarado, V.; Cortés, F. B. The effects of SiO2 nanoparticles on the thermal stability and rheological behavior of hydrolyzed polyacrylamide based polymeric solutions. Journal of Petroleum Science and Engineering 2017, 159, 841852.


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24. Nassar, N. N.; Betancur, S.; Acevedo, S.; Franco, C. A.; Cortés, F. B. Development of a Population Balance Model to Describe the Influence of Shear and Nanoparticles on the Aggregation and Fragmentation of Asphaltene Aggregates. Industrial & Engineering Chemistry Research 2015, 54, (33), 8201-8211. 25. Institute, E., IP 469: Determination of saturated, aromatic and polar compounds in petroleum products by thin layer chromatography and flame ionization detection, 2011. 26. Cortés, F. B.; Montoya, T.; Acevedo, S.; Nassar, N. N.; Franco, C. A. Adsorption-desorption of n-c7 asphaltenes over micro-and nanoparticles of silica and its impact on wettability alteration. CT&F-Ciencia, Tecnología y Futuro 2016, 6, (4), 89106. 27. Drelich, J.; Fang, C.; White, C. Measurement of interfacial tension in fluid-fluid systems. Encyclopedia of surface and colloid science 2002, 3, 3158-3163. 28. Lowell, S.; Shields, J. E. Powder surface area and porosity; Springer Science & Business Media: New York, 2013. 29. Foo, K.; Hameed, B. Insights into the modeling of adsorption isotherm systems. Chemical Engineering Journal 2010, 156, (1), 2-10. 30. Schramm, L. L., Surfactants: fundamentals and applications in the petroleum industry; Cambridge University Press: Cambridge, 2000. 31. Betancur, S.; Carmona, J. C.; Nassar, N. N.; Franco, C. A.; Cortés, F. B. Role of Particle Size and Surface Acidity of Silica Gel Nanoparticles in Inhibition of Formation Damage by Asphaltene in Oil Reservoirs. Industrial & Engineering Chemistry Research 2016, 55, (21), 6122-6132. 32. Montoya, T.; Coral, D.; Franco, C. A.; Nassar, N. N.; Cortés, F. B. A novel solid–liquid equilibrium model for describing the adsorption of associating asphaltene molecules onto solid surfaces based on the “chemical theory”. Energy & Fuels 2014, 28, (8), 4963-4975. 33. Guzmán, J. D.; Betancur, S.; Carrasco-Marín, F.; Franco, C. A.; Nassar, N. N.; Cortés, F. B. Importance of the Adsorption Method Used for Obtaining the Nanoparticle Dosage for Asphaltene-Related Treatments. Energy & Fuels 2016, 30, (3), 2052-2059. 34. Domínguez, A.; Fernández, A.; González, N.; Iglesias, E.; Montenegro, L. Determination of critical micelle concentration of some surfactants by three techniques. J. Chem. Educ 1997, 74, (10), 1227. 35. Rosen, M. J.; Kunjappu, J. T. Surfactants and interfacial phenomena; John Wiley & Sons: New York, 2012. 36. Polanyi, M. Adsorption from the point of view of the Third Law of Thermodynamics. Verh. Deut. Phys. Ges 1914, 16, 1012-1016. 37. Rouquerol, J.; Rouquerol, F.; Llewellyn, P.; Maurin, G.; Sing, K. S. Adsorption by powders and porous solids: principles, methodology and applications; Academic press: Oxford, 2013. 38. Sanjay, M.; Simanta, B.; Kulwant, S. Paraffin problems in crude oil production and transportation: a review. SPE Production & Facilities 1995, 10, (01), 50-54. 39. Salager, J.-L. Surfactantes en solución acuosa. Cuaderno FIRP 1993, 201, 1-19. 40. Thommes, M.; Kaneko, K.; Neimark, A. V.; Olivier, J. P.; Rodriguez-Reinoso, F.; Rouquerol, J.; Sing, K. S. Physisorption of gases, with special reference to the evaluation of surface area and pore size distribution (IUPAC Technical Report). Pure and Applied Chemistry 2015, 87, (9-10), 1051-1069. 41. Franco, C.; Patiño, E.; Benjumea, P.; Ruiz, M. A.; Cortés, F. B. Kinetic and thermodynamic equilibrium of asphaltenes sorption onto nanoparticles of nickel oxide supported on nanoparticulated alumina. Fuel 2013, 105, 408-414.



42. Franco, C. A.; Cortés, F. B.; Nassar, N. N. Adsorptive removal of oil spill from oil-in-fresh water emulsions by hydrophobic alumina nanoparticles functionalized with petroleum vacuum residue. Journal of colloid and interface science 2014, 425, 168-177. 43. Polanyi, M., Verh. d. deutsch. phys. Ges 1914, 16, (1012), 18. 44. Franco, C. A.; Montoya, T.; Nassar, N. N.; Pereira-Almao, P.; Cortés, F. B. Adsorption and Subsequent Oxidation of Colombian Asphaltenes onto Nickel and/or Palladium Oxide Supported on Fumed Silica Nanoparticles. Energy & Fuels 2013, 27, (12), 7336-7347. 45. Nassar, N. N. Asphaltene adsorption onto alumina nanoparticles: kinetics and thermodynamic studies. Energy & Fuels 2010, 24, (8), 4116-4122. 46. Kamal, M. S.; Hussein, I. A.; Sultan, A. S. Review on Surfactant Flooding: Phase Behavior, Retention, IFT, and Field Applications. Energy & Fuels 2017, 31, (8), 7701-7720. 47. Moeini, F.; Hemmati-Sarapardeh, A.; Ghazanfari, M.-H.; Masihi, M.; Ayatollahi, S. Toward mechanistic understanding of heavy crude oil/brine interfacial tension: The roles of salinity, temperature and pressure. Fluid phase equilibria 2014, 375, 191-200. 48. Barut, K. D.; Ari, F. F. C.; Öner, F. Development and characterization of a cationic emulsion formulation as a potential pDNA carrier system. Turkish Journal of Chemistry 2005, 29, (1), 27-40. 49. Cheraghian, G.; Hendraningrat, L. A review on applications of nanotechnology in the enhanced oil recovery part B: effects of nanoparticles on flooding. International Nano Letters 2016, 6, (1), 1-10. 50. Minale, M.; Merola, M. C.; Carotenuto, C. Effect of solvents on the microstructure aggregation of a heavy crude oil. Fuel Processing Technology 2018, 177, 299-308. 51. Taborda, E. A.; Alvarado, V.; Franco, C. A.; Cortés, F. B. Rheological demonstration of alteration in the heavy crude oil fluid structure upon addition of nanoparticles. Fuel 2017, 189, 322-333. 52. Taborda, E. A.; Franco, C. A.; Lopera, S. H.; Alvarado, V.; Cortés, F. B. Effect of nanoparticles/nanofluids on the rheology of heavy crude oil and its mobility on porous media at reservoir conditions. Fuel 2016, 184, 222-232.

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