Mechanistic Insights Economic Modeling and Research Priorities for Nanoparticle Assisted Enhanced Oil Recovery
Hamid
Mohammad
Soleimani¹
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Emailhamid.soleimani90@yahoo.com
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School of Chemical, Petroleum and Gas Engineering
Iran University of Science and Technology (IUST)
16846-13114
Narmak
Tehran
Iran
Hamid Mohammad Soleimani*¹
Abstract
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This comprehensive review synthesizes recent advances (2021–2025) in nanoparticle-assisted enhanced oil recovery (NP-EOR), integrating mechanistic understanding, transport phenomena, and economic modeling. Through systematic analysis of more than 30 experimental and field studies, we establish a refined taxonomy of nanoparticle classes—including silica, metal oxides, iron-oxide, carbonaceous nanostructures, and nanoclays—based on their distinct mechanisms and performance characteristics. The integration of recent experimental studies on nanoclay systems (Soleimani & Sadeghi, 2023; Soleimani & Sadeghi, 2024, 2025) provides critical insights into stability optimization, practical dosing windows, and retention behavior. Our analysis demonstrates that synergistic mechanisms combining wettability alteration, interfacial tension reduction, and rheology control yield maximum incremental recovery (25–45% in laboratory settings). We present a sophisticated economic modeling framework incorporating Net Present Value (NPV) and Internal Rate of Return (IRR) analyses with Monte Carlo simulation, accounting for retention losses and scaling factors (Rahman et al., 2022; Kandiel et al., 2025). Key findings indicate that economic viability is highly sensitive to field-scale recovery factors (ΔRRfield), full-cycle nanoparticle costs, and oil price volatility, with lab-to-field scaling factors (α ≈ 0.3–0.6) requiring conservative estimation until pilot validation. This is the first review to integrate empirical nanoclay retention and stability datasets into a probabilistic techno-economic framework, providing a structured protocol for pilot translation and field implementation.Keywords:
nanoparticles
enhanced oil recovery
nanoclay
wettability alteration
interfacial tension
economic modeling
lab-to-field scaling
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1.School of Chemical, Petroleum and Gas Engineering, Iran University of Science and Technology (IUST), Narmak, Tehran 16846 − 13114, Iran.
*Corresponding Author: hamid.soleimani90@yahoo.com
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1.Introduction
Nanoparticle-assisted EOR (NP-EOR) has evolved from proof-of-concept demonstrations to targeted field applications, driven by the unique capabilities of nanomaterials to manipulate fluid-fluid and rock-fluid interactions at the pore scale (Iravani et al., 2023; Tong et al., 2023). Multiple nanoparticle classes—including silica (both bare and surface-modified), metal oxides (Al₂O₃, TiO₂, MgO, ZrO₂), iron-oxide/magnetic particles, carbonaceous nanostructures (carbon dots, graphene quantum dots), and nanoclays (particularly montmorillonite)—have demonstrated effectiveness through four primary mechanisms: wettability alteration, interfacial tension (IFT) reduction, foam/emulsion stabilization, and injected-fluid rheology modification (Al-Asadi et al., 2022; Gholamzadeh et al., 2024; Salem et al., 2024).
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Recent systematic reviews converge on several critical insights. First, mechanistic complementarity significantly enhances recovery outcomes, with combinations of wettability alteration, IFT reduction, and foam/rheology control producing superior results compared to single-mechanism interventions (Xu et al., 2022; Salem et al., 2024). Second, nanoparticle stability and transport represent rate-limiting factors, as high temperatures and multivalent ion concentrations promote aggregation and retention, reducing deliverable doses and increasing required injection masses (Hutin et al., 2023; Hamza et al., 2025). Third, economic viability depends critically on field-scale recovery factors, full-cycle nanoparticle costs, and oil prices, necessitating conservative lab-to-field scaling (α ≈ 0.3–0.6) until pilot validation (Rahman et al., 2022; Kandiel et al., 2025). Finally, environmental considerations and produced-water management are essential components of realistic appraisals and regulatory planning (Razavifar et al., 2024).This review integrates recent experimental advancements, particularly concerning nanoclay systems (Soleimani & Sadeghi, 2023; Soleimani & Sadeghi, 2024, 2025), to provide updated mechanistic understanding, refined transport analysis, and enhanced economic modeling capabilities for NP-EOR applications.
2.Methods: Literature Selection and Synthesis Framework
We conducted a systematic review of peer-reviewed experimental, review, and pilot studies published between 2021 and 2025, prioritizing works reporting core-flood, micromodel, dynamic light scattering/zeta potential stability, transport/retention, and field pilot outcomes (Iravani et al., 2023; Al-Asadi et al., 2022; Rezvani et al., 2021). Data extraction encompassed nanoparticle class and dose, hydrodynamic size and zeta potential in test salinity, core properties (permeability/porosity), test temperature/salinity, measured ΔIFT and contact angle changes, laboratory incremental recovery (ΔRR_lab), retention metrics, and field results where available. For economic modeling, conservative engineering assumptions were applied where numerical cost data were absent, with appropriate sensitivity bounds. Soleimani and colleagues' experimental datasets (Soleimani & Sadeghi, 2023; Soleimani & Sadeghi, 2024, 2025) were utilized to parameterize nanoclay stability versus dose and surfactant system behavior in economic mass-balance and retention submodel. We conducted a systematic review of peer-reviewed experimental, review, and pilot studies published between 2021 and 2025. The selection process followed a PRISMA-style workflow shown Fig. 1.
Fig. 1
The selection process followed a PRISMA-style workflow
Step Description:
Initial Search: The process begins with the Identification of approximately 250 potential studies from various databases.
Screening by Title/Abstract: By reviewing the titles and abstracts, the number of studies is reduced to around 120. Studies that are clearly irrelevant to the research topic are excluded.
Eligibility Check: The remaining studies (approx. 60) are thoroughly assessed against strict eligibility criteria (NP-EOR topic, publication years 2021–2025, and the presence of lab or field data).
Final Inclusion for Synthesis: Finally, 30 or more studies that meet all the criteria are selected for the final stage of data analysis and synthesis.
This standard process ensures that only the most relevant and high-quality studies are included in the final review.
3.Mechanistic Synthesis and Performance Analysis
1.
Silica and Surface-Modified Silica Nanoparticles
Silica nanoparticles adsorb onto rock and oil surfaces, creating hydrated films and increasing disjoining pressure to shift wettability toward water-wet conditions and facilitate oil mobilization (Gholinezhad et al., 2022; Alilou et al., 2023). Surface modifiers—including silane coupling agents and polymer grafts—enable tuning of hydrophilicity and colloidal stability, though sensitivity to divalent ions and elevated temperatures necessitates optimized coating strategies (Hutin et al., 2023)
2. Metal Oxides and Inorganic Nanosheets
Metal oxides and layered nanosheets (e.g., zirconium phosphate) provide Lewis acid/base sites that interact with crude oil components to reduce IFT and modify wettability. Several studies report superior IFT reduction for Al₂O₃ and MgO in high-salinity environments compared to SiO₂ (Hamza et al., 2025; Kandiel et al., 2025; Qing et al., 2022)
3. Iron-Oxide (Magnetic)
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Fe₃O₄ and core-shell magnetic particles stabilize foams and emulsions by forming particulate interfacial layers. Laboratory investigations demonstrate extended foam half-life and potential recyclability at surface facilities, though practical subsurface magnetic recovery remains unproven (Rezvani et al., 2021; Yin et al., 2025)Carbonaceous Nanostructures.4. Carbonaceous Nanostructures
Carbon dots and graphene quantum dots exhibit amphiphilic interfacial activity and significant IFT reduction, even in saline environments (Gholamzadeh et al., 2024; Razavifar et al., 2024). Scaling cost-effective synthesis and understanding environmental fate represent ongoing research challenges.
5. Nanoclays: Experimental Advances and Implications
Recent systematic investigations of montmorillonite nanoclay for water-based EOR (Soleimani & Ghasemi, 2024; Soleimani & Sadeghi, 2024, 2025) have yielded critical insights for mechanism understanding and practical implementation. Stability optimization across salt compositions and surfactant systems has identified nanoclay concentrations and surfactant choices that maximize colloidal stability in representative reservoir brines (Soleimani & Sadeghi, 2023). Experimental results demonstrate that optimized nanoclay formulations induce measurable wettability shifts and modest IFT reductions relative to base brines, consistent with enhanced oil mobilization mechanisms (Soleimani & Sadeghi, 2024). Flow and core-flood performance tests reveal that nanoclay-assisted formulations produce incremental oil in oil-wet cores, with recovery magnitude dependent on dose, surfactant presence, and flow regimes (Soleimani & Sadeghi, 2025). Critically, these experiments quantify retention behavior and flow characteristics, showing that optimized nanoclay formulations cause limited permeability impairment, while overdosing increases pore-blocking risks. The combined stability and flooding data enable identification of practical dosing windows where stability, transport, and incremental recovery are balanced—providing an empirical basis for setting pilot concentrations and parameterizing retention in economic models.
6. Nanoparticle-Surfactant/Polymer Synergies
Nanoparticles frequently act synergistically with surfactants and polymers, reducing surfactant adsorption, stabilizing foams, and modifying polymer rheology under saline conditions (Xu et al., 2022; Kandiel et al., 2025). Experimental findings on surfactant-nanoclay systems (Soleimani & Sadeghi, 2023) demonstrate how surfactant-assisted stabilization can tune nanoclay behavior for EOR applications, supporting broader literature on nanoparticle-surfactant synergies.
7. Transport, Retention, and Pore-Scale Considerations
Retention (through sorption and straining) and aggregation determine the fraction of injected nanoparticles that reach target zones (Rahman et al., 2022). Recent experimental studies have quantified retention behavior In core tests (Soleimani & Sadeghi, 2024, 2025), providing retention curves that can be directly incorporated into injection mass-balance calculations and economic models, significantly improving delivered dose estimation realism.comparartive table of nanoparticle classes is listed in Table 1.
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Nanoparticle Class
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Dominant Mechanism(s)
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Typical Dose Range
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ΔIFT Reduction
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Wettability Alteration
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ΔRR_lab (%)
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Key Limitations
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Silica (bare/modified)
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Wettability alteration, disjoining pressure
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0.01–0.1 wt%
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Moderate
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Strong (oil-wet → water-wet)
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15–35
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Sensitive to divalent ions, aggregation at high T
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Metal oxides (Al₂O₃, MgO, TiO₂, ZrO₂)
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IFT reduction, wettability
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0.01–0.05 wt%
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High
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Moderate
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20–40
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Cost, surface reactivity
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Iron-oxide (Fe₃O₄)
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Foam/emulsion stabilization
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0.01–0.05 wt%
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Low–moderate
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Limited
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10–25
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Subsurface magnetic recovery unproven
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Carbonaceous (dots, GQDs)
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IFT reduction, amphiphilic activity
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0.005–0.02 wt%
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Very high
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Moderate
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20–45
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Cost-effective synthesis, environmental fate
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Nanoclays (montmorillonite)
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Wettability alteration, modest IFT reduction
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0.05–0.2 wt%
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Low–moderate
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Moderate
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10–30
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Overdosing → pore blocking, retention risk
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4.Laboratory-to-Field Translation: Protocol and Pilot Design Implications
Based on integrated literature and experimental evidence (Soleimani & Sadeghi, 2023; Soleimani & Sadeghi, 2024, 2025), we recommend a structured protocol for translating nanoclay and broader nanoparticle laboratory results to pilot applications:
1.
Stability Triage: Perform dynamic light scattering and zeta potential measurements in candidate reservoir brines (including divalent ions) and screen surfactant co-formulations to identify stable nanofluid windows (Soleimani & Sadeghi, 2023).
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Core Tests with Retention Tracking: Conduct core-flood experiments with upstream and downstream sampling and nanoparticle-label/tracer co-injection to derive retention curves and assess potential permeability changes (Soleimani & Sadeghi, 2025).
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Practical Dosing Window Determination: Utilize static IFT/contact angle measurements and dynamic core results to select the lowest effective nanoparticle concentration that achieves target wettability/IFT shifts while limiting retention and formation damage (Soleimani & Sadeghi, 2024).
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Pilot Configuration: Implement staged injection with monitoring wells, nanoparticle analysis in produced water, and contingency plans for produced-water treatment, incorporating environmental monitoring and multi-year surveillance.
5.Advanced Economic Modeling Framework
We present a enhanced economic modeling framework that integrates empirical retention and dose data (Soleimani & Sadeghi, 2024; Soleimani & Sadeghi, 2024, 2025) to provide realistic cost and delivered dose inputs for viability assessment.Workflow of Economic model is shown Fig. 2..
Fig. 2
Workflow of Economic Model
Process Description:
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Retention & Stability Data: Starts with collecting laboratory and field data on nanoparticle retention and stability - fundamental performance metrics.
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Mass Balance: Analyzes the relationship between injected mass (Minj) and effectively delivered mass (Mdelivered) to understand transport efficiency.
3.
Cost Components: Breaks down the economic factors including nanoparticle costs (Cnp), logistics, and treatment expenses.
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Monte Carlo Simulation: Runs probabilistic analysis using key variables:
· ΔRRlab: Recovery factor improvement from lab data
· α: Scaling factor
· fret: Retention factor
· Poil: Oil price
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NPV/IRR Probability Distributions: Generates probability distributions for Net Present Value and Internal Rate of Return to assess economic viability under uncertainty.
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Decision Support: Provides the final output to guide decisions about proceeding with pilot testing or full field deployment based on integrated technical and economic analysis
5.1 Mass-Balance and Retention Analysis
The delivered mass at target distance is calculated as:
Mdelivered= Ctarget × PVtarget × φtarget
where φ_target represents pore volume at target.The required injected mass is:
M injected = Mdelivered / (1 - fret)
Experimental retention curves(Soleimani & Sadeghi, 2025) enable estimation of fret as a function of injected pore volumes and brine composition, allowing precise sizing of Minjected and consequent nanoparticle material costs.
5.2 Comprehensive Cost Components
Full-cycle nanoparticle cost (per barrel injected) should include:
· Nanoparticle material cost (raw nanoclay + modification)
· Formulation and mixing costs (surfactant, pH/salinity adjustment)
· Logistics and injection preparation
· Produced water nanoparticle monitoring and treatment allocation
· Environmental monitoring and contingency provisioning
5.3 Integrated NPV/IRR Modeling with Probabilistic Analysis
Our economic model incorporates Net Present Value (NPV) and Internal Rate of Return (IRR) calculations with Monte Carlo sampling for ΔRRlab, scaling factors (α), retention fractions (fret), nanoparticle costs (Cnp), and oil prices (Poil). The model outputs probability distributions for NPV > 0, IRR, and tornado charts for sensitivity analysis. Scenario analysis includes staged reinjection to offset retention losses and evaluate economic impact.
6.Discussion and Research Agenda
Integrating recent experimental results (Soleimani & Sadeghi, 2023; Soleimani & Sadeghi, 2024, 2025) strengthens the practical case for nanoclay as a cost-effective nanoparticle family with genuine EOR potential when properly formulated and injected. Stability mapping and retention quantification reduce two critical uncertainties: deliverable nanoparticle concentration at distance and dosing windows that balance efficacy with formation safety. Economic modeling demonstrates that nanoclay programs can achieve attractiveness under specific conditions: stable formulated dispersions in reservoir brine, measured retention below critical thresholds (cumulative fret < 20–30% over transport path), and achievable ΔRRlab that yields ΔRRfield ≥ 0.03–0.05 after conservative scaling.
Remaining challenges include long-term stability under reservoir temperature and chemical conditions, potential unforeseen formation interactions at field scale, and environmental/regulatory constraints on surfactant and nanoparticle discharge. Future pilot work should prioritize retention measurement and produced-water fate studies to reduce investment risk.research gaps and priorities is listed in Table 2.
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Research Gap
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Why It Matters
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Recommended Action
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Long-term stability under reservoir T/P/salinity
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Most studies ≤ 6 months
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Multi-year stability tests with real brines
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Retention quantification at field scale
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Lab data may not scale
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Tracer/label pilots with retention profiling
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Produced-water fate & treatment
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Environmental/regulatory risk
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Develop monitoring & treatment protocols
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Standardized reporting
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Current heterogeneity prevents comparison
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Adopt unified metrics (ΔRR, zeta, IFT, contact angle)
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Economic scaling
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Lab-to-field α uncertain
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More pilot data to refine α (0.3–0.6 → validated ranges)
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Cost-effective synthesis
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High cost limits deployment
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Green/low-cost synthesis of nanoclay & hybrids
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7.Conclusions and Recommendations
1.
Nanoclay (montmorillonite) is supported by experimental evidence (Soleimani & Sadeghi, 2023; Soleimani & Sadeghi, 2024, 2025) as a practical, cost-effective nanoparticle class for water-based EOR when co-formulated with appropriate surfactants and dosed within empirically derived windows.
2.
Stability screening (DLS/zeta), core-flood retention profiling, and tracer/label pilots are essential preconditions for scaling nanoclay EOR; Soleimani and colleagues' datasets provide concrete starting points for dosing and retention expectations.
3.
Economic viability depends critically on deliverable ΔRRfield, retention (fret), nanoparticle costs (Cnp), and oil price; using empirical retention curves significantly improves realism of NPV/IRR estimates (Rahman et al., 2022; Kandiel et al., 2025).
4.
Research priorities include long-term stability at reservoir temperature/salinity, produced-water fate and treatment, pilot designs with nanoparticle labeling, and development of low-cost, low-impact formulation strategies.
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Funding
No funding was received for conducting this study.
Declaration of Competing Interest
The author declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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Acknowledgement
The authors would like to thank all the researchers whose work contributed to the literature reviewed in this study.
Ethics Approval and Consent to Participate
Not applicable.This article is a comprehensive review of existing literature and does not involve any direct human participation, animal experiments, or clinical trials. Therefore, ethical approval and consent to participate are not required.
Consent for Publication
Not applicable. This manuscript does not contain any individual person's data in any form (including any individual details, images, or videos). As a comprehensive review article, it is based solely on analysis and synthesis of previously published literature, and thus no consent for publication from individuals is required.
Clinical Trial Number
Not applicable.This study is a literature review and does not involve any clinical trial.
Data availability
Not applicable.
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Author Contribution
Hamid Mohammad Soleimani was solely responsible for all aspects of this research. He independently conceptualized the study, designed the systematic review methodology, and conducted the comprehensive literature analysis covering experimental, mechanistic, and economic dimensions of nanoparticle-assisted enhanced oil recovery (NP-EOR). He performed the integration of recent nanoclay datasets into the mechanistic synthesis and economic modeling framework, including the development of probabilistic NPV/IRR simulations. He also structured the manuscript, wrote all sections, and critically revised the content to ensure scientific rigor, clarity, and alignment with journal standards. The author confirms full responsibility for the integrity and accuracy of the work and approves the final version for submission.
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