Innovative Role of Magnesium Oxide Nanoparticles and Surfactant in Optimizing Interfacial Tension for Enhanced Oil Recovery

Abstract

Enhancing oil recovery efficiency is vital in the energy industry. This study investigates magnesium oxide (MgO) nanoparticles combined with sodium dodecyl sulfate (SDS) surfactants to reduce interfacial tension (IFT) and improve oil recovery. Pendant drop method measurements revealed a 70% IFT reduction, significantly improving nanoparticle dispersion stability due to SDS. Alterations in Zeta Potential and viscosity, indicating enhanced colloidal stability under reservoir conditions, were key findings. These results suggest that the MgO-SDS system offers a promising and sustainable alternative to conventional methods, although challenges such as scaling up and managing nanoparticle–surfactant dynamics remain. The preparation of MgO nanofluids involved magnetic stirring and ultrasonic homogenization to ensure thorough mixing. Characterization techniques included density, viscosity, pH, Zeta Potential, electric conductivity, and electrophoretic mobility assessments for the nanofluid and surfactant–nanofluid systems. Paraffin oil was used as the oil phase, with MgO nanoparticle concentrations ranging from 0.01 to 0.5 wt% and a constant SDS concentration of 0.5 wt%. IFT reduction was significant, from 47.9 to 26.9 mN/m with 0.1 wt% MgO nanofluid. Even 0.01 wt% MgO nanoparticles reduced the IFT to 41.8 mN/m. Combining MgO nanoparticles with SDS achieved up to 70% IFT reduction, enhancing oil mobility. Changes in Zeta Potential (from −2.54 to 3.45 mV) and pH (from 8.4 to 10.8) indicated improved MgO nanoparticle dispersion and stability, further boosting oil displacement efficiency under experimental conditions. The MgO-SDS system shows promise as a cleaner, cost-effective Enhanced Oil Recovery (EOR) method. However, challenges such as nanoparticle stability under diverse conditions, surfactant adsorption management, and scaling up require further research, emphasizing interdisciplinary approaches and rigorous field studies.

1. Introduction

Enhanced Oil Recovery (EOR) techniques are increasingly critical as conventional oil extraction methods, including primary and secondary recovery, near their operational limits in terms of efficiency [1,2]. These methods leave a substantial proportion of oil unrecovered within reservoirs, posing significant challenges for meeting rising global energy demands [3]. Consequently, the petroleum industry has prioritized the development of advanced methods to access and extract this remaining trapped oil. EOR serves as a pivotal phase in this pursuit by employing various strategies to modify the physical and chemical properties of reservoir fluids and rocks, thereby mobilizing residual oil [4].

Among the most prevalent EOR methods are chemical injection, thermal recovery, and gas-based techniques, each with distinct mechanisms and applications [5]. However, these methods face challenges concerning environmental sustainability and economic feasibility. For instance, the use of surfactants and polymers has been associated with environmental degradation and elevated operational costs [6,7]. These limitations highlight the pressing need for innovative and efficient EOR solutions that are both economically viable and environmentally friendly [8].

A critical factor in many EOR processes involves reducing the interfacial tension (IFT) between the displacing fluid and the trapped oil. By lowering the IFT, the capillary forces that trap oil within reservoir pores can be mitigated, thereby enhancing oil mobility. In particular, the following aspects are considered:

• Capillary Forces: The interfacial tension (IFT) between the displacing fluid and the oil strongly influences the capillary forces that trap the oil in the pores of the reservoir rock.
• Mobilization of Trapped Oil: Reducing the IFT lowers the capillary forces, which in turn enhances the mobility of the trapped oil. This reduction in IFT promotes the coalescence of oil droplets and allows the displacing fluid to sweep more oil toward the production well.
• Improved Sweep Efficiency: By improving the fluid’s ability to displace oil, the overall sweep efficiency is increased, leading to higher oil recovery factors.

Nanotechnology has emerged as a promising solution to overcome these limitations in EOR applications [9]. Nanoparticles, characterized by their high surface-area-to-volume ratio, exhibit unique physical and chemical properties that enable superior interactions with reservoir fluids and rock surfaces [10]. Additionally, their nanoscale dimensions allow them to traverse the porous structures of reservoirs, potentially accessing regions that are inaccessible to conventional agents [11]. Over the past decade, silica-based nanoparticles have received significant attention for EOR applications, demonstrating promising results in altering the wettability of reservoir rocks and reducing interfacial tension (IFT) [12,13].

Despite these advancements, diverging hypotheses exist regarding the effectiveness of different nanoparticle types. While silica nanoparticles have shown success, some studies suggest that metal oxide nanoparticles, such as magnesium oxide (MgO) and aluminum oxide (Al₂O₃), may offer superior results [14,15,16]. Other metal oxide nanoparticles, such as zirconium dioxide (ZrO₂), cerium oxide (CeO₂), titanium dioxide (TiO₂), zinc oxide (ZnO), and iron oxide (Fe₂O₃), exhibit unique properties that make them excellent candidates for EOR [17,18].

Recent studies have highlighted the potential of these metal oxide nanoparticles to enhance oil recovery via multiple mechanisms and formulations [19,20]. For example, MgO nanoparticles have demonstrated particular efficacy in reducing fine migration by modifying surface properties, a critical factor in maintaining reservoir permeability and oil flow [21,22]. Similarly, Ogolo et al. [23] explored the role of metal oxide nanoparticles in mitigating clayey fines migration, reporting that aluminum oxide nanoparticles could immobilize migrating fines by influencing reservoir pH levels. Nonetheless, challenges persist, including nanoparticle agglomeration, which can lead to pore blockage and compromise permeability, as observed by [9]. This finding, however, contrasts with evidence suggesting challenges in the stability and dispersion of such nanoparticles under reservoir conditions [18].

Building upon this context, this study aims to evaluate the potential of MgO nanoparticles, both independently and in conjunction with an SDS surfactant, to reduce IFT and improve oil recovery. SDS is hypothesized to enhance nanoparticle dispersion stability, enabling uniform distribution at the oil–water interface. By combining MgO nanoparticles with SDS, this study explores a synergistic approach to optimizing nanoparticle performance, increasing stability, and maximizing oil recovery under reservoir conditions. This investigation seeks to address critical knowledge gaps in the field, offering insights that contribute to the broader goal of achieving sustainable and efficient EOR technologies.

2. Materials and Methods

2.1. Nanoparticles and Base Fluids

This study employed high-purity MgO nanoparticles, supplied by MKnano (MK Impex Corp., Mississauga, ON, Canada), characterized by its specific surface area, bulk density, and purity (

Table 1. Properties of used materials.

Properties	MgO Nanopowder	SDS
Specific surface area (m2/g)	90	N.A
Bulk density (g/L)	100–150	490–560
Average molecular weight (g/mol)	40.3	288.38
Chemical formula	MgO	CH3(CH2)11OSO3Na
Purity	>99.9%	>99.9%

). To verify the characteristics of the MgO nanoparticles used in this study in terms of the purity and nanoscale size, additional characterization was performed. Dynamic Light Scattering (DLS) was employed to determine the particle size distribution, while X-ray Diffraction (XRD) analysis verified the crystalline structure and composition. The results demonstrated that the MgO nanoparticles are within the expected size range and exhibit high purity, as illustrated in Figure 1. These findings validate the suitability of the nanoparticles for the intended applications. Synthetic brine was prepared by dissolving 3.0 wt.% sodium chloride (NaCl) in deionized water, simulating reservoir salinity (approximately 30,000 ppm). The oil phase used in all experiments was paraffin oil, selected for its stable and reproducible properties. SDS, sourced from Sigma Aldrich (St. Louis, MO, USA), was used as a stabilizing agent in nanofluid preparations.

2.2. Instrumentation and Characterization Methods

2.2.1. Density and pH Measurements

Density was measured using ISOLAB 50 mL pycnometers (ISOLAB Laborgeräte GmbH, Eschau, Bavaria, Germany), ensuring high precision in mass-to-volume calculations. The pH and surface conductivity of the prepared systems, including brine, nanofluids, and surfactant-enhanced nanofluids, were measured with a Hach IQ240 digital pH meter (Hach Company, Loveland, CO, USA) under ambient conditions.

2.2.2. Ultrasonic Mixing

Consistent nanoparticle mixing and dispersion were achieved using the Sonics Vibracell VCX 750 Ultrasonic Homogenizer (Sonics & Materials, Inc., Newtown, CT, USA), operated at 50–80% amplitude with a power output of 750 watts. Additional mixing during preparation was facilitated by an IKA RCT Basic magnetic hot plate stirrer (IKA-Werke GmbH & Co. KG, Staufen, Germany).

2.2.3. Zeta Potential Analysis

The Malvern Zetasizer Nano ZS (Malvern Panalytical Ltd., Worcestershire, UK) was employed to evaluate nanofluid stability. This instrument measures Zeta Potential, electric conductivity, and electrophoretic mobility, providing insights into nanoparticle interactions and dispersion stability. High absolute Zeta Potential values signify greater nanoparticle stability due to strong electrostatic repulsion.

2.3. IFT Measurements

IFT was measured using the Core Lab (Tulsa, OK, USA) “Temco” Pendant Drop IFT-10-P system, capable of replicating reservoir conditions at pressures up to 10,000 psi and temperatures up to 350 °F. Pendant drop formation was captured using an 8 MP HD CCD camera, and IFT values were calculated using Axisymmetric Drop Shape Analysis (ADSA) software (https://www.ramehart.com/diadv.htm accessed on 6 January 2025). This system ensures precise measurements (uncertainty: ±0.2–0.5 mN/m), validated in prior studies [24]. This approach enables accurate characterization of fluid interactions (IFT) under reservoir conditions. Figure 2 and Figure 3 show the schematic of the IFT system and measurements using the Pendant drop method, respectively.

2.4. Research Method

A comprehensive overview of the experimental procedure followed in this study is summarized in Figure 4. The experimental procedure flowchart systematically outlines the preparation, characterization, and IFT measurements of the fluids investigated, including the base fluid (synthetic brine), nanofluids, and surfactant nanofluids. The figure highlights the critical steps in the process, such as the assessment of fluid density, viscosity, pH, Zeta Potential, and electrophoretic mobility, which are key parameters for evaluating the physical and chemical behavior of fluids. Additionally, it illustrates the focus areas of the IFT measurements, emphasizing the effects of nanofluid concentrations and the surfactant (SDS) on IFT reduction.

2.4.1. Nanofluid Preparation and Characterization

Nanofluid Synthesis: MgO nanofluids were synthesized at varying concentrations (0.01, 0.03, 0.05, 0.1, and 0.5 wt.%) in synthetic brine solution following a two-step protocol:

• High-speed magnetic stirring for 15 min.
• Ultrasonic homogenization for 30 min at 50–80% amplitude to ensure uniform nanoparticle dispersion.

SDS was incorporated at a constant concentration of 0.5 wt.% across all nanofluid compositions. An additional 15 min of sonication was performed after SDS addition to further stabilize the nanofluids. Figure 4 shows the workflow of the experimental procedure.

2.4.2. Nanofluid Stability Analysis

Theoretical Background

Stability is critical in EOR applications, as particle aggregation can alter fluid properties and reservoir performance. Electrostatic repulsion between nanoparticles, quantified by Zeta Potential, governs this stability [25].

Stabilization Techniques

To mitigate particle aggregation, the following techniques were employed:

• Surfactant Addition: SDS acts as a surfactant, creating electrostatic and steric barriers to prevent aggregation [26].
• pH Control: Adjusting pH optimizes nanoparticle surface charges, enhancing repulsion forces and reducing aggregation risks [27].
• Ultrasonic Vibration: High-frequency sound waves break up particle clusters and improve dispersion uniformity [28].
• Surface Modification: Chemical treatment of nanoparticle surfaces can introduce functional groups that enhance stability by creating additional repulsive mechanisms between particles [29].

Stability Assessment

Zeta Potential serves as a critical indicator of nanofluid stability in this experimental study Figure 5.

A high absolute Zeta Potential value (positive or negative) signifies strong repulsive forces between particles, resulting in a well-dispersed and stable nanofluid that is critical for EOR applications. Conversely, low Zeta Potential values indicate weak inter-particle repulsion, which increases the risk of aggregation and potential system destabilization.

Multiple techniques have been developed to assess nanofluid stability, each offering unique insights into particle behavior:

• Sedimentation Balance Method: This tracks particle settling rates and suspension stability over time [30].
• UV-Vis Spectrophotometry: This monitors particle concentration and dispersion through light absorption [31].
• Zeta Potential Analysis: This measures the electrical charge at particle interfaces [32].
• Light Scattering Method: This evaluates particle size distribution and aggregation [33].
• Direct Observation: This provides visual confirmation of nanofluid stability [34].

In this study, the Malvern Zetasizer Nano ZS was employed to comprehensively characterize the fluid systems by measuring the following:

• Zeta Potential (mV);
• Electric conductivity (mS/cm);
• Electrophoretic mobility (µmcm/Vs).

By systematically measuring these parameters, researchers can optimize nanofluid formulations, evaluate nano-surfactant effectiveness, and ensure stable suspension properties critical for EOR applications.

2.4.3. Fluid Characterization

Comprehensive Characterization: Fluid properties were measured using standardized laboratory techniques:

• Density was determined using ISOLAB 50 mL calibrated pycnometers.
• Viscosity was measured with the Brookfield KF30 Falling Ball Viscometer (Brookfield Engineering Laboratories, Inc., Middleborough, MA, USA).
• pH and Surface Conductivity were measured using a digital pH meter (Hach IQ240, Hach Company, Loveland, CO, USA).

The results for each fluid system, including brine, nanofluids, and SDS-enhanced nanofluids, are summarized in

Table 2. Fluid properties of all fluids at ambient temperature.

Fluid	Density, (g/cc)	Dynamic Viscosity (cP)	Kinematic Viscosity (mm2/s)	pH	Surface Conductivity (mV)
Paraffin Oil	0.85	2.03	2.01	N.A	N.A
Brine (3 wt% NaCl)	1.014	0.75	0.74	8.4	−83.05
MgO 0.01 wt%	1.015	0.70	0.69	10	−176.85
MgO 0.03 wt%	1.015	0.83	0.82	10.3	−194
MgO 0.05 wt%	1.015	0.83	0.82	10.2	−186.7
MgO 0.1 wt%	1.016	0.85	0.84	10.4	−199.4
MgO 0.5 wt%	1.019	0.92	0.90	10.8	−223.05
MgO 0.01 wt% + SDS	1.018	0.76	0.75	9.7	−163.7
MgO 0.03 wt% + SDS	1.018	0.82	0.80	9.9	−172.9
MgO 0.05 wt% + SDS	1.017	0.82	0.80	10.2	−189.6
MgO 0.1 wt% + SDS	1.017	0.83	0.81	10.3	−192.6
MgO 0.5 wt% + SDS	1.017	0.88	0.86	10.4	−199

, offering a detailed overview of density, viscosity, pH, and conductivity for all compositions.

3. Results

3.1. Stability

The stability assessment of MgO nanofluids highlighted notable disparities between the brine-based and SDS-based systems across varying nanoparticle concentrations. In brine-based fluids, Zeta Potential values ranged from −12.35 mV at 0.01 wt% MgO to 3.45 mV at 0.5 wt% MgO, as depicted in Figure 5. These values fall within the unstable range (−30 mV to +30 mV), signifying inadequate colloidal stability. Conversely, the SDS-based fluids exhibited a marked improvement in stability, with Zeta Potential values spanning from −28.75 mV to −39.7 mV over the same concentration range (Figure 5). The increasingly negative Zeta Potential values in the SDS-enhanced system suggest stronger electrostatic stabilization.

Additionally, the pH of both systems increased with rising MgO concentration, ranging from 8.4 to 10.8 in brine and from 9.7 to 10.4 in SDS-based fluids, consistent with the basicity of MgO (Figure 6). A slight decrease in electric conductivity was observed with increasing MgO concentrations in both systems, declining from 60.95 mS/cm to 50.9 mS/cm (Figure 6). This reduction likely results from ion adsorption onto the nanoparticle surfaces. Overall, the inclusion of SDS significantly improved the stability of MgO nanofluids, likely due to a combination of steric and electrostatic stabilization mechanisms. Dynamic and kinematic viscosities followed a similar trend, increasing from 0.75 cP to 0.92 cP in brine and from 0.76 cP to 0.88 cP in SDS systems (Figure 7).

3.2. IFT Reduction

The IFT behavior of MgO nanofluids revealed distinct differences between brine-based and SDS-based systems, with significant implications for EOR. In the brine-based system, IFT values ranged inconsistently from 26.9 mN/m to 47.9 mN/m, showing no definitive trend (Figure 8). This variability suggests that MgO nanoparticles alone, when dispersed in brine, are insufficient to achieve substantial IFT reduction, potentially due to inadequate stabilization or ineffective interaction at the oil–water interface.

Conversely, the SDS-based system exhibited a consistent and pronounced reduction in IFT with increasing MgO concentration. Specifically, the IFT decreased from 15.66 mN/m at 0.01 wt% MgO to an exceptionally low 5.6 mN/m at 0.5 wt% MgO, representing a 64.2% reduction (Figure 8). This dramatic improvement strongly indicates a synergistic interaction between the SDS surfactant and MgO nanoparticles.

The synergism is hypothesized to arise from the adsorption of SDS molecules onto the surface of MgO nanoparticles, which enhances their dispersibility and stability at the oil–water interface. This adsorption modifies the surface energy of the nanoparticles, enabling their alignment and effective participation in forming a robust interfacial barrier. The SDS molecules further stabilize the nanoparticles in the aqueous phase, preventing aggregation and ensuring their active involvement in reducing capillary forces. These combined effects result in a significant decrease in IFT, which is particularly advantageous for EOR processes.

Such low IFT values are instrumental in reducing capillary forces, enhancing oil mobilization, and improving sweep efficiency during oil recovery operations. The revised understanding of this interaction mechanism underscores its practical implications and highlights the potential of MgO nanoparticles in SDS-based systems as effective agents for improving EOR performance.

4. Discussion

4.1. Significance of Results

The findings emphasize the critical role of surfactants in enhancing the stability and IFT-reducing performance of MgO nanofluids. The enhanced Zeta Potential values in the SDS-based system reflect strong electrostatic repulsion, preventing nanoparticle agglomeration and ensuring colloidal stability. This observation supports the compatibility of MgO-SDS nanofluids for reservoir conditions. Coupled with the observed pH and viscosity trends, this stability underscores the potential of these nanofluids in EOR applications. The observed 64.2% IFT reduction achieved with the SDS-MgO system corroborates the findings of [35], which demonstrated similar concentration-dependent reductions in IFT.

Compared to traditional EOR techniques, this study highlights a promising pathway for achieving significant oil displacement with nanoparticle–surfactant systems. The MgO-SDS combination not only matches but potentially enhances the IFT-lowering capabilities of previously studied surfactant-based EOR methods as shown in

Table 3. Comparative analysis with other chemical EOR technologies.

Criteria	MgO-SDS Combination	Alternative Nanoparticles (e.g., ZnO, SiO2)	Alternative Surfactants (e.g., CTAB, Triton X-100)
IFT Reduction Efficiency	Superior due to synergy	Moderate, often requires surface modification	Moderate, depending on salinity and temperature
Cost	Low	Moderate to high due to synthesis and functionalization	Moderate
Environmental Impact	Low, biodegradable	Potentially harmful depending on the material	Variable, some are non-biodegradable
Thermal/Salinity Tolerance	High	High (varies by nanoparticle)	Moderate
Scalability	High	Moderate (complex preparation)	High

. This result aligns with the findings of [5,35] which demonstrate the importance of ultra-low IFT values in boosting recovery rates. While ultra-low IFTs (10⁻³ mN/m) were not achieved here, the reduction to 5.6 mN/m still represents a significant advancement for EOR technology.

4.2. Implications

The ability to achieve IFT values as low as 5.6 mN/m with MgO-SDS nanofluids highlights their potential for efficient oil displacement. This result suggests that such systems can effectively mobilize trapped oil, leading to improved recovery rates. Importantly, the synergistic interaction between MgO nanoparticles and the SDS surfactant reflects the broader potential of integrating nanotechnology with chemical EOR techniques [36,37].

These findings also indicate that nanofluid-based EOR methods could offer an alternative to conventional methods with higher economic and environmental feasibility. While challenges remain, the observed compatibility of MgO-SDS nanofluids with reservoir conditions points to their potential scalability for industrial applications.

4.3. Limitations

While the results demonstrate the potential of MgO-SDS nanofluids, several challenges remain:

• Testing Conditions: This study was conducted under ambient conditions, whereas reservoir environments exhibit higher temperatures and pressures that may alter fluid behavior.
• Long-Term Stability: The durability of nanofluid stability under prolonged storage or operational conditions remains unclear.
• Conductivity Trends: The observed decline in electrical conductivity with increasing MgO concentration warrants further investigation into its implications for ionic interactions in reservoirs.

Additionally, potential environmental and economic concerns, such as the scalability of SDS-based nanofluids and the impact of surfactant degradation, should be considered in future studies.

4.4. Future Directions

Future research should focus on the following areas to build upon the current findings:

• Reservoir Conditions: Evaluate the performance of MgO-SDS nanofluids under elevated pressures and temperatures to replicate realistic reservoir environments.
• Surfactant Alternatives: Investigate the effects of alternative surfactants or co-surfactant systems to optimize IFT reduction and stability.
• Field-Scale Validation: Conduct field-scale tests to validate laboratory findings and assess the economic viability of MgO-SDS nanofluids for EOR applications.
• Sustainability Studies: Explore the environmental impact and potential biodegradability of MgO-SDS nanofluids to ensure sustainable deployment in oil recovery operations [38,39].

Finally, interdisciplinary collaborations could explore integrating nanofluid EOR systems with other advanced recovery technologies, such as CO₂ injection or thermal recovery, to achieve synergistic benefits.

5. Conclusions

The evaluation of MgO nanofluids demonstrates that incorporating the SDS surfactant significantly enhances their performance for EOR applications. The SDS-MgO nanofluid system exhibited a pronounced synergistic effect, achieving a substantial reduction in IFT from 15.66 mN/m to 5.6 mN/m as the MgO concentration increased from 0.01 wt% to 0.5 wt%. This 64.2% reduction in IFT is critical for EOR, as it directly improves oil mobilization and sweep efficiency by reducing capillary forces.

Stability analysis further validated the effectiveness of the SDS-based system. Zeta Potential values became increasingly negative (−28.75 mV to −39.7 mV) with rising MgO concentrations, reflecting enhanced electrostatic stabilization and superior colloidal stability. Additionally, the modest increases in viscosity (from 0.76 cP to 0.88 cP) and pH (from 9.7 to 10.4) indicate a stable and well-dispersed nanofluid system without the excessive thickening that could hinder flow in reservoir conditions. The slight reduction in electric conductivity (from 60.95 mS/cm to 56.5 mS/cm) likely results from ion adsorption onto nanoparticle surfaces, contributing to the system’s improved interfacial and stability characteristics.

In contrast, the brine-based MgO nanofluid displayed inconsistent IFT values and significantly poorer stability, underscoring its limited applicability for EOR purposes. The combined advantages of substantial IFT reduction and enhanced stability in the SDS-MgO system highlight its potential as a promising formulation for EOR applications. These findings emphasize the critical role of surfactant–nanoparticle interactions in optimizing nanofluids for advanced oil recovery processes. Future work should focus on refining this formulation, exploring its performance under reservoir conditions, and conducting field-scale tests to assess its practical viability in improving oil recovery rates.