Micro/Nanoparticle Characteristics and Flow in Porous Media: A Review towards Enhanced Oil Recovery
Abstract
:1. Introduction
2. Materials and Structure Designs
2.1. Materials of Micro/Nanoparticles
2.2. Fabrications and Designs of Micro/Nanoparticles
3. EOR Mechanisms of Micro/Nanoparticles
3.1. Reduction of Interfacial Tension
3.2. Alteration of Wettability
3.3. Improvement of Sweep Efficiency
3.4. Interfacial Chemical Reactions
4. Experimental Findings and Computational Modeling
4.1. Field Scale Experiments and Simulations
4.2. Core Flood Experiments and Simulations
4.3. Micro-Model Experiments and Pore-Scale Simulations
5. Challenges and Limitations
6. Future Directions
7. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Material | Size | Fabrication | Structure Design | Function | Mechanism | EOR |
---|---|---|---|---|---|---|
Silica | 10–100 nm | Sol–gel process | Spherical, Rods | Interface regulation | Alters rock wettability, reduces IFT | 15–25% |
Titanium Dioxide (TiO2) | 5–50 nm | Hydrothermal synthesis | Spherical, Rods | Photocatalytic activity | Decomposes organic materials, reduces viscosity, acts as a catalyst | 20–50% |
Iron Oxide (Fe3O4) | 10–100 nm | Co-precipitation | Spherical, Cubic, Magnetic | Magnetic properties, increased mobility | Aids in tracing and targeting, reduces viscosity | 20–30% |
Zinc Oxide (ZnO) | 10–50 nm | Chemical vapor deposition | Spherical, Rods | Catalytic properties | Enhances chemical reactions, reduces viscosity, acts as a reagent with oil | 18–25% |
Silver | 10–100 nm | Chemical reduction | Spherical, Cubic | Antimicrobial properties | Prevents microbial-induced souring, acts as a catalyst | 12–18% |
Gold | 1–100 nm | Citrate reduction | Spherical, Rods | Catalytic properties, increased stability | Alters wettability, improves sweep efficiency, acts as a catalyst | 15–25% |
Carbon Nanotube | 1–10 nm | Chemical vapor deposition | Tubular, Multi-walled | High surface area, strength | Alters wettability and IFT, enhances sweep efficiency | 22–32% |
Graphene Oxide | 1–20 nm | Hummers’ method | Layered, Sheets | High surface area, conductivity | Alters wettability, reduces IFT | 18–28% |
Polymer-coated | 10–100 nm | Emulsion polymerization | Core-shell, Spherical | Increased stability, functionalization | Alters wettability, reduces IFT, acts as a reagent with oil | 20–30% |
Polymers | 50–200 nm | Emulsion polymerization, precipitation polymerization | Spherical, Network | Enhance viscosity, improve sweep efficiency | Increases water viscosity, enhances sweep efficiency, improves mobility control | 20–35% |
Nanoemulsions | 20–200 nm | Ultrasonication, high-pressure homogenization, spontaneous emulsification | Droplets, Mixed-phase | Enhance oil mobilization, reduce viscosity, improve sweep efficiency | Reduces IFT, stabilizes emulsion, disperses oil droplets uniformly | 25–40% |
Scale | Method | Scheme | Goal | Advantage | Limitation |
---|---|---|---|---|---|
Field | Modeling and simulation | Darcy Law | EOR, flow field prediction | Well-established, simple to apply | Assumes homogeneity, limited accuracy in complex reservoirs |
Reservoir simulation software (ECLIPSE version 300, CMG version 2023.1) | EOR strategy development, production optimization | Comprehensive, considers geological and operational data | Requires detailed input data, can be computationally intensive | ||
Experiment | Pilot testing | Validate EOR methods, scale-up evaluation | Real-world validation, informs full-field application | Expensive, long duration, risk of non-representative results | |
Core | Modeling and simulation | Lattice Boltzmann Method (LBM) | Flow field prediction, EOR | Captures pore-scale/meso-scale phenomena, adaptable | High computational cost, complex setup |
Finite Element/Volume Method (FEM/FVM) | Flow field prediction, EOR, Stress and deformation analysis | Accurate for complex geometries, versatile | Computationally intensive, requires fine meshing | ||
Experiment | Core flooding with Computed Tomography (CT)/Computed Tomography (NMR) | Revealing mechanisms, EOR, Pore-scale visualization | Visual observation, detailed analysis, Non-destructive, high-resolution | Expensive, limited by sample size | |
Micro/Pore | Modeling and simulation | Navier–Stokes (N-S) equations | Flow field prediction, understanding flow dynamics | Accurate for complex flows, high fidelity | Computationally intensive, requires fine discretization |
Lattice Boltzmann Method (LBM) | Flow field prediction, pore-scale fluid dynamics | Captures detailed flow phenomena, flexible boundary conditions | High computational cost, complex setup | ||
Experiment | Microfluidic models | Revealing mechanisms, EOR, Microscale visualization | High control over experimental conditions, real-time observation | Scale-up issues, material compatibility | |
Molecular | Modeling and simulation | Molecular Dynamics (MD) | Molecular interactions, nano-scale flow dynamics | Detailed molecular insights, accurate at the atomic level | High computational cost, limited to very small systems |
Density Functional Theory (DFT) | Electronic structure calculations, chemical reactions | High accuracy for quantum mechanical properties | Extremely computationally intensive, limited to small systems | ||
Experiment | Nuclear Magnetic Resonance (NMR)/Raman spectroscopy | Molecular structure determination, interaction analysis | Detailed molecular information, High sensitivity, non-destructive | Requires large samples, expensive equipment, limited to vibrational transitions |
Bottleneck of EOR | Details | Future Direction | Big Picture |
---|---|---|---|
High production costs and economic feasibility | High costs associated with the production, modification, and deployment of specialized nanoparticles, along with extensive post-injection monitoring | AI-accelerated particle design | AI can reduce costs by optimizing particle properties and production methods through simulations and machine learning models |
Complex reservoir heterogeneity | Geological variations in reservoirs affect the distribution and efficacy of injected particles, making outcomes difficult to predict and generalize across different fields | Big-data driven approaches | Utilizing big data can help in understanding reservoir heterogeneity better, leading to more tailored EOR strategies |
Environmental concerns and sustainability | Nanoparticles such as metal oxides and heavy metals can be toxic. Their long-term persistence, potential for bioaccumulation, and the environmental impact of production and disposal are major concerns | Bio-based schemes, non-toxic and biocompatible formulations, comprehensive lifecycle analysis | Bio-based nanoparticles can mitigate environmental impacts by using sustainable and biodegradable materials, while lifecycle analyses ensure minimal long-term impact from production to degradation |
Particle stability under reservoir conditions | Stability refers to nanoparticles’ ability to resist changes in harsh reservoir conditions. Instability can lead to particle degradation, aggregation, and reduced functionality | Smart nanoparticles responsive to reservoir conditions | Smart nanoparticles can dynamically adjust to changing reservoir conditions, improving efficiency and stability |
Limited understanding of nanoparticle interactions | The interactions between nanoparticles and reservoir fluids/rocks at the nano-scale are not fully understood, leading to unpredictable behaviors and outcomes | Advanced modeling and simulation techniques | Improved modeling can provide deeper insights into nano-scale interactions and predict macro-scale impacts more accurately |
Scalability from lab to field | Successful lab-scale results are often challenging to replicate at the field scale due to differences in conditions and scales | Integrated hybrid methods | Combining chemical, thermal, microbial, and nano-enhanced techniques can create more robust and scalable EOR solutions |
Energy-intensive processes | The synthesis, functionalization, and deployment of nanoparticles involve energy-intensive processes, and additional energy is required to inject micro/nanofluids into the reservoir | Renewable energy-powered nanoparticle synthesis | Using renewable energy for nanoparticle production can lower the carbon footprint and enhance sustainability |
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Lao, J.; Cheng, H.; Wang, Y.; Song, H. Micro/Nanoparticle Characteristics and Flow in Porous Media: A Review towards Enhanced Oil Recovery. Energies 2024, 17, 4136. https://doi.org/10.3390/en17164136
Lao J, Cheng H, Wang Y, Song H. Micro/Nanoparticle Characteristics and Flow in Porous Media: A Review towards Enhanced Oil Recovery. Energies. 2024; 17(16):4136. https://doi.org/10.3390/en17164136
Chicago/Turabian StyleLao, Junming, Haoran Cheng, Yuhe Wang, and Hongqing Song. 2024. "Micro/Nanoparticle Characteristics and Flow in Porous Media: A Review towards Enhanced Oil Recovery" Energies 17, no. 16: 4136. https://doi.org/10.3390/en17164136
APA StyleLao, J., Cheng, H., Wang, Y., & Song, H. (2024). Micro/Nanoparticle Characteristics and Flow in Porous Media: A Review towards Enhanced Oil Recovery. Energies, 17(16), 4136. https://doi.org/10.3390/en17164136