The Effect of Wettability Alteration - American Chemical Society

Dec 2, 2016 - of Ministry of Education Department of Thermal Engineering, Tsinghua ... Petroleum Exploration and Production Research Institute, SINOPE...
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Experimental Investigation of Silica-Based Nanofluid Enhanced Oil Recovery: The Effect of Wettability Alteration Rong Li,† Peixue Jiang,† Cheng Gao,†,‡ Feng Huang,† Ruina Xu,*,† and Xue Chen† †

Beijing Key Laboratory for CO2 Utilization and Reduction Technology Key Laboratory for Thermal Science and Power Engineering of Ministry of Education Department of Thermal Engineering, Tsinghua University, Beijing 100084, China ‡ Petroleum Exploration and Production Research Institute, SINOPEC, Beijing 100083, China ABSTRACT: Enhanced oil recovery (EOR) using nanofluids has been proposed in recent years, but the mechanism of oil recovery enhancement through nanofluid injection still needs further study. In this study, the pore-scale performance and mechanism of nanofluid EOR were investigated based on a micromodel experiment. The micromodel sample was designed to compare the silica-based homogeneous water-wet sandstone reservoirs. The behavior of 0.1% wt water-base silica nanofluiddisplacing oil (dodecane) was compared to the deionized (DI) water-displacing case. Residual oil saturation gradually decreases from 50% to 43% as the DI water injection flow rate increases from 0.5 to 5.0 μL/min. In the nanofluid-injection case, residual oil saturation decreases from 24% to 20% as the flow rate varies in the same range. About 25% saturation of incremental oil recovery is obtained by nanofluid injection compared to DI water injection. This implies significant improvement in oil recovery performance from nanofluid injection. Through investigation of detailed pore-scale fluid distribution, the wettability alteration of the oil-bearing pore wall from a strongly water-wet condition to the neutrally wet condition is observed in the presence of nanoparticles. The wettability alteration behavior in a natural sandstone sample was investigated via a spontaneous imbibition test. The imbibition rate slows down significantly in the presence of nanoparticles indicating that the wettability alteration mechanism observed in the micromodel experiment is also valid in the case of natural water-wet sandstones and consequently can enhance the oil recovery. The analysis based on Wenzel’s model indicates that the nanoparticle adsorption-induced nonuniform pore wall roughness change is the possible mechanism for wettability alteration.

1. INTRODUCTION The nanoparticles dispersed in a liquid phase (i.e., nanofluids) were proposed by Choi1 to improve the heat transfer performance of the liquid. The thermal properties,2−4 convective heat transfer, and boiling performance5−7 of various nanofluids were investigated during the past two decades and have shown promising improvement. In recent years, nanofluids are also proposed as an attractive agent for enhanced oil recovery (EOR). Promising results and improved oil recovery performance by injecting nanoparticles suspension have been reported based on various experimental studies.8−13 To the best of our knowledge, the initial conceptual mechanism potentially available for nanofluid EOR, namely, structural disjoining pressure, was proposed and validated experimentally by Wasan and Nikolov.14 They showed that the nanoparticles formed two-dimensional wedge like layered structures in the confines of the three-phase contact region of a wedge film formed between an oily soil and the solid substrate, and these structures can separate the oil from the pore wall.14−16 Very recently, Zhang et al.17 verified the structural disjoining pressure mechanism for crude oil recovery at different scales via nanofluid/crude oil/glass substrate contact line dynamic experiments and sandstone imbibition experiments. Monfared et al.18 investigated the wettability alteration of a calcite surface through experimental treatment of water-based silica nanofluids. The calcite surface was altered from a strongly oil-wet condition to a neutrally wet and strongly water-wet condition depending on the nanoparticle concentration and © 2016 American Chemical Society

salinity and therefore potentially benefits oil recovery in carbonate reservoirs. The release of carboxylate groups from the oil-wet calcite surface and their replacement with silica nanoparticles were suggested as responsible for wettability alteration. Besides, the performance of zirconium oxide nanofluids19 for altering the wettability of a carbonate reservoir has also been investigated experimentally. Hendraningrat et al.20 reported the water−oil−silica contact angle decreased from 55° to 22° as the nanoparticle concentration in the aqueous phase increased from 0 to 0.1% wt. They proposed that the wettability alteration observed in their study resulted in additional oil recovery compared to brine flooding in sandstone reservoirs. Joonaki and Ghanaatian21 evaluated the EOR performances of the three kinds of water base nanofluids, namely, the aluminum oxide, iron oxide, and saline treated silica nanofluids. Their core flooding experiments were conducted using initially water wet sandstones. The presence of nanoparticles induced interfacial tension reduction and the wettability alteration from water-wetting to the neutral-wetting and, consequently, the improved oil recovery performance. Li et al.22 observed experimentally that the nanoparticle absorption-induced wettability alteration could possibly occur in completely reverse ways, namely, from water-wet to oil-wet or from oil-wet to water-wet depending on initial reservoir wettability and surface treatment of the nanoparticles. Maghzi Received: August 10, 2016 Revised: December 1, 2016 Published: December 2, 2016 188

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Figure 1. Particle size distribution and the zeta potential of 0.1 wt % nanofluid.

et al.23 conducted a micromodel experiment to investigate the silica-based nanoparticle-induced heavy oil recovery improvement at the pore scale. The micromodel observation indicated that initially the oil−wet glass surface had been altered to waterwet conditions in the presence of silica nanofluids. Besides the structural disjoining pressure and wettability alteration by various types of nanoparticles and surface modification methods, more complex mechanisms for improving oil recovery were mentioned in previous studies. The combination of nanoparticles with the water-soluble polymer and surfactant8 was reported to benefit the performance of oil recovery compared to the surfactant of a polymer solution. Emulsification8 mechanisms were considered more effective than wettability alteration mechanisms in the presence of the nanoparticle, polymer, and surfactant combined EOR process. In some cases, low-cost nanofluids, that is, natural nanosize clay particles dispersed in brine, were proposed as sacrificing material in combination with other expensive EOR chemicals, including surfactants and polymers to reduce the absorptive retention on the rock surface.24,25 The nanoparticles can decrease the adsorption of polymer solution onto the rock surface and thus improve the efficiency of polymer injection. The potential applicability of nanofluids for preventing the formation damage of the heavy oil reservoirs due to asphaltene precipitation was addressed experimentally by Mohammadi et al. 26 and Franco et al. 27 Worthen et al. 28 observed experimentally that nanofluids can stabilize CO2-in-water foam and thus can control the CO2 mobility in the EOR process. Nguyen et al.29 systematically evaluated the foam stability and the EOR efficiency of the nanoparticle stabilized CO2 foam through the pore-scale micromodel experiments. In summary, various nanoparticles or their combinations with various types of surfactant and polymer solution for EOR have

been investigated in the laboratory, including interfacial tension (IFT) measurements, sessile-drop wettability tests, micromodel experiments, and core flooding experiments. Effective mechanisms of EOR through nanofluid injections also showed great variety, although the nanofluids can more or less improve oil recovery. Focusing on the nanofluid injection-induced wettability alteration, the observed behaviors also varied significantly depending on the surface treatment of nanoparticles, mineral composition, and initial wetting property of the reservoir rock surface. To better understand wettability alteration behavior and EOR performance from nanofluid injection, further experimental studies are needed. We focused, in particular, on the behavior of the water-based nanofluid with charge-stabilized silica nanoparticles displacing the oil in the water-wet reservoir mainly composed of silica surface. The chemical composition nanoparticle was selected as identical to the major reservoir minerals. This design focused on the nanofluid-induced structural effect on the pore surface and eliminated the chemistry-induced complexity. Micromodels are microfluidic devices with a transparent face that enables visualization of fluids within spatially structured pore networks created by etching or other microfabrication techniques. The flow experiments using micromodels have been considered a straightforward and powerful experimental method to characterize the two-phase or multiphase flow mechanism, wettability alteration, and pore-scale oil recovery performance.23,30−36 To investigate the detailed pore-scale nanofluid EOR mechanism, a micromodel flow experiment was conducted in this study. Besides, a spontaneous imbibition test was also conducted using the natural water-wet Berea sandstones which were mainly composed of silica minerals, to investigate EOR performance of silica nanofluids on a larger scale. The experimental fluid used in this study is introduced in 189

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concentration is 0.1% wt. Because the nanofluid is charge-stabilized, the interfacial property change due to the additional surfactant or organic polymers is negligible. The interfacial property change of the aqueous phase possibly results from the effects of nanoparticle absorption at interfaces.

Section 2. The experimental system setup, procedure, and samples are described in Section 3, and the results and discussions are presented in Section 4.

2. EXPERIMENTAL FLUIDS A water-based silica (SiO2) nanofluid was prepared by diluting a commercially available, highly concentrated colloidal silica, LUDOX tm-50 colloidal silica37 (Sigma-Aldrich). Based on the LUDOX manual, the nanoparticles are charge-stabilized, meaning a charge is induced on the particle surfaces so that they repel each other to keep the stability of the suspensions. The 50% wt concentration colloidal silica was diluted to 0.1% wt using the DI water. The nanofluid was pretreated by high-intensity ultrasound for 30 min before the micromodel experiment and the core imbibition test to ensure the nanoparticles were well-dispersed. The particle size in the dispersion was measured by a Malvern particle size analyzer after 48 h to test the stability of the nanofluid. The particle size distribution of nanofluid is about 40 nm, which is almost identical with the data from the manufacturer. This indicates that the aggregation of nanoparticles during the experimental period is negligible. The zeta potential result is presented in Figure 1b. The overall zeta potential value around −40 mV indicates the strong enough charge strength to stabilize the nanofluid. Dodecane was selected as the oleic phase in the micromodel experiments. To visualize clear boundary of oil/water/silica interface, the oil was dyed using Nile Red fluorescence dye with 30 ppm concentration. The properties of dyed oil, DI water, and the diluted nanofluid are listed in Table 1. The results indicate that the dispersed

3. EXPERIMENTAL SAMPLE, SYSTEM SETUP, AND PROCEDURE 3.1. Experimental Setup. The experimental setup of the micromodel experiment is presented in Figure 2. Three piston transfer cylinders containing oil, DI water, and nanofluid were connected to the inlet of the micromodel and driven by an ISCO 100DX syringe pump. The fluid injection flow rate was controlled by the ISCO pump with 0.01 μL/min accuracy. To reduce the dead volume of the system, the PEEK tubing with 0.01 in. inner diameter and 1/16 in. outer diameter was used for the connection. An Omega pressure transducer (PX01C0-3.5KGI) and a K-type thermocouple (0.1 K accuracy) were used to monitor the pressure and the temperature near the micromodel inlet. Downstream of the micromodel was directly connected to a collecting beaker, and therefore all of the experimental cases in this study were conducted under ambient pressure. The micromodel was loaded on a sample holder with special fittings at inlet and outlet. The micromodel was visualized by an inverted microscope (Ti-E Nikon series) with a fluorescence module. Using the long-working-distance 5× objective lens and the high-resolution CCD camera (Nikon Digital Sight DS-Ri1), the imaging of the micromodel could be up to 1.65 μm per pixel. The oil saturation S0 was calculated from the stitched image covering the entire porous zone by dividing the area of the oil-occupied zone with the area of porous zone. The uncertainty of the S0 depends on the image resolution and the observed length of aqueous−oleic interface in the two-dimensional images. As mentioned in Section 2, the dodecane was dyed with Nile Red. The fluorescent peak excitation and emission wavelengths of Nile Red dissolved in oil are 493 and 513 nm, respectively.32 The FITC fluorescent module (excitation filter with bandpass wavelength λex = 475−495 nm; receiving filter with bandpass wavelength λem = 500− 540 nm) was selected to match the excitation wavelength and the emission wavelength of Nile Red-dyed dodecane. 3.2. Experimental Procedure. Before each experimental case, the pore volume and dead volume of the entire system needs to be saturated with oil. The sample was cleaned by 50 pore volumes of isopropanol to remove all of the oil and water. Then the sample was flooded with depressurized CO2 (5 bar) to remove dry the isopropanol and the dissolved air. Finally, the fluorescent dyed oil (vacuum treated

Table 1. Fluid Properties of DI Water, Nanofluid, and Dodecane fluid DI water dodecane 0.1% wt nanofluid dodecane

viscosity (mPa·s) 0.894 1.364 0.869

viscosity ratio log M

interfacial tension (mN/m)

0.183

39.16

0.182

28.84

1.364

nanoparticle has almost no impact on the single-phase properties of the aqueous phase, including density and viscosity, but the aqueous− oleic interfacial tension is reduced by about 30% when the particle

Figure 2. Experimental setup and procedure. 190

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Figure 3. Geometric design and SEM scanned image of micromodel sample. for 4 h to remove the dissolved air) was injected into the micromodel with a large flow rate (about 500 μL/min) until all the pores were filled with fluorescent solution while scanning through all parts of the sample. The tubing was then carefully switched to DI water or the nanofluid transfer cylinder to start oil recovery. The initial injection rate of DI water or the nanofluid was set as 0.5 μL/min. The injection process lasted at least 10 pore volumes, from the moment that the aqueous phase reached the micromodel inlet. The injection was kept until the flooding reached the steady state, which can be judged by stabilized inlet pressure and the motionless fluid interface in the entire porous zone. After reaching the steady state, the stitched large image covered the entire porous zone, which was acquired using the mobile objective stage. Then the flow rate was increased to reach the new steady states. The flow rate was gradually increased from 0.5 to 5.0 μL/min. The schematic diagram of the experimental procedure is shown in Figure 1b. To avoid the influence of possible particle retention and wettability alteration to the following experiments, once the micromodel sample has been nanofluid-flooded, it will not be reused. 3.3. Experimental Sample: Micromodel. In this study, the micromodel was prepared through dry etching in silicon wafers,32,33 yielding structures with vertical walls and much higher precision than wet-etched glass as shown in Figure 3c. The etched silicon surface was oxidized in a 1000 °C oven to ensure the chemical composition of the surface was compatible with silica mineral, considered one of the most common minerals of natural sandstone oil reservoirs. Then the models were sealed with a fused Pyrex silica glass plate by anodic bonding to ensure that the pore fluid could be safely pressurized to 1.5 MPa without leaking or breaking. The detailed etching pattern of the micromodel is shown in Figure 3. The etched porous zone overall length was 20 mm; the overall width was 15 mm, and the etching depth was 30 μm. The crosswisearranged 500 μm circles represent the solid part of the porous media, and the rest represents the pore space containing fluid. The porosity of the etched pattern was about 21%. As presented in Figure 3b, the narrowest zone of flow path, namely, the pore throat, was 30 μm width. The less-confined geometries with hydraulic length of about 112 μm, namely, the pore body, was interconnected with the adjacent pore bodies though the pore throats. Each pore body was interconnected with three of the adjacent pore bodies. 3.4. Spontaneous Imbibition Experiment. The spontaneous imbibition test merged an initially oil-saturated sandstone core sample into the aqueous phase (can be DI water or nanofluid in this study) and measured the change of the oleic-phase saturation at various times during spontaneous imbibition by the weighing method.

Two pieces of core samples obtained from cutting one piece of homogeneous sample, namely, twin cores,38 were selected for comparison of DI water and nanofluid imbibition behavior. The cores were named Berea #2−4 and Berea #2−5, respectively. After 80 °C oven drying for 12 h, the dry core samples were weighted. Then the cores were merged in an oil-containing beaker and vacuumed for 12 h to saturate with the oleic phase. Then the cores were weighted again to measure the pore volume and porosity. After the oil-saturated cores were prepared, the cores were merged into an aqueous phase containing beaker to imbibe the aqueous phase spontaneously. The cores were weighted continuously using a highprecision electronic balance (ADAM PWC 124, 0.1 mg precision). The oleic-phase saturation Soil is calculated via eq 1, Soil =

(mt − m0)/(ρaqu − ρoil ) (mos − mdry )/ρoil

(1)

where mt and m0 represent the measured mass of the core at time t and initial moment when the core has been merged into the aqueous-phase containing beaker, and mos represents the mass of oil-saturated core. The uncertainty of the measured oil saturation simply depends on the balance-weighting accuracy of mt, because the densities are known at given temperature and the weighing uncertainty can be significantly reduced and thus, neglected in cases of saturated and dry cores via the repetitive weighing. Therefore, for the core samples in this study, the uncertainties can be simply estimated as eq 2,

|Soil| =

|Δ(mt − m0)|/(ρaqu − ρoil ) (mos − mdry )/ρoil

= 0.002 (2)

The estimated uncertainty of the saturation is ±0.2% in our experimental setup (the last digit of balance is rounded off due to fluctuation during the transient process).

4. RESULTS AND DISCUSSION The images of residual oil distribution after DI and nanofluid injection cover the entire porous zone are presented in Figure 4 and Figure 5, respectively. In the DI water-injection case as presented in Figure 4, the aqueous phase forms thin finger-like preferential flow paths and shows the low macroscopic sweep efficiency, although the micromodel is homogeneous. As the flow rate increases, the aqueous phase can intrude the bypassed oil zone and form a new flow path. In contrast, in the nanofluidinjection case, the higher sweep efficiency can be observed, 191

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case, the residual oil saturation reduces from 24% to 20% as the flow rate varies in the same range. About 25% saturation of additional oil is recovered by nanofluid injection compared to the DI water injection, implying significant potential oil recovery enhancement. The nondimensional number Ca = uμ/σ is involved to eliminate the effect of nanoparticle-induced interfacial tension change. As shown in Figure 6b, under a compatible Ca number, the trend of oil recovery enhancement is still significant. This indicates that the interfacial tension change may not be the first-order mechanism for oil recovery enhancement. The three-phase contact zones on straight walls (located at the boundary of the porous zone) are focused to present the contact angle, as shown in Figure 7a and b. To capture the precise and sharp interface, the binarization operation has been applied based on the original images. The interface curvature along the z-direction (assuming the x−y plane is parallel to the etching pattern) interferes the quantitative accuracy of the contact angle measured from the projected images in x−y plane. The idea of contact angle estimation based on the 2D image was proposed in the previous micromodel study by Zhang et al.39 Then, Kim et al.31 mentioned the contact angle measured from their micromodel images to present the wettability alteration. Therefore, the contact angle based on the 2D images has been regarded as the evidence to present the wettability and wettability alteration trend qualitatively. To avoid the confusion with the precise contact angle often obtained from sessile drop method, the top view 2D micromodel based contact angle is named as apparent contact angle in this study. Treiber et al.40 defined the contact angle of a water/oil/rock surface system as follows: water-wet in the range of 0−75°, intermediate/neutral-wet in the range of 75−105°, and oil-wet in the range of 105−180°. In the DI water-injection case, the observed apparent contact angles range from 25° to 40° corresponding to the strongly water-wet condition. In the nanofluid-injection case, the apparent contact angles range from 70° to 110°, confirming that wettability altered from the strongly water-wet region to the neutrally wet (or weakly water/oil-wet) region. To investigate the detailed local pore-fluid distribution states after 0.5 μL/min DI water- and nanofluid-injection cases, the aqueous-phase swept zones with a certain amount of residual oil selected are presented in Figure 8. In the DI water-injection case, a certain amount of connected water forming the continuous flow path is observed. Some disconnected water blobs and oleic-phase ganglia can also be observed. The disconnected water blobs have a small size and occupy the narrow throat. The isolated oil ganglia have various sizes occupying one to tens of pore bodies. These ganglia are often disconnected from other oleic-phase ganglia and thus immobilized by some small aqueous-phase blobs occupying single throats, which are the possible results of snap-off events. Once trapped by the aqueous phase occupying the throats, the oil ganglia are very difficult to remobilize because of the driving force needed to overcome the capillary entrance pressure of the throat. As shown in Figure 8b, unlike the pore-fluid distribution observed in the DI water-flooding case, a certain amount of isolated small residual oil blobs occupy the pore throats in the nanofluid-injection case. Both nanofluid and oil can occupy the throats or pore bodies, interconnected as larger ganglia or isolated as small blobs. The oil ganglia trapped by small blobs of

Figure 4. Residual oil distribution after aqueous-phase injection under different flow rates. The oil is shown in bright green, and the aqueous phase is shown in black. The inlet and outlet of the micromodel are located at the left and right sides of the images, respectively.

Figure 5. Residual oil distribution after nanofluid injection under different flow rates. The oil is shown in bright green, and the aqueous phase is shown in black. The inlet and outlet of the micromodel are located at left and right sides of the images, respectively.

implying that the aqueous-phase preferential flow can be eliminated in nanofluid-injection cases. The bypassed oil also can be mobilized by increasing the flow rate. In the nanofluidswept zone, the microscopic residual oil saturation is low, and the small blobs of oil prefer to occupy the throats instead of pore bodies. The overall residual oil saturation is calculated based on the stitched images captured at steady states of each flow rate. As presented in Figure 6a, the residual oil saturation gradually decreases from 50% to 43% as the DI water-injection flow rate increases from 0.5 to 5.0 μL/min. In the nanofluid-injection 192

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Figure 6. Variation of oil saturation with flow rate and capillary number. The capillary number Ca is calculated as Ca = uμ/σ.

reasonable to assume that the impact of organic contents, especially the surface active components on wettability, can be neglected since the silica nanofluid is stabilized by surface charge and negligible organic matters are involved during the manufacturing and diluting procedure. Also, dispersed nanoparticles and the micromodel surface are identical in chemical composition. Thus, the wettability alteration does not result from the change of surface chemistry. The possible mechanism of wettability alteration is the variation of the surface structure. The retention of nanoparticles on the pore wall surface can increase the surface roughness. To characterize the roughness of the surface, the Wenzel roughness47,48 factor Rs is defined as eq 3, Rs =

Figure 7. Local detailed view of two-phase fluid distribution near a straight edge of the sample after 0.5 μL/min injection. To capture the precise and sharp interface, the binarization operation has been applied based on the original images.

ARough AApparent

(3)

where ARough represents the actual surface area of the rough surface and AApparent represents projected surface area, which equals the area of a perfectly smooth surface with identical macroscopic geometry and material. Then the Wenzel equation turns out that

the aqueous phase occupying a single throat are not observed in Figure 8b. Instead, the aqueous phase shows well-connected morphology and continuous flow paths. This implies that the snap-off events in the nanofluid-injection case are not as frequent as those in the DI water-injection case. The observation on the contact angle and the pore fluid distribution indicates that the wettability altered from strongly water-wet to neutrally wet or even weakly oil-wet condition at the nanofluid swept zone. The reservoir wettability alteration from a strongly water-wet condition to neutrally wet condition is expected to result in the oil recovery enhancement of previous studies.41,42 In a strongly water-wet porous media, during imbibition, the nonwetting phase tends to snap off as the aqueous-phase saturation increases and thus traps more of the nonwetting phase. The higher frequency of the snap-off events under strongly water-wet condition can be verified via the more aqueous phase occupying the pore throats. In contrast, as the wettability is altered to a less water-wet region, the snap off is suppressed, and the piston-like advancing aqueous phase/oil interface results in less trapped oil.43 This point is supported by several previous pore-scale studies,44−46 including both experimental and numerical studies. The wettability in the presence of nanofluid can be influenced by several variables, including the material and surface treating of nanoparticles, initial wettability of the pore wall, and other possible surface active organic matters involved for nanofluid stabilization. In this study, however, it is

Rs =

cos θw ≥1 cos θ0

(4)

where θw is the Wenzel contact angle at rough surface, and θ0 is the contact angle of the smooth surface of the same material. With increasing roughness, the surface will become more waterwet if the surface with less roughness is originally water-wet. Therefore, the increasing roughness resulting from nanoparticle adsorption is expected to alter the wettability to more a waterwet condition. This expectation from the Wenzel model is consistent with the experimental observations obtained by Hendraningrat et al.20 but inconsistent with our observation. The inconsistency results from the local heterogeneity of roughness in the nanofluid swept zone. The Wenzel contact angle model corresponds to the rough wall with uniformly distributed roughness. In this case, however, the nanofluid contact pore wall has greater roughness than the oil contact wall. To characterize the wettability on this kind of wall with nonuniform roughness, the Wenzel model must be modified. Assuming the roughness is uniform at the surface, combining eq 3 and eq 4, and Young’s equation, eq 5 can be derived as −ΔAApparent σOA cos θRough = ΔARough σAS − ΔARough σOS (5) 193

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Figure 8. Local detailed view of two-phase fluid distribution after 0.5 μL/min injection.

Figure 9. Schematic plot of contact zone with nonuniform surface roughness Rs.

where ΔAApparent and ΔARough represent the actual and projected area covered by a small movement Δx of contact line with length L as presented in Figure 9a, and it turns out the relation that ΔAApparent = LΔx. In the equation, σOA, σOS, and σAS represent the interfacial tension between oil/aqueous, oil/ solid, and aqueous/solid, respectively. The right-hand side of eq 5 represents the variation of the total interfacial free energy of aqueous/solid and oil/solid interface. The left-hand side can be rewritten as −ΔAApparent σOA cos θRough = −(σOAL)Δx cos θRough

Since the surface has been in contact with nanofluid, the roughness will increase due to adsorption; the covered actual area for a Δx contact line movement (the nanofluid is advancing), for the nanofluid/solid interface, namely, ΔARough,nano, is larger than that of original oil/solid interface, ΔARough,oil. Accounting for this interfacial area change, or equivalently, the roughness change, the original interfacial equation and Wenzel’s contact angle equation can be modified as −ΔAApparent σOA cosθNano = ΔARough,nanoσAS − ΔARough,oil σOS

(6)

(7.1)

The right-hand side of the equation represents the work of the oil/aqueous-phase interfacial tension. The fully rewritten Wenzel’s model, that is, eq 5, can be considered as an energy balance at the three-phase contact zone.

⎛ R s,oilσOS − R s,NanoσAS ⎞ θNano = arccos⎜ ⎟ σOA ⎠ ⎝ 194

(7.2)

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Energy & Fuels where Rs,oil and Rs,Nano represent the Wenzel roughness of oiland nanofluid-contact zones, respectively. We have Rs,Nano > Rs,oil based on the previous discussion, and therefore θNano > θW. The increasing aqueous-phase contact angle observed in this study is expected as a result of nanoparticle absorption-induced nonuniform surface roughness change. The interfacial tension, σOA, also decreases in presence of the nanoparticles. According to eq 7.1, the wettability will be altered to the stronger waterwet condition if the interfacial tension reduces solely. Resulting from the trading-off of these two factors, the influence of roughness change dominates the wettability alteration behavior, in case of this study. As result, the wettability is altered from the strongly water-wetting to neutrally wetting condition as we observed. Although the alteration of silica surface wettability is directly visualized at the pore scale during nanofluid injection in the micromodel experiments, the highly purified pore wall chemical composition and extremely homogeneous pore structure of the micromodel samples are still concerned with being incompatible with the realistic reservoir rock. As mentioned above, the change in roughness may cause the nanofluid wettability alteration. The roughness of natural rock pore wall also differs from the precisely etched micromodel, and thus the wettability and its alteration behavior need to be further investigated in the natural rock samples. The oil recovery performance of nanofluid in a natural sandstone sample is evaluated in this section via a spontaneous imbibition test. The dynamic imbibition test results are presented in Figure 10. The significant difference can be observed in the oil

effective capillary radius. The aqueous−oleic interfacial tension is reduced about 30% in the presence of 0.1% wt nanoparticles based on our measurement. However, the interfacial tension reduction is still not compatible with such a big difference in the imbibition rate in the presence of silica nanoparticles. Therefore, it is reasonable to expect the increase of contact angle, that is, the wettability alteration, to result in the slowing down of spontaneous imbibition. It indicates that the wettability alteration mechanisms observed in the artificial micromodels still work with natural water-wet sandstones. Although the natural sandstone surface is considered rougher than the dry-etched smooth surface, the absorbed nanoparticles can still significantly increase the specific surface area of the aqueous swept zone, and thus make it less water-wet. The final oil saturation So,f does not show significant difference in the nanofluid case compared to the DI water case, although the imbibition driving force is depressed due to wettability alteration. This implies that, compared to DI water, the nanofluid can more easily mobilize the oil if the flow driving forces are compatible, and thus final oil recovery can be improved by forced injection of nanofluid. After the imbibition test, the cores were carefully loaded in a Hassler type core holder and flooded by methanol for 100 pore volumes to remove the remaining aqueous and oleic phase. Then the samples are dried and crashed to take the SEM images. The methanol cleaning step ensures that no additional nanoparticles deposit on the pore wall result from the drying of the nanofluid. The SEM images of the Berea #2−4 (nanofluid imbibition sample) and the Berea #2−5 (DI water imbibition sample) are presented in Figure 11. Comparing with the DI water

Figure 11. SEM images of core samples after imbibition test.

imbibition sample, the result of nanofluid imbibition sample clearly shows the existence of the nanosize dots attaching on the pore wall. The sizes of nanodots are uniform and consistent with the typical size measured by the Malvern particle size analyzer as presented in Figure 1a. This observation indicates the adsorption of nanoparticles on the pore wall, and consequently, the surface roughness changes.

Figure 10. Change of oil saturation during spontaneous imbibition. The uncertainty of the oil saturation measurement is 0.2%.

saturation reduction rate. The characteristic time of imbibition is the time when 90% total oil production is reached. The characteristic times are 80 min in the DI water imbibition case and 660 min in the nanofluid imbibition case. The imbibition rate is significantly slowed down in the presence of nanoparticles. Spontaneous imbibition is driven by capillary pressure imbalance, which can be expressed as eq 8 when the porous media is simplified as a capillary bundle model:49

5. CONCLUSIONS In this study, the EOR mechanism and performance in the silica-based water-wet reservoir using a charge-stabilized silica nanofluid is investigated experimentally. A forced imbibition experiment is conducted using a dry-etched micromodel with silica surface. In the presence of nanoparticles, the final residual oil saturation is decreased from about 50% to 20% when the concentration of nanofluid is as low as 0.1% wt, implying a significant improvement in oil recovery efficiency. However, further studies on the influence of nanoparticle concentration

2σ cos θ (8) R The similar permeability and porosity of the twin cores (22.9%, 690 mD for Berea #2−4 and 22.3% 675 mD for Berea #2−5) indicate the similar pore structure and thus the similar Pc =

195

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Energy & Fuels

(9) Wei, B.; Li, Q.; Jin, F.; Li, H.; Wang, C. The Potential of a Novel Nanofluid in Enhancing Oil Recovery. Energy Fuels 2016, 30 (4), 2882−2891. (10) Ehtesabi, H.; Ahadian, M. M.; Taghikhani, V.; Ghazanfari, M. H. Enhanced Heavy Oil Recovery in Sandstone Cores Using TiO2 Nanofluids. Energy Fuels 2014, 28 (1), 423−430. (11) Bayat, A. E.; Junin, R.; Samsuri, A.; Piroozian, A.; Hokmabadi, M. Impact of Metal Oxide Nanoparticles on Enhanced Oil Recovery from Limestone Media at Several Temperatures. Energy Fuels 2014, 28 (10), 6255−6266. (12) Hu, Z.; Azmi, S. M.; Raza, G.; Glover, P. W.; Wen, D. Nanoparticle-Assisted Water-Flooding in Berea Sandstones. Energy Fuels 2016, 30 (4), 2791−2804. (13) Giraldo, J.; Benjumea, P.; Lopera, S.; Cortes, F. B.; Ruiz, M. A. Wettability Alteration of Sandstone Cores by Alumina-Based Nanofluids. Energy Fuels 2013, 27 (7), 3659−3665. (14) Wasan, D. T.; Nikolov, A. D. Spreading of nanofluids on solids. Nature 2003, 423 (6936), 156−159. (15) Kondiparty, K.; Nikolov, A. D.; Wu, S.; Wasan, D. T. Wetting and spreading of nanofluids on solid surfaces driven by the structural disjoining pressure: Statics analysis and experiments. Langmuir 2011, 27, 3324−3335. (16) Wasan, D. T.; Nikolov, A. D.; Kondiparty, K. The wetting and spreading of nanofluids on solids: role of the structural disjoining pressure. Curr. Opin. Colloid Interface Sci. 2011, 16, 344−349. (17) Zhang, H.; Nikolov, A. D.; Wasan, D. T. Enhanced Oil Recovery (EOR) Using Nanoparticle Dispersions: Underlying Mechanism and Imbibition Experiments. Energy Fuels 2014, 28 (5), 3002−3009. (18) Monfared, A. D.; Ghazanfari, M. H.; Jamialahmadi, M.; Helalizadeh, A. Potential Application of Silica Nanoparticles for Wettability Alteration of Oil−Wet Calcite: A Mechanistic Study. Energy Fuels 2016, 30 (5), 3947−3961. (19) Karimi, A.; Fakhroueian, Z.; Bahramian, A.; Khiabani, N. P.; Darabad, J. B.; Azin, R.; Arya, S. Wettability Alteration in Carbonates using Zirconium Oxide Nanofluids: EOR Implications. Energy Fuels 2012, 26 (2), 1028−1036. (20) Hendraningrat, L.; Torsæter, O. Effects of the Initial Rock Wettability on Silica-Based Nanofluid-Enhanced Oil Recovery Processes at Reservoir Temperatures. Energy Fuels 2014, 28 (10), 6228−6241. (21) Joonaki, E.; Ghanaatian, S. The Application of Nanofluids for Enhanced Oil Recovery: Effects on Interfacial Tension and Coreflooding Process. Petrol. Sci. Technol. 2015, 33 (7), 794−801. (22) Li, S.; Kaasa, A. T.; Hendraningrat, L.; Torsæter, O. Effect of silica nanoparticles adsorption on the wettability index of Berea Sandstone. International Symposium of the Society of Core Analysts Held in Napa Valley, California, USA, 2013, Sept 16−19. (23) Maghzi, A.; Mohammadi, S.; Ghazanfari, M. H.; Kharrat, R.; Masihi, M. Monitoring wettability alteration by silica nanoparticles during water flooding to heavy oils in five-spot systems: A pore-level investigation. Exp. Therm. Fluid Sci. 2012, 40, 168−176. (24) Cheraghian, G.; Khalilinezhad, S. S. Effect of Nanoclay on Heavy Oil Recovery During Polymer Flooding. Pet. Sci. Technol. 2015, 33 (9), 999−1007. (25) Khalilinezhad, S. S.; Cheraghian, G. Mechanisms behind injecting the combination of nano-clay particles and polymer solution for enhanced oil recovery. Appl. Nanosci. 2016, 6, 923. (26) Mohammadi, M.; Fakhroueian, Z.; Bahramian, A.; Azin, R.; Arya, S. Inhibition of Asphaltene Precipitation by TiO2, SiO2, and ZrO2 Nanofluids. Mohsen. Energy Fuels 2011, 25 (7), 3150−3156. (27) Franco, C. A.; Nassar, N. N.; Ruiz, M. A.; Pereiraalmao, P.; Cortes, F. B. Nanoparticles for Inhibition of Asphaltenes Damage: Adsorption Study and Displacement Test on Porous Media. Energy Fuels 2013, 27 (6), 2899−2907. (28) Worthen, A. J.; Bryant, S. L.; Huh, C.; Johnston, K. P. Carbon dioxide-in-water foams stabilized with nanoparticles and surfactant acting in synergy. AIChE J. 2013, 59 (9), 3490−3501.

are needed to evaluate the optimum nanoparticle concentration. The change of residual oil saturation with the Ca number implies that the reduction of interfacial tension may not be the dominating mechanism for the nanofluid EOR. The wettability alteration from strongly water-wet condition to neutrally wet condition observed via pore-scale visualization is the first major mechanism for oil recovery enhancement. The theoretical analysis based on Wenzel’s model indicates that the nanoparticle adsorption-induced nonuniform pore wall roughness change is a possible mechanism for wettability alteration. For the core scale, similar wettability alteration behavior in the presence of nanoparticles is also investigated via a spontaneous imbibition experiment using the water-wet sandstone sample. The results indicate that the silica-based nanofluid injection is a promising method for enhancing oil recovery in the water-wet sandstone reservoirs by altering the wettability to the neutrally wet condition.

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AUTHOR INFORMATION

Corresponding Author

*Address: Department of Thermal Engineering, Tsinghua University, Beijing 100084, China. Telephone: (8610) 62792294. Fax: (8610) 62792294. E-mail: ruinaxu@mail. tsinghua.edu.cn. ORCID

Ruina Xu: 0000-0001-8561-560X Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This project was supported by the National Key Research and Development Plan (No. 2016YFB0600805) and National Natural Science Foundation of China (No. 51376104). The authors appreciate helpful discussions and suggestions from Dr. Jiamin Wan. The authors declare no competing financial interest.

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REFERENCES

(1) Choi, S. U. S.; Eastman, J. A. Enhancing thermal conductivity of fluids with nanoparticles; Argonne National Laboratory: Argonne, IL, 1995. (2) Patel, H. E. Thermal conductivities of naked and monolayer protected metal nanoparticle based nanofluids: Manifestation of anomalous enhancement and chemical effects. Appl. Phys. Lett. 2003, 83 (14), 2931−2933. (3) Lee, S.; Choi, S. U. S.; Li, S.; Eastman, J. A. Measuring thermal conductivity of fluids containing oxide nanoparticles. J. Heat Transfer 1999, 121 (2), 280−289. (4) Jang, S. P.; Choi, S. U. S. Role of Brownian motion in the enhanced thermal conductivity of nanofluids. Appl. Phys. Lett. 2004, 84 (21), 4316−4318. (5) Ma, H. B.; Wilson, C.; Borgmeyer, B.; Park, K.; Yu, Q. S.; Choi, S. U.; Tirumala, M. Effect of nanofluid on the heat transport capability in an oscillating heat pipe. Appl. Phys. Lett. 2006, 88 (14), 3116−3116. (6) Qu, J.; Wu, H. Y.; Cheng, P. Thermal performance of an oscillating heat pipe with Al2O3-water nanofluids. Int. Commun. Heat Mass Transfer 2010, 37, 111−115. (7) Bang, I. C.; Chang, S. H. Boiling heat transfer performance and phenomena of Al2O3-water nano-fluids from a plain surface in a pool. Int. J. Heat Mass Transfer 2005, 48 (12), 2420−2428. (8) Sedaghat, M. H.; Mohammadi, H.; Razmi, R. Application of SiO2 and TiO2 nano particles to enhance the efficiency of polymersurfactant floods. Energy Sources, Part A 2016, 38 (1), 22−28. 196

DOI: 10.1021/acs.energyfuels.6b02001 Energy Fuels 2017, 31, 188−197

Article

Energy & Fuels (29) Nguyen, P.; Fadaei, H.; Sinton, D. Pore-Scale Assessment of Nanoparticle-Stabilized CO2 Foam for Enhanced Oil Recovery. Energy Fuels 2014, 28 (10), 6221−6227. (30) Buckley, J. S. Multiphase displacements in micromodels, in Interfacial Phenomena in Petroleum Recovery; Morrow, N. R., Ed.; Marcel Dekker: New York, 1991; pp 157−189. (31) Kim, Y.; Wan, J.; Kneafsey, T.; Tokunaga, T. Dewetting of silica surfaces upon reactions with supercritical CO2 and brine: pore-scale studies in micromodels. Environ. Sci. Technol. 2012, 46, 4228−4235. (32) Grate, J. W.; Zhang, C.; Wietsma, T. W.; Warner, M. G.; Anheier, N. C., Jr.; Bernacki, B. E.; Orr, G.; Oostrom, M. A note on the visualization of wetting film structures and a nonwetting immiscible fluid in a pore network micromodel using a solvatochromic dye. Water Resour. Res. 2010, 46, W11602. (33) Grate, J. W.; Warner, M. G.; Pittman, J. W.; Dehoff, K.; Wietsma, T. W.; Zhang, C.; Oostrom, M. Silane modification of glass and silica surfaces to obtain equally oil-wet surfaces in glass-covered silicon micromodel applications. Water Resour. Res. 2013, 49 (8), 4724−4729. (34) Khajepour, H.; Mahmoodi, M.; Biria, D.; Ayatollahi, S. Investigation of wettability alteration through relative permeability measurement during MEOR process: A micromodel study. J. Pet. Sci. Eng. 2014, 120, 10−17. (35) Armstrong, R. T.; Wildenschild, D. Investigating the pore-scale mechanisms of microbial enhanced oil recovery. J. Pet. Sci. Eng. 2012, 94-95, 155−164. (36) de Haas, T. W.; Fadaei, H.; Guerrero, U.; Sinton, D. Steam-ona-chip for oil recovery: the role of alkaline additives in steam assisted gravity drainage. Lab Chip 2013, 13, 3832−3839. (37) Shchukarev, A.; Rosenqvist, J.; Sjoberg, S. XPS study of the silica−water interface. J. Electron Spectrosc. Relat. Phenom. 2004, 137140, 171−6. (38) Bikkina, P. K.; Wan, J.; Kim, Y.; Kneafsey, T. J.; Tokunaga, T. K. Influence of wettability and permeability heterogeneity on miscible CO2 flooding efficiency. Fuel 2016, 166, 219−226. (39) Zhang, C.; Oostrom, M.; Grate, J. W.; Wietsma, T. W.; Warner, M. G. Liquid CO2 displacement of water in a dual-permeability pore network micromodel. Environ. Sci. Technol. 2011, 45 (17), 7581−7588. (40) Treiber, L. E.; Duane, L. E.; Archer, L.; Owens, W. W. A laboratory evaluation of the wettability of fifty oil-producing reservoirs. SPEJ, Soc. Pet. Eng. J. 1971, 12, 531−540. (41) Jadhunandan, P.; Morrow, N. R. Effect of wettability on waterflood recovery for crude oil/brine/rock systems. SPE Reservoir Eng. 1995, 10, 40−46. (42) Zhao, X.; Blunt, M. J.; Yao, J. Pore-scale modeling: Effects of wettability on waterflood oil recovery. J. Pet. Sci. Eng. 2010, 71 (3−4), 169−178. (43) Anderson, W. G. Wettability Literature Survey-Part 6: The Effects of Wettability on Waterflooding. JPT, J. Pet. Technol. 1987, 39, 1605−1622. (44) Wardlaw, N. C. The Effects of Geometry, Wettability, Viscosity, and Interfacial Tension on Trapping in Single Pore-Throat Pairs. J. Cdn. Pet. Technol. 1982, 21 (3), 21−27. (45) Blunt, M. J. Pore level modeling of the effects of wettability. SPE J. 1997, 2, 494−510. (46) Mahmud, W. M.; Nguyen, V. H. Effects of Snap-Off in Imbibition in Porous Media with Different Spatial Correlations. Transp. Porous Media 2006, 64, 279. (47) Wenzel, R. N. Resistance of solid surfaces to wetting by water. Ind. Eng. Chem. 1936, 28, 988−94. (48) Quere, D. Wetting and Roughness. Annu. Rev. Mater. Res. 2008, 38, 71−99. (49) Dong, M.; Dullien, F.; Dai, L.; Li, D. Immiscible Displacement in the Interacting Capillary Bundle Model Part I. Development of Interacting Capillary Bundle Model. Transp. Porous Media 2005, 59 (1), 1−18.

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DOI: 10.1021/acs.energyfuels.6b02001 Energy Fuels 2017, 31, 188−197