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Study of Nanoparticle-Stabilized Foams in Harsh Reservoir Conditions

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Abstract

Many oil reservoirs are at high temperatures and contain brines of high salinity and hardness. The focus of this work is to develop robust foams stabilized by a mixture of nanoparticles and surfactants for such reservoirs. Two types of silica nanoparticles (Si-NP1, Si-NP2) with different grafted low molecular weight ligands/polymers were used. First, aqueous stability analysis of these nanoparticle dispersions were conducted at high-temperature (80 °C) and high-salinity conditions (API Brine; 8 wt% NaCl and 2 wt% CaCl2). The screened nanoparticles were used in combination with an anionic surfactant. Second, bulk foam and emulsion stability tests were performed to investigate their performance in stabilizing the air–water and oil–water interface, respectively. Third, foam flow experiments in the absence of oil were performed to characterize the foam rheology. Finally, oil displacement experiments were conducted in an in-house, custom-built 2D sand pack with flow visualization. The sand pack had two layers of different mesh size silica sand which yielded a permeability contrast of 6:1. Brine floods followed by foam floods (80% quality) were conducted, and foam flow dynamics were monitored. The grafting of low molecular weight polymers/ligands on silica nanoparticle surfaces resulted in steric stabilization under high-temperature and high-salinity conditions. Foam flow experiments revealed a synergy between Si-NP2 and surfactant in stabilizing foam in the absence of crude oil. In the oil displacement experiments in the layered sand packs, the waterflood recoveries were low (~ 33% original oil in place) due to channeling in the top high-permeability zone, leaving the bottom low-permeability zone completely unswept. Foam flooding with just the surfactant leads to a drastic improvement in sweep efficiency. It resulted in an incremental oil recovery as high as 43.3% OOIP. Different cross-flow behaviors were observed during foam flooding. Significant cross-flow of oil from low-permeability zone to high-permeability zone was observed for the case of surfactant. Conversely, the Si-NP2-surfactant blend resulted in no cross-flow from the low-permeability region with complete blocking of the high-permeability region due to the formation of in situ emulsion. Such selective plugging of high-perm zones using nanoparticles with tailored surface coating and concentration has significant potential in recovering oil from heterogeneous reservoirs.

Introduction

Gas flooding has been commercially applied as an enhanced oil recovery technique for more than 50 years. The microscopic displacement efficiency of gas injection is excellent especially when the reservoir pressure is above the minimum miscibility pressure (MMP) where gas is either partially or completely miscible with oil (Orr 2007). However, due to inherent low viscosity and density of gases, gas injection leads to viscous fingering and gravity segregation. Reservoir heterogeneity further leads to poor volumetric sweep efficiency (Lake et al. 1986). Foam is a promising technique to improve sweep efficiency in gas floods (Bertin et al. 1998; Rossen 1996). It can reduce the mobility of gas by several orders of magnitude by increasing the apparent viscosity of gas (Hirasaki and Lawson 1985), while the liquid phase mobility remains unchanged (Eftekhari and Farajzadeh 2017). Moreover, gas trapping further reduce the gas mobility during foam flow in porous media (Kovscek and Bertin 2003; Tang and Kovscek 2006). The concept of foam was first introduced by Boud (1958). Since then, several successful foam field trials have been reported (Hoefner et al. 1995; Rossen et al. 2017; Skauge et al. 2002).

Conventionally, surfactants have been used to stabilize foam in field applications. However, foam stability is quite challenging under high-temperature and/or high-salinity (HTHS) conditions. There are two main reasons for this. First, foam strength typically decreases with increase in temperature. This is because of reduction in liquid phase viscosity at higher temperatures, which expedites the liquid drainage process in foam lamellae and plateau border. Second, the aqueous stability of conventional surfactants limits their use under HTHS conditions. Several researchers have investigated novel surfactant-stabilized foams for HTHS conditions. Chen et al. (2015) reported CO-2-in-water (C/W) foam using a nonionic surfactant with a high degree of ethoxylation. Similarly, Cui et al. (2016) studied Ethomeen C12 surfactant-stabilized C/W foam for HTHS applications in carbonates. This surfactant was only stable at lower pH (close to 4) as it required complete protonation of C12 to be soluble. Xue et al. (2015) reported viscous C/W foams at a high salinity of 14.6% TDS brine at 120 °C using CO2-soluble ionic surfactants. Recently, Alzobaidi et al. (2017) reported highly stable C//W foams of viscosity more than 100 cp using zwitterionic surfactants at 120 °C. The high apparent viscosity of the foam was attributed to the viscoelastic nature of the surfactant. Such surfactant-stabilized foams could potentially be made more robust using nanoparticles with tailored surface coatings.

In the last decade, there is a recent surge in both applied and fundamental research in the field of multifunctional nanoparticles for subsurface applications. It includes use of nanoparticle in Foam EOR (Emrani et al. 2017; Kim et al. 2016; Singh and Mohanty 2016a), nanofluid EOR (Xu et al. 2015; Zhang et al. 2014), emulsion-based EOR (Xu et al. 2017), hydraulic fracturing fluids (Barati et al. 2012), wettability alteration (Karimi et al. 2012), acid treatment of shales (Singh et al. 2017) and drilling fluids (Zakaria et al. 2012). One of the advantages of nanoparticles is that they could be grafted or modified with different functional groups to impart desirable characteristics for subsurface applications. These included viscosity increment (Ponnapati et al. 2011), improved aqueous stability (Griffith and Daigle 2017) and desired surface wettability (Panthi et al. 2017). It makes the nanoparticles quite lucrative for oilfield applications. However, colloidal stability of nanoparticles under high-temperature and high-salinity conditions is a challenge. According to the Derjaguin–Landau–Verwey–Overbeek (DLVO) theory, the sum of attractive van der Waals (vdW) forces and repulsive electrostatic forces dictate the stability of the nanoparticles (Israelachvili 2015). The presence of high amount of monovalent and divalent ions screens the inherent charges on nanoparticles, which reduces the electrostatic repulsion between particles. The Debye length, which is a measure of the distance over which the electrostatic repulsion is felt in the solution, decreases with an increase in salinity (Eslahian et al. 2014). For example, for a salinity of 150 mM, the Debye length is only 0.8 nm (Jiang et al. 2009). In such cases, nanoparticles aggregate due to the van der Waals forces (Elimelech et al. 2013). Moreover, if the nanoparticles are negatively charged such as bare silica nanoparticles at pH 7, the presence of oppositely charged ions such as Ca+2 could result in interparticle bridging which expedites the nanoparticle aggregation (Wuelfing et al. 2001).

There are several approaches which could be adopted to achieve colloidal stability of nanoparticles under harsh conditions on temperature and salinity. One such approach is steric stabilization which involves adsorbing or grafting macromolecules or ligands on the nanoparticle surface (Bagaria et al. 2013; Worthen et al. 2016; Yang and Liu 2010). The presence of these ligands results in steric hindrance, which reduces the probability of two nanoparticles to collide or interact. Additionally, the ligands should have the ability to solvate under the given harsh conditions in aqueous media and form hydration shell around the nanoparticles. Such ligands can provide steric stabilization to the core nanoparticles (Napper 1983).

In our previous study, we showed that a mixture of hydrophilic, PEG-coated silica nanoparticles and anionic surfactant (alpha olefin sulfonate) results in synergistic stabilization of foams in both bulk and homogeneous porous media (Singh and Mohanty 2015). We demonstrated that as the concentration of nanoparticles increases, the mobility reduction factor of surfactant-NP foam in homogeneous 1D core increases up to a factor of two. Recently, we showed that such synergy is even more pronounced in a heterogeneous layered sand pack system by performing visualization experiments (Singh and Mohanty 2017). These experiments allowed us to identify different cross-flow behavior governing the foam flow in such heterogeneous media such as flow diversion from high-perm to low-perm zones. In this work, the first objective was to investigate the stability of two types of silica nanoparticles (grafted with different ligands/polymers) under high-temperature and high-salinity conditions. The screened nanoparticle system was then evaluated as a foam stabilizer in bulk and porous media. Finally, we evaluated and visualized the foaming performance of these surface-modified nanoparticles along with an anionic surfactant in layered, heterogeneous sand pack.

Methodology

Materials

Two different types of surface-modified silica nanoparticles were used in the study. These nanoparticles were coated with different low molecular weight ligands. Polyethylene glycol-coated particle was supplied by Nyacol NanoTechnologies, Inc and GLYMO ((3-glycidyloxypropyl)trimethoxysilane)-coated particle was supplied by a local vendor. These nanoparticles are referred in this paper as Si-NP1 and Si-NP2. The sizes of Si-NP1 and Si-NP2 in DI water at pH 7 were 20 and 12 nm, respectively. An anionic surfactant, Amphoam (Weatherford) with a sulfonate head group (68% active), was used in these experiments. Sand (US Silica) of two different mesh sizes, 100–120# and 40–70#, was used to prepare heterogeneous sand packs. Crude oil was obtained from a reservoir, and it had a viscosity of 32 cp at 25 °C and density of 0.825 g/cm3. The viscosity was measured using an AR-G2 rheometer from TA instruments. Sodium chloride (Fisher Chemical), calcium chloride (Sigma-Aldrich) and nitrogen (research grade, Matheson) were used as received. Ultrapure water with a resistivity greater than 18.2 MΩ cm was used to prepare brine solutions. The zeta potential of nanoparticle solutions was characterized with a Delsa Nano analyzer which employs dynamic light scattering principle. It uses laser Doppler electrophoresis based on Smoluchowski approximation to measure the zeta potential of the nanoparticles.

Aqueous Stability of Nanoparticles and Surfactants

The aqueous stability of nanoparticles or surfactant solutions were evaluated under varying salinity conditions at three different temperatures 25, 60 and 80 °C. To prevent evaporation of the samples, custom-made borosilicate glass vials were used. These vials were sealed from the top using Teflon-threaded caps and chemical-resistant O-rings. Ten ml of 0.5 wt% nanoparticles solution with varying salinity (of 1–8 wt% NaCl and API brine) was taken in the vials and placed in different ovens operating at 25, 60 and 80 °C. The aqueous stability of the samples was monitored visually for 2 months. A stable sample was optically clear, while an unstable sample had a hazy and translucent appearance.

Bulk Foam Stability

The morphology of foam flowing in bulk is different from foam in porous media. The bubble sizes of foam, which is a key foam characterization parameter, in bulk are the order of magnitude smaller than the size of the medium holding it, whereas the bubble sizes are similar to pore sizes for the cases of foam flow in porous media. Albeit these differences, bulk foam stability tests are often conducted as a basic screening tool to compare and evaluate foaming tendency of different formulations (Singh et al. 2018; Singh and Mohanty 2016b). One of such common tests is the static foam test in which decay of foam volume with time is monitored. In this work, bulk foam stability of nanoparticle-surfactant mixtures is evaluated at 25 °C and 80 °C. The salinity of the system was kept constant; API brine (8 wt% NaCl + 2 wt% CaCl2) was used. A 10-ml sample was taken in a glass vial and was sealed using a PTFE-lined cap. The vial was hand shaken vigorously for 15 s to generate foam. The foam height (above the drained liquid phase) was recorded as a function of time.

Bulk Emulsion Stability

The injection of surface-active components such as surfactants or nanoparticles during oil displacement experiment could lead to in situ emulsion formation. Therefore, bulk emulsion stability experiments were performed to understand the role of nanoparticles in emulsion stability. A varying ratio of oil and API brine solution (containing surfactant or nanoparticles or a blend) was taken in glass vials. The mixtures were mixed at high shear using a rotor–stator homogenizer (Ultra Turrax, T25, IKA Werke, Germany) operating at 10,000 rpm for 30 s. The relative emulsion height, a measure of emulsion stability, was monitored with time. The type of emulsion (o/w or w/o) was determined by drop dilution test in which a small of amount of oil or water was added to the emulsion to see if which one mixes with it to determine the external continuous phase of the emulsion.

Oil-Free Foam Flow Experiments

The foam flow dynamics in the presence of oil can be significantly altered due to the foam–oil interaction or in situ emulsion formation. To decouple this effect of oil, foam flow experiments in the absence of oil were performed in homogeneous Berea core to characterize the rheology of foam. Figure 1 shows the experimental schematic. The apparatus was built to co-inject nitrogen gas and aqueous (brine/surfactant/surfactant-nanoparticle blend) solution using two series-D syringe pumps (Teledyne ISCO, NE) through a sand pack (0.6 inch diameter and 6 inch long) to ensure proper mixing and foam generation. The downstream pressure of the experiment was maintained by a back-pressure regulator (Equilibar, NC, and Swagelok, OH) at 110 psi which was installed downstream of the sand pack. The experiment was performed at the room temperature. Nitrogen gas and surfactant or surfactant-NP blend were co-injected through the foam generator to make a foam of 80% quality (volume fraction of gas) to displace the core which is initially saturated with 100% brine. The pressure drop across the core was measured using Rosemount differential pressure transducers. An automated data acquisition system (LabView, National Instruments) was used to record the pressure. After the end of each run, the core was flushed with 20 PV of methanol-brine (2 wt% NaCl) mixture (1:1 by vol) to break the foam completely. It was followed by an injection of more than 30 PV of API brine to flush the methanol. The system was intermittently pressurized and depressurized to remove any trapped gas from the system. The pressure drop of brine injection post core-cleaning was similar to initial brine flow pressure drop in all cases indicating complete removal of trapped foam.

Fig. 1
figure1

Schematic of the apparatus for oil-free foam flow experiments

Preparation of 2D Heterogeneous Sand pack

Foams can divert flow from high-permeability regions to low-permeability regions in heterogeneous porous media. The foam flow phenomenon in a heterogeneous medium is much complex as compared to foam flow in 1D, homogeneous core. To understand and visualize the foam flow dynamics in a heterogeneous medium, a simplified layered sand pack model was fabricated. An in-house sand pack holder made of stainless steel was designed with one face made of a transparent acrylic plate (thickness: 0.75 inches) for visualization. The dimension of the interior of the holder was 5.4 inch × 2.9 inch × 1 inch. There were three injection ports on the left side and three production ports on the right side, as shown in Fig. 2. Stainless steel screens (400 mesh) were welded on these ports to prevent sand flow. The holder was packed with two layers of silica sand: the top layer using 40–70 mesh and the bottom layer using 100–120 mesh. The permeability of the top layer was 22.6 Darcy, while that of the bottom layer was 3.8 Darcy. Thus, the permeability contrast was about 6:1. The layer permeability was measured by flowing water through a 1D tube (1 ft long; 1 inch in diameter) packed with each sand. The permeability and the porosity of the two-layer system were measured to be 15.7 Darcy and 31%, respectively.

Fig. 2
figure2

Schematic of the apparatus for oil displacement experiments

Oil Displacement Experiments

Foam flow experiments were conducted to investigate the dynamics of foam flow in a heterogeneous porous medium in the presence of reservoir crude oil. Foams were stabilized by either a surfactant or a surfactant-nanoparticle blend. Figure 2 shows the experimental schematic which is similar to the previous setup, but the core is replaced with heterogeneous sand pack. Petrophysical properties such as porosity and permeability of the sand pack were determined using standard methods (e.g., gas expansion method and gas permeability method; Peters 2012) before performing the vacuum saturation with crude oil. The conventional technique of oil saturation is to displace the brine-saturated porous media with crude oil at constant high pressure. However, due to the high-permeability contrast (6:1) in the present system, it was not possible to achieve high initial oil saturation using this technique. Therefore, the initial oil saturation was obtained by vacuum saturation which resulted in 100% initial oil saturation for every case. After the crude oil saturation, the whole setup was pressurized with a back pressure of 110 psi, and more than 0.5 PV of oil was injected. The brine flood was then conducted at 10 ft/D for 4 PV until no oil was produced. Nitrogen gas and surfactant or surfactant-NP blend were then co-injected through the foam generator to make a foam of 80% quality (volume fraction of gas). This foam was injected into the two-layer sand pack at an average interstitial velocity of 4 ft/D. This pre-generated foam was injected through the ports on the left side of the heterogeneous sand pack for more than 20 PV. Oil recovery and pressure drops were monitored at each step. The displacement of crude oil by injection fluid was captured using a Supereyes® microscope.

Results

Aqueous Stability of Nanoparticles and Surfactants

First, the aqueous stability of two different nanoparticles was evaluated under varying salinity conditions at three different temperatures 25, 60 and 80 °C. Figure 3 shows the stability of both the nanoparticles. Both nanoparticles were stable for a wide range of salinity at room temperature (25 °C). The stability and salt tolerance of both nanoparticles decreased with an increase in the temperature. Si-NP1 was found stable only below 2 wt% NaCl and 1 wt% NaCl salinity at 60 °C and 80 °C, respectively. At higher salinities, precipitation of the nanoparticles was observed indicating severe aggregation. However, Si-NP2 was found to be more stable than Si-NP1 with a salt tolerance of 8 wt% at 60 °C and 2 wt% at 80 °C. This shows that the GLYMO surface coating was more efficient than PEG surface coating in providing steric stabilization of the silica nanoparticles under high salinity. Based on these results, Si-NP2 nanoparticles were chosen in the subsequent experiments. Note that the pH of the Si-NP2 solutions was 8.5 and was not modified in this test.

Fig. 3
figure3

Aqueous stability of a Si-NP1 and b Si-NP2 at different temperature and varying salinity: hollow symbols represent clear solution (stable) and filled symbols represent precipitation (unstable)

The Si-NP2 nanoparticles are highly negatively charged under natural pH of 8.5 as confirmed via zeta potential measurements. A decrease in surface charge (less negative) of the nanoparticle (to a limit) is desirable as it would reduce the interaction with the divalent ions and thus increasing stability and salt tolerance of the system. A decrease in pH of the solutions is expected to reduce the surface charge of the system and hence can increase the stability of the nanoparticles. Therefore, the pH of Si-NP2 solutions was varied from 8.5 to 2. The salinity of the solutions was kept constant and equal to API brine (8 wt% NaCl and 2 wt% CaCl2) which represents a high-salinity brine with high hardness. Figure 4 shows the results of the aqueous stability of the nanoparticles after 2 months. The solutions were found to be completely clear for the cases of pH 2 and 3.5 at the three temperatures. For pH 5 and 6.5, cloudy solutions were observed indicating some aggregations of nanoparticles at 60 and 80 °C. For higher pH such as 7 and 8.5, precipitations of nanoparticles were observed indicating poor aqueous stability at 60 and 80 °C.

Fig. 4
figure4

Aqueous stability of Si-NP2 at varying pH and constant API brine salinity (8 wt% NaCl + 2 wt% CaCl2). The hollow symbols, semi-filled symbols and filled symbols represent a clear solution, cloudy solution and precipitation, respectively

Zeta potential of the Si-NP2 system was then measured as a function of pH to better understand this stability trend. The zeta potential of these nanoparticles at their natural pH of 8.5 was − 30 mV in DI water. As the pH of the solution was reduced, the magnitude of zeta potential was reduced (becomes less negative) from − 30 to − 7 mV corresponding to pH 8.5 and 2, respectively, in DI water as shown in Fig. 5. Such reduction in particle charge reduces the interaction with divalent ions such as Ca+2 and increases nanoparticle stability. For very high-salinity and high-temperature conditions, these nanoparticles are stable at low pH < 3.5 for more than 6 months. The equilibrium in situ pH of the reservoir fluids during carbon dioxide flooding is reported to be close to 3 (Kharaka et al. 2006). Thus, these nanoparticles could be used to stabilize carbon dioxide-in-water foams under reservoir conditions.

Fig. 5
figure5

Zeta potential of Si-NP2 as a function of pH in DI water

Bulk Foam Stability

Based on the aqueous stability results, the Si-NP2 nanoparticles were chosen for further foam studies in bulk and porous media. Static foam test is the most common bulk foam stability tests. Recently, Jones et al. (2016) reported a good correlation between bulk foam stability and apparent foam viscosity (in porous media) in the absence of oil. The Si-NP2 nanoparticles, when mixed in a vial in the presence of air, do not have any affinity to form foam irrespective of the salt concentration. It is due to the hydrophilic nature of the nanoparticles (even though the coating has small hydrophobic chains). Therefore, to stabilize foam, an anionic surfactant was used in addition. The objective of the static foam tests in the present study was to investigate an optimum surfactant concentration, if any, to be used in the blend of Si-NP2 and surfactant blend. In this test, the total nanoparticle concentration was kept constant at 0.5 wt%, and salinity was API brine. The surfactant concentration was varied from 0 to 1 wt%. A small amount of blend was taken in a glass vial and was shaken vigorously for 15 s to make static foam. The decay in foam height was recorded at 25 °C.

Figure 6 shows the static foam in the vials with varying concentration of surfactant at time t = 0 min. Figure 6a demonstrates the vial with only 0.5 wt% Si-NP2 nanoparticles solutions. It can be seen that nanoparticles alone show negligible foaming tendency. The initial foam height, which is often referred in the literature as foamability, increases with the increase in surfactant concentration. Note that the CMC of this surfactant is close to 0.125 wt% as measured in a previous study (Panthi et al. 2017). Figure 7 shows the decay of foam heights at 25 °C. The foam heights were normalized with respect to maximum possible height (which is the maximum foam height for the case of 1 wt% surfactant at t = 0 min) to obtain relative foam height. Several observations can be made from the plots. Foam strength increases monotonically with the increase in surfactant concentration and no optimum surfactant concentration was observed for foam stability as evident from foamability as well as foam decay behavior. Based on this test, a surfactant concentration of 0.5 wt% was chosen for foam flooding in the subsequent oil displacement experiments.

Fig. 6
figure6

Static foam at time t = 0 min at 25 °C formed using 0.5 wt% Si-NP2 nanoparticles and increasing concentrations of surfactant. The concentration of surfactant was a 0 wt%, b 0.0625 wt%, c 0.125 wt%, d 0.25 wt%, e 0.5 wt% and f 1 wt%. The salinity was constant in each sample and equal to API brine (8 wt% NaCl and 2 wt% CaCl2)

Fig. 7
figure7

Static foam test with formulations containing 0.5 wt% Si-NP2 nanoparticles and varying concentration of surfactant at 25 °C. The salinity was constant in each sample and equal to API brine (8 wt% NaCl and 2 wt% CaCl2)

Bulk Emulsion Stability

In this experiment, crude oil and aqueous formulation were taken in different volumetric ratio and were mixed under high shear to generate emulsions. The oil fraction, analogous to foam quality, was varied from 20 to 80%. Emulsion heights were monitored over time, and relative emulsion height (normalized height w.r.t maximum possible height) was plotted as a function of time. First, 0.5 wt% surfactant in API brine (pH = 3.5) was taken as the aqueous phase. (0.5 wt% concentration was chosen as it is a typical surfactant concentration used in field applications; higher concentration can improve stability, but would make it more expensive.) Figure 8a shows the digital images of the different vials with varying oil fraction. The drop dilution test showed that all the cases were an oil-in-water emulsion. No catastrophic phase inversion was observed even at 80% oil fraction. Figure 8b shows the plot of relative emulsion height. All emulsions (different oil fraction) coalesced in less than 250 min. Figure 8c shows the typical separated phases such as foam, crude oil, emulsion and surfactant solution observed in the vials. Interestingly, emulsion half-life, a measure of emulsion stability, was found to be higher for the lower oil fraction cases (20–60%) as compared to higher oil fraction (70–80%) as shown in Fig. 11. Note the scale of the plot is log base 10. It clearly shows that emulsion stability is a strong function of oil–water ratio with a decrease in stability as oil fraction increases.

Fig. 8
figure8

a Digital images of oil–water emulsions stabilized using 0.5 wt% surfactant with oil fraction varying from 20 to 80%; b plot of decay of corresponding relative emulsion height with time; c digital image of vial containing 50% quality emulsion at T = 112 min showing the different separated phases

In the second case, 0.5 wt% Si-NP2 nanoparticles in API brine (pH = 3.5) were taken as the aqueous phase. The drop dilution test showed that emulsion type for oil fraction 20–70% was oil-in-water while for the case of 80% was water-in-oil. Such catastrophic phase inversion of the emulsion when oil/water fraction in change has been widely reported in the literature (Binks and Lumsdon 2000a, b). Interestingly, the emulsion stability behavior was found to be dramatically different. The relative emulsion height for all cases except 80% oil fraction cases remains constant even after more than 1 year of preparation (Fig. 9a, b). Two key observations can be made from this result. First, the Si-NP2 nanoparticles alone can stabilize oil–water interface and thus are interfacially active (Interface here is oil–water). Note that these nanoparticles showed no bulk foaming tendency indicating no affinity for the air–water interface. Second, once these nanoparticles are brought to the interface via mechanical stirring, they are irreversibly adsorbed on the interface and provide ultra-stable emulsion stability.

Fig. 9
figure9

a Digital images of oil–water emulsions stabilized using 0.5 wt% Si-NP2 with oil fraction varying from 20 to 80%; b plot of decay of corresponding relative emulsion height with time

In the last case, a blend of 0.5 wt% surfactant and 0.5 wt% Si-NP2 in API brine (pH = 3.5) was taken as the aqueous phase. The decay in emulsion height was relatively slower as compared to the surfactant case (Fig. 10b), but much faster for the case of nanoparticles alone (half-life > 1 year). The emulsion half-lives were much higher than that of the surfactant cases for oil fraction of 20–70% (Fig. 11). Since both surfactant and nanoparticles are oil–water interfacial active, they both compete for the interface. This complex interaction works antagonistically toward emulsion stability in the present case. These results show that emulsion stability can be tuned by varying the concentration of surfactant and nanoparticles from ultra-stable (half-life ~ order of years) to moderately stable (half-life ~ order of minutes).

Fig. 10
figure10

a Digital images of oil–water emulsions stabilized using 0.5 wt% surfactant and 0.5 wt% Si-NP2 blend with oil fraction varying from 20 to 80%; b plot of decay of corresponding relative emulsion height with time

Fig. 11
figure11

Half-lives of emulsions stabilized using different formulations

Oil-Free Foam Flow Experiments

The objective of these experiments was to quantify the foam rheology of surfactant-nanoparticle blend in the absence of crude oil. The Berea core used in this experiment was 1 ft long, 1.5 inch in diameter with permeability and porosity of 246 mD and 21.4%, respectively. First, a base case was performed in which the API brine (pH = 3.5) and nitrogen gas were injected at 80% quality (gas volume fraction) for more than 5 PV into an initially brine-saturated core. Figure 12a shows the transient pressure drop profile of this case (black curve). The steady-state pressure drop at the end of the experiment was low and equal to 1.28 ± 0.16 psi. The core was then flushed with more than 30 PV of API brine, and the system was intermittently pressurized and depressurized to remove any trapped gas. In the second case, 0.5 wt% surfactant in API brine (pH = 3.5) was used as a foaming agent. The surfactant solution and nitrogen gas were co-injected at 80% quality to displace the brine for more than 7 PV. The pressure drop for the first 2PV of foam injection was low and similar to the base case indicating only weak foam propagation through the core due to the high initial in situ water saturation. The pressure drop slowly starts to build up after 2 PV, and average pressure drop at the end of the experiment was 2.35 ± 0.33 psi. The foam resistance factor (a ratio of pressure drop due to foam case and base case) was 1.84. The core was then cleaned to remove trapped foam as discussed earlier in the methodology section. In the subsequent cases, the surfactant concentration was kept constant while nanoparticle concentration in the solution was increased from 0 to 0.5 wt%. In all cases, the pressure drops were low for less than 2 PV. The average pressure drop at the end of the experiment for 0.1 wt%, 0.3 wt%, 0.5 wt% was 3.54 ± 0.77, 5.92 ± 1.46, 7.25 ± 5.66 psi, respectively, as shown in Fig. 12b. A clear synergy between surfactant and Si-NP2 in stabilizing foam under high-salinity conditions was observed with foam resistance factor increasing from 1.84 (surfactant case) to 5.66 (surfactant + 0.5 wt% Si-NP2). There are several mechanisms by which hydrophilic nanoparticles such as Si-NP2 can increase the stability of surfactant-stabilized foams as discussed in our previous study (Singh and Mohanty 2015). These include particle detachment energy (Binks and Lumsdon 2000a, b), the maximum capillary pressure of coalescence (Denkov et al. 1992) and film drainage kinetics (Horozov 2008). In the subsequent section, the role of these nanoparticles in stabilizing foams in the presence of oils was studied.

Fig. 12
figure12

a Pressure drop profile for different aqueous formulations; b average pressure drop at the end of the experiment for surfactant formulation (0.5 wt%) with varying Si-NP2 concentration

Oil Displacement Experiments

The oil displacement experiments were performed to evaluate and visualize foaming performance of the surfactant and the surfactant-nanoparticle mixture under high-salinity conditions. Since the visualization required the use of transparent acrylic sheet whose pressure/temperature rating was not very high, the experiments were performed under low pressure (~ 110 psi) and room temperature. As high-pressure CO2, which would have yielded an equilibrium pH ~ 3–4, could not be used, the pH of the aqueous phase was adjusted using a weak acid. Before conducting the oil displacement experiments, another independent experiment was performed in which API brine of pH 3.5 was injected in a brine-saturated (pH 7) sand pack. When HCL was used to lower the pH of the injection brine, the effluent pH was found to be close to 5.5 even after several pore volumes of injection. This was possibly because of strong reactivity of HCL acid with the minerals present in sand grains. However, when citric acid was used, the pH was able to propagate along the sand pack, and the effluent pH was found to be 3.5. Therefore, in these experiments, citric acid was used to adjust the pH.

Flood 1 was conducted with the surfactant as the foaming agent. The sand pack was vacuum-saturated with crude oil which resulted in the initial oil saturation of 100%. Figure 13 shows the injection schedule, cumulative oil recovery (secondary y-axis) and overall pressure drop (primary y-axis) across the sand pack. First, brine flood was conducted at 10 ft/D to mimic a waterflood in a reservoir. It was continued for more than 4 PV until no oil was produced. The pH of injected brine was adjusted to 3.5 using citric acid. The waterflood oil recovery was 33.6% OOIP (original oil in place), and oil saturation was reduced to 66.4%. The pressure drop during water flood was very low (0.04 psi). The oil recovery during this stage was low due to channeling of injected brine through the top high-permeability layer. Note that the permeability contrast between the top and bottom layer was 6:1. Figure 14a shows the oil displacement profile after 4 pore volume of brine injection. Although the mobility ratio of brine (1 cp) displacing oil (32 cp) is unfavorable, the sweep in the top layer was good (visually), as seen from Fig. 14a, because of the high permeability of the layer. The pH of the effluent was tested at the end of water flood, and it was close to 3.5. Then, foam flooding was performed at 4 ft/D using the anionic surfactant as the foaming agent. The formulation had 0.5 wt% surfactant in API brine. The pH was lowered to 3.5 using the citric acid. The foam quality (volume fraction of gas) was kept constant at 80%.

Fig. 13
figure13

Pressure drop profile (black, left axis) and cumulative oil recovery (blue, right axis) for Flood 1

Fig. 14
figure14

Oil distributions during Flood 1 (left), Flood 2 (middle) and Flood 3 (right) at different pore volumes of foam injection (PVI)

Figure 14b–h shows the oil displacement profiles during foam injection; injected foam PV is indicated (does not include water flood). In the first 2 PV of foam injection, the foam only swept the top layer (Fig. 14b) and recovered about 11.5% OOIP oil. It is to be noted that even though the top layer looked clean after brine flood visually, it has a significant amount of residual oil left which was recovered by foam in the first 3 PV (7 PV including water flood). The pressure drop during this stage increased (as compared to brine injection) indicating an increase in apparent foam viscosity. Figure 14c shows how foams start diverting injection fluid from the high-permeability layer to the low-permeability layer. The displacement in the lower layer is almost piston-like at 6 PV foam injection (Fig. 14d). The oil from the lower layer moves into the upper layer without much oil production from the cell during 4-8 PV foam injection. This cross-flow behavior has been typically observed during foam flow in heterogeneous systems and has been reported in a previous study (Singh and Mohanty 2017).The oil pushed into the upper layer was eventually produced between 8 and 14 PV of foam injection. The foam flood was continued for more than 18 PV. The pressure drop across the sand pack increased to 1.4 psi by the end of the experiment. The ultimate cumulative oil recovery was 76.9% OOIP, the incremental oil recovery by foam was 43.3% OOIP, and the final oil saturation was 23.1%. The foam tends to generate easily in the high-permeability layer and blocks it due to the formation of viscous foams. This shows the self-regulating capabilities of foam which make it lucrative as a conformance control tool in a heterogeneous system such as the present one.

In Flood 2, we wanted to explore the potential synergism of using the Si-NP2 nanoparticles with the anionic surfactant and understand how these surface-modified nanoparticles alter the foam flow dynamics. The sand pack was again packed with clean, dry sand in a similar way as before and was vacuum-saturated with crude oil with an initial saturation of 100%. After an initial water flood, a foam flood was conducted using a mixture of the surfactant (0.5 wt%) and Si-NP2 nanoparticles (0.5% Si-NP2) as the foaming agent. The formulation was prepared in API brine (8 wt% NaCl and 2 wt% CaCl2) with a pH of 3.5. Figure 15 shows the injection procedure, cumulative oil recovery (secondary y-axis) and overall pressure drop (primary y-axis) across the sand pack.

Fig. 15
figure15

Pressure drop profile (black, left axis) and cumulative oil recovery (blue, right axis) for Flood 2

Similar to Flood 1, first a brine flood was conducted at 10 ft/D. It was continued for more than 5 PV. The brine flood oil recovery was 31.7% OOIP, and oil saturation was reduced to 68.3% which is similar to the Flood 1. Then, nanoparticle-surfactant solutions and nitrogen gas were co-injected with a quality of 80% at 4 ft/D. Figure 14 shows the comparison of oil distribution due to foam flooding at different pore volumes (PV) of foam injection for the surfactant case (left) and the blend case (right). The initial oil displacement process by the blend foam (< 6 PV) was similar to the surfactant case in Fig. 14a–d vs i–l. The foam first swept the high-permeability layer resulting in 10% OOIP additional oil recovery, whereas the corresponding recovery in Flood 1 was 20% OOIP. The pressure drop during this stage increased to 0.2 psi compared to 0.04 psi during waterflood. (Note that brine flood was performed at 2.5 times faster rate.) The cross-flow of foams from high-permeability to low-permeability was clearly evident from Fig. 14k–m. However, during this flood, no cross-flow of oil from low-permeability layer to high-permeability was observed as opposed to the surfactant foam case, as shown in Fig. 16. The flow in the high-permeability layer was completely blocked. This is due to the nanoparticle-assisted oil-in-water emulsions as observed in the bulk emulsion stability tests. The foam flood, in this case, was continued for more than 21 PV. The ultimate cumulative oil recovery was 60.8% OOIP, the incremental oil recovery by foam was 29.0% OOIP, and the final oil saturation was 39.2%. The pressure drop never built up above 0.25 psi in Flood 2, much lower than about 1.2 psi in Flood 1. Presumably, it is because most of the foaming agents (surfactant-nanoparticles) were consumed in the in situ emulsion formation. Interestingly, the emulsion formation was only observed in the top high-permeability zone, and the bottom swept zone was almost clear (Fig. 14m–p). In the bulk emulsion stability test, we showed that emulsion stability increases with an increase in water-to-oil ratio. Since the high-perm zone has a relatively higher water saturation post-waterflood, it could lead to stronger in situ emulsion formation. Although the final recovery in the Si-NP2-surfactant blend case was low, it resulted in selective plugging of the high-permeability layer which is desirable in the field applications. Such flow behavior was not observed when PEG-coated silica nanoparticles were used in our previous study (Singh and Mohanty 2017). It shows that nanoparticle surface coating can alter foam flow dynamics in heterogeneous porous media.

Fig. 16
figure16

Cross-flow mechanisms observed during foam flooding a surfactant case; b surfactant-NP blend (1:1) case in oil displacement experiments

In order to evaluate if the stability of the in situ emulsion formation can be tuned, we reduced the nanoparticle concentration from 0.5 to 0.1 wt% in the Flood 3. Similar injection scheme was followed as in the previous floods. Figure 17 shows the cumulative oil recovery (secondary y-axis) and overall pressure drop (primary y-axis) across the sand pack. The brine flood recovery was 30.73% OOIP similar to previous floods, and oil saturation was reduced to 69.27%. Initial foam flow dynamics was quite similar to Floods 1 and 2 where cross-flow from high-perm layer to low-perm layer was observed (Fig. 14r, s). In this case, also, cross-flow from low-perm to high perm was not observed. The presence of emulsion in the top layer was not clearly apparent from visual images as opposed to the case of Flood 2 in which formation of the in situ emulsion was clearly visible (light brown oily stuff in the top layer, Fig. 14m–p). However, by monitoring the foam flow dynamics, it was clear that in this case also, cross-flow in top layer was limited. The foam flood was continued for more than 28 PV. The average pressure drop across the sand pack was 3.28 psi by the end of the experiment which was higher than the Flood 2 indicating stronger foam formation. This shows that by tuning the nanoparticle concentration, it is possible to control the in situ foam and emulsion stability. The incremental oil recovery by foam was 38% OOIP which was higher than Flood 2 (29% OOIP) because of the better sweep of the top layer due to relatively weaker emulsion formation (Fig. 14u–w). The ultimate cumulative oil recovery was 68.7% OOIP, and the final oil saturation was 31.3%. These results show that it is possible to design and optimize the concentration and surface coating of silica nanoparticles for conformance control application. Such tailored surface-modified nanoparticles show immense potential to act as a foam EOR agent under harsh reservoir conditions such as high-temperature and high-salinity conditions.

Fig. 17
figure17

Pressure drop profile (black, left axis) and cumulative oil recovery (blue, right axis) for Flood 3

Conclusion

The following conclusions can be drawn from this work:

  1. 1.

    Silica nanoparticles were sterically stabilized using (3-glycidyloxypropyl)trimethoxysilane (GLYMO) coating under high salinity (API brine) at 80 °C for pH < 3.5. These nanoparticles show no signs of aggregation even after 6 months.

  2. 2.

    Foam flow experiments in the absence of oil showed synergy between surfactant and nanoparticles in stabilizing foam with threefold increment in foam resistance factor compared to surfactant case.

  3. 3.

    Foam flood in heterogeneous sand packs with a reservoir crude oil showed that incremental oil recovery of 29.1–43.3% OOIP (over waterflood) using immiscible foams.

  4. 4.

    Despite the presence of a permeability contrast (6:1), which is favorable of channeling of gas through high-permeability region, the foam was effective in diverting fluid to the low-permeability region even in the presence of crude oil. This cross-flow behavior was observed in both cases: foams stabilized by surfactant alone and surfactant-Si-NP2 mixtures.

  5. 5.

    Significant cross-flow of oil from low-permeability region to high-permeability region was observed for the case of surfactant foam flood. Conversely, the Si-NP2 (0.5 wt%) resulted in no cross-flow with complete blocking of the high-permeability region due to the formation of in situ emulsion. Such selective plugging of high-permeability channels via nanoparticles with optimum surface coating could have significant potential in recovering oil from heterogeneous reservoirs.

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Acknowledgements

We are thankful to the sponsors of Gas EOR Industrial Affiliates Project at The University of Texas at Austin for partial funding of this work.

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Correspondence to Kishore K. Mohanty.

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Singh, R., Mohanty, K.K. Study of Nanoparticle-Stabilized Foams in Harsh Reservoir Conditions. Transp Porous Med 131, 135–155 (2020). https://doi.org/10.1007/s11242-018-1215-y

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Keywords

  • Foam
  • Nanoparticles
  • Surfactants
  • High temperature
  • High salinity