Control of Asphaltene Aggregation in Reservoir Model Oils along the

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Control of Asphaltenes Aggregation in Reservoir Model Oils along Production Streamline by Fe3O4 and NiO Nanoparticles Mozhdeh Igder, Negahdar Hosseinpour, Azadeh Amrollahi Biyouki, and Alireza Bahramian Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.8b01062 • Publication Date (Web): 16 May 2018 Downloaded from http://pubs.acs.org on May 16, 2018

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Control of Asphaltenes Aggregation in Reservoir Model Oils along Production Streamline by Fe3O4 and NiO Nanoparticles Mozhdeh Igdera, Negahdar Hosseinpoura,b,*, Azadeh Amrollahi Biyoukia, Alireza Bahramiana a

Institute of Petroleum Engineering, College of Engineering, University of Tehran, P.O. Box:

11155/4563, Tehran, Iran b

Oil & Gas Processing Center of Excellence, School of Chemical Engineering, College of

Engineering, University of Tehran, P.O. Box: 11155/4563, Tehran, Iran Keywords: Asphaltene aggregation; flow assurance; shear stress; oil viscosity; nanoparticles; insitu oil upgrading.

ABSTRACT

Iron oxide (Fe3O4) and nickel oxide (NiO) nanoparticles were employed to control the aggregation of asphaltenes in reservoir model oils along production streamline from far-field region to near wellbore area to wellbore conditions. Fe3O4 and NiO nanoparticles with an average particle size of 30 and 78 nm, respectively, were synthesized via a simple precipitation method and characterized by XRD, BET, FTIR, and FESEM imaging techniques. Asphaltenes were extracted from an Iranian heavy oil sample and their structure and functional groups were characterized. The asphaltenes were dissolved in toluene at the concentration of 400 mg/L, designated as reservoir model oil. The average size of the asphaltenes nanoaggregates in the model oil, as determined by dynamic light scattering (DLS), is 18 nm, representative

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of the size of asphaltenes aggregates in reservoir oils. The nanoparticles were added to the model oil at an optimum ratio of 0.09 m2 BET surface area/g of the asphaltenes, and the samples were shaken at 70 rpm to approach equilibrium. In order to simulate the effects of pressure depletion on aggregation of asphaltenes at far-field conditions, n-heptane was added at different volume ratios to the thus-obtained equilibrium model oil followed by shaking to approach new equilibrium, designated as far-field tests. The equilibrium samples obtained from the far-field tests were exposed to shear stress in a flow assurance apparatus to simulate the effects of shear rate on aggregation/fragmentation of asphaltenes at near wellbore/wellbore conditions, classified as near-wellbore tests. The Couette-Taylor flow assurance apparatus consists of two concentric cylinders and the fluid in the annular space is subjected to shear stress by rotation of the internal cylinder. In order to determine the size distribution of the asphaltenes aggregates at the far-filed and near-wellbore conditions, the samples were exposed to magnetic field or centrifugation and the supernatant liquids were subjected to DLS analysis. It is found from the far-field tests that the asphaltenes onset point, i.e. the average aggregate size of 500 nm, is obtained at 21, 29, and 45 vol.% of n-C7 in the absence of the nanoparticles, in the presence of NiO, and in the presence of Fe3O4, respectively. The higher activity of the Fe3O4 nanoparticles for the control of the asphaltenes aggregation is attributed to the number and strength of the interactions of the asphaltenes functional groups with the surface sites of the nanoparticles. Furthermore, the near-wellbore tests results show that the shear stress leads to aggregation where the size of the asphaltenes nanoaggregates is smaller than around 50 nm. Fragmentation of the asphaltenes aggregates is the result of shear stress for samples with the aggregates sizes of higher than about 50 nm. This may be ascribed to the effects of the shear stress on the development of electrostatic fields (aggregation) as well as fragmentation (break up) of the asphaltenes aggregates in the model oils.

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1. INTRODUCTION One of the most important challenges associated with the production of oil from petroleum reservoirs is asphaltenes aggregation, flocculation, precipitation, and deposition especially on the surface of the porous media and wellbores. Asphaltenes are a solubility class of crude oil components that are soluble in light aromatics such as toluene and benzene but insoluble in lowmolecular-weight paraffins such as n-hexane and n-heptane.1, 2 The molecular structure of asphaltenes consists of carbon, hydrogen, and heteroatoms such as sulfur, nitrogen, oxygen, and metals. This describes the asphaltenes as the most polar and heaviest components of reservoir oils. Based on the modified Yen-Mullins model, the asphaltenes molecular structure is composed of a single aromatic sheet containing 4-10 fused rings and a small number of peripheral aliphatic chains.3-5 The average molecular weight and molecular size of the asphaltenes are reported to be 750 Da and 1.5 nm, respectively. The molecular structure and functional groups of asphaltenes lead to the asphaltenes self-association and aggregation. Therefore, asphaltenes are dispersed in reservoir oils as nanoaggregates of 5−20 nm sizes, depending on the pressure, temperature, and the oil composition.6, 7 During oil production, the changes in pressure, temperature, and composition of the reservoir oil as well as the turbulence and shear rate imposed on the oil lead to the destabilization and self-association of the asphaltenes nanoaggregates resulting in the formation of clusters of nanoaggregates.8-10 As the size of the asphaltenes clusters approaches 500 nm, their apparent weight prevails over Brownian forces of suspension and the asphaltenes clusters precipitate out of the liquid phase.11 The asphaltenes aggregation increases progressively the viscosity of the reservoir oil, dissipating the natural drive of the reservoirs.12, 13 In addition, adsorption of the asphaltenes aggregates onto the surface of the reservoir minerals and wellbores causes a detrimental damage within porous media and even clogging within wellbores.14 Wettability alteration of the pore surfaces of reservoir rocks because of the asphaltenes deposition leads to a negative change in the capillary pressure and relative permeability, resulting in a lower 3


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recovery factor.15, 16 The problems associated with the asphaltenes precipitation and deposition at the conditions of the wellbores and surface facilities are well-documented in the literature.17 Zougari et al.18 showed that the deposition rate of asphaltenes on wall surfaces is enhanced as the shear stress imposed on the oil decreases. This may imply that the higher the shear stress, the lower is the size of asphaltenes aggregates at the simulated wellbore test conditions. Therefore, control of the aggregation of the asphaltenes during production is of prime importance. Nanoparticle technology is found to have potential applications in upstream oil operations and recovery.19-27 Nanoparticles with sizes of 1-100 nm are very smaller than the 25-50 µm interparticle pore sizes of reservoir rocks, thus easily transportable in the porous media with no potential for formation damage while they are dispersed and stable.25, 28 In addition, the high surface to volume ratio and tunable surface sites are the other characteristics of the nanoparticles, making them good candidates for adsorption of asphaltenes aggregates from reservoir oils.19, 22, 23 Metal oxides nanoparticles have been employed as adsorbent/catalysts for in-situ upgrading of reservoir oils.19, 21-23, 26, 29-31 Hosseinpour et al. reported that the isotherms of asphaltenes adsorption onto different acid/base metal oxides nanoparticles, including NiO, Fe2O3, WO3, MgO, CaCO3, ZrO2, follow the Langmuir-type behavior with the adsorption capacity of 1.23−3.67 mg/m2.22 Acid-base interaction and electrostatic attraction were found as the dominant forces contributing to the asphaltenes adsorption onto the nanoparticles. Rapid adsorption of asphaltenes aggregates from asphaltenes/toluene solutions onto γ-Al2O3 nanoparticles has been reported by Nassar et al.19. It is found in the literature that the affinity of transition metal oxides nanoparticles for the adsorption of asphaltenes decreases in the order of NiO > Co3O4> Fe3O4.29 Both monolayer and multi-layer adsorption of asphaltenes onto the nanoparticles have been reported in the literature.19, 30, 31 Majority of the published results in the literature indicates that asphaltenes form monolayer coverage on surface sites of metal oxides nanoparticles exhibiting the Langmuir-type adsorption isotherms.19, 22, 23 Zamani et al.28 reported that 14-18% of the nanoparticles stabilized in aqueous 4


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phase are retained in a sand pack under simulated flow conditions of reservoirs. More recently, asphaltenes were used as the indigenous surfactants of reservoir oils for in-situ synthesis of NiO nanoparticles in the oil medium.26 As compared to ex-situ prepared NiO, the in-situ prepared nanoparticles exhibit a higher capacity for adsorption of the asphaltenes. In this work, the effects of metal oxides nanoparticles on control of the aggregation of asphaltenes at the simulated conditions of far-field and near-wellbore/wellbore are investigated. Fe3O4 and NiO nanoparticles are synthesized and their textural and structural properties are characterized. Asphaltenes are isolated from a heavy oil sample and dissolved in toluene to prepare reservoir model oil. The nanoparticles are added to the model oil and the size distribution of the asphaltenes aggregates are monitored by adding n-heptane and exposing to shear stress. The nanoparticles are expected to control the asphaltenes aggregation and make a significant delay in the asphaltenes precipitation onset. 2. MATERIALS AND METHODS 2.1. Materials Iron (III) nitrate (Fe(NO3)3·9H2O, Merck) and Nickel (II) nitrate (Ni(NO3)2·6H2O, Merck) were used as the Fe3O4 and NiO nanoparticles precursor salt, respectively. Ammonia solution (NH4OH, Merck) and urea solution (CO(NH2)2, Merck) were utilized as the precipitating agent during the synthesis of the nanoparticles. Asphaltenes were extracted from a dead oil sample of a heavy oil field. Toluene (99.8%, Merck) and n-heptane (99%, Merck) were utilized for either preparation of model oils or extraction of the asphaltenes. The chemicals were used as received with no further purifications. 2.2. Methods 2.2.1. Synthesis and characterization of NiO and Fe3O4 nanoparticles 5


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Nickel oxide (NiO) and magnetic iron oxide (Fe3O4) nanoparticles were synthesized via a simple precipitation method. An aqueous solution containing 0.05 M Ni(NO3)2·6H2O or Fe(NO3)3·9H2O was prepared for the synthesis of NiO or Fe3O4, respectively. 0.5 M urea or ammonia solution was added dropewise to the Ni- or Fe-precursor salt aqueous solution, respectively, for titration of the metal cations at fixed pH 10. The synthesis solutions were stirred at 400 rpm and 60oC for 12 h in sealed beakers. The resultant solutions were centrifuged at 5000 rpm for 10 min and the precipitates were washed, with de-ionized water, and centrifuged several times to achieve neutral pH. The thusobtained solid samples were dried at 80oC overnight and then calcined at 700oC in static air for 3 h. The crystalline structure of the nanoparticles was determined with X-ray powder diffraction (XRD) by a X’Pert Philips diffractometer using Cu-Kα1 (λ = 1.54056 Å) radiation, operating at a low scanning rate in the 2θ range of 5-70°. The Si(111) reflection was used as an external standard to calibrate peak positions. The specific surface area (SBET) of the synthesized nanoparticles was measured by the Brunauer-Emmett-Teller (BET) method using a Quantachrome CHEMBET-3000 apparatus. The samples were de-gassed at 400oC for 3 h under 20 cm3/min flow of N2. Then, the BET surface area was measured by adsorption of N2 at the liquid nitrogen temperature using the single-point method. The surface density of the acidic and basic sites of the nanoparticles was determined by NH3-temperature programmed desorption (NH3-TPD) and CO2-TPD, respectively, following the procedure reported in our previous work.22 The Fourier transform infrared (FTIR) transmission spectra of the nanoparticles were recorded on a Bruker-Alpha spectrometer to determine the structure as well as the functional groups on the surface of the nanoparticles. The samples were mixed with KBr powder and passed into thin transparent disks. Scanning of the spectral region from 4000-400 cm-1 was done with a resolution of 4 cm-1. In order to correct the interference of the ambient humidity, the background spectrum was collected on a thin KBr disk. The surface morphology and particle size of the samples were determined with field-emission scanning electron microscopy (FESEM) using a Hitachi S-6140 instrument. 6


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2.2.2. Asphaltenes extraction and model oil preparation Asphaltenes were extracted from an Iranian heavy oil sample by precipitation in excess n-heptane following the modified ASTM 2007-03 standard procedure. Prior to the asphaltenes extraction, the dead oil sample of the field was initially centrifuged at 7000 rpm for 1 h to remove water and particulates present in common field samples. A specified mass of the heavy oil was mixed with nheptane at the ratio of 1:40 g/mL in a sealed glass bottle. The mixture was then subjected to ultrasonic irradiation using an Ultrasonic Cleaner Elmasonic PH350EL apparatus for 30 min followed by stirring at 650 rpm for 24 h at room temperature. The mixture became two-phase and black precipitates were formed in the bottle. After decanting the supernatant liquid, the precipitates were mixed with fresh n-heptane at the ratio of 1:4 (g/mL) and then shaken for 10 min in order to remove any possible accompanying maltenes. The resultant mixture was centrifuged at 3500 rpm for 45 min. The washing with fresh n-heptane and subsequent centrifugation were repeated several times until the color of the asphaltenes became shiny black. The thus-obtained solid asphaltenes were dried at 60°C and refined and stored in a dessicator. The elemental composition of the asphaltenes was measured according to the ASTM D5291 (for C, H, and N) and UOP 864 (for S) standards. The oxygen content of the asphaltenes was measured by temperature-programmed pyrolysis as described in our previous report.21 The functional groups of the asphaltenes were characterized by FTIR spectroscopy following the procedure described in section 2.2.1. The acid number and base number of the asphaltenes were measured by titration method as detailed in our previous work.22 The size of the asphaltenes nanoaggregates as well as the configuration of the asphaltene molecules within the nanoaggregates has a significant effect on the aggregation and growth of the asphaltenes nanoaggregates. The average size of the asphaltenes nanoaggregates in reservoir oils is in the range of 5-20 nm depending on the reservoir conditions and oil composition.7, 10 Therefore, instead of preparing live oil by dissolving separator gas in dead oil at high pressures, model oil was prepared 7


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at atmospheric conditions to study the aggregation of the asphaltenes at the simulated conditions of far-field and near-wellbore/wellbore. Reservoir model oil was prepared by dissolving the asphaltenes in toluene at different concentrations. The size distribution of the asphaltenes nanoaggregates in the model oil was determined by dynamic light scattering (DLS-Malvern ZS Nano analyser-Malvern Instrument Inc, UK). DLS analysis showed that the average size of the asphaltenes aggregates in the 400 mg/L asphaltenes/toluene solution is 18 nm, representative of the size of asphaltenes aggregates in reservoir oils. Therefore, the asphaltene/toluene solution with the concentration of 400 mg/L was designated as model oil in this study. 2.2.3. Design of experiments A series of experiments was conducted to find the optimum ratio of the nanoparticles to the model oil for efficient removal and control of the asphaltenes aggregation. Different ratios of the nanoparticles were added to the model oil and the samples were shaken at 70 rpm for 24 h in an incubator (Fan Azma Gostar Ltd, Iran) to approach equilibrium. Following centrifugation of the equilibrium mixtures at 5000 rpm for 30 min, the supernatant liquids were analyzed by UV-vis spectroscopy (T90+ UV-vis spectrometer PG Instruments, Ltd., England), as described in our previous study.22 The optimum ratio was obtained by plotting the equilibrium adsorbed mass of the asphaltenes versus total mass of the asphaltenes present in the model oil. Therefore, the Fe3O4 and NiO nanoparticles were added to the model oil at the optimum ratio followed by shaking to achieve equilibrium, named static samples. In order to simulate the aggregation of the asphaltenes at far-field and near-wellbore/wellbore conditions, two series of aggregation-control experiments were designed and performed. 2.2.3.1. Far-field tests

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At far-field conditions, the growth of asphaltenes aggregates is mainly due to pressure depletion and there is no significant shear stress on the reservoir oil. Therefore, in the first series of the experiments, designated as far-field tests, different volume ratios of n-heptane as the asphaltenes precipitant were added to the static samples. The mixtures were shaken for 24 h at room temperature to approach new equilibrium. After the equilibrium was established, the mixtures were subjected to centrifugation or magnetic separation and the size distribution of the asphaltenes aggregates in the supernatant liquids was determined by DLS. The precipitated solids, i.e. the nanoparticles containing adsorbed asphaltenes, were analyzed with thermogravimetric analysis (TGA, Mettler Toledo- SF2) to determine the aggregate size and morphology of the adsorbed asphaltenes. 2.2.3.2. Near-wellbore tests In the second series of the aggregation-control experiments, the equilibrium samples obtained from the far-field tests were subjected for 1 h to different shear stresses of 22 and 278 mPa in a flow assurance apparatus at room temperature. The Couette-Taylor flow assurance apparatus consists of two concentric cylinders and the fluid in the annular space is subjected to shear stress by rotation of the internal cylinder. The diameter of the PTF Teflon internal cylinder is only 10 mm smaller than the external cylinder made of stainless steel 316 A. Optical images of the flow assurance apparatus are presented in section S1, Supporting Information. The design of the apparatus is based on achieving linear radial velocity in the 5 mm-radius annular space. Therefore, the shear stress on the fluids layers from the internal rotating cylinder to the external static cylinder is almost constant. For calculation of the shear stress, the viscosity of the supernatant liquids was measured according to the ASTM-D 445 and ISO 3104 standards by a U-tube Ostwald viscometer (Cannon-Fenske Company). The near-wellbore tests were conducted on the far-field samples containing the magnetic Fe3O4 nanoparticles and no tests were done in the presence of NiO. The samples obtained from the near-wellbore tests were exposed to magnetic separation and the supernatant liquids were 9


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subjected to DLS analysis. Table 1 summarizes the different series of experiments conducted in this study. Figure S2, Supporting Information, illustrates the experimental steps followed in this work. Table 1. The description of the experiments. Experiment ID

Experimental conditions

Far-field #1

In the absence of the nanoparticles and shear stress

Far-field #2

In the presence of the nanoparticles and absence of shear stress

Near-wellbore #1

In the presence of shear stress and absence of the nanoparticles

Near-wellbore #2

In the presence of shear stress and the Fe3O4 nanoparticles

3. RESULTS AND DISCUSSION 3.1. Characterization 3.1.1. Nanoparticles characterization Figure 1 exhibits the XRD patterns of the synthesized metal oxides nanoparticles. The resolved diffraction peaks indicate that crystalline structure of the nanoparticles is well developed during the synthesis process. The peak positions in the XRD pattern of the synthesized Fe3O4 and NiO nanoparticles corresponds to cubic magnetite (JCPDS 01-1111) and rhombohedral NiO (JCPDS 22-1189), respectively. The mean size of the crystallites (dXRD) of the nanoparticles is calculated by applying Scherrer’s equation on the main diffraction peak of their diffractogram, as summarized in Table 2. The average crystallite size of the NiO is around 78% larger than that of the Fe3O4 nanoparticles, inline with the sharpness of the diffraction peaks.

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Figure 1. X-ray diffraction patterns of the synthesized Fe3O4 and NiO nanoparticles. The BET specific surface area and the density of the acidic and basic surface sites of the synthesized nanoparticles are listed in Table 2. The surface area of the nanoparticles is high enough. Assuming nonporous spherical distinct particles, the average particle size (dBET (nm)) is estimated by dBET=6000/(ρ × SBET) where ρ is the skeletal density of the metal oxides (g/cm3) and SBET is the specific surface area of the nanoparticles (m2/g). The average particle size of the Fe3O4 sample is much smaller than that of the NiO nanoparticles. The crystallite size (dXRD) of both Fe3O4 and NiO is much smaller than dBET, indicating the presence of a degree of polycrystallinity in the structure of the nanoparticles. NH3-TPD and CO2-TPD data reveal that the surface sites of the NiO are acidic and responsible for the adsorption of NH3. However, the chemistry of the surface sites of the Fe3O4 nanoparticles is amphoteric and the density of their acidic sites is much higher than that of their basic sites. Considering both the acidic and basic sites, the density of the total surface sites of Fe3O4 is 12% lower than that of NiO. However, the number of the surface sites for a unit mass of the Fe3O4 nanoparticles is 49% higher than that of NiO since the surface area for a unit mass of the synthesized magnetite is almost 67% higher than that of the NiO nanoparticles. Table 2. The textural and surface properties of the synthesized nanoparticles.

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BET specific surface area (m2/g)

Particle size, i.e. dBET, (nm)

Crystallite size, i.e. dXRD, (nm)

Aciditya (µmol NH3/m2)

Basicitya (µmol CO2/m2)

Fe3O4

55

30

7.8

2.04

0.21

NiO

33

78

13.8

2.52

0.00

Metal oxide

a

The precision for NH3-TPD and CO2-TPD data is ±6%.

3.1.2. Solid asphaltenes characterization The asphaltenes carbon, hydrogen, sulfur , nitrogen, and oxygen content as obtained via elemental analysis is 82.58, 7.93, 6.98, 1.00, and 1.51 wt%, respectively. The H/C molar ratio in the asphaltenes structure is 1.14, indicating the presence of aromatic and aliphatic moieties in the asphaltenes molecular structure since the H/C ratio is slightly higher than that of benzene. The acid number and base number of the asphaltenes as determined by potentiometric titration are 2.75 and 12.34 mg of KOH/g, respectively. This may imply that the asphaltenes are more basic in nature. The XRD pattern of the solid asphaltenes is illustrated in Fig. 2. The broad peaks in the diffractogram show that the stacking of the asphaltene molecules in solid state is a structure with a high degree of short-range order. The (002) and (10) peaks are ascribed to the aromatic sheets of the asphaltenes while the aliphatic moieties of the asphaltenes result in the γ peak centered at 2θ = 20.4o.32 Therefore, it is inferred from the XRD pattern that the structure of the asphaltene molecules consists of polycyclic aromatic sheets and peripheral substituents. As illustrated in Fig. 2, the aromatic sheet diameter of the asphaltenes molecules (La), the average height of the stack of aromatic sheets perpendicular to the plane of the sheets (Lc), the layer distance between the aromatic sheets (dm) and finally the number of aromatic sheets (M) in a stacked cluster are estimated by applying the Warren’s and Bragg’s equations.32 B is the full width of the peaks at half-maximum and λ is the X-ray wavelength. La is obtained to be 1.29 nm, in closed agreement with the size of ≈1 nm reported in the literature.5

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Figure 2. X-ray diffraction patterns of the solid asphaltenes. Inset: Gaussian deconvolution of the lower-angle peaks. 3.2. Asphaltenes aggregation control 3.2.1. Static tests In order to find the optimum ratio of the nanoparticles to the model oil for the adsorption and control of aggregation of the asphaltenes, the static tests were conducted at room temperature with different dose of the nanoparticles. Figure 3 gives the asphaltenes adsorption onto Fe3O4 and NiO as a function of the dose of the nanoparticles. The adsorption curve for both the Fe3O4 and NiO approaches the line of symmetry asymptotically as the nanoparticles dose increases. This indicates that the adsorbed mass of the asphaltenes continually approaches the asphaltenes initial mass in the liquid, implying that the nanoparticles surface sites are becoming saturated with the asphaltenes.

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Figure 3. Asphaltenes adsorption at room temperature as a function of the dose of nanoparticles. Compared to the NiO sample, Fe3O4 exhibits a higher adsorbed mass of the asphaltenes since the adsorption curve over Fe3O4 gives the smallest distance to the line of symmetry. This may be ascribed to the more basic nature of the asphaltenes as well as the higher number of the mostly acidic surface sites for unit mass of Fe3O4 compared to that of NiO (see Table 2). The saturation dose is defined as the point at which the slope of the curves approaches the slope of the symmetry line and thereafter the distance to the line remains constant. The saturation dose for the Fe3O4 and NiO nanoparticles is at 7 and 10 g/g, respectively. Therefore, in order to be far from saturation, the optimum dose of the nanoparticles in all the asphaltenes aggregation control experiments was chosen at 25% of their saturation dose. It means that 14 mg of Fe3O4 or 20 mg of NiO nanoparticles were added to 20 mL of the model oil with 400 mg/L asphaltenes concentration. This corresponds to the ratio of around 0.09 m2 BET surface area of the nanoparticles /g of the asphaltenes. The FTIR spectra of the solid asphaltenes, NiO nanoparticles, and the NiO after asphaltenes adsorption at the optimum dose in the static test are illustrated in Fig. 4. The spectrum of the solid asphaltenes exhibits a small absorption band centered at 3048 cm-1 which corresponds to C–H vibration in aromatic double bonds (=C–H) and the peaks at 2922 and 2852 cm-1 corresponding to C-H stretching mode in aliphatic groups.33 The relatively wide absorption band at 1595 cm-1 is associated with the stretching vibrations of C=C aromatic bonds.34 The stretching vibration of – 14


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C=O in carboxyl groups makes a low intensity absorption band at 1704 cm-1.35 No absorption bands associated with nitrogen containing groups are observed in the spectrum of the asphaltenes, similar to what reported by Perez-Hernandez et al.36. The FTIR results are in agreement with the XRD pattern of the asphaltenes confirming the presence of both aromatic and aliphatic moieties in the asphaltenes structure.

Figure 4. FTIR spectra of solid asphaltenes, bare NiO, and NiO with adsorbed asphaltenes. The FTIR spectrum of the NiO nanoparticles presents a broad infrared absorption shoulder at 568 cm-1 corresponding to the stretching vibration of OH groups hydrogen-bound to Ni–O at the surface of the crystalline structure.37 The sharp absorption bands at 2922, 2852 and 1458 cm-1 in the asphaltenes spectrum appear in the FTIR spectrum of the NiO nanoparticles after the asphaltenes adsorption. Figure 5 presents the FESEM micrograph of the nanoparticles before and after asphaltenes adsorption at the optimum dose in the static tests. Surface morphology of the Fe3O4 sample (Fig. 5a left side) shows loosely attached sphere-like nanoparticles with the sizes of 20–45 nm, in agreement with the average size obtained from the BET measurements (see Table 2). Adsorption of 15


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the asphaltenes onto the Fe3O4 surface (Fig. 5a right) alters the morphology of the sample leading to the appearance of almost evenly distributed particles with a relatively larger average size of around 60 nm possessing more distinguishable boundaries. The surface of NiO (Fig. 5b left) is composed of almost agglomerated nanoparticles. After the adsorption of the asphaltenes (Fig. 5b right), the NiO nanoparticles become more distinct and their surface boundaries are discernible with the sizes of 50-90 nm. The asphaltenes adsorption onto the metal oxides surfaces leads to a decline in the surfaces Gibbs energy. Therefore, after adsorption of the asphaltenes, the nanoparticles exhibit weaker interactions with their neighboring particles. Therefore, as observed in Fig. 5, the surface morphology of the nanoparticles containing adsorbed asphaltenes exhibits almost distinct particles with more distinguishable surface boundaries.

Figure 5. FESEM micrograph of (a) Fe3O4 and (b) NiO before (left) and after (right) asphaltenes adsorption. Scale bar is 500 nm. 16


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3.2.2. Far-field tests The far-field tests were designed to assess the activity of the nanoparticles for the control of the asphaltenes aggregation in the absence of shear stress. In order to simulate the effects of pressure depletion on asphaltenes aggregation, n-heptane was added to the model oil in the presence and absence of the nanoparticles and the aggregation growth was monitored by DLS. The aggregate size distribution of the asphaltenes in the model oil in the absence of the nanoparticles as a function of the vol.% of added n-heptane is shown in Fig. 6. The average size of the asphaltenes aggregates in the equilibrium far-field samples in the absence of the nanoparticles grows from 18 nm to 38, 89, 167, 465, 778, and 1080 nm by adding 5, 10, 15, 20, 25, and 30 vol.% n-heptane. By addition of nheptane, the aromaticity of the model oil decreases and self-association of the asphaltenes leads to aggregation and growth.38 The tendency of the asphaltenes for self-association is low at lower concentrations of n-C7 but it is rapidly increased when the volume fraction of n-heptane approaches 15%. The average size of the asphaltenes aggregates at the precipitation onset point is considered 500 nm. Therefore, the results indicate that a fraction of the asphaltenes precipitates out when the concentration of the n-C7 is higher than around 20 vol.%.

17


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Figure 6. The asphaltenes aggregate size distribution in the model oil in the absence of the nanoparticles as a function of the added vol.% of n-heptane at room temperature. Figure 7 illustrates the rate of asphaltenes aggregate growth in the equilibrium far-field liquid samples in the absence and presence of the nanoparticles as a function of n-C7 concentration. At all concentrations of n-C7, the average sizes of the asphaltenes aggregates are smaller in the presence of the nanoparticles compared to those in the nanoparticles-free model oil. This is attributed to the capacity of the nanoparticles for the asphaltenes adsorption. The asphaltenes are adsorbed on the surface sites of the nanoparticles spontaneously, resulting in a lower molar concentration of the asphaltenes in the liquid phase.19, 22, 30 This leads to a lower degree of self-association and thus smaller aggregates sizes. Therefore, the asphaltenes tend to migrate to the nanoparticle surface sites as smaller aggregates. For instance, at 25 vol.% n-C7, the average aggregates size of the asphaltenes is 778 nm in the nanoparticles-free model oil and it becomes very small and equal to 343 and 445 nm in the presence of the Fe3O4 and NiO nanoparticles. The model oil is becoming brownish when the amount of the added n-heptane approaches 70 vol.% in the presence of the nanoparticles, as illustrated in Fig. S3, Supporting Information. The aromaticity of the model oil seems to reach a critical value when the volume fraction of the n-C7 as a precipitant approaches 15%, leading to higher tendencies of asphaltenes for self-association and higher rate of aggregation. As observed in Fig. 7, the asphaltenes onset point is at 21, 29, and 45 vol.% of n-heptane in the absence of the nanoparticles, in the presence of NiO, and in the presence of Fe3O4 nanoparticles, respectively.

18


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Figure 7. The aggregate growth of the asphaltenes in the absence and presence of Fe3O4 and NiO nanoparticles during the far-field tests at room temperature. Therefore, the nanoparticles control the rate of the asphaltenes aggregation. The higher activity of Fe3O4 for the aggregation control may be ascribed to the number and strength of the interactions of the Fe3O4 amphoteric surface sites with the acidic and basic functional groups of the asphaltenes, as reported elsewhere.22, 31 The aggregation control may indicate that the asphaltenes tendency for interaction with the nanoparticles surface sites is higher than that for self-association in the liquid phase. At low concentration of n-C7, the aromaticity of the liquid is high enough and the selfassociation tendency of the asphaltenes and their propensity for interaction and adsorption on the surface sites of the nanoparticles are almost the same. This is why the nanoparticles exhibit a low activity for the asphaltenes aggregation control when the model oil aromaticity is high. As the aromaticity of the model oil approaches the critical value, the tendency of the asphaltenes for adsorption onto the nanoparticles surfaces increases and all the surface sites may become saturated, leading to a high activity for the control of the asphaltenes aggregation. In addition, upon further adsorption, the aggregates of the adsorbed asphaltenes may grow on each surface site of the nanoparticles.

19


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In order to assess the growth of the asphaltenes aggregates on the nanoparticles surfaces, the solid precipitates obtained from the far-field tests, at the n-C7 concentrations lower than the onset points, were subjected to TGA analysis. Figure 8 exhibits the TGA mass loss of the asphaltenes adsorbed onto NiO in the far-field tests. For the sake of comparison, the TGA curve of the solid asphaltenes is also included in Fig. 8. All the TGA profiles consist of a low- temperature and a hightemperature peak. A mass-loss peak in a TGA profile is a temperature at which the slope of the profile changes suddenly. The low-temperature mass-loss peak is associated with the oxidation of the peripheral aliphatic moieties of the asphaltenes, and the high-temperature peak in the TGA profiles is attributed to the oxidation of the polynuclear aromatic sheets of the asphaltenes.21 Compared to the oxidation of the solid asphaltenes, both the low- and high-temperature mass-loss peaks of the adsorbed asphaltenes are shifted to lower temperatures by the NiO nanoparticles. This is ascribed to the catalytic activity of the NiO nanoparticles as well as the dispersion of the asphaltenes on the surface.21, 26, 29, 30 For the asphaltenes adsorbed onto the NiO surface, there are only two oxidation peaks and they shift to higher temperatures as the asphaltenes aggregate size in the accompanying liquid phase of the samples increases. The absence of any extra mass-loss peaks in the TGA profile of the adsorbed asphaltenes may indicate monolayer adsorption on the surface sites of the nanoparticles, in agreement with the reports in the literature.19, 22 For multi-layer adsorption of the aggregates, multiple oxidation peaks are expected since the asphaltenes aggregates in close contact with the surface are oxidized at lower temperatures when compared to those far from the catalytic surface. Therefore, it is inferred that monolayer adsorption of the asphaltenes aggregates occurs on the surface sites of the nanoparticles and the adsorbed aggregates grow as the asphaltenes in the liquid phase become destabilized.

20


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Energy & Fuels

Figure 8. TGA mass loss curves of solid asphaltenes and the asphaltene adsorbed onto the NiO nanoparticles in the far-field tests. 3.2.3. Near-wellbore tests The near-wellbore tests were design and conducted to study the activity of the nanoparticles for the control of the asphaltenes aggregation under shear stress. The equilibrium samples, in which the asphaltenes are far from the precipitation onset point as determined by the far-field tests, were subjected to shear stress in a Couette-Taylor flow assurance apparatus. The density and dynamic viscosity of the model oils are measured to be about 0.84 g/cm3 and 0.65 cP, respectively. The density and viscosity of the model oils are not a function of their n-heptane content. By applying the shear rate of 60 and 750 rpm on the model oils, the shear stress in the liquid layers is calculated to be 22 and 278 mPa, respectively. The far-filed samples containing less than 15 vol.% of n-C7 and without the no nanoparticles , were subjected to the 22 and 278 mPa shear stress for 1 h and the average size of the asphaltenes aggregates were measured, as reported in Table 3. As the shear stress is increased by 12.6 times, the size of the asphaltenes aggregates becomes larger and the growth is more intense for smaller aggregates sizes. Therefore, for having remarkable growth of the aggregates, all the near-wellbore tests were carried out at the shear stress of 278 mPa. 21


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Table 3. The average aggregates size of the asphaltenes in the model oil, without nanoparticles, exposed to different shear stresses of 22 and 278 mPa for 1 h at room temperature. Model oil without nanoparticles

Aggregate size (nm) at shear stress of 22 mPa

Aggregate size (nm) at shear stress of 278 mPa

Aggregate size growth (%)

Without n-C7

15.8

23.2

46.9

5 vol.% n-C7

33.0

46.4

40.6

15 vol.% n-C7

47.1

63.5

34.8

Figure 9 presents the alteration of the asphaltenes aggregate size in the far-field test samples exposed to the shear stress of 278 mPa during the near-wellbore tests. In both presence and absence of the Fe3O4 nanoparticles, the shear stress leads to the aggregates growth when the initial size of the asphaltenes aggregates, known from the far-field test, is smaller than around 50 nm. Fragmentation of the asphaltenes aggregates with the initial sizes of larger than 50 nm is a result of exposition to the shear stress. In addition, the presence of the Fe3O4 nanoparticles gives rise to the control of the growth of the asphaltenes aggregates. Furthermore, the rate of fragmentation decreases and aggregation starts to prevail as the initial size of the asphaltenes aggregates become large enough. Aggregate growth in the presence of shear stress is a dynamic process resulting from two main opposing processes, i.e. aggregation and fragmentation. In general, the rate of these two processes is not equal and the growth or break up of the asphaltenes aggregates occurs depending on which process is predominant. The rate of aggregation depends on the rate of collision of the aggregates and the probability of coagulation after collision.39 In addition, the asphaltenes aggregates have surface charges originating from their acidic/basic functional groups. Therefore, the subjection of the oil to shear stress results in different velocities for different layers of the liquid, leading to self-association of the aggregates due to attraction via overlapping of their associated electric fields.18 Fragmentation of the aggregates, on the other hand, occurs as a response to the shear stress applied on the liquid and is a function of the aggregates size.38, 40 As a 22


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Energy & Fuels

conclusion, the aggregation is the dominant process when the asphaltenes aggregates are smaller than around 50 nm, while fragmentation is predominant for samples with larger aggregates of the asphaltenes.

Figure 9. The size of the asphaltenes aggregates in the presence and absence of the Fe3O4 nanoparticles in the near-wellbore and far-field tests done at room temperature. The interaction of the asphaltenes with the surface sites of the nanoparticles seems to decrease the possibility of the asphaltenes aggregation in the liquid even when aggregation is the predominant process. This may indicate that the broken-up asphaltenes aggregates in the liquid tend to be adsorbed onto the nanoparticles surfaces. This leads to the control of the asphaltenes aggregation in the near-wellbore tests. 4. CONCLUSIONS Crystalline Fe3O4 and NiO nanoparticles were synthesized and their surfaces were characterized in terms of the texture and chemistry. The surface of the Fe3O4 nanoparticles contains amphoteric sites while the surface sites of the NiO are acidic. The surface density of the sites of both the nanoparticles is almost the same. The functional groups of the solid asphaltenes extracted from an 23


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oil sample were also characterized. The base number of the asphaltenes is 4.5 times of their acid number. 400 mg/L of the solid asphaltenes were dissolved in toluene to prepare model oil. Two series of experiments, designated as far-field and near-wellbore tests, were designed and conducted to assess the capability of the nanoparticles for the control of the asphaltenes aggregation. The results of the far-field tests show that the strength of the self-association and interaction of the asphaltenes with the surface sites of the nanoparticles are a function of the aromaticity of the model oil. At high aromaticities, the asphaltenes tend to self-associate and the nanoparticles exhibit a low activity for the aggregation control. However, when the model oil aromaticity decreases and approaches a critical value, the asphaltenes adsorption onto the nanoparticles is predominant and the nanoparticles control the asphaltenes aggregation. Compared to NiO, the Fe3O4 nanoparticles exhibit a higher activity for the aggregation control. This may be ascribed to the strength and amphoteric nature of the surface sites of Fe3O4. In addition, monolayer adsorption of the asphaltenes onto the surface of the nanoparticles is inferred from the TGA analyses. Furthermore, the near-wellbore tests show that shear stress can lead to aggregation and fragmentation of the asphaltenes aggregates both in the presence and absence of the nanoparticles. Aggregation is dominant when the size of the asphaltenes nanoaggregates is smaller than around 50 nm, and for larger sizes fragmentation prevails. Shear stress and the aggregates size control the fragmentation of the asphaltenes aggregates. The interaction of the asphaltenes with the nanoparticles leads to the control of the aggregation under shear stress.

ASSOCIATED CONTENT Supporting Information Available: The optical images of the Couette-Taylor flow assurance apparatus used in this study, summary of the experimental steps followed in this work, the optical image of the far-field tests samples. This material is available in the online version. 24


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Energy & Fuels

AUTHOR INFORMATION *Corresponding Author E-mail address: [email protected] (N. Hosseinpour) Tel: +98 (21) 61114712, Fax: +98 (21) 88632976 ACKNOWLEDGMENTS The authors are grateful to Ali Fazlali from Dr. Hosseinpour’s research group at the Institute of Petroleum Engineering of the University of Tehran for helping in gathering a part of the nearwellbore tests results. REFERENCES 1.

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Control of Asphaltene Aggregation in Reservoir Model Oils along the

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