Evaluating the role of black rice husk ash nanoparticles in enhancing foam stability for enhanced oil recovery

Introduction: Foams have been considered for their ability to control in solution, gas injection improved oil recovery (IOR) processes, for blocking and diverting using either gelled foams, and for gas and oil ratio control at production wells. In a range of applications, a foam meets a range of oil saturations, which requires the design of a foam with the necessary stability for oil saturation. The stability of foams in oil is extremely important for the oil industry. Core flood experiments by different investigators suggest that oil becomes harmful to foam at oil saturation levels above 5% to 20%. The use of such foams is notably advantageous over the use of simple fluids with similar nominal mobility because of the foam and with a viscosity higher than that of the displaced fluids. This is because surfactant-stabilized foams reduce the mobility of the gas present in the higher permeability portions. This causes a diversion of the displacing gas to the formation parts that were previously unswept. Additional oil can be recovered from underswept areas.

Methods: The black rice husk ash used in this study was sourced from a Japanese rice husk ash company. The anionic foaming surfactant, Sodium Dodecyl Benzene Sulfonate (SDBS), was obtained from Sigma. The experimental setup included two 1.5-liter cylinders for the mixed solution and one cylinder for CO. A sand pack measuring 30 cm in length and 2.5 cm in radius was used, and the sand and black rice husk ash were sieved using a 0.125 mm sieve. It was then filled with local white sand particles of 0.0125 mm. The high-pressure pump employed for the fluid pressure was a 100DX syringe pump capable of operating at pressures of up to 10,000 psi (690 bar).

Results: 0.5 wt. % concentration of rice husk ash and SDBS surfactant was mixed with 1000 mL of water. The mixture was stirred on a magnetic stir plate for over 20 min. The experimental setup is illustrated The experiment conducted without a sand pack and with a sand pack. Pressure pumps were connected to a CO₂ gas cylinder and a mixed solution of rice husk ash and SDBS surfactant via a connector, which also included a flow meter to monitor the flow rate. Foam generators were attached to produce foam for the experiment. Pressure meter was attached via a large connector to monitor the pressure during the experiment. The sand pack experimental design offers valuable insights into the foam lifespan and stability under sand pack conditions relevant to EOR. An oil field firm (Dongying, China) provided the oil. Oil was extracted from the unconsolidated sandstone reservoir of the oilfield. The oil viscosity of the black rice husk ash and SDBS surfactant was 40 mPa. Three core flood and three foam-flooding experiments were conducted to obtain the best results. The first experiment failed because of the leakage of gas at the connecting point, which was difficult to detect. After completing the sand pack experiments, the foaming mechanism was investigated further.

Discussion: Foam volume and sand pack influence: without a sand pack, the initial foam volume of black rice husk ash foam is relatively high. However, in the presence of a sand pack, the volume decreases. Adding black rice husk ash liquid at a modest concentration can optimize foam volume across various temperatures. The foam drainage half-life is significantly influenced by incorporating black rice husk ash at different liquid flow rates. Viscosity and bubble stability: The addition of black rice husk ash foaming agents to oil reduces its viscosity. Despite a significant increase in bubble velocity, the stability of the bubbles decreases. However, these tiny foam bubbles exhibit longer stability compared to the initial phase. Foam stability in sand pack conditions: In sand pack conditions, black rice husk ash positively impacts foam stability and strength both before and after flooding. However, the foam lifetime becomes limited after sand pack flooding. Oil recovery enhancement: Injecting black rice husk ash foam into a sand pack increases oil recovery. Microscopic studies and recovery points indicate that the silica nanoparticles in black rice husk ash contribute significantly to foam ability and stability.

1 Introduction

Foams have been considered for their ability to control solutions, improve oil recovery (IOR) through gas injection, block and divert using gelled foams, and regulate gas-to-oil ratio at production wells. In a range of applications, foam encounters a range of oil saturations, which requires the design of foam with sufficient stability for oil saturation. The stability of foams in oil is crucial for the oil industry. Core flood experiments by different investigators suggest that oil becomes harmful to foam at oil saturation levels above 5%–20%. Mobility control can be defined as the reduction process of the mobility ratio to improve the volumetric sweep efficiency and reduce CO₂ cycling (Enick et al., 2012). The use of such foams is notably advantageous over simple fluids with similar nominal mobility because the foam exhibits a viscosity higher than that of the displaced fluids. This is because surfactant-stabilized foams reduce the mobility of gas in the higher-permeability zones, causing the displacing gas to divert into the formation areas that were previously unswept. Additional oil can be recovered from underswept areas. Given that the mobility of the foam in higher-permeability areas is reduced compared to that in lower-permeability zones, horizontal and vertical sweep efficiencies are possibly achieved (Cui et al., 2010).

Nanotechnology is already playing a crucial role in petroleum engineering (Chevalier and Bolzinge, 2013). Foam-aided enhanced oil recovery (EOR) can improve sweep efficiency by reducing CO₂ mobility (Farajzadeh et al., 2012). However, surfactant-based foams face challenges owing to surfactant adsorption on rock surfaces, necessitating constant regeneration and increasing raw material costs. Additionally, polymers struggle to withstand the salinity, pressure, and temperature of reservoirs. Nanoparticles offer an alternative solution to these challenges by modifying specific oil properties (Horozov, 2008). However, fly ash particles differ from mineral fly ash in terms of surface characteristics, exhibiting an irregular, porous, coke-like structure with unburned carbon content. Therefore, surface property and particle size modifications are required before using fly ash as a foam stabilizer in concrete. Studies have shown that fly ash can stabilize CO₂ foam, making it promising for EOR applications. Fly ash was divided into carbon-rich and carbon-lean fractions to evaluate the emulsion and foam stability. As a byproduct of coal-fired power plants, coal fly ash can serve as an economical nanoparticle source (Lee et al., 2015). Additionally, black rice husk ash, which is rich in silica, has shown potential to enhance foam stability and improve foam performance in oil recovery applications (Ahmad et al., 2021).

2 Background

Prediction, comparison, and improvisation points of black rice husk ash (BRHA) nanoparticles in enhanced oil recovery are very valuable for foam EOR. Their cost-effectiveness and hierarchical structure are notable in contrast to silica-based nanoparticles previously used for foam stabilization (such as mesoporous silica or fumed silica). This study aimed to investigate the main characteristics of BRHA and current silica nanoparticles, including particle size, surface charge, stabilization mechanism, foam half-life, and application conditions. The key points are as follows:

• The new nanoparticle, black rice husk ash, was tested for improving foam stability and efficiency under harsh reservoir conditions and high synthesis cost, where foam stability is typically poor.

• Black rice husk ash nanoparticles can change the wettability of reservoir conditions. For example, sodium (C14–16) olefin sulfonate (SOS)-functionalized silica nanoparticles can change the contact angle from 20° (oil-wet) to 173° (strongly water-wet).

• There is significant potential for the use of a composite flooding system composed of non-ionic surfactants and nanoparticles. For instance, the oil recovery rate is 16% greater than that of a water flooding system, where alkanolamide and nanoSiO₂ lower the oil–water interfacial tensions (IFTs) to an ultra- low value.

It has been demonstrated that partially hydrophobic silica nanoparticles produce stable air bubbles in an aqueous phase. The particles were primarily sized 10–30 nm, but aggregates considerably larger than this were present at the interface. In contrast, bubbles of the same initial size stabilized in portions that decreased very rapidly. If the particles were excessively hydrophobic, no stable bubbles were formed. It was observed that no hydrophobic particles tested exhibited high foamability (Sydansk et al., 2011). Foam stability in the presence of oil is crucial when using foam as a displacement fluid or for gas–oil ratio control in production wells. Core flood experiments have shown that oil can negatively impact foam stability when oil saturation exceeds 5%–20% Cui et al. (2010). As a tertiary recovery method, EOR involves injecting special fluids, such as miscible gas, chemicals, or thermal energy, and is not limited to a specific phase in a reservoir’s productive life (Enick et al., 2012). Nanotechnology involves the creation of functional materials, devices, and systems by manipulating matter at the nanoscale. Nanoparticles typically range from 1 to 100 nm in size (Sheng, 2013). Their presence forms a wedge film structure owing to interfacial force imbalances among the solid, oil, and aqueous phases, thereby increasing the film tension near the vertex. The spreading of nanofluids toward the wedge from the bulk solution is driven by the spreading coefficient, which exponentially increases as the film thickness decreases (Das et al., 2007; Hendraningrat et al., 2013). This study aimed to analyze the effect of black rice husks on specific characteristics, such as foam stability and foamability, under sand pack conditions. The findings indicate that the foam stability potential of black rice husk ash is highly promising and may enhance oil recovery in EOR.

3 Materials and methods

The black rice husk ash used in this study was sourced from a Japanese rice husk ash company. The treated rice husk ash is illustrated in Figure 1. The anionic foaming surfactant, sodium dodecyl benzene sulfonate (SDBS), was obtained from Sigma. The experimental setup included two 1.5-L cylinders for the mixed solution and one cylinder for CO. A sand pack measuring 30 cm in length and 2.5 cm in radius was used, and the sand and black rice husk ash were sieved using a 0.125 mm sieve. It was then filled with local white sand particles of 0.0125 mm. The high-pressure pump used to generate fluid pressure was a 100DX syringe pump, capable of operating at pressures up to 10,000 psi (690 bar).

Figure 1

Figure 1. Characterization of black rice husk: (a) raw black rice husk ash, screened sample; (b) ball milling treatment; and (c) treated rice husk ash.

Figure 1a presents the characterization of raw black rice husks and samples of black rice husk ash. Figure 1b presents the ball milling treatment process, and Figure 1c presents the treated rice husk ash.

For sample preparation, a 30 cm sand pack was filled with white sand. The black rice husk ash particles used in the experiment ranged from 10 to 100 nm. The sand pack was made airtight to prevent leakage and vacuumed for 45 min after filling. The weights of both dry and wet sand packs were recorded for the foam sand pack experiment. Porosity and permeability measurements were also conducted as part of the experimental procedure.

3.1 FT-IR—ball milling treatment

The zirconia tank containing the granules and grinding balls was placed in the ball milling device, which was set to rotate at 1,500 rpm. After 2 hours of milling, a sample of black rice husk ash was collected. The ash particles were separated using two sieves, and a particle sizer was used to determine their sizes. The surfaces and structures of the samples were analyzed using a scanning electron microscope (SEM). FT-IR analysis was primarily performed to qualitatively assess the starting materials and the produced black rice husk ash by identifying the characteristic peaks corresponding to different types of bonding. The typical FT-IR spectra of the starting materials, including black rice husk ash, ground granulated blast-furnace slag (GGBS), palm oil fuel ash, rice husk ash, metakaolin, and slag ash, exhibited peaks at approximately 3,400 cm⁻¹, 1,640 cm⁻¹, 1,175 cm⁻¹, 1,100 cm⁻¹, and 460 cm⁻¹. The spectra were baseline-adjusted and normalized prior to comparison. Multiple peak-fitting techniques were applied to closely monitor the prominent peak at approximately 1,000 cm⁻¹, which was used to quantify the amount of fly ash produced. The height (intensity) of the corresponding peaks was used for the quantitative analysis.

3.2 Microscopic visualization of oil recovery

The porous medium used for microscopic visualization was a glass micromodel with a pore size of 50–100 μm. Image analysis methodology: Images were captured using a confocal laser scanning microscope (CLSM) at ×20 magnification, and the foam bubble size and distribution were quantified using ImageJ software (Version 1.53t) with the Analyze Particles tool. The effects of temperature, gas, and viscosity reducer concentration on the behavior of liquid solutions in porous media were examined using various experimental designs. Black rice husk liquid was first prepared in a PVT sampler with a bubble-point pressure of 8.0 MPa to initiate the experiment. Heating and shaking were used to maintain a constant temperature. The ratio of oil to dissolved gas changed during the experiment; however, the bubble-point pressure remained constant at 8.0 MPa. The amount of dissolved gas in the oil decreased as the temperature increased. Both the ISCO and manual pumps were employed to simultaneously pressurize the interior and exterior of the micromodel to 8.5 MPa. The model was heated using a heating muff to achieve the desired temperature. The micromodel was then filled with the prepared liquid, and the inlet was sealed. The foam liquid was injected at a flow rate of 0.05 mL/min, and the backpressure was maintained at 8.5 MPa. Upon opening the outlet of the model, the pressure decreased at a rate of 40 kPa/min. The entire experiment was recorded on a camera for further analysis, as shown in Figure 2.

Figure 2

Figure 2. Microscopic visualization of the ash–liquid system in porous media: (a) measurement setup, (b) in the absence of oil and ash, and (c) in the presence of oil and ash.

3.3 Experiment for foam flooding

A 0.5 wt. % concentration of rice husk ash and SDBS surfactant was mixed with 1,000 mL of water. The mixture was stirred on a magnetic stirrer for more than 20 min. The experimental setup is illustrated in Figures 3a,b. Figure 3a shows the experiment conducted without a sand pack. Pressure pumps were connected to a CO₂ gas cylinder and a mixed solution of rice husk ash and SDBS surfactant via a connector, which also included a flow meter to monitor the flow rate. Foam generators were attached to produce foam for the experiment. Figure 3b depicts a setup similar to that in Figure 3a, with the addition of a sand pack connected for observation. A pressure meter was attached via a large connector to monitor the pressure during the experiment. The sand pack experimental design offers valuable insights into the foam lifespan and stability under sand pack conditions relevant to EOR. An oil field firm (Dongying, China) provided the oil. Oil was extracted from the unconsolidated sandstone reservoir of the oilfield. The oil viscosity of the black rice husk ash and SDBS surfactant was 40 mPa · s. Three core flood and three foam-flooding experiments were conducted to obtain the best results. The first experiment failed because of gas leakage at the connecting point, which was difficult to detect. After completing the sand pack experiments, the foaming mechanism was investigated further.

Figure 3

Figure 3. Sand pack experiment (a) without sand pack and (b) with sand pack.

4 Results and discussions

4.1 Structural and morphology characteristics of black rice husk ash

FT-IR analysis was performed to identify the initial components and bonding types present in the samples by examining their characteristic peaks. KBr pellets were prepared, and FT-IR spectra were recorded with baseline correction over the range of 4,000–400 cm⁻¹. A typical FT-IR spectrum of the starting ash material is presented in Figure 4. The broad peak at approximately 3,400 cm⁻¹ corresponds to the –OH asymmetric stretching and bending vibrations. The peak at 1,631 cm⁻¹ is attributed to the bending vibration of the –OH group. Bands induced by Si–O bonds appeared at 1,045 cm⁻¹. The most significant peak, known as the Si–O–T peak, appears in the 1,300–800 cm⁻¹ region, where T represents tetrahedral-bonded Si or Al. As shown in Figure 4b, this broad main peak consists of several distinct peaks assigned to Si–O–Si (found in quartz, mullite, and amorphous silica), Al–O–Al (alumina), and Si–O–Al bonds. The areas under the individual peaks were calculated to quantify their contributions. Figure 4a displays the different components of black rice husk ash, with colors representing the regions of the highest silica concentration. ZnO was measured at 10.352%, while the lowest observed component was SrO at 0.1%. The data confirmed that SiO₂ has a very high scale factor in black rice husk ash, highlighting its strong potential for applications requiring a high silica content.

Figure 4

Figure 4. (a) Observation percentage of the different components of black rice husk. (b) Important peaks for ash nanoparticles and their corresponding information.

The primary constituents of black rice husk ash, Si–O–Si and SiO₂, are represented by the absorption peaks at approximately 3,500 cm⁻¹, 1,200 cm⁻¹ and 900 cm⁻¹. The broad adsorption peak at approximately 1700 cm⁻¹ is attributed to the stretching vibrations of adsorbed water and hydroxyl groups on the surface of the black rice husk ash particles. The presence of carbonate impurities in black rice husk is indicated by the adsorption peaks at approximately 1,450 cm⁻¹ and 870 cm⁻¹, which are associated with C–O stretching and bending vibrations. The remaining organic components are reflected by the absorption peaks at 1,500 cm, which correspond to vibrations in the organic matter. The most prominent peak in the FT-IR spectrum is the Si–O–T peak, sometimes referred to as the primary Si peak, as reported by Karkevandi-Talkhooncheh et al. (2018).

4.2 Particles size analysis

The mechanically treated black rice husk ash and particle size assessment are shown in Figure 5. The initial black rice husk ash had a particle size of 100 μ, but mechanical treatment caused it to decrease to a size between 80 and 250 nm. Black rice husk ash also showed a notable decrease in the particle size. The overall volume was significantly affected. The breakdown of larger black rice husk ash particles into smaller particles was linked to particle size reduction. SiO₂ is the primary component of black rice husk ash, which also contains significant amounts of calcium, iron, and aluminum oxides. Amorphous quartz, mullite, and crystalline phases are the forms of SiO₂. The active black rice husk ash was smaller, as shown in Figure 5.

Figure 5

Figure 5. Particle size of black rice husk ash.

Additionally, red and blue peaks were observed, which correspond to microscopic nanoparticles within the 10 nm range. This decrease in the black rice husk ash size caused by ball friction is consistent with existing research. Bulk fluctuations during mechanical activation can drastically change the reactive nature of solids, resulting in phase transitions.

4.3 Foam generation and stabilization

Initially, the experiment was conducted without a sand pack to evaluate the lifespan and foaming ability of the foam. The foam was generated using a foam generator. The gas pressure was maintained at 1.5 MPa for the first 10 min and then increased to 5.5 MPa between 10 and 20 min, as shown in Table 1.

Table 1

Table 1. Pressure observation of foam generation.

The flow rate was set to 1 mL/min, and the foam life was observed in a 150 mL flask. The initial foam height was 100 mL, and the foam stability was recorded at different intervals. The total foam stability lifetime was 42 min, as shown in Table 2. Initially, with a foam height of 100 mL, the foam life was 17 min. However, when the foam height decreased to 70 mL, the foam life shortened to only 5 min, with poor stability. At this height, the foam lamellae disintegrated rapidly, and as the foam volume fraction increased, the lamella height continued to decrease. Interestingly, when the foam height reached 65 mL, the foam life increased again and stabilized for 20 min owing to the early strength of the foam.

Table 2

Table 2. Foam life in different time ranges.

4.4 Black rice husk CO₂ sand-pack foam experiment

A sand pack experiment was conducted after the black rice husk ash demonstrated promising foam stability. This experiment aimed to understand the foam behavior under sand pack conditions. The parameters of the sand pack experiment are presented in Table 3. The dry sand pack weighed 2,744.9 g before vacuuming, and after vacuuming, the wet sand pack weighed 3,124.4 g. The study examined the effect of black rice husk ash nanoparticles on foam stability, with particularly focus on the temperature tolerance of aqueous CO₂ foam. Key parameters measured included the foam’s half-life of liquid drainage and its initial foam volume at various temperatures. The results showed that the initial foam volume increased with temperature up to a point and then declined as the temperature increased further. To evaluate the flow characteristics and EOR performance of different foam systems, sand pack foam flooding experiments were conducted across a range of temperatures. These tests also demonstrated how the injection fluid volume influences sand pack pressure. Nanosilica particle-stabilized CO₂ foam in porous media was studied, and it was concluded that stable CO₂ foam can be generated with nanoparticle concentrations between 4,000 ppm and 6,000 ppm, using commercially available silica nanoparticles. However, foam generation by nanoparticles was later found to be affected by reservoir pressure, salinity, and temperature. The stability and behavior of CO₂ nanofoam depend on flow conditions (Wasan, 2007; Nikolov et al., 2013). CO₂ foam can effectively control CO₂ mobility and surfactant behavior, thereby improving reservoir sweep efficiency. Nanoparticles enhance the performance of CO₂ foam under harsh reservoir conditions (Espinosa et al., 2010). Numerous studies have shown that nanoparticle-stabilized foams maintain their stability for longer periods, even under extreme conditions (Binks et al., 2008).

Table 3

Table 3. Sand pack parameters.

The gas pressure was slightly higher than that of the pure surfactant solution, which could be attributed to the fact that a fraction of the SDBS surfactant was adsorbed on black rice husk nanoparticles. The pressure of liquid was observed in different ranges; the liquid outcome drainage changed significantly with the addition of black rice husk ash at different temperatures. The stability of foam without a sand layer was high; it degraded with increasing temperatures because liquid drainage and CO₂ diffusion became more pronounced. During the past few years, nanotechnology has become a noticeable aspect of the EOR sector. Solid particles can stabilize emulsions without surfactants (Li et al., 2016). Interfacial tension is decreased by the adsorption of nanoparticles at the gas–liquid interface. Second, the interfacial viscoelastic modulus is increased by the nanoparticles (Li et al., 2019). The suitability of fly ash (FA) and GGBS for concrete structures was investigated at different curing temperatures. At different temperatures, the compressive strength, heat of hydration, and open porosity of SCC specimens were evaluated. Pulverized fuel ash, silica fumes, and fine limestone powder were the additions combined with raw rice husk ash. In Table 4, the pressure of the liquid was observed at the beginning of the experiment. For the first 5 min, the liquid started to come out, and after 35 min, an oil–liquid effluent of 25 mL was observed. In the mid 15 min, the outcome of liquid was 5 mL. This indicated that the water advance occurred in the core. Following the water breakthrough, oil production was gradually observed at the same rate in mL. The viscosity of the fluids resulted in a high flow challenge in porous media, resulting in a large differential pressure when flooding was performed. The differential pressure of flooding at 650 kPa was lower than in the flooding experiments, as shown in Table 4. This was caused by the viscosity of oil and foams at the level of temperatures. The flooding differential pressure correlated well with the viscosity of foam systems. The maximum differential pressure during black rice husk foam flooding increased slightly toward the end, and the total liquid effluent was 50 mL, comprising 25 mL of water and 25 mL of oil. It demonstrates how the significant potential silica in rice husk ash influenced the behavior of foam life and height at concentrations of 100 mL and 65 mL. Black rice husk is a functional nanoparticle for foam stability. The mechanical characteristics of high-strength concrete with varying amounts of rice husk ash substituted for regular Portland cement (Kishore et al., 2011).

Table 4

Table 4. Liquid pressure flow.

Depending on the quality of the foam and the injection speed, it can resist foam flow. They claimed that there was a shear-thinning characteristic between the injection speed and foam mobility. The viscosity of the foam increased as the shear rate decreased. It has been claimed that improving the quality of foam can enhance its perceived viscosity. Nonionic surfactants and hydrophilic nanoparticles work together to stabilize CO₂ foam (Li et al., 2019). Nanoparticles are used as a form of EOR which alters the characteristics of oil to help in freeing the stuck oil. (Li et al., 2016). The particles have been shown to act as stabilizers in a variety of foam and emulsion systems in (collection emulsions) and can be attractive to the environment as alternatives to conventional surfactants (Mansaray and Ghaly, 1998). However, compared to their effects in emulsions, the action of particles in foam stabilization is inherently more complicated (Abedini and Torabi, 2014). One significant improved oil recovery technique that has shown promise in pilot and experimental investigations is foam flooding using foam-assisted water-alternating gas (FAWAG). The goal of this study was to track the movement of the foam front after injection into a porous medium. Recent studies have shown a significant increase in oil recovery when using foam compared to water, with foam achieving an average of 30% higher recovery than water alone. Foam in porous media prevents fingering during oil displacement, resulting in a more stable displacement—a desirable outcome for several processes, including soil remediation techniques and EOR (Osei-Bonsu et al., 2016; Khan et al., 2024). Foam is generated by mixing different fluids, and the properties of each fluid influence the overall characteristics of the foam. The fluids used in this study included brine (30,000 ppm), surfactant at concentrations of 0.1 wt%, 0.5 wt%, and 1 wt%, and Baronia oil and gas. Injection tests were performed on an Idaho core using a test rig, as shown in Figure 5. The displacement test rig, as shown in Figure 6 comprised several components, including a confining chamber, a core holder measuring 12 in length and 1.5 in diameter, an external pump with a capacity of 500,000 cc, four accumulators, a furnace with a maximum temperature of 110 °C, and a confining pressure system with a maximum pressure of 150 psi. Additional equipment included pressure indicators, three- and two-way valves, a liquid container, an LCR meter (Keithley), and four electrodes. The goal of low-salinity water flooding (LSWF) is to modify the interactions between fluids and rocks by altering wettability and reducing IFT (Malakoutikhah et al., 2024).

Figure 6

Figure 6. Displacing rig and flow chart.

4.5 Water and residual oil saturation

Figure 7 shows a comparison of the water saturation reduction after water and foam flooding. Residual oil saturation is a key parameter in the design of effective foam-flooding processes. The results, depicted in Figure 7b, compare the residual oil saturation at three different surfactant concentrations. The residual oil volume was calculated by subtracting the produced oil volume (effluent) from the initial volume of oil injected during forced displacement. The results indicate that the residual oil saturation is influenced by the surfactant concentration used in the experiments.

Figure 7

Figure 7. Water saturation and oil saturation: (a) water saturation at different surfactant amounts after water and foam flooding, (b) oil saturation after foam flooding, and (c) oil recovery for water and foam flooding.

Strong emulsions reduce the oil recovery factor because their large droplet sizes block small pores, resulting in only partial displacement of residual oil, thus lowering the overall recovery. Such strong emulsions are detrimental to the improvement of recovery during foam flooding. The introduction of surfactants affects production performance by modifying the pore space behavior, and their addition can enhance oil recovery. Overall, the results demonstrate that foam flooding achieves higher oil recovery than water flooding, and selecting the appropriate surfactant concentration is a critical factor for optimizing foam flooding performance.

4.6 Validation of the models: model predicted plot

The subsequent prediction models accurately represented the actual data, as indicated by the coefficient of variation and foam life measured after 5 min for each foam composition. This suggests that the proposed models are effective for assessing the foaming ability of rice husk ash. Similar approaches can be applied to other types of solid particles, such as iron oxides and alumina. For example, alternative anionic surfactants include sodium alkyl sulfates with both shorter and longer hydrocarbon chains than SDS. Additionally, other organic solvents that are moderately polar compared to ethylene glycol (EG) should be considered. This study employed nano-graphite (NG) as a foam stabilizer to improve the stability of regular foam under high-temperature conditions (Zhao et al., 2021). The statistical significance of the effects of the process parameters was evaluated using p-values, with a p-value of 0.0003 indicating that the model’s significance represented a good fit between the experimental and actual data (Figure 8). The analysis of the residuals, presented in Figures 9, 10, shows that the errors were normally distributed. Figure 9 illustrates the relationship between the experimental data residuals and the residuals at the equilibrium states of foam life and foamability. Specifically, (a) the predicted plot residuals, which are externally studentized, are displayed with 80% simultaneous limits (Bonferroni) in blue and individual limits. (b) The residual represents the difference between the observed and predicted values, which varies according to the input variables. To standardize these differences, an adjustment was applied by dividing the residual values by the standard error of the residuals. This approach provides a uniform assessment, particularly when identifying potential data outliers.

Figure 8

Figure 8. Half-life predicted.

Figure 9

Figure 9. Residual by the predicted plot.

Figure 10

Figure 10. Studentized residuals.

The analysis revealed that rice husk ash positively impacted foam life and foamability, with the residual confirming this improvement. Surfactant A exhibited strong foamability and stability, where the foam half-life initially increased and then decreased with increasing surfactant concentration.

The optimal foaming agent concentration used in this experiment was 0.15 wt%. Similarly, the addition of nanoparticles improved the foam stability. As the concentration increased, the foam half-life initially increased and then decreased. The nanoparticles demonstrated optimal performance as a foam stabilizer at a concentration of 0.05 wt%. The zeta potential was moderately affected by the anionic surfactants. Their negative zeta potential increased (Kosmulski et al., 2022).

4.7 Model validation of fit summary

A fit summary, as presented in Tables 5, 6, was utilized to evaluate the model’s validity. The model demonstrated its accuracy, indicating a high level of agreement between the model’s predictions and the actual data. This result confirms that the experimental design was satisfactory for predicting foamability and foam stability. The model also exhibited a statistically significant probability (prob > F = 0.0003), affirming the robustness of the experimental methodology. The proposed design of experiment (DOE) approach enabled accurate modeling with comprehensive coverage of the experimental trials. The residual variance, measured by the root mean square error (RMSE), further supports the model’s predictive reliability in assessing the effectiveness of rice husk ash on foamability and foam stability. The data fitting quality was assessed using the determination coefficient (F). In this study, the foam’s determination coefficient demonstrated that the proposed second-order polynomial model effectively captured the experimental responses. The accuracy of the estimated parameters was quantified by the standard error, which is calculated as the square root of the variance divided by the number of observations. The model also tested the hypothesis that the lack of fit error equals 0. One way to quantify the prediction error is through the standard error estimate, where a larger standard error indicates a poorer fit of the regression model to the actual data. Consequently, the model’s low standard error further supports its reliability and predictive capability.

Table 5

Table 5. Parameter estimates.

Table 6

Table 6. Effect tests.

The impact of rice husk ash on foaming capacity after a 5-minute break was investigated, revealing that rice husk ash is the primary factor influencing foam characteristics. Notably, the presence of rice husk ash had a minimal effect on foamability when assessed without a sand pack. The predicted equation indicates that varying the rice husk ash concentration from a low to a high level slightly reduces foam life. However, the overall effect of rice husk ash remains positive as increasing the concentration of rice husk ash nanoparticles generally enhances foam life. It was also observed that the presence of a sand pack does not significantly alter the foam’s performance when rice husk ash is varied. This indicates that the foam’s stability remains consistent irrespective of changes in rice husk ash concentration in the presence of a sand pack. Table 6 presents the evaluation of quadratic terms for collective factors, highlighting the significant interaction between surfactants and rice husk ash. This interaction significantly affects both stabilization and outcome rates. The interaction effect of rice husk ash demonstrated that maintaining a constant foam life can sometimes be achieved by increasing the surfactant concentration, suggesting a synergistic relationship between these components.

4.8 Interaction profiles

The interaction effects between foam life and stability are shown in Figure 11. These interactions are represented within the foam half-life rim, highlighting how the combination of rice husk ash and surfactant positively influenced foam longevity. The results demonstrate that the interaction between these two components enhances the foam life, indicating a synergistic effect that improves the overall foam stability. The prediction profiles for different parameters illustrate the foam life and stability under sand pack conditions as a function of the three additive parameters considered in the DOE. These profiles are presented in Figure 10, which specifically displays the effectiveness of oil, surfactant, and rice husk ash nanoparticle combination on foam life after 3 minutes. The time–range profiles highlight the ultimate efficacy of rice husk ash nanoparticles. As shown in Figure 10, the foam life rate exhibited a slight decrease over the 7-minute range. However, a notable increase in foam life was observed within the 3- to 5-minute range. In the mid-time range, the impact of both rice husk ash and surfactant was found to be statistically insignificant, indicating that their interaction did not significantly influence foam life during that period.

Figure 11

Figure 11. Interaction profiles.

5 Microscopic visualization of oil recovery

The same sand pack experimental liquid solution, consisting of SDBS surfactant, black rice husk ash, and oil, was further analyzed using microscopic imaging and rheometer measurements (Anton Paar, MCR 302, Austria). The oil’s viscosity was assessed over a temperature range of 40 °C–60 °C, and the contents of the oil recovery components were determined according to the NB/SH/T 0509-2010 standard. The analysis revealed that the oil sample contained 8.34 wt% of asphaltene, resin, and aromatics, indicating a substantial presence of both resin and asphaltene. These components are critical in influencing the oil’s viscosity and stability, particularly in the context of EOR applications. In the PVT sampler, the fluid liquid was generated at a bubble-point pressure of 8.0 MPa. The selected temperature was set to initiate heating and shaking. During the process, the dissolved gas-to-oil ratio remained variable, while the bubble-point pressure was consistently maintained at 8.0 MPa. Notably, the ratio of dissolved gas to oil decreased as the temperature increased. The micromodel was positioned in a micromodel holder, and an ISCO pump was used for testing. Both the ISCO pump and a manual pump were used to pressurize the interior and exterior of the model to 8.5 MPa, respectively. The required temperature was achieved by heating the model using a heating muffler. The resulting liquid was injected into the microscopic model. After injection, the inlet of the model was closed, and the flow rate was set to 0.05 mL/min to ensure controlled fluid displacement within the micromodel.

5.1 Initial stage

The back pressure was set to 8.5 MPa, which exceeded the bubble-point pressure. Once the model’s outlet was opened, the pressure was gradually reduced at a rate of 40 kPa/min, and the experiment was recorded using a high-speed camera. Phase 1, single-phase condition: Initially, the bubble-point pressure in the visual model ranged from 8.0 to 8.5 MPa. At this stage, no gas release was observed as all the gas remained dissolved in the liquid, representing a single-phase state. Phase 2, gas evolution and dispersion: As the experiment progressed and the pressure decreased below the bubble point, gas began to escape from the oil, forming tiny dispersed bubbles (see Figure 12a). Initially, the number of bubbles was low, and they remained mostly stationary and small. However, as the pressure continued to decrease, the volume of the tiny bubbles gradually increased. Phase 3, bubble mobility: When the pressure decreased to approximately 6.5 MPa, the bubbles started moving freely within the pore space. Despite this mobility, image analysis indicated that movement was somewhat restricted, with a measured velocity of 10.6 m/s. This limited movement can be attributed to the high viscosity of the oil, which hinders the free flow of bubbles within the porous medium.

Figure 12

Figure 12. Microscopic visualization of foam: (a) initial stage, (b) middle stage, and (c) late stage.

During the foam flow through the glass model, bubble coalescence was observed, where multiple small bubbles merged to form a single larger bubble. This phenomenon indicates the instability of smaller bubbles, leading to their aggregation into a more stable and larger structure.

5.2 Middle stage

The experiment entered the middle stage when the pressure decreased to approximately 4.3 MPa. At this point, more gas was released from the black rice husk ash foam oil–liquid mixture, resulting in an increase in the bubble volume. The bubbles also became larger in diameter, eventually exceeding the pore size. As shown in Figure 12b, the foam remained stable, with the gas continuing to exist as dispersed bubbles rather than forming a continuous gas phase. During this stage, the bubble velocity increased significantly compared with that in the early stage, reaching approximately 786.1 m/s. As the bubbles move through the pores, they deform, and larger bubbles can be shared by skeletal particles and split into two smaller bubbles. These smaller bubbles then travel through two separate porous channels on either side of the skeletal particles. When these smaller bubbles come into contact, their liquid films gradually merge, leading to coalescence into larger bubbles. This dynamic interaction between bubble formation, division, and merging highlights the complexity of foam flow in porous media. In the middle stage of foam flow, the liquid tends to be thermodynamically stable because bubbles spontaneously coalesce to minimize the interfacial area and energy of the dispersion system. This stability is primarily due to the high pressure, which is correlated with more stable bubbles. At this stage, the interfacial tension was relatively low, making bubble coalescence less likely. However, the high velocity of the liquid can cause large bubbles to break into smaller bubbles, driven by the pressure difference. In this context, bubble division predominates, while spontaneous coalescence acts as the opposing force. Therefore, the balance between division and coalescence determines the foam’s structure during this stage. Bulk stability tests and macroscopic analyses have demonstrated the positive effect of nanoparticles (NPs) with moderate hydrophobicity and optimal concentrations on stabilizing interfaces between immiscible fluids. However, the pore-scale mechanisms that translate these stabilizing effects into in situ behavior in porous environments remain insufficiently understood. This challenge arises because NPs can accumulate, and interfaces are continuously formed and broken. During the bubble division process, a large bubble divides into two smaller bubbles as it approaches two adjacent pores. This splitting mechanism was observed during foam movement through the glass model, where the bubble entered two separate pores, resulting in division. In another scenario, when the bubble becomes elongated while passing through a pore, it can split into several smaller bubbles. This phenomenon highlights the dynamic nature of bubble division as foam flows through the porous medium.

5.3 Last stage

In the final stage of foam flow, the majority of the gas is released from the interfaces between particles and bubbles, as shown in Figure 12c. This occurs as the pressure decreases to a low level, causing the displacement energy to dissipate gradually. The bubble velocity at this stage is significantly reduced, calculated at 16.3 m/s. During this phase, the coalescence velocity of bubbles becomes greater than their division velocity, resulting in a decrease in the number of bubbles. This phenomenon is attributed to the high interfacial tension and the low stability of the mixed liquid. When the pressure decreases to 1.4 MPa, which is below the pseudo bubble-point pressure, a continuous gas phase begins to form, marking the transition from dispersed bubbles to a more stable gas phase. Bubble deformation occurs when the bubble elongates and reshapes as it moves through a pore. After passing through the pore, surface tension restores the bubble to its spherical shape, significantly impacting gas flow by increasing gas-phase resistance. This phenomenon reduces gas mobility, highlighting the important role of surface tension in foam behavior within porous media. These experiments specifically examined how foam bubbles deform in response to pressure changes as they navigate through porous structures. The maximum change in surface tension can be calculated using the proposed model, which accurately predicts behavior of nanofluids with both increasing and decreasing surface tension. Moreover, the model enables the calculation of the nanoparticle concentration at which surface tension stabilizes, indicating nanoparticle saturation within the nanofluid. Among the available models, the proposed one most effectively represents the surface tension dynamics in nanofluids. For foam to be successfully used for subsurface applications, nanoparticle surface modification is essential (Chaudhry et al., 2024). It was investigated whether fly ash could create stable foam. Additionally, the hydrophilicity of fly ash was examined by tracking the sedimentation time (Ahmad et al., 2017).

6 Oil recovery and bubble generation factors

Based on bubble diameter, number of bubbles, and velocity, the experiment can be categorized into four stages. In the early stage, there are three types of bubbles: few tiny bubbles, many modest, uniform bubbles, and no bubbles at all. During this phase, a continuous gas phase is observed, along with numerous small, homogeneous bubbles in the later stage. One of the key characteristics of the liquid foam phase is the occurrence of multiple bubble division, coalescence, and distortion processes. These interactions primarily take place within the liquid phase of the foaming agents, which consists of particles and oil.

• Effect of temperature on bubble velocity and oil recovery: The bubble velocity and oil recovery factor increase significantly as the temperature increases. This occurs because viscosity decreases with higher temperatures.

• Impact on bubble stability: Despite the increase in velocity, bubble stability decreases as the temperature increases. Experimental results indicate that the mixed liquid solution performs better at 80 °C compared to 60 °C and 100 °C. Therefore, 80 °C is considered the optimal temperature for achieving a balanced effect.

• Optimal temperature for bubble stability: A comprehensive analysis suggests that maintaining the temperature at approximately 80 °C provides the optimal enhancement of bubble stability within the mixed liquid.

• Influence of viscosity reducer content: Increasing the viscosity reducer content lowers the viscosity of the black rice husk ash foaming agents and oil mixture. However, despite a notable increase in bubble velocity, the stability of the bubbles decreases. When the liquid viscosity is high, bubble formation becomes difficult.

In porous media, oil-based foam primarily flows through the formation of bubbles, which occurs through two mechanisms. Bubble division at pore gorge: The most common method involves a large bubble entering two adjacent pores. As the bubble reaches the pore gorge, it splits due to capillary resistance, creating two smaller bubbles, one in each pore. This process accounts for the majority of bubble formation. Bubble stretching and splitting: A less common method involves stretching a large bubble through a narrow opening until it divides into two smaller parts. This mechanism is less frequent in oil-based foam flow. According to the Young–Laplace equation, bubbles with a smaller diameter exhibit higher pressure, which increases CO₂ dissolution within the thin film formed by these tiny bubbles.

7 Conclusion and recommendation

The following are the key findings based on the effectiveness of black rice husk ash nanoparticles for EOR.

• Foam volume and sand pack influence: without a sand pack, the initial foam volume of black rice husk ash foam is relatively high. However, in the presence of a sand pack, the volume decreases. Adding black rice husk ash liquid at a modest concentration can optimize foam volume across various temperatures. The foam drainage half-life is significantly influenced by incorporating black rice husk ash at different liquid flow rates.

• Viscosity and bubble stability: the addition of black rice husk ash foaming agents to oil reduces its viscosity. Despite a significant increase in bubble velocity, the stability of the bubbles decreases. However, these tiny foam bubbles exhibit longer stability compared to the initial phase.

• Foam stability in sand pack conditions: under sand pack conditions, black rice husk ash positively impacts foam stability and strength both before and after flooding. However, the foam lifetime becomes limited after sand pack flooding.

• Oil recovery enhancement: injecting black rice husk ash foam into a sand pack increases oil recovery. Microscopic studies and recovery points indicate that the silica nanoparticles in black rice husk ash contribute significantly to foamability and stability.

• The potential for EOR is discussed. The high silica content in black rice husk ash enhances foam stability and strength during foam flooding, making it a promising nanoparticle for EOR.

The following further studies are required on black rice husk ash nanoparticles.

• Testing under varying permeabilities: the performance of black rice husk ash nanoparticles can be further evaluated under high- and low-permeability conditions to assess their effectiveness in different reservoir environments.

• Evaluation with high-viscosity oil: future studies could challenge black rice husk ash nanoparticles using high-viscosity oil to evaluate their potential for foam stability and their role in EOR under challenging fluid conditions.

• Chemical treatment of black rice husk ash: chemical treatments can be applied to black rice husk ash to examine the effects of chemical modifications on its foam stability and foamability, thereby elucidating the influence of chemical reactions on its performance in EOR processes.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author contributions

IA: Writing – review and editing, Conceptualization, Writing – original draft. WZ: Project administration, Writing – original draft. TW: Formal Analysis, Writing – original draft. JK: Methodology, Writing – original draft. SI: Writing – original draft, Funding acquisition.

Funding

The authors declare that financial support was received for the research and/or publication of this article. This research was funded by the 2024 Leading Scientific and Technological Innovation Talent Team: Shale Oil Geology and Engineering Integrated Fracturing and Prevention Technology Innovation Team (grant number: CYCX24015) and the Nazarbayev University Collaborative Research Program 2025-2027611 with project reference number 111024CRP2014.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The authors declare that no Generative AI was used in the creation of this manuscript.

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