VGO nanofluids for enhanced thermal oil recovery application

Journal of Petroleum Science and Engineering xxx (xxxx) xxx

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Enhanced thermal conductivity and reduced viscosity of aegirine-based VR/VGO nanofluids for enhanced thermal oil recovery application Robert Mustafin a, Abdallah D. Manasrah a, Gerardo Vitale a, Roohollah Askari b, Nashaat N. Nassar a, * a b

Department of Chemical and Petroleum Engineering, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada Department of Geological and Mining Engineering and Sciences, Michigan Technological University, Houghton, MI, USA, 49931

A R T I C L E I N F O

A B S T R A C T

Keywords: Nanoparticles Vacuum residue Vacuum gas oil Nanofluids Thermal conductivity Oil recovery

The depleting of the available conventional energy supplies together with an industrial shift towards uncon­ ventional resources like heavy oil/bitumen has become more pronounced. The steam-based heating methods are primarily used by the oil industry for the heavy oil/bitumen recovery. However, the thermal recovery methods are energy-intensive and have limited applications, especially for both thin and deep reservoirs. Therefore, there is a high priority need to investigate alternative approaches. To date, the most progressive alternative technique that has proven its potential during pilot-plant tests is nanocatalytic in-situ heavy oil/bitumen upgrading via hotfluid injection. Hence, the continual improvement of this technique is of utmost importance. This study aims to propose a new injecting nanofluid system suitable for high-temperature injection into the reservoir with consecutive heavy oil/bitumen upgrading and recovery. Here we report a new type of copper-based nanofluid using a blend of vacuum gas oil (VGO) and vacuum residue (VR) as the mother solvent. The nanoparticles were prepared by low-temperature hydrothermal synthesis route. Their detailed surface, morphology and size char­ acterizations were achieved by X-ray diffraction, dynamic light scattering and scanning electron microscopy. The stable nanofluids were prepared by dispersing copper-based nanoparticles in a mixture of VGO and VR, at different ratios and temperatures. A set of measurements to determine the thermal conductivity and viscosity of the nanofluid with different loading of nanoparticle were performed. The thermal conductivity values of nanofluid systems are substantially higher than that of the base fluids. The nanofluid for 2 wt% of copper-doped aegirine nanoparticles dispersed in VGO and VGO/VR mixture exhibits a maximum thermal conductivity of 20% and 24%, respectively. It was found that the thermal conductivity of nanofluids increases with decreasing the hydrodynamic particle size. Moreover, the presence of chemo-physical interactions between nanoparticles and base fluid further enhances the thermal conductivity. Also, the temperature augmentation in a range from 80 to 110 � C exhibited a positive effect on thermal conductivity enhancement of vacuum residue-based nanofluid system. This particular nanofluid may find potential applications in enhancing heavy oil upgrading and recovery.

1. Introduction

2009). Hence, it is necessary to explore the exploitation of unconven­ tional reservoirs like oil sands and shale oil that are forming more than 70% of the total oil resources (Felix et al., 2006). The in-situ production of bitumen from oil sands reservoirs relays on the lowering the oil viscosity through heating the reservoir. The thermal enhanced oil recovery (TEOR) processes are the most commonly prac­ ticed methods for heavy oil extraction. TEOR can broadly be divided into two main categories, namely: steam injection and in situ combus­ tions (Shah et al., 2010). Among them, steam-assisted gravity drainage (SAGD) which is an economically proven technique to produce bitumen

The 2018 BP Energy Outlook indicates the importance of fossil fuelbased energy in the global energy market up to the 2040 year (Kisman and Lau, 1994; Liddle, 2014). To maintain the sensitive energy balance between demand and supply, an abundant amount of energy is extracted from conventional oil fields (Owen et al., 2010). However, the oil pro­ duction volume from conventional reservoirs is continuously depleting and in the foreseeable future will become not enough to meet the €o €k et al., worldwide energy demand (Campbell and Laherr�ere, 1998; Ho

* Corresponding author. E-mail address: [email protected] (N.N. Nassar). https://doi.org/10.1016/j.petrol.2019.106569 Received 18 July 2019; Received in revised form 25 September 2019; Accepted 7 October 2019 Available online 10 October 2019 0920-4105/© 2019 Published by Elsevier B.V.

Please cite this article as: Robert Mustafin, Journal of Petroleum Science and Engineering, https://doi.org/10.1016/j.petrol.2019.106569

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whereby two nearly horizontal wells are drilled in a bottom of the thick formation. Hence, high viscosity of bitumen is the main limitation for underground recovery, thus it should be decreased in order to reduce the flow resistance of bitumen through porous media. In SAGD, steam is employed as the heat carrier to reduce the viscosity of bitumen, and consequently, reduce the flow resistance of bitumen through porous media which increases the production rate (Shah et al., 2010). Heat conduction is a key parameter in delivering the heat into cold bitumen where the estimation of thermal conductivity of the solid-fluid mixture becomes significant (Askari et al., 2017; Heidari et al., 2017; Ikram et al., 2018). SAGD is a high energy-intensive process which exhibits the necessity of fuel supply as a heat source for steam generation as well as an abundance of water resources and water processing facilities (United States. Congress. Senate. Committee on and Natural, 2009). Addition­ ally, it is associated with greenhouse gases emissions. Furthermore, the SAGD process is limited to good quality reservoirs in terms of depth and thickness. Thus, it is essential to investigate alternative ways of in-situ recovery of heavy oil that should be environmentally friendly and cost-effective amid slumping oil prices (Hashemi et al., 2013). Such an approach becomes possible with the introduction of nanoparticles into the field of the oil recovery process. Different mechanisms of nano­ particle application in conventional oil fields are described in the liter­ ature (Bazazi et al., 2019; Sagala et al., 2019), such as interfacial tension reduction (Hendraningrat et al., 2013; Hendraningrat and Torsæter, 2015; Nwidee, 2017), wettability alteration (Karimi et al., 2012; Kon­ diparty et al., 2011; Wasan et al., 2011), the inhibition of formation damage (Franco et al., 2013b), asphaltene disaggregation (Nassar et al., 2015) and viscosity reduction (Nassar et al., 2011a, 2011b, 2011c, 2012). Specifically, the viscosity reduction of heavy oil and bitumen was successfully achieved by integrating nanoparticles in the process scheme, in the pilot-plant tests for nanocatalysis in-situ heavy oil/bitu­ men upgrading via hot-fluid injection developed by Pereira-Alamo and co-workers at the University of Calgary (Almao, 2012). In that process, heat is provided by hot fluid injection instead of steam. This hot fluid is a mixture of heated vacuum residue (VR) and/or vacuum gas oil (VGO). For a successful application, several points are considered to improve the quality of produced oil, namely: (1) the transportation of catalysts through the sand medium inside the formation should be achieved (Hashemi et al., 2013), whereby a catalyst in nanoscale has to be pre­ pared and applied; (2) the presence of hydrogen is mandatory to mobilize heavy oil/bitumen and co-reactants to provide catalytic re­ actions inside the formation; (3) it is necessary to maintain enough temperature and pressure conditions for targeted upgrading degree. Two major steps have to be considered during hot fluid injection, namely: the reservoir should be saturated with dispersed nanocatalysts that are attached to reservoirs core; and the targeted transport depth of the reservoir should be attained by manipulating a number of factors, such as injection temperature, pressure and flow rate (Hashemi, 2013). These considered mechanisms can be achieved by dispersing nano­ particles into different oil-based media such as VGO and VR (Rodriguez, 2017). Since the low economical value of VR, it would be beneficial to use it as a carrier fluid in the form of nanofluid (Hovsepian, 2016). The unique properties of nanoparticles such as high surface area to volume ratio, high degree of dispersion in porous media, excellent adsorption affinity, high catalytic activity and good thermal conductivity provide a great impact on enhancement in heat transfer coefficient of the VR-nanofluids. Therefore, decoration of reservoir with these nanofluids leads the reservoir to start acting as “pseudo-packed fixed-bed reactor,” (Hovsepian, 2016) in which the partially upgraded product that meets pipeline requirements is pumped to the surface. Despite all of these benefits, continual improvement of hot fluid injection technique is of utmost importance. Herein, we proposed a naturally-derived nanofluid system with enhanced thermal conductivity, a key parameter in thermal EOR using in-house prepared copper-doped aegirine. The copper aegirine is develop based on the iron-silicate pyroxene mineral, known as aegirine

(NaFeSi2O6) which is a naturally-derived crystalline material in the earth’s crust. In terms of catalytic effects, our research group has recently proven that copper/iron-based silicate materials have a great catalytic activity towards upgrading the heavy residual feedstocks like petroleum coke and asphaltenes due to its high chemical and thermal stability and unique physical-chemical properties (Hmoudah, 2016; Manasrah, 2018). For a comparison, copper oxide nanoparticles were also employed in this study as a control material in nanofluids appli­ cation. These copper-based materials are prepared using a low-temperature hydrothermal synthesis route and characterized using XRD, BET, and SEM. After preparing the nanofluids by dispersing different concentration of copper-doped aegirine nanoparticles into different oil media such as mineral oil, glycerol oil, vacuum gas oil and vacuum residue, the thermal conductivity and viscosity are measured. The effects of nanoparticles concentration on the thermal conductivity, the thermal properties of VR-VGO material and VR-nanofluid are investigated using copper-doped aegirine. This study provides vital in­ sights about the use of nanofluids as a hot fluid injection which might have favorable effects and strategic importance on enhancing heavy oil/bitumen upgrading and recovery processes. 2. Experimental work 2.1. Materials The chemicals and reagents such as sodium hydroxide (NaOH, 99 wt % purity), anhydrous ferric chloride (FeCl3, 97 wt% purity), sulfuric acid (H2SO4, 98 wt% purity), cupric acetate monohydrate (Cu (CH3COO).2H2O, 99 wt% purity), sodium silicate (27 wt % SiO2, 10.85 wt% Na2O), and copper (II) nitrate (Cu(NO3)2, 98% purity) were purchased from Sigma-Aldrich, Ontario, Canada and used as received. Four different types of oil-based media were used for preparation of nanofluids, namely vacuum residue (VR) from Athabasca bitumen and vacuum gas oil (VGO), both obtained from a local industrial partner in Alberta; glycerol obtained from Sigma-Aldrich Ontario, Canada, and mineral oil was purchased from Calumet Penreco LLC, Pennsylvania, USA. 2.2. Preparation of nanoparticles 2.2.1. Copper-doped aegirine nanoparticles Copper-doped aegirine nanoparticles (7.5 wt% Cu-doped on FeNaO6Si2) were prepared by controlled time and low-temperature hydrothermal synthesis route. The acidic solution was prepared by careful addition of ~12.8 g of concentrated H2SO4 to 65.0 g of deionized water under magnetic stirring (300 rpm). This step was followed by dissolving ~9.0 g of anhydrous iron chloride (FeCl3) in diluted sulfuric acid solution and subsequent dissolution of ~4.5 g of copper (II) acetate. On the other hand, the basic solution was prepared by dissolving ~21.5 g of NaOH in 45.0 g of distilled water under magnetic stirring (300 rpm) and then 43.3 g of sodium silicate was added to this alkaline solution and agitated until complete homogenization. Further, the acid solution was slowly added to the basic solution under 300 rpm and stirred for 15 min at its own temperature to produce a homogeneous fluid-like brown gel. Then, the prepared gel was transferred to a 300 mL stainless-steel Parr reactor (series 2950), heated up to 453 K for 72 h with agitation at 300 rpm. After reaching the desired crystallization time, the obtained solution was cooled down; filtered and washed with distilled water until the pH level was close to 7, and then the gel was allowed to dry overnight at room temperature. Finally, the dried mass was ground until the homogeneous powder of copper-doped aegirine nanoparticles was obtained. The as-synthesized solid was labelled as CuAeg. 2.2.2. Copper oxide nanoparticles The copper (II) oxide (CuO) nanoparticles were synthesized by 2

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calcination of copper (II) nitrate precursor and used as a control sample. 10.0 g of Cu(NO3)2 were powdered in porcelain capsule and immersed into Barnstead 62700 Furnace for 12 h under 573 K with the heating step rate 15 K/min. After calcination, black CuO nanoparticles powder was obtained, cooled overnight and ground for further characterizations. Worth mentioning here that the copper oxide nanofluid was used as a control sample for the comparison purpose. 2.3. Characterization of nanoparticles 2.3.1. X-ray diffraction (XRD) The crystalline structure for the prepared nanoparticles was identi­ fied using X-ray diffraction (XRD). XRD was also performed to estimate crystalline domain size by using X-ray Ultima III Multi-Purpose Diffraction System (Rigaku Corp., The Woodlands, TX) with Cu Kα ra­ diation operating at 40 kV and 44 mA with a θ-2θ goniometer. The analyzer has a 0.5 mm in depth glass sample holder that was filled with uniformly distributed material for analysis and provided scans in the range of 3–90� 2-θ degrees using a 0.02� step and a counting time of 1.0� per min. The crystalline domain sizes of the prepared nanoparticles were estimated using the Scherrer’s equation as implemented in the software JADE by fitting the experimental profile to a pseudo-Voigt profile function, and then, calculating the full width at half maximum of the peak. 2.3.2. Textural properties The surface area and porosity of the prepared materials were measured following the Bruneur-Emmett-Teller (BET) method. The analysis was accomplished by performing nitrogen physisorption at 77 K using TriStar II 3020, Micromeritics Instrument Corporation, Norcross, GA. Before the analysis, the samples were degassed at 423 K and pretreated inside the sample holder cells under a flow of nitrogen overnight. 2.3.3. Scanning electron microscopy A field emission electron microscope Quanta 250, manufactured by FEI, a type of scanning electron microscope (SEM), was used to inves­ tigate the size and morphology of the prepared materials. The tested materials were prepared by placing a tiny amount of powder over a carbon tape. Then, the carbon tape sample holder was taped in order to allow the extra amount of powder to release out. After that, the tape with material powder was inserted inside the microscope chamber. Selected images were taken under different magnifications.

Fig. 1. Schematic representation of the two-step preparation method of different types of nanofluids.

measurements were performed using a TP08 probe (Hukseflux, Holland) connected with a computer via Field Point relay system which was fulfilling the role of controller unit for data collection and voltage supply (National Instrument, USA). The TP08 probe offers a practical and fast measurement of thermal conductivity of the medium. The probe is directly inserted into a cell filled with the target specimen. The cell has a specific dimension that the wall effect on the TC measurements are minimized. The probe has a heating element inside which acts as a heat line source where the increase in the sample temperature is automati­ cally registered every 3 s over a period of 200 s; synchronizing with Field Point relay system. The TC of each sample is calculated using a graphical technique from the straight line constructed by plotting the amount of heat released against time in a semi-log plot. Five thermal conductivity measurements were recorded in 1 h for each sample and each temper­ ature to ensure that the sample was at thermal equilibrium, and the averaged value was presented as a final TC. The thermal conductivity probe was firstly calibrated and validated with the known thermal conductivity solution using 5% agar gel, which has a thermal conduc­ tivity value close to pure water (0.6 W/mK) at 293 K. The calibration results showed the uncertainty of measurements to be about 2%.

2.4. Nanofluid preparation The two-step method was implemented to prepare all types of nanofluid systems considered in this study following the schematic representation shown in Fig. 1. The nanoparticles were initially syn­ thesized in dry powder form as previously explained. Then, a specified amount of each powder was slowly and gradually added to 80 mL of base fluid at 298 K and magnetic agitation (300 rpm). Afterwards, the solu­ tion was stirred for 120 min before being physically stabilized in an ultrasonic bath with 2700 Hz for 60 min to break the Van-der-Waals forces between nanoparticles and oil media and thus ensure better dispersing of nanomaterials in the base fluid matrix. For high-viscous media like VR-VGO based matrix and VR-VGO nanofluid systems, the VR was firstly heated up to 363 K to reduce its initial viscosity and then the nanoparticles and/or VGO were gradually added into the media under 300 rpm magnetic stirring.

2.5.2. Dynamic light scattering analysis Dynamic light scattering (DLS) analysis was performed to estimate the average hydrodynamic particle size of prepared nanoparticles in the nanofluid solutions. For this purpose, the Zetasizer Nano Series system from Malvern Instruments Ltd. was utilized to analyze the size of solid particles suspended in liquid media. To get the permissible level of op­ tical transparency in dilution, it was decided to fix the concentration of nanoparticles at 20 ppm (0.002 wt%) and follow the procedure of

2.5. Characterization of prepared nanofluids 2.5.1. Thermal conductivity measurements The thermal conductivity (TC) of the prepared nanofluid systems was measured right after the sonication process and placed in such a way to ensure identical conditions of measurements for all samples. The TC 3

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nanofluid preparation as described earlier. After applying the sonication of nanofluids for 30 min, the DLS analysis was conducted.

1011148, and aegirine PDF 9000327 for CuO and CuAeg, respectively. The sharp peaks appearing in the expected positions confirmed the formation of the crystalline materials. Positions and relative intensities of the diffraction peaks of the samples are in a great agreement with previously reported studies (Hmoudah, 2016; Wang et al., 2002). Table 1 displays the obtained crystalline domain sizes for CuO and CuAeg nanoparticles which were estimated with the commercial soft­ ware JADE by fitting the experimental profile to a pseudo-Voigt profile function and calculating the full width at half maximum (FWHM) of the peak using the Scherrer’s equation. As shown in the table, low crystal­ line domain sizes can be observed for CuO and CuAeg nanoparticles which may have favourably affect the TC enhancement as smaller-sized nanoparticles can possibly enhance TC compare with the larger size one (Manasrah et al., 2018; Tawfik, 2017). To get an insight into the surface atomic structure of the prepared materials, the optimized (001) surfaces of presented nanocrystalline materials are depicted in Fig. 3. As shown in Fig. 3a, the atomic structure of CuAeg is similar to 7.5Ni-doped aegirine reported by Sebakhy et al. (2018). However, instead of Ni, dispersion of the metallic Cu clusters on

2.5.3. Viscosity measurements The rheological behavior of VR and VR-based nanofluid were eval­ uated using a rheometer (MCR 302, Anton Paar). The rheometer is equipped with 25 mm cone-and-plate geometry which has a cone angle of 1 and truncation of 47 μm. A Peltier temperature system (P-PTD 200) attached to the chamber provides a temperature range from 233 to 473 K with high heating and cooling rates of 40 K/min with an accuracy of 0.1 K. A stainless-steel concentric cylinder was used to determine the dynamic viscosity of VR-based nanofluid over temperature range from 353 to 383 K. The nanofluid was placed between the concentric cylin­ ders and allowed to achieve temperature stabilization for 5 min. To ensure accurate results, the rheometer was calibrated with pure ethylene glycol at 298 K, and the viscosity results were within a maximum de­ viation of �2%. The viscosity measurements were taken in triplicates and the averaged value was presented in the results within averaged with a maximum standard deviation of �4.5%. 3. Results and discussion

Table 1 Crystalline domain sizes obtained by XRD for the prepared materials.

3.1. Nanoparticles characterization Fig. 2 shows the XRD patterns for the CuO, and CuAeg along with the reported values of targeted material from the COD database. As shown, the XRD patterns are matched with COD file numbers of ternorite PDF

Particle type

Crystalline domain size by XRD (nm)

CuO CuAeg

15.6 � 1 10.3 � 2

Fig. 2. XRD patterns and their comparison with targeted materials for a) CuO, and b) CuAeg nanoparticles. 4

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Fig. 3. Corey-Pauling-Koltun (CPK) surface representation of the surface (001) of a) CuAeg, and b) CuO. Blue atoms represent copper atoms, red atoms represent oxygen, yellow atoms represent silicon, dark green atoms represent sodium while light blue atoms represent iron. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

the surface of the aegirine-carrier was replaced in our case for CuAeg. On the other hand, CuO nanoparticles have significantly more dispersed Cu atoms on the surface compared with CuAeg as shown in Fig. 3b, which could play a role in TC enhancement of the nanofluid. However, the TC enhancement of nanofluid is more dependent on particle size and the € dispersion of nanoparticles in the media (Manasrah et al., 2017; Ozerinç

observations were reported for the natural aegirine counterparts but with a difference in scale (Hmoudah, 2016). Noteworthy mentioning, the actual hydrodynamic size of all tested particles in the oil media was measured with DLS analysis as presented in the upcoming section. 3.2. Thermal conductivity enhancement of prepared oil-based nanofluids

et al., 2010). Moreover, it was reported that the surface area of nanomaterial might play a significant role in TC enhancement, as heat transfer takes place at the surface of the particles (Choi and Eastman, 1995). The measured BET surface area of synthesized CuAeg and CuO were 151.0 and 3.0 m2/g, respectively. It is clear that a high surface area was ob­ tained for CuAeg nanoparticles, which may have a potential effect on the TC enhancement as high chances for surface-liquid interactions between the nanoparticles and the oil-medium will be taken place. However, for CuO nanoparticles, the estimated surface area was low which might suggest the possibility of aggregation of this material in the solution producing particles comprising smaller ones (Coy Plazas, 2013). To confirm the morphologies of these materials, SEM analysis was con­ ducted for CuO and CuAeg and the obtained images under different magnifications are presented in Figs. 4 and 5. Fig. 4 shows that mono-dispersed micronic-scale dandelion-like aggregates of smaller CuO nanoparticle resided in spherical and rod shapes in a range of 60–450 nm. This may be attributed to the fact that CuO nanoparticles have a tendency to agglomerate due to their structure, high surface energy and high surface tension. Similar aggregation can be observed for CuAeg nanoparticles in Fig. 5. Comparing the XRD and BET data for the prepared materials, the CuAeg particles seem to be aggregated and composed of smaller-sized nanoparticles in a range from 60 to 200 nm which were more visible at higher magnifications. Meanwhile, elon­ gated fibrous-like monoclinic prismatic crystals of about 1 μm in the longest direction that look like spear point could be noticed. Similar

The effects of the as-prepared nanoparticles on the enhancement of the thermal conductivity of different base fluids were investigated by dispersing them into conventional oil such as mineral oil (MO) and glycerol oil (GO). This would allow us to understand the interaction behavior of nanoparticles with the oil media before applying it in a complex oil matrix like VR and VGO. 3.2.1. Mineral oil-based nanofluid The enhancement of thermal conductivity of mineral oil-based nanofluid was investigated by dispersing different concentrations of as-prepared materials into the mineral oil matrix. Fig. 6 shows the enhancement of TC against particle concentrations (wt%) where Knf and Kbf denote the nanofluid and bulk thermal conductivities, respec­ tively. As seen, an enhancement in the TC was obtained with an upward trend toward to the dosage of nanoparticles. The highest TC enhance­ ment was observed for CuAeg-based mineral oil nanofluid with a peak at 20.6% for 2 wt% concentration. This enhancement is almost twice as large as TC enhancement of mineral oil-based fluid obtained by Chiesa et al. for 1 vol% loading concentration of silicon carbide nanoparticles in the presence of surfactant (Chiesa and Das, 2009). It was reported that the use of surfactant might enhance the TC of nanofluid by improving the compatibility between the added material and the oil-based fluid (Ghadimi et al., 2011). However, this is not the case in our study, the use of surfactant might have many drawbacks. It is known that the TC of surfactants is lower than that of the base fluids, therefore adding such

Fig. 4. SEM images of CuO nanocrystalline material at different magnifications. 5

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Fig. 5. SEM images of CuAeg nanocrystalline material at different magnifications.

Fig. 6. Percent enhancement of TC at different loadings of nanoparticles in the mineral oil-based fluid.

Fig. 7. Hydrodynamic particle size distribution from DLS analysis for different mineral oil-based nanofluids.

material will improve the stability, however, it will reduce the TC of suspension (Timofeeva et al., 2011). In addition, one of the major drawback in surfactant addition is the occurrence of foaming when the nanofluid is flowing or experiencing temperature augmentation (Almanassra et al., 2019; Yang and Hu, 2017). Thus, it would have straight adverse impacts on the targeted application of our nanofluid systems during EOR application. At the same time, surfactants might have a corrosion effect on the pipelines and could be unstable under high-temperature conditions, which disables the bonding between nanoparticles and surface modifiers (Wu et al., 2009). Another important finding is the TC enhancement of CuO nano­ particles with a peak at 15% for 2 wt% loading. At this concentration, the difference between CuO and CuAeg nanoparticles became more pronounced. These observations can be attributed to the fact the CuAeg nanoparticles have less tendency to aggregate according to DLS analysis presented in Fig. 7. As seen, for the same mass concentration, CuAegbased nanofluid has remarkably more well-distributed particles inside the mineral oil matrix, thereby, higher TC enhancement. Such depen­ dence of higher TC enhancement on smaller particle size and higher surface area is in accordance with the reported findings on nanofluids of Al2Cu and Ag2Al using water and ethylene (Chopkar et al., 2007, 2008). It was confirmed that under higher concentration the deviation of TC enhancement between nanoparticles of different sizes became more vivid. Such a trend was observed by many research studies, which confirms that the type, size of particles and their interactions with the

base fluids are the major factors that affect the agglomeration (Hadadian et al., 2013; Yu et al., 2008). Moreover, the viscosity of mineral oil was the lowest among the tested base fluids which was 178 cP at room temperature with TC value of ~0.118 W/m K. This value was low enough to create favorable conditions to settle large aggregates and micro-particles out from the solution, which leads to poor distribution and occurrence of regions with “particle free” liquid. Such “particle free” regions have high thermal resistance that oppositely affects TC enhancement (Keblinski et al., 2002). 3.2.2. Glycerol-based nanofluid To prevent settling of larger particles and investigate the effect of particle loading on the TC of more-viscous media, glycerol-based fluid was chosen as a based-media for nanofluids. Fig. 8 represents the enhancement in TC at different loadings of nanoparticles in the glycerolbased fluid. As shown, a similar trend of TC enhancement is observed for both CuO and CuAeg nanoparticles and TC increases linearly with the increase in the nanoparticle loading. As expected, the CuAeg nano­ particles show higher TC values compare with CuO. Comparing with mineral oil-based nanofluid, the same trend in the TC enhancement was determined for CuAeg nanoparticles with a reduction in the TC from 20.6% to 18.3% at 2 wt%. A similar trend can be also observed for CuO nanoparticles. Under the similar preparation conditions, the distinction in the TC enhancement between glycerol and mineral oil systems could 6

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As shown, the size of CuAeg and CuO nanoparticles in glycerol was found to be higher than that in mineral oil nonfluids. Such increase in the particles size can possibly form a so-called highly concentered clusters (HCC) without an inter-liquid level (Tahmooressi et al., 2017). Hence, it was reported that forming HCC-clustering of nanoparticles leads to the undesirable reduction of TC of nanofluids whereas extended agglomerates can provide an increase in TC which can probably be observed for CuO and CuAeg-mineral oil nanofluid systems (Prasher et al., 2006). Similar findings were experimentally affirmed by studying the effect of Fe cluster size on thermal conductivity of ethylene glycol-based nanofluid systems (Sebakhy et al., 2018). Accordingly, those aforementioned facts can explain the high size of CuO and Cu Age clusters in glycerol nanofluid systems, as a result, a noticeable effect on TC enhancement was observed. To avoid forming such clusters and enhancing the TC of nanofluid, enough sonication time might be applied to break Van der Waals’ forces between nanoparticles inside the more-viscous solution. Nevertheless, the enhancement of TC is always a synergized effect of many parameters and mechanisms such as dis­ persibility, stability, and the Brownian motion of nanoparticles in the based fluids (Tawfik, 2017; Wang et al., 2002). Consequently, a better distribution of active material across the media with less particle-free zones existence was observed, which obviously leads to higher TC enhancement. Thus, it can be concluded that the mechanism mainly responsible for TC enhancement is the distribution/stability of particles inside the solution. Based on that, the thermal conductivity of complex structure-based fluids such as VGO and VR has been investigated in this study for the first time as an injection fluid for thermal enhancing oil recovery as will be revealed in the next sections.

Fig. 8. TC enhancement as a percent value for different nanoparticle loading in glycerol-based fluid.

be referred to their difference in the thermos-physical properties such as viscosity and TC values. The glycerol has a higher initial TC (~0.280 W/ m K) and viscosity (648 cP) values at 295 K than that of the mineral oil (Timofeeva et al., 2011), thus lower TC enhancement trend was observed for mineral oil. Similar observations were observed by Tsai et al. (2008) whereas the thermal conductivity of nanofluids decreased by altering the viscosity from 4.2 to 5500 cP. Furthermore, it was re­ ported that the high viscous fluids reduce the ability of interactions between nanoparticles and based fluids, less particle-to-particle in­ teractions occurring inside the solution, thus reducing the heat transfer inside the solution (Moghadassi et al., 2010). Therefore, in our case, lower interactions between the nanoparticles and based fluids can be observed in glycerol compared with mineral oil nanofluids, leading to the diminishment of the heat transfer between the nanoparticles which also explains the lower enhancement of TC for CuO-glycerol nanofluid systems. To confirm that, the DLS analysis for CuAeg and CuO in glycerol-based fluids was conducted and the results presented in Fig. 9.

3.2.3. VGO-based nanofluid The enhancement of thermal conductivity of CuO and CuAeg nano­ fluids at different loadings in VGO-based fluid is represented in Fig. 10. As expected, a significant increase in the TC of nanofluid was observed with increasing the concentration of nanoparticles. The CuAeg nano­ particles were revealed to have a higher enhancement in thermal con­ ductivity compared with CuO either in complex based-fluid like VGO or simple matrices like mineral oil and glycerol. However, the trend rate of TC enhancement in VGO-nanofluid is appearing to be different than that of mineral oil and glycerol base fluids. This difference can be attributed to the thermophysical properties of base fluids such as viscosity and thermal conductivity, and the chemical complexity structure of VGO. Worth mentioning that the viscosity and TC of neat VGO at room

Fig. 9. Hydrodynamic particle size distribution from DLS analysis for glycerolbased fluid.

Fig. 10. The TC enhancement of VGO-based nanofluid at different types and loadings of nanoparticles. 7

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temperature condition are 500 cP and ~0.112 W/m K, respectively. Nevertheless, a noticeable amount of asphaltenes can be minorly pre­ sented in the VGO during the distillation fractions of crude oil which might be interacting with the surface of the suspended nanoparticles in the nanofluids (Franco et al., 2013a; Parlov Vukovi�c et al., 2015). These types of interactions by either interfacial tension and/or adsorption have a significant effect on asphaltenes behavior in the oil matrix due to the presence of these particles in the solution (Ramirez-Corredores, 2017; Sagala et al., 2019). It was reported that the electrostatic and van der Waals attractions are the most dominant interactions between the asphaltene aggregates and surface of nanoparticles, and thus the nano­ particles can be employed for adsorption and effective removal of asphaltene aggregates from oils as an approach for the in-situ oil upgrading (Hmoudah, 2016; Nassar et al., 2011c). Such strong in­ teractions may also increase the catalytic effect of nanoparticles with high-affinity values for various reactions. Therefore, the particles that involved in the interaction with asphaltenes will positively affect their distribution within the base fluid and remain stable inside the solution as asphaltenes could act as a surfactant, thus favourably affect TC enhancement. These findings can be also confirmed by the DLS results of VGO-nanofluids which shows good stability of these nanoparticles in the nanofluids as presented in Fig. 11. Another possible mechanism of TC enhancement could be also related to the interfacial properties of the particles and base fluid. The molecular-level layering of fluid and solid interface has proven to impact the TC of the nanofluids (Keblinski et al., 2002). By increasing the thickness and ordered-shell of this interface around the particles a higher value of thermal conductivity can be obtained. Based on that, it can be concluded that the CuAeg nanoparticles exhibited the highest TC enhancement with the maximum enhancement of 21.3%. Therefore, our proposed nanoparticles, CuAeg, will be used with 2 wt% loading for further investigations and perform experiments using VGO-VR mixtures as a possible carrier fluid for thermal EOR methods.

Table 2 Viscosity and TC value of VGO-VR mixtures. VR concentration in VGO (wt%) Viscosity, cP TC value (W/m K)

0 500 0.112

5 817 0.115

10 1179 0.122

15 1786 0.125

20 2750 0.130

concentration of VR in the matrix increased. The effect of VR addition to VGO matrix on the TC value with and without nanoparticles loading is shown in Fig. 12. It is clearly seen that with the increasing amount of VR from 0 wt% to 20 wt% a linear in­ crease in TC value is observed, without nanoparticles addition. This observation can be supported by the fact that VR contains conductive metals such as Fe, Al, Ni, V and others, which might have a positive effect on the TC value of VGO-VR matrix (Dorbon, 1984). Moreover, adding nanoparticles to the VGO-VR matrix leads to significantly enhanced TC as well. As shown in the figure, at a fixed amount of CuAeg nanoparticles loading (2 wt%) the thermal conductivity of VR-VGO matrix is notice­ ably increased with the increasing of VR concentration. Interestingly, this enhancement on TC of VR-VGO matrix in the presence of nano­ particles is much higher than that without nanoparticles, at the same experimental conditions. However, a reduction on the thermal con­ ductivity of VGO-VR nanofluids was noticed at 5 wt% VR, before it starts increasing with VR concentration with the presence of 2 wt% CuAeg nanoparticles. This drop in the TC enhancement can be attributed to several factors; namely: First, the VR is a solid material at room tem­ perature conditions which has a critical effect on viscosity and complexity of the base fluid after dissolution, thus isolating the nano­ particles. Second, the possible formation of cluster network structure of matrix being introduced after 5% of VR dosage (Andersen, 2008; Mullins et al., 2012). In addition, another mechanism could be responsible for TC enhancement by the addition of nanoparticles due to the physico­ chemical interactions between nanoparticles and media. Adsorption is one among those interactions, in which the asphaltenes molecules can be adsorbed on the surface of CuAeg nanoparticles (Hmoudah, 2016). Taken into the consideration that the amount of asphaltenes in VR-VGO matrix is increased by increasing the concentration of VR, thereby the possibility of nanoparticles to be engaged in the formation of well-diffused fractal and porous structures across the media will be increased (Rahmani et al., 2005; Serra and Casamitjana, 1998). Since the asphaltenes exhibit amphiphilic behavior (Montoya et al., 2014), it

3.2.4. Matrix of VGO-VR nanofluids As discussed early, the CuAeg nanoparticles revealed a high TC enhancement in the oil-based media. Therefore, the thermophysical properties of VGO-VR matrix using CuAeg nanoparticles were investi­ gated in this part of the study as a potential fluid for thermal EOR. Table 2 shows the changes in viscosity and TC for VGO-VR based fluids with the loading of VR in the matrix. As seen, there is a continuous in­ crease in both TC and viscosity values in VGO-VR matrix as the

Fig. 12. The effect of VR concentrations on the TC values of VGO-VR based fluid with and without 2 wt% of CuAeg nanoparticles.

Fig. 11. Hydrodynamic particle size distribution for VGO-based fluid. 8

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Journal of Petroleum Science and Engineering xxx (xxxx) xxx

can be concluded that the asphaltenes adsorption as associated clusters from the solution onto the surface of nanoparticles will lead to forming small-sized clusters consist of nanoparticles interconnected by asphal­ tene molecules. Such smaller-sized clusters might be stabilized due to the short-range attractive forces between nanoparticles and long-range repulsive forces between clusters themselves, thus leading to the high stability of system (Sciortino et al., 2004). In that case, structural behavior of asphaltenes might be mimicking the graphene-like materials in terms of the heat transfer mechanism, thereby acting as heat conductive paths inside the solution. Such plausible mechanisms due to the similarity of graphene materials and asphaltenes in TC enhancement and the formation of network inside the solution have been described by Tahmooressi et al. (2017) in which a percolation network via dispersing carbon materials into the silicone oil was observed.

from the solution to the surface of nanoparticles. Therefore, the nano­ particles in this case could take a part of a viscoelastic network that consists of smaller-sized fractal clusters of nanoparticles interconnected by asphaltenes. To provide evidence of these smaller-sized clusters for­ mation, the viscosity measurements for both VR and CuAeg-VR nano­ fluid systems were conducted. The viscosity results as a function of shear rate and temperature for the VR-based fluids with and without CuAeg nanoparticles are presented in Fig. 14a and b. As shown, along with TC enhancement, a significant reduction in viscosity was observed after the addition of CuAeg nanoparticles and under elevation of temperature. The fact that a decrease in viscosity aligned with reduction of asphaltene cluster size was proven by many researchers, in which the nanoparticles could change the aggregation mechanism of asphaltenes and cease its growth (Eyssautier et al., 2011; Nassar et al., 2015). Similar findings were observed by Hashemi et al. (2013), in the presence of trimetallic nanocatalysts in VGO matrix employed as a hot fluid injec­ tion for enhanced heavy oil recovery. The authors reported a significant reduction in viscosity and increment in API. Moreover, it can be concluded that with the temperature augmentation, a larger number of small-sized clusters are formed. Consequently, TC is further enhanced in the presence of small clusters. This mechanism is not likely to be solely responsible for TC enhancement, as it can be expressed as a synergistic effect of different mechanisms. Another potential mechanism of TC enhancement is due to the intensification of nanoparticle vibrations as well as the resultant micro-convection with temperature augmentation (Shahsavar and Bahiraei, 2017). Such nanoparticle vibrations can play a role in more inter-cluster connections generation and coherent cluster disassociation. In addition, asphaltenes contain multi-hydroxy and multi-amine molecules that exhibit an increase in TC properties with an elevation of the temperature. Hence, asphaltenes will transfer heat more effectively through the connections between nanoparticles at higher temperatures. These findings led us to conclude that adding CuAeg nanoparticles to the VR would enhance the thermal conductivity and maintain a constant temperature of the injection fluid thus enhancing the recovery of bitumen or heavy oil. In addition, CuAeg nanoparticles could act as catalysts for enhancing the hydrocracking reaction in the presence of hydrogen source during the heavy oil recovery (Elahi et al., 2019).

3.2.5. Temperature effects on TC performance of VR nanofluids Because the VR exists as a solid-state at room temperature, the effects of temperature on the TC and viscosity of CuAeg-VR nanofluids were studied. Fig. 13a represents the TC values of VR-nanofluids with and without 2 wt% CuAeg nanoparticle loading as a function of the tem­ perature whereas Fig. 13b shows the percentage enhancement of TC as a function of the temperature. As seen, with the temperature augmenta­ tion, both VR-fluid and VR-nanofluid system experienced an increase in TC values, however, a slight increase without nanoparticles. In the absence of nanoparticles, it can be observed that almost unnoticeable enhancement in TC which can be attributed to chemical characteristics of media. The existence of metals, multi-hydroxy and multi-amine molecules in the VR matrix are playing a role in TC enhancement under the elevation of temperature (Ramos-Pallares, 2017; Sastri and Rao, 1999). The high temperature will increase the mobility of these metals and thus increasing their ability to transfer the heat. On the other hand, by adding a 2 wt% of CuAeg to the VR medium, the enhancement in TC was more noticeable, which correlates with major studies on nanofluids and their TC dependence on temperature (Li and Peterson, 2006; Tawfik, 2017). A plausible explanation of the mechanism that stands behind TC enhancement is strongly interrelated with CuAeg nanoparticles interaction with asphaltenes as mentioned before. It should be pinpointed that due to the high content of asphal­ tenes in the VR, the asphaltene clusters tend to form a stable viscoelastic network inside the solution (Parlov Vukovi�c et al., 2015; Wang and Ferguson, 2016). However, after the addition of CuAeg nanoparticles to the VR, the physical interactions could take place via adsorption which causes disaggregation of asphaltene flocs and migration of asphaltenes

4. Conclusion This study is a first attempt to investigate the main factors that stand behind TC enhancement of oil-based nanofluid systems, which might

Fig. 13. a) TC values against temperature for both VR and VR-nanofluid and b) the percentage enhancement of TC as a function of temperature for VR-nanofluids. 9

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Journal of Petroleum Science and Engineering xxx (xxxx) xxx

Fig. 14. a) Viscosity values at 353 K for VR and CuAeg-VR nanofluid system against shear rate, and b) viscosity values at a fixed shear rate (80/s) against temperature increase for VR and CuAeg-VR nanofluid system.

have favorable effects on heavy oil/bitumen recovery while applied during thermal EOR methods. The effect of CuAeg and CuO nano­ particles on TC properties of mineral oil, glycerol and VGO-VR was investigated under 0.5, 1.0 and 2.0 wt% loadings. The CuAeg nano­ particles showed a high TC enhancement rate, which has the smallest crystalline domain size and demonstrated the smallest average hydro­ dynamic particle size inside the base fluid media. The thermos-physical properties of VGO-VR nanofluids with a fixed concentration of CuAeg nanoparticles were investigated. It has been proven that the increase of VR concentration in VGO matrix from 0 wt% to 20 wt% leads to higher TC value of the base fluid. Moreover, a linear increase in TC values was observed in VGO-VR nanofluids when 2 wt% CuAeg nanoparticles were loaded to the matrix. It was also found that TC of VR nanofluids with 2 wt% CuAeg exhibited stable upwards trend with respect temperature augmentation. At 383 K, the TC was determined to be 0.254 W/m K, which is 23.5% higher than TC of neat VR. Along with TC enhancement, a significant decrease in viscosity was observed in VR-nanofluid after adding CuAeg nanoparticles and under elevation of temperatures. These valuable findings can open doors for further investigations of nanofluid TC properties in boundaries of the study of in-situ nanocatalytic upgrading of heavy oil/bitumen via hot fluid injection. Therefore, this study is intended for proposing a new hot injecting nanofluid system suitable for enhanced thermal oil recovery with consecutive heavy oil/ bitumen catalytic upgrading. This nanofluids could also be used as catalysts during hot fluid injection where SAGD operation is inappli­ cable. The catalytic activity of the injecting hot nanofluid has been addressed in previous study (Hashemi et al., 2013).

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Acknowledgments The authors are grateful to the Natural Sciences and Engineering Research Council of Canada (NSERC) (Grant No. RGPIN-2015-05222), the Department of Chemical and Petroleum Engineering at the Schulich School of Engineering at the University of Calgary. A great acknowl­ edgement to Dr. Christophrer Debuhr for providing access to the instrumentation facility for analytical electron microscope in the Geo­ science Department and Dr. Hossein Hejazi for his technical help to the first author. References Almanassra, I.W., et al., 2019. An experimental study on stability and thermal conductivity of water/CNTs nanofluids using different surfactants: a comparison study. J. Mol. Liq. 111025.

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