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Nanotechnology for Oil and Gas Applications
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Nanotechnology for Oil and Gas Applications

A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: closed (30 March 2017) | Viewed by 95479

Special Issue Editor

Prof. Dr. Dongsheng Wen

E-Mail Website
Guest Editor
School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, UK
Interests: nanotechnology; enhanced oil recovery; solar energy; multiphase flow; multiscale modelling

Special Issue Information

Dear Colleauges,

The global demand of energy is expected to increase by as much as 50% in the next 20 years, and the demand for oil and gas will also increase. The era of finding “easy oil” is coming to an end, and future supply will become more reliant on fossil fuels produced from non-conventional reservoirs and from enhanced oil recovery process, which calls for new technologies. Nanotechnology may offer an alternative promising solution.

The potentiality of applying nanotechnology in oil and gas sectors is enormous, which ranges from reservoir characterisation, drilling operation, exploration and production, to flow assurance. Research and development of novel nanotechnologies has received intensive attention in the last decade, including the development of contrast-agent type of nanoparticles, controlled delivery of chemicals, and nanoparticles enabled oil recovery. Following an explosion of hype and speculation, it is beginning to see some advances. A sizable community has now formed, which starts to generate a critical mass in the area. However, it has to be admitted that the research in this field is just at the beginning, and that most of the studies are still at the laboratory scale.

This Special Issue will act as a timely platform to advance the nanotechnology applications in oil and gas sectors, including but not limited to reservoir characterisation, enhanced oil recovery, surface processing and flow assurance, and promote researchers of various areas of nanotechnology to disseminate their most recent findings and define the frontier of nanotechnology in oil and gas applications.

Prof. Dr. Dongsheng Wen
Guest Editor

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Keywords

  • Nanotechnology
  • nanoparticle
  • enhanced oil recovery
  • flow assurance

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Published Papers (10 papers)

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4494 KiB  
Article
Transport and Deposition of Carbon Nanoparticles in Saturated Porous Media
by Zhongliang Hu, Jin Zhao, Hui Gao, Ehsan Nourafkan and Dongsheng Wen
Energies 2017, 10(8), 1151; https://doi.org/10.3390/en10081151 - 5 Aug 2017
Cited by 31 | Viewed by 6126 | Correction
Abstract
Carbon nanoparticles (CNPs) are becoming promising candidates for oil/gas applications due to their biocompatibility and size-dependent optical and electronic properties. Their applications, however, are always associated with the flow of nanoparticles inside a reservoir, i.e., a porous medium, where insufficient studies have been [...] Read more.
Carbon nanoparticles (CNPs) are becoming promising candidates for oil/gas applications due to their biocompatibility and size-dependent optical and electronic properties. Their applications, however, are always associated with the flow of nanoparticles inside a reservoir, i.e., a porous medium, where insufficient studies have been conducted. In this work, we synthesized CNPs with two different size categories in 200 nm carbon balls (CNP-200) and 5 nm carbon dots (CNP-5), via a hydrothermal carbonation process. Comprehensive experiments in packed glass bead columns, as well as mathematical simulations, were conducted to understand the transport and deposition of CNPs under various ionic strength, particle sizes and concentration conditions. Our results show that the retention of CNP-200 is highly sensitive to the salinity and particle concentrations, while both of them are unaffected in the transport of small CNP-5. Supplemented with Derjaguin-Landau-Verwey-Overbeek (DLVO) theory, the clean bed filtration theory with blocking effect can successfully fit the experimental breakthrough curves of CNP-200. However, the high breakthrough ability for CNP-5 regardless of ionic strength change is in conflict with the energy interactions predicted by traditional DLVO theory. Full article
(This article belongs to the Special Issue Nanotechnology for Oil and Gas Applications)
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Figure 1

Figure 1
<p>(<b>a</b>) SEM picture for Carbon ball at ~200 nm; (<b>b</b>) TEM picture for carbon dots at ~5 nm.</p> Full article ">Figure 2
<p>Measured and simulated breakthrough curves for representative CNP-200 transport experiments at ionic strength varying from 1 mM to 10 mM in brine-saturated columns packed with glass beads: (<b>a</b>) DI water; (<b>b</b>) 1 mM; (<b>c</b>) 2 mM; (<b>d</b>) 5 mM; (<b>e</b>) 10 mM. The pH was buffered to around 7 by using HCl and NaOH solution, both are available at 0.1 M and 0.01 M.</p> Full article ">Figure 3
<p>Values of (<b>a</b>) attachment term (<math display="inline"> <semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>a</mi> <mi>t</mi> <mi>t</mi> </mrow> </msub> </mrow> </semantics> </math>); (<b>b</b>) detachment term (<math display="inline"> <semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>d</mi> <mi>e</mi> <mi>t</mi> </mrow> </msub> </mrow> </semantics> </math>) and (<b>c</b>) dimensionless <math display="inline"> <semantics> <mrow> <msub> <mi>ρ</mi> <mi>b</mi> </msub> <msub> <mi>s</mi> <mrow> <mi>m</mi> <mi>a</mi> <mi>x</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>c</mi> <mi>o</mi> </msub> </mrow> </semantics> </math> as a function of ionic strength, obtained from the simulations of each transport experiment and their empirical prediction curves. (Figures are plotted in logarithmic scale.).</p> Full article ">Figure 4
<p>BTCs of CNP-200 corresponding to different influent concentration: (<b>a</b>) 3.1 ppm; (<b>b</b>) 4.5 ppm; (<b>c</b>) 6.4 ppm; (<b>d</b>) 8.0 ppm. The ionic strength is 1 mM.</p> Full article ">Figure 5
<p>Size dependent retention of CNPs at 1 mM CaCl<sub>2</sub>: (<b>a</b>) Carbon ball (~200 nm), 6.4 ppm; (<b>b</b>) Carbon ball (~200 nm), 8.0 ppm; (<b>c</b>) carbon dots (~5 nm), 10 ppm; (<b>d</b>) carbon dots (~5 nm), 24.8 ppm.</p> Full article ">Figure 6
<p>Breakthrough of CNP-5 (10 ppm) in glass beads-packed column at room temperature with ionic strength ranging from 1 mM CaCl<sub>2</sub> to the standard of API brine.</p> Full article ">Figure 7
<p>Total interaction energy between particles and collectors as a function of distance at various ionic strength, at pH 7. (<b>a</b>) the interaction energy between CNP-200 particle-particle; (<b>b</b>) the interaction energy between CNP-200 particle- collector (glass beads); (<b>c</b>) the interaction energy between CNP-5 particle-particle; (<b>d</b>) the interaction energy between CNP-5 particle-collector (glass beads).</p> Full article ">
14171 KiB  
Article
2D Numerical Simulation of Improving Wellbore Stability in Shale Using Nanoparticles Based Drilling Fluid
by Jiwei Song, Ye Yuan, Sui Gu, Xianyu Yang, Ye Yue, Jihua Cai and Guosheng Jiang
Energies 2017, 10(5), 651; https://doi.org/10.3390/en10050651 - 9 May 2017
Cited by 21 | Viewed by 6245
Abstract
The past decade has seen increased focus on nanoparticle (NP) based drilling fluid to promote wellbore stability in shales. With the plugging of NP into shale pores, the fluid pressure transmission can be retarded and wellbore stability can be improved. For better understanding [...] Read more.
The past decade has seen increased focus on nanoparticle (NP) based drilling fluid to promote wellbore stability in shales. With the plugging of NP into shale pores, the fluid pressure transmission can be retarded and wellbore stability can be improved. For better understanding of the interaction between shale and NP based drilling fluid based on previous pressure transmission tests (PTTs) on Atoka shale samples, this paper reports the numerical simulation findings of wellbore stability in the presence of NP based drilling fluid, using the 2D fluid-solid coupling model in FLAC3D™ software. The results of previous PTT are discussed first, where the steps of numerical simulation, the simulation on pore fluid pressure transmission, the distribution of stress and the deformation of surrounding rock are presented. The mechanisms of NP in reducing permeability and stabilizing shale are also discussed. Results showed that fluid filtrate from water-based drilling fluid had a strong tendency to invade the shale matrix and increase the likelihood of wellbore instability in shales. However, the pore fluid pressure near wellbore areas could be minimized by plugging silica NP into the nanoscale pores of shales, which is consistent with previous PTT. Pore pressure transmission boundaries could also be restricted with silica NP. Furthermore, the stress differential and shear stress of surrounding rock near the wellbore was reduced in the presence of NP. The plastic yield zone was minimized to improve wellbore stability. The plugging mechanism of NP may be attributed to the electrostatic and electrodynamic interactions between NP and shale surfaces that are governed by Derjaguin-Landau-Verwey-Overbeek (DLVO) forces, which allowed NP to approach shale surfaces and adhere to them. We also found that discretization of the simulation model was beneficial in distinguishing the yield zone distribution of the surrounding rock in shales. The combination of PTT and the 2D numerical simulation offers a better understanding of how NP-based drilling fluid can be developed to address wellbore stability issues in shales. Full article
(This article belongs to the Special Issue Nanotechnology for Oil and Gas Applications)
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Figure 1

Figure 1
<p>Atoka shale sample used in the pressure transmission tests (PTTs).</p> Full article ">Figure 2
<p>Experimental set up of PTT [<a href="#B19-energies-10-00651" class="html-bibr">19</a>].</p> Full article ">Figure 3
<p>PTT of Atoka shale. (<b>a</b>) #1 Atoka shale sample; (<b>b</b>) #2 Atoka shale sample.</p> Full article ">Figure 4
<p>Pressure load model of shale formation in numerical simulation.</p> Full article ">Figure 5
<p>Flow chart of numerical simulation.</p> Full article ">Figure 6
<p>Cell subdivision of the calculation model in numerical simulation (3600 grids and 7440 nodes).</p> Full article ">Figure 7
<p>Time dependent pore fluid pressure contour map. The unit of pressure is defaulted as Pa in FLAC3D™, the same as below. (<b>a</b>) 1 h; (<b>b</b>) 24 h.</p> Full article ">Figure 8
<p>Pore fluid pressure of shale in contact with sea water vs. time at different distance.</p> Full article ">Figure 9
<p>Pore fluid pressure of shale in contact with sea water vs. distance at different time.</p> Full article ">Figure 10
<p>Pore fluid pressure contour map with different drilling fluid pressure. (<b>a</b>) 1 h at 30 MPa (<span class="html-italic">P<sub>f</sub></span>); (<b>b</b>) 1 h at 40 MPa (<span class="html-italic">P<sub>f</sub></span>); (<b>c</b>) 24 h at 30 MPa (<span class="html-italic">P<sub>f</sub></span>); and (<b>d</b>) 24 h at 40 MPa (<span class="html-italic">P<sub>f</sub></span>).</p> Full article ">Figure 11
<p>Influence of drilling fluid types on pore fluid pressure transmission of shale. (<b>a</b>) Near the wellbore; (<b>b</b>) 0.2 m from the wellbore.</p> Full article ">Figure 12
<p>Time dependent pore pressure transmission boundary in the shale. (<b>a</b>) 10 h (BM); (<b>b</b>) 10 h (BM + NP); (<b>c</b>) 24 h (BM); (<b>d</b>) 24 h (BM + NP); (<b>e</b>) 48 h (BM); and (<b>f</b>) 48 h (BM + NP).</p> Full article ">Figure 13
<p>Time dependent stress contour map. The symbol “−” before the numbers refers to compressive stress. Otherwise, it refers to tensile stress, the same as follows. (<b>a</b>) <span class="html-italic">x</span> direction stress for 1 h; (<b>b</b>) <span class="html-italic">y</span> direction stress for 1 h; (<b>c</b>) <span class="html-italic">x</span> direction stress for 48 h; and (<b>d</b>) <span class="html-italic">y</span> direction stress for 48 h.</p> Full article ">Figure 14
<p>Time dependent stress near the wellbore at the minimum horizontal stress direction.</p> Full article ">Figure 15
<p>Shear stress distribution at different times with sea water. (<b>a</b>) 1 h; (<b>b</b>) 48 h.</p> Full article ">Figure 16
<p>Displacement contour map around the surrounding rock. (<b>a</b>) <span class="html-italic">x</span> direction displacement for 1 h; (<b>b</b>) <span class="html-italic">y</span> direction displacement for 1 h.</p> Full article ">Figure 17
<p>Displacement change trend of the surrounding rock. (<b>a</b>) <span class="html-italic">x</span> direction at the minimum horizontal stress direction; (<b>b</b>) <span class="html-italic">y</span> direction at the maximum horizontal stress direction.</p> Full article ">Figure 18
<p>Plastic yield distribution of the surrounding rock. (<b>a</b>) 24 h; (<b>b</b>) 48 h.</p> Full article ">Figure 19
<p>Contrast on plastic yield distribution of the surrounding rock with different fluid density. (<b>a</b>) 1 h at 30 MPa (<span class="html-italic">P<sub>f</sub></span>); (<b>b</b>) 1 h at 40 MPa (<span class="html-italic">P<sub>f</sub></span>); (<b>c</b>) 24 h at 30 MPa (<span class="html-italic">P<sub>f</sub></span>); and (<b>d</b>) 24 h at 40 MPa (<span class="html-italic">P<sub>f</sub></span>).</p> Full article ">Figure 20
<p>Contrast in the stress difference of the surrounding rock with/without NP.</p> Full article ">Figure 21
<p>Contrast of the shear stress distribution of the surrounding rock with/without NP. (<b>a</b>) BM for 10 h; (<b>b</b>) “BM + NP” for 10 h; (<b>c</b>) BM for 48 h; and (<b>d</b>) “BM + NP” for 48 h.</p> Full article ">Figure 22
<p>Contrast on the yield zone distribution of the surrounding rock with/without the NP. (<b>a</b>) BM for 10 h; (<b>b</b>) “BM + NP” for 10 h; (<b>c</b>) BM for 24 h; and (<b>d</b>) “BM + NP” for 24 h.</p> Full article ">Figure 23
<p>PTT curves of Longmaxi group shale in China with different solutions.</p> Full article ">Figure 24
<p>SEM pictures of the shale. (<b>a</b>) Original shale magnified by 2400 times; (<b>b</b>) Shale contacted with nano-SiO<sub>2</sub> in PTT magnified by 2400 times; (<b>c</b>) Original shale magnified by 30,000 times; and (<b>d</b>) Shale contacted with nano-SiO<sub>2</sub> in PTT magnified by 30,000 times.</p> Full article ">Figure 25
<p>Statistics of pore size distribution of SEM pictures. (<b>a</b>) Original shale; (<b>b</b>) Shale contacted with nano-SiO<sub>2</sub>.</p> Full article ">Figure 26
<p>A sparse and dense cell subdivision result of the calculation model in numerical simulation. (<b>a</b>) 1800 grids and 3720 nodes; (<b>b</b>) 7200 grids and 14880 nodes.</p> Full article ">Figure 27
<p>Contrast on the yield zone distribution of shear failure of the surrounding rock with/without the NP and with more sparse mesh. (<b>a</b>) BM for 10 h; (<b>b</b>) “BM + NP” for 10 h; (<b>c</b>) BM for 24 h; and (<b>d</b>) “BM + NP” for 24 h.</p> Full article ">Figure 27 Cont.
<p>Contrast on the yield zone distribution of shear failure of the surrounding rock with/without the NP and with more sparse mesh. (<b>a</b>) BM for 10 h; (<b>b</b>) “BM + NP” for 10 h; (<b>c</b>) BM for 24 h; and (<b>d</b>) “BM + NP” for 24 h.</p> Full article ">Figure 28
<p>Contrast on the yield zone distribution of shear failure of the surrounding rock with/without the NP and with denser mesh. (<b>a</b>) BM for 10 h; (<b>b</b>) “BM + NP” for 10 h; (<b>c</b>) BM for 24 h; and (<b>d</b>) “BM + NP” for 24 h.</p> Full article ">
16730 KiB  
Article
Flow Behavior and Displacement Mechanisms of Nanoparticle Stabilized Foam Flooding for Enhanced Heavy Oil Recovery
by Teng Lu, Zhaomin Li and Yan Zhou
Energies 2017, 10(4), 560; https://doi.org/10.3390/en10040560 - 20 Apr 2017
Cited by 28 | Viewed by 6532
Abstract
In this study, nanoparticle stabilized foam experiments were performed in bulk tests, micromodels, and sandpacks at elevated temperatures and pressures to investigate the flow behavior and displacement mechanisms for enhanced heavy oil recovery. The results from the bulk tests showed that the stability [...] Read more.
In this study, nanoparticle stabilized foam experiments were performed in bulk tests, micromodels, and sandpacks at elevated temperatures and pressures to investigate the flow behavior and displacement mechanisms for enhanced heavy oil recovery. The results from the bulk tests showed that the stability of the foam and oil in water (O/W) emulsion improved when silica nanoparticles (SiO2) were added, compared with the anionic surfactant alone. Also, the SiO2 nanoparticles increased the dilatational viscoelasticity of the gas-water interface, which is an important fluid property and mechanism for improving heavy oil recovery. The micromodel studies demonstrated that several gas bubbles and oil droplets were stably dispersed during the nanoparticle stabilized foam flooding. The gas bubbles and oil droplets plug pores through capture-plugging and bridge-plugging, thereby increasing the sweep efficiency. The trapped residual oil is gradually pushed to the pores by the elastic forces of bubbles. Subsequently, the residual oil is pulled into oil threads by the flowing gas bubbles. Then, a greater improvement in displacement efficiency is obtained. The sandpack tests showed that the tertiary oil recovery of nanoparticle stabilized foam flooding can reach about 27% using 0.5 wt % SiO2 nanoparticles. The foam slug size of 0.3 pore volume (PV) and the gas liquid ratio (GLR) of 3:1 were found to be the optimum conditions in terms of heavy oil recovery by nanoparticle stabilized foam flooding in this study. A continuous nanoparticle dispersion and N2 could be more effective compared with the cyclic injection pattern. Full article
(This article belongs to the Special Issue Nanotechnology for Oil and Gas Applications)
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Figure 1

Figure 1
<p>(<b>a</b>) Image of the micromodel test experimental setup; (<b>b</b>) a simplified schematic of the micromodel test experimental setup.</p> Full article ">Figure 2
<p>Image of the micromodel.</p> Full article ">Figure 3
<p>Simplified schematic of the sandpack test experimental setup.</p> Full article ">Figure 4
<p>Half-life of various foam systems at different temperatures: 0.5 wt % HY-2 solution and1.0 wt % SiO<sub>2</sub> nanoparticles with 0.5 wt % HY-2 dispersion.</p> Full article ">Figure 5
<p>Relationship of dilational viscoelasticity with the frequency of different systems at 30 °C: 0.5 wt % HY-2 solution/N<sub>2</sub> interface and 1.0 wt % SiO<sub>2</sub> nanoparticles with 0.5 wt % HY-2 aqueous dispersion/N<sub>2</sub> interface.</p> Full article ">Figure 6
<p>Photos of the bottle test for oil and brine at room temperature. (<b>a</b>) Oil and brine before mixing; (<b>b</b>) Oil and brine after being turned upside down five times; (<b>c</b>) Oil and nanoparticle-surfactant before mixing; (<b>d</b>) Oil and nanoparticle-surfactant after being turned upside down five times.</p> Full article ">Figure 7
<p>Half-life of the emulsions at different temperatures (surfactant emulsion, 0.5 wt % HY-2 solution + oil; nanoparticle-surfactant dispersion emulsion, 0.5 wt % HY-2 + 1 wt % nanoparticle + oil).</p> Full article ">Figure 8
<p>Schematic of nanoparticle bridging between oil droplets.</p> Full article ">Figure 9
<p>Nanoparticle-surfactant-stabilized gas bubbles near the inlet of the micromodel. (<b>a</b>) 0.01 PV foam injected; (<b>b</b>) 0.2 PV foam injected.</p> Full article ">Figure 10
<p>Oil droplets in the porous media.</p> Full article ">Figure 11
<p>Flowing gas bubbles accelerating the formation of oil droplets. (<b>a</b>) Gas bubbles deform when in contact with an oil droplet; (<b>b</b>) Oil droplets are formed under the action of gas bubbles.</p> Full article ">Figure 12
<p><b>The</b> micro-elastic force (<span class="html-italic">F</span><sub>e</sub>) of gas bubbles to strip the oil droplet.</p> Full article ">Figure 13
<p>Gas bubbles and oil droplets flowing in the porous media.</p> Full article ">Figure 14
<p>An oil droplet driven by gas bubbles.</p> Full article ">Figure 15
<p>Micro-elastic force (<span class="html-italic">F</span><sub>e</sub>) acting on the flowing oil droplets.</p> Full article ">Figure 16
<p>Capture-plugging in pore-throat. (<b>a</b>) Gas bubble capture-plugging; (<b>b</b>) Oil droplet capture-plugging.</p> Full article ">Figure 17
<p>Force analysis for the capture-plugging of pore-throats with gas bubbles.</p> Full article ">Figure 18
<p>Gas bubble remigration in a pore-throat. (<b>a</b>) 0.251 PV foam injected; (<b>b</b>) 0.262 PV foam injected; (<b>c</b>) 0.271 PV foam injected; (<b>d</b>) 0.275 PV foam injected.</p> Full article ">Figure 19
<p>Force analysis during the remigration of gas bubbles in pore-throats. (<b>a</b>) Capture-plugging; (<b>b</b>) Elastic deformation; (<b>c</b>) Steady migration; (<b>d</b>) Deformation recovery.</p> Full article ">Figure 20
<p>Bridge-plugging in pore-throats. (<b>a</b>) Gas bubble bridge-plugging; (<b>b</b>) Oil droplet bridge-plugging.</p> Full article ">Figure 21
<p>Force analysis for bridge-plugging in pore-throats with gas bubbles.</p> Full article ">Figure 22
<p>Image of residual oil droplets trapped in the sand grains.</p> Full article ">Figure 23
<p>Residual oil droplet trapping after water flooding.</p> Full article ">Figure 24
<p>The micro-elastic force (<span class="html-italic">F</span><sub>e</sub>) acting on residual oil droplets trapped in pore-throats.</p> Full article ">Figure 25
<p>Pore-scale images of the residual oil droplets pushed by the gas bubbles. (<b>a</b>) 0.105 PV; (<b>b</b>) 0.124 PV.</p> Full article ">Figure 26
<p>Pore-level images of the formation of oil threads. (<b>a</b>) 0.108 PV; (<b>b</b>) 0.135 PV.</p> Full article ">Figure 27
<p>Pore-level images of the formation of oil threads in the interchange of pores. (<b>a</b>) 0.148 PV; (<b>b</b>) 0.159 PV.</p> Full article ">Figure 28
<p>The micro-elastic force (<span class="html-italic">F</span><sub>e</sub>) of gas bubbles mobilizing oil droplets.</p> Full article ">Figure 29
<p>The micro-elastic force (<span class="html-italic">F</span><sub>e</sub>) of gas bubbles mobilizing oil droplets at the interchange of pores.</p> Full article ">Figure 30
<p>Effect of the nanoparticle concentration on oil recovery.</p> Full article ">Figure 31
<p>Differential pressure changes as a function of the fluid injected for Runs 1 and 4.</p> Full article ">Figure 32
<p>Effect of foam slug size on oil recovery.</p> Full article ">Figure 33
<p>Effect of the GLR on oil recovery.</p> Full article ">Figure 34
<p>Injection patterns of the nanoparticle dispersion and N<sub>2</sub>.</p> Full article ">Figure 35
<p>Effect of the injection pattern on oil recovery.</p> Full article ">
4100 KiB  
Article
CO2 Foam Stability Improvement Using Polyelectrolyte Complex Nanoparticles Prepared in Produced Water
by Negar Nazari, Jyun-Syung Tsau and Reza Barati
Energies 2017, 10(4), 516; https://doi.org/10.3390/en10040516 - 11 Apr 2017
Cited by 33 | Viewed by 5224
Abstract
Despite the increasing interest in CO2 foam flooding for enhanced oil recovery applications, it is challenging to have a successful field operation as the performance of the surfactant is often affected by the presence of crude oil and salinity of the water. [...] Read more.
Despite the increasing interest in CO2 foam flooding for enhanced oil recovery applications, it is challenging to have a successful field operation as the performance of the surfactant is often affected by the presence of crude oil and salinity of the water. It is also challenging to dispose of huge amounts of water associated with the field operation. Due to the incompatibility of the produced water with chemicals used in the foam system, the produced water cannot be used as an injecting fluid. The objective of this project is to design a chemical system compatible with produced water which may fully utilize the oil field produced water as an injecting fluid and make the foam injection economically viable and environmentally friendly. In this study, we investigate the performance of a foam system with a surfactant and the addition of polyelectrolyte and polyelectrolyte complex nanoparticles (PECNP) in various salinities of produced water. A recipe is developed to prepare a nanoparticle solution that is sustainable in high salinity produced water. The rheological property of the foam, the stability, and durability of the foam with and without the presence of crude oil are measured and compared as the water salinity is changed. It is found that foam stability and durability deteriorated when water salinity increased. However, by the addition of polyelectrolyte and PECNP in the system, the foam stability and durability was improved even in high salinity water with or without the presence of crude oil. Full article
(This article belongs to the Special Issue Nanotechnology for Oil and Gas Applications)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Schematic diagram of the interfacial tension measurement setup [<a href="#B13-energies-10-00516" class="html-bibr">13</a>] (with permission from Society of Petroleum Engineers, 2015).</p> Full article ">Figure 2
<p>Schematic diagram of the Anton Paar rheometer setup [<a href="#B13-energies-10-00516" class="html-bibr">13</a>] (with permission from Society of Petroleum Engineers, 2015).</p> Full article ">Figure 3
<p>Schematic diagram of the Anton Paar rheometer setup [<a href="#B13-energies-10-00516" class="html-bibr">13</a>] (with permission from Society of Petroleum Engineers, 2015).</p> Full article ">Figure 4
<p>Interfacial tension vs. the surfactant concentration for different systems in 33,667 ppm salinity of diluted MLP brine.</p> Full article ">Figure 5
<p>Interfacial tension vs. the surfactant concentration for different systems in 67,333 ppm salinity of diluted MLP brine.</p> Full article ">Figure 6
<p>The viscosity vs. shear rate for three different systems at 33,667 ppm salinity of diluted MLP brine.</p> Full article ">Figure 7
<p>The viscosity vs. shear rate for three different systems at 67,333 ppm salinity of diluted MLP brine.</p> Full article ">Figure 8
<p>The foam decay time for the surfactant and different ratios of PECNP:surfactant in 33,667 ppm salinity of diluted MLP brine. The ratio of 1:9 shows the best result.</p> Full article ">Figure 9
<p>The foam decay time for the surfactant and different ratios of PECNP:surfactant in 67,333 ppm salinity of diluted MLP brine. The ratio of 2:8 shows the best result.</p> Full article ">Figure 10
<p>The foam decay time for three different systems of generated CO<sub>2</sub> foam in 33,667 ppm salinity of diluted MLP brine without crude oil in the system. The PECNP-surfactant shows the best result.</p> Full article ">Figure 11
<p>The foam decay time for three different systems of generated CO<sub>2</sub> foam in 67,333 ppm salinity of diluted MLP brine without crude oil in the system. The PECNP-surfactant shows the best result.</p> Full article ">Figure 12
<p>Foam decay vs. time for three different systems of generated CO<sub>2</sub> foam in 33,667 ppm salinity of diluted MLP brine in the presence of Mississippian crude oil. The PECNP-surfactant system shows the most durable foam system in the presence of crude oil.</p> Full article ">Figure 13
<p>Foam decay vs. time for three different systems of generated CO<sub>2</sub> foam in 67,333 ppm salinity of diluted MLP brine in the presence of Mississippian crude oil. The PECNP-surfactant system shows the most durable foam system in the presence of crude oil.</p> Full article ">Figure 14
<p>CO<sub>2</sub> foam generated by (<b>a</b>) surfactant and (<b>b</b>) PECNP-surfactant with Mississippian crude oil after 15 min in 33,667 ppm salinity of diluted MLP brine.</p> Full article ">Figure 15
<p>CO<sub>2</sub> foam generated by (<b>a</b>) surfactant and (<b>b</b>) PECNP-surfactant with Mississippian crude oil after 5 min in 67,333 ppm salinity of diluted MLP brine.</p> Full article ">
4844 KiB  
Article
Effect of Nanoparticles on Spontaneous Imbibition of Water into Ultraconfined Reservoir Capillary by Molecular Dynamics Simulation
by Xiao Wang, Senbo Xiao, Zhiliang Zhang and Jianying He
Energies 2017, 10(4), 506; https://doi.org/10.3390/en10040506 - 8 Apr 2017
Cited by 19 | Viewed by 7454
Abstract
Imbibition is one of the key phenomena underlying processes such as oil recovery and others. In this paper, the influence of nanoparticles on spontaneous water imbibition into ultraconfined channels is investigated by molecular dynamics simulation. By combining the dynamic process of imbibition, the [...] Read more.
Imbibition is one of the key phenomena underlying processes such as oil recovery and others. In this paper, the influence of nanoparticles on spontaneous water imbibition into ultraconfined channels is investigated by molecular dynamics simulation. By combining the dynamic process of imbibition, the water contact angle in the capillary and the relationship of displacement (l) and time (t), a competitive mechanism of nanoparticle effects on spontaneous imbibition is proposed. The results indicate that the addition of nanoparticles decreases the displacement of fluids into the capillary dramatically, and the relationship between displacement and time can be described by l(t) ~ t1/2. Based on the analysis of the dynamic contact angle and motion behavior of nanoparticles, for water containing hydrophobic nanoparticles, the displacement decreases with the decrease of hydrophobicity, and the properties of fluids, such as viscosity and surface tension, play a major role. While for hydrophilic nanoparticles, the displacement of fluids increases slightly with the increase of hydrophilicity in the water-wet capillary and simulation time, which can be ascribed to disjoining pressure induced by “sticking nanoparticles”. This study provides new insights into the complex interactions between nanoparticles and other components in nanofluids in the spontaneous imbibition, which is crucially important to enhanced oil recovery. Full article
(This article belongs to the Special Issue Nanotechnology for Oil and Gas Applications)
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<p>The simulation system contains a water-based nanofluid (red) laden with well-distributed spherical nanoparticles (light green) and a capillary (blue): (<b>a</b>) the 3D perspective of the top view; and (<b>b</b>) the side view.</p> Full article ">Figure 2
<p>The snapshots of nanofluids with different types of nanoparticles as time evolutions. Here, the <span class="html-italic">x</span>-axis shows the wettability of nanoparticles changing via characteristic energy and the <span class="html-italic">y</span>-axis is the simulation time.</p> Full article ">Figure 3
<p>(<b>a</b>) The density distribution profiles of the nanofluids along the capillary at simulation time 2.0 ns. Different types of nanoparticles (characteristic energy increases from 0.15 to 0.50) are used in the nanofluids. Here, the x axis is the distance from the entrance of the capillary, and the y axis is the density of the fluids. Different background colors show different regions: (green) Part I; (pink) Part II; (yellow) Part III. (<b>b</b>) Water configuration in different regions: (blue) Part I; (pink) Part II. The yellow atoms are the capillary, while the red and white atoms are oxygen and hydrogen, respectively.</p> Full article ">Figure 3 Cont.
<p>(<b>a</b>) The density distribution profiles of the nanofluids along the capillary at simulation time 2.0 ns. Different types of nanoparticles (characteristic energy increases from 0.15 to 0.50) are used in the nanofluids. Here, the x axis is the distance from the entrance of the capillary, and the y axis is the density of the fluids. Different background colors show different regions: (green) Part I; (pink) Part II; (yellow) Part III. (<b>b</b>) Water configuration in different regions: (blue) Part I; (pink) Part II. The yellow atoms are the capillary, while the red and white atoms are oxygen and hydrogen, respectively.</p> Full article ">Figure 4
<p>The nanofluid displacement as a function of time in the capillary: (<b>a</b>) for water and hydrophobic nanoparticles; and (<b>b</b>) for hydrophilic nanoparticles.</p> Full article ">Figure 5
<p>(<b>a</b>) Schematic of the extremity of the shell and fitting the contact angle; dynamic contact angles of different nanofluids in the cylindrical pore from (<b>b</b>) to (<b>d</b>): (<b>b</b>) water and hydrophobic nanoparticles; (<b>c</b>) water and mix-wettability nanoparticles; and (<b>d</b>) hydrophilic nanoparticles, where the smoothed lines are the running average of the scattered data points.</p> Full article ">Figure 6
<p>(<b>a</b>) The configuration of fluids containing water molecules and hydrophobic and hydrophilic nanoparticles in imbibition simulation systems at 2.0 ns and 4.0 ns; and (<b>b</b>) Three types of behaviors of hydrophilic nanoparticles in fluids.</p> Full article ">Figure 7
<p>(<b>a</b>) The density distribution profiles and (<b>b</b>) the radial distribution function for water molecules around nanoparticles; and (<b>c</b>) tracked movement configuration of the selected first water layer (black dashed line shows a certain tracking area radius of about 5.5 Å to the center of nanoparticles except for <span class="html-italic">ε</span> = 0.4) around nanoparticles at 1.9 ns and 2.0 ns. For <span class="html-italic">ε</span> = 0.4, the black circle is only shown for guidance as two nanoparticles are included.</p> Full article ">Figure 8
<p>The mean square displacement of nanoparticles in the capillary: (<b>a</b>) along the radial direction; and (<b>b</b>) along the axial direction.</p> Full article ">
3134 KiB  
Article
Alkaline Earth Element Adsorption onto PAA-Coated Magnetic Nanoparticles
by Qing Wang, Valentina Prigiobbe, Chun Huh and Steven L. Bryant
Energies 2017, 10(2), 223; https://doi.org/10.3390/en10020223 - 14 Feb 2017
Cited by 6 | Viewed by 4760
Abstract
In this paper, we present a study on the adsorption of calcium (Ca2+) onto polyacrylic acid-functionalized iron-oxide magnetic nanoparticles (PAA-MNPs) to gain an insight into the adsorption behavior of alkaline earth elements at conditions typical of produced water from hydraulic fracturing. [...] Read more.
In this paper, we present a study on the adsorption of calcium (Ca2+) onto polyacrylic acid-functionalized iron-oxide magnetic nanoparticles (PAA-MNPs) to gain an insight into the adsorption behavior of alkaline earth elements at conditions typical of produced water from hydraulic fracturing. An aqueous co-precipitation method was employed to fabricate iron oxide magnetic nanoparticles, whose surface was first coated with amine and then by PAA. To evaluate the Ca2+ adsorption capacity by PAA-MNPs, the Ca2+ adsorption isotherm was measured in batch as a function of pH and sodium chlorite (electrolyte) concentration. A surface complexation model accounting for the coulombic forces in the diffuse double layer was developed to describe the competitive adsorption of protons (H+) and Ca2+ onto the anionic carboxyl ligands of the PAA-MNPs. Measurements show that Ca2+ adsorption is significant above pH 5 and decreases with the electrolyte concentration. Upon adsorption, the nanoparticle suspension destabilizes and creates large clusters, which favor an efficient magnetic separation of the PAA-MNPs, therefore, helping their recovery and recycle. The model agrees well with the experiments and predicts that the maximum adsorption capacity can be achieved within the pH range of the produced water, although that maximum declines with the electrolyte concentration. Full article
(This article belongs to the Special Issue Nanotechnology for Oil and Gas Applications)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>TEM images of (<b>a</b>) MNPs; (<b>b</b>) NH<sub>2</sub>-MNPs; (<b>c</b>) PAA-8k-MNPs; (<b>d</b>) PAA-100k-MNPs; and (<b>e</b>) PAA-450k-MNPs.</p> Full article ">Figure 2
<p>Hydrodynamic diameter (<span class="html-italic">D<sub>H</sub></span>) distribution of MNPs, NH<sub>2</sub>-MNPs, PAA-8k-MNPs, PAA-100k-MNPs, and PAA-450k-MNPs in DI-H<sub>2</sub>O.</p> Full article ">Figure 3
<p>TGA curves of MNPs, NH<sub>2</sub>-MNPs, and PAA-MNPs.</p> Full article ">Figure 4
<p>XRD patterns of MNPs, NH<sub>2</sub>-MNPs, and PAA-MNPs with the location of the peaks of the reference magnetite (grey dots).</p> Full article ">Figure 5
<p>Langevin curves of MNPs, NH<sub>2</sub>-MNPs, and PAA-MNPs at room temperature.</p> Full article ">Figure 6
<p>Titration results expressed as adsorption capacity of H<sup>+</sup> vs. pH for NaCl concentration between 0.01 to 3.00 wt % corresponding to 0.002 to 0.3 m, respectively.</p> Full article ">Figure 7
<p>Adsorption results expressed as adsorption capacity of Ca<sup>2+</sup> vs. pH for NaCl concentration between 0.0 to 1 wt % corresponding to 0.0 to 0.1 m, respectively.</p> Full article ">Figure 8
<p>Experimental and modeling results expressed as normalized adsorption capacity (<span class="html-italic">q<sub>e</sub></span>/<span class="html-italic">Z<sub>t</sub></span>) of Ca<sup>2+</sup> vs. pH at various electrolyte concentration. Adsorption capacity of (<b>a</b>) protons and (<b>b</b>) calcium onto PAA-MNPs’ surface.</p> Full article ">Figure 9
<p>Effect of the electrolyte concentration and Ca<sup>2+</sup> adsorption on the stability of a PAA-MNPs’ suspension of concentration 0.01 g/L.</p> Full article ">Figure 10
<p>Adsorption capacity (<span class="html-italic">q<sub>e</sub></span>) and surface potential as a function of pH and cation concentration at various electrolyte concentrations. Parts (<b>a</b>), (<b>c</b>), (<b>e</b>), and (<b>g</b>) report the adsorption capacity of protons. Parts (<b>b</b>), (<b>d</b>), (<b>f</b>), and (<b>h</b>) report the adsorption capacity of calcium.</p> Full article ">
12419 KiB  
Article
Chemical Flooding in Heavy-Oil Reservoirs: From Technical Investigation to Optimization Using Response Surface Methodology
by Si Le Van and Bo Hyun Chon
Energies 2016, 9(9), 711; https://doi.org/10.3390/en9090711 - 5 Sep 2016
Cited by 48 | Viewed by 6862
Abstract
Heavy-oil resources represent a large percentage of global oil and gas reserves, however, owing to the high viscosity, enhanced oil recovery (EOR) techniques are critical issues for extracting this type of crude oil from the reservoir. According to the survey data in Oil [...] Read more.
Heavy-oil resources represent a large percentage of global oil and gas reserves, however, owing to the high viscosity, enhanced oil recovery (EOR) techniques are critical issues for extracting this type of crude oil from the reservoir. According to the survey data in Oil & Gas Journal, thermal methods are the most widely utilized in EOR projects in heavy oil fields in the US and Canada, and there are not many successful chemical flooding projects for heavy oil reported elsewhere in the world. However, thermal methods such as steam injection might be restricted in cases of thin formations, overlying permafrost, or reservoir depths over 4500 ft, for which chemical flooding becomes a better option for recovering crude oil. Moreover, owing to the considerable fluctuations in the oil price, chemical injection plans should be employed consistently in terms of either technical or economic viewpoints. The numerical studies in this work aim to clarify the predominant chemical injection schemes among the various combinations of chemical agents involving alkali (A), surfactant (S) and polymer (P) for specific heavy-oil reservoir conditions. The feasibilities of all potential injection sequences are evaluated in the pre-evaluation stage in order to select the most efficient injection scheme according to the variation in the oil price which is based on practical market values. Finally, optimization procedures in the post-evaluation stage are carried out for the most economic injection plan by an effective mathematic tool with the purpose of gaining highest Net Present Value (NPV) of the project. In technical terms, the numerical studies confirm the predominant performances of sequences in which alkali-surfactant-polymer (ASP) solution is injected after the first preflushing water whereby the recovery factor can be higher than 47%. In particular, the oil production performances are improved by injecting a buffering viscous fluid right after the first chemical slug rather than using a water slug in between. The results of the pre-evaluation show that two sequences of the ASP group have the highest NPV corresponding to the dissimilar applied oil prices. In the post-evaluation, the successful use of response surface methodology (RSM) in the estimation and optimization procedures with coefficients of determination R2 greater than 0.97 shows that the project can possibly gain 4.47 $MM at a mean oil price of 46.5 $/bbl with the field scale of a quarter five-spot pattern. Further, with the novel assumption of normal distribution for the oil price variation, the chemical flooding sequence of concurrent alkali-surfactant-polymer injection with a buffering polymer solution is evaluated as the most feasible scheme owing to the achievement of the highest NPV at the highly possible oil price of 40–55 $/bbl compared to the other scheme. Full article
(This article belongs to the Special Issue Nanotechnology for Oil and Gas Applications)
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Full article ">Figure 1
<p>Chemical properties used for the simulation: (<b>a</b>) the dependence of IFT values of O-W on the alkaline concentrations corresponding with no surfactant and 0.2 wt % surfactant in the solution; (<b>b</b>) viscosity behavior of the polymer solution.</p> Full article ">Figure 2
<p>Progression of relative permeability curves following the increase of surfactant: (<b>a</b>) initial condition; (<b>b</b>) intermediate curves formed by interpolation scheme; (<b>c</b>) straighten curves.</p> Full article ">Figure 3
<p>Oil production performance of water flooding and two flooding sequences of the (P) group in which the first injected polymer solutions have viscosity of 15 and 20 cp.</p> Full article ">Figure 4
<p>Oil production performance of water flooding and the sequences of the (A) group. The injections of a buffering ASP solution after the first alkaline flooding prove to be more efficient than using an AS slug with a buffering polymer solution, whereas the sequence without a buffering viscous fluid results in the worst performance owing to the severe oil bypassing mechanism.</p> Full article ">Figure 5
<p>Oil production performance of water flooding and the sequences of the (AS) group. The employments of AS solution right after the preflushing water does not improve the oil recovery significantly compared to water flooding even when using a buffering polymer solution.</p> Full article ">Figure 6
<p>Oil production performance of water flooding and the sequences of the (ASP) group: (<b>a</b>) first chemical slug is 15 cp ASP solution; (<b>b</b>) first chemical slug is 20 cp ASP solution. The repeated injections of ASP solution with a slug of water in between achieve the highest oil recovery than the sequences using a buffering polymer solution.</p> Full article ">Figure 7
<p>Comparison of the cumulative oil production between the most potential flooding sequences of each group and water flooding. The sequence W-ASP(20)-W-ASP(15)-W performs the highest oil production and also requires highest injected volume.</p> Full article ">Figure 8
<p>(<b>a</b>) The historical and forecasted oil price (<a href="http://www.eia.gov" target="_blank">www.eia.gov</a>); (<b>b</b>) Normal distribution of the oil price: probability density and cumulative distribution curves, with the maximum, minimum and mean values are 60, 30 and 46.5 $/bbl, respectively.</p> Full article ">Figure 9
<p>NPVs of different potential chemical flooding sequences and water flooding according to the change of the oil price from 30 to 60 $/bbl.</p> Full article ">Figure 10
<p>Estimated results of the oil recovery factor and total chemical expenses by the RSM: (<b>a</b>) W-ASP-W; (<b>b</b>) W-ASP-P-W.</p> Full article ">Figure 11
<p>Correlations between the design variables and the response surfaces. W-ASP-W: (<b>a1</b>) <span class="html-italic">a-s</span> vs. <span class="html-italic">RF</span>; (<b>a2</b>) <span class="html-italic">a-p</span> vs. <span class="html-italic">RF</span>; (<b>a3</b>) <span class="html-italic">p-w</span> vs. <span class="html-italic">RF</span>. W-ASP-P-W: (<b>b1</b>) <span class="html-italic">a-p<sub>2</sub></span> vs. <span class="html-italic">RF</span>; (<b>b2</b>) <span class="html-italic">p<sub>2</sub> -w</span> vs. <span class="html-italic">RF</span>. Within the range of the designs, the increases in the chemical concentration corresponding to a low injected volume of postflushing fluid help to improve the ultimate recovery factor.</p> Full article ">Figure 12
<p>NPVs for various oil prices: (<b>a</b>) 1000 estimated cases and the optimal case of W-ASP-W; (<b>b</b>) 1000 cases and the optimal case of W-ASP-P-W; (<b>c</b>) comparison of the most optimal cases of the two sequences.</p> Full article ">Figure 13
<p>NPV possibility curves following the normal distribution of the oil price for the most optimal case of two sequences.</p> Full article ">

Review

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8779 KiB  
Review
Nano-Based Drilling Fluids: A Review
by Zisis Vryzas and Vassilios C. Kelessidis
Energies 2017, 10(4), 540; https://doi.org/10.3390/en10040540 - 15 Apr 2017
Cited by 200 | Viewed by 18248
Abstract
Nanomaterials are engineered materials with at least one dimension in the range of 1–100 nm. Nanofluids—nanoscale colloidal suspensions containing various nanomaterials—have distinctive properties and offer unprecedented potential for various sectors such as the energy, cosmetic, aerospace and biomedical industries. Due to their unique [...] Read more.
Nanomaterials are engineered materials with at least one dimension in the range of 1–100 nm. Nanofluids—nanoscale colloidal suspensions containing various nanomaterials—have distinctive properties and offer unprecedented potential for various sectors such as the energy, cosmetic, aerospace and biomedical industries. Due to their unique physico-chemical properties, nanoparticles are considered as very good candidates for smart drilling fluid formulation, i.e., fluids with tailor-made rheological and filtration properties. However, due to the great risk of adapting new technologies, their application in oil and gas industry is not, to date, fully implemented. Over the last few years, several researchers have examined the use of various nanoparticles, from commercial to custom made particles, to formulate drilling fluids with enhanced properties that can withstand extreme downhole environments, particularly at high pressure and high temperature (HP/HT) conditions. This article summarizes the recent progress made on the use of nanoparticles as additives in drilling fluids in order to give such fluids optimal rheological and filtration characteristics, increase shale stability and achieve wellbore strengthening. Type, size and shape of nanoparticles, volumetric concentration, addition of different surfactants and application of an external magnetic field are factors that are critically evaluated and are discussed in this article. The results obtained from various studies show that nanoparticles have a great potential to be used as drilling fluid additives in order to overcome stern drilling problems. However, there are still challenges that should be addressed in order to take full advantage of the capabilities of such particles. Finally the paper identifies and discusses opportunities for future research. Full article
(This article belongs to the Special Issue Nanotechnology for Oil and Gas Applications)
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<p>Schematic representation of the drilling process. The wells can be vertical (pictured), inclined and even horizontal.</p> Full article ">Figure 2
<p>Measured apparent viscosity of bentonite fluid samples with and without addition of NP as a function of shear rate at 25 °C and atmospheric pressure [<a href="#B12-energies-10-00540" class="html-bibr">12</a>] (with permission from AADE, 2011).</p> Full article ">Figure 3
<p>(<b>a</b>) Shear stress versus shear rate of various drilling fluids at 25 °C and 6.9 bar. Solid lines indicate Herschel-Bulkley fits; (<b>b</b>) Cumulative LP/LT fluid filtration volumes as a function of square-root of time [<a href="#B13-energies-10-00540" class="html-bibr">13</a>] (with permission from Elsevier, 2015).</p> Full article ">Figure 4
<p>(<b>a</b>) Yield point values for samples that have 0.5 wt % of NP compared to that of the base fluid (7 wt % Ca-bentonite suspension) at different temperatures [<a href="#B11-energies-10-00540" class="html-bibr">11</a>] (with permission from SPE, 2016); (<b>b</b>) CT scan images of the filter cakes generated by the drilling fluids that have 0.5 wt % ferric oxide (Fe<sub>2</sub>O<sub>3</sub>) nanoparticle under static condition at a differential pressure of 300 psi and a temperature of 250 °F [<a href="#B15-energies-10-00540" class="html-bibr">15</a>] (with permission from SPE, 2017).</p> Full article ">Figure 5
<p>30 min HP/HT cumulative filtrate volume of the samples containing different concentrations of iron oxide (Fe<sub>2</sub>O<sub>3</sub>) nanoparticles at 250 °F and 300 psi differential pressure [<a href="#B10-energies-10-00540" class="html-bibr">10</a>] (with permission from SPE, 2015).</p> Full article ">Figure 6
<p>30 min-HP/HT filtrate volume of the base fluid and samples containing 0.5 wt % iron oxide and 0.5 wt % nanosilica at 250 °F and 300 psi differential pressure [<a href="#B10-energies-10-00540" class="html-bibr">10</a>] (with permission from SPE, 2015).</p> Full article ">Figure 7
<p>Rheograms for the samples have different concentrations of iron oxide (Fe<sub>2</sub>O<sub>3</sub>) nanoparticles in 7.0 wt % aqueous bentonite suspensions at 78 °F [<a href="#B10-energies-10-00540" class="html-bibr">10</a>] (with permission from SPE, 2015).</p> Full article ">Figure 8
<p>(<b>a</b>) Transmission Electron Microscope (TEM) image of the synthesized Fe<sub>3</sub>O<sub>4</sub> (magnetite) nanoparticles [<a href="#B20-energies-10-00540" class="html-bibr">20</a>] (with permission from ASME, 2016).; (<b>b</b>) Yield stress as a function of temperature for the base fluid and sample containing 0.5 wt % CM Fe<sub>3</sub>O<sub>4</sub> NP [<a href="#B21-energies-10-00540" class="html-bibr">21</a>] (with permission from SPE, 2016).</p> Full article ">Figure 9
<p>SEM images of the filter cakes formed from after HP/HT filtration test at 24.1 bar (300 psi) and 121 °C (250 °F) (magnification of ×5000) for the (<b>a</b>) base fluid; (<b>b</b>) nanofluid containing 0.5 wt % CM Fe<sub>3</sub>O<sub>4</sub> NP [<a href="#B21-energies-10-00540" class="html-bibr">21</a>] (with permission from SPE, 2016).</p> Full article ">Figure 10
<p>(<b>a</b>) SEM image of regular Pal (needle like clusters); (<b>b</b>) Yield point and plastic viscosity vs. temperature for the nano-modified drilling fluids [<a href="#B32-energies-10-00540" class="html-bibr">32</a>] (with permission from Elsevier, 2013).</p> Full article ">Figure 11
<p>(<b>a</b>) SEM image of a single large flake graphene oxide (LFGO) flake; (<b>b</b>) API filtration loss results for LFGO, PGO, a 1:1 mix and a 3:1 mix of LFGO and PGO suspensions at 2 g/L carbon-content concentrations in 2.9 g/L (0.75 lbm/bbl) xanthan gum solution [<a href="#B33-energies-10-00540" class="html-bibr">33</a>] (with permission from American Chemical Society, 2012).</p> Full article ">Figure 12
<p>Plots of (<b>a</b>) viscosity; and (<b>b</b>) shear stress as a function of shear rate for PAC/CNC/BTWDFs at various bentonite concentrations [<a href="#B38-energies-10-00540" class="html-bibr">38</a>] (with permission from American Chemical Society, 2015).</p> Full article ">Figure 13
<p>Comparison of experimental data and rheological models at 40 °C [<a href="#B44-energies-10-00540" class="html-bibr">44</a>] (with permission from Elsevier, 2016).</p> Full article ">Figure 14
<p>HP/HT fluid loss after aging at different MWCNTs concentration [<a href="#B45-energies-10-00540" class="html-bibr">45</a>] (copyright ANSInet, 2014).</p> Full article ">Figure 15
<p>(<b>a</b>) Predicted and measured shear stress shear rate data for 6.3 wt % bentonite mud containing 0.5 wt % silica nanoparticles using different rheological models; (<b>b</b>) Residual plot for 6.3 wt % bentonite mud containing 0.5 wt % silica nanoparticles [<a href="#B50-energies-10-00540" class="html-bibr">50</a>] (copyright Afolabi et al. 2017).</p> Full article ">Figure 16
<p>A schematic representation of mud losses while drilling in the case of (<b>a</b>) typical LCM; and (<b>b</b>) NP [<a href="#B2-energies-10-00540" class="html-bibr">2</a>] (with permission from Springer, 2015).</p> Full article ">Figure 17
<p>Trivariate models plots for shear stress and viscosity at different temperatures [<a href="#B7-energies-10-00540" class="html-bibr">7</a>] (copyright Elsevier, 2016).</p> Full article ">Figure 18
<p>Trivariate first-principles shear stress versus temperature and shear rate at different NP concentrations [<a href="#B8-energies-10-00540" class="html-bibr">8</a>] (with permission from SPE, 2017).</p> Full article ">Figure 19
<p>A fracture is quickly sealed by wellbore strengthening material isolating it from the wellbore, either (<b>a</b>) at the entrance of the fracture [<a href="#B58-energies-10-00540" class="html-bibr">58</a>] (with permission from SPE, 2015); or (<b>b</b>) by entering the fracture [<a href="#B59-energies-10-00540" class="html-bibr">59</a>] (with permission from SPE, 2010).</p> Full article ">Figure 20
<p>Comparison of gel strength of bentonite-based and nano-based fluids [<a href="#B1-energies-10-00540" class="html-bibr">1</a>] (with permission from SPE, 2011).</p> Full article ">Figure 21
<p>Variation of thermal conductivity of nano-enhanced water-based mud (NWBM) and microfluid-enhanced water-based mud (MWBM) for (<b>a</b>) CuO particles; and for (<b>b</b>) ZnO particles. Unfilled symbols: NWBM, filled symbols: MWBM [<a href="#B42-energies-10-00540" class="html-bibr">42</a>] (with permission from SPE, 2016).</p> Full article ">Figure 22
<p>Yield stress at different magnetic flux densities for fluids that contain 0.5 and 1.0 wt % of CM iron oxide (Fe<sub>3</sub>O<sub>4</sub>) NP [<a href="#B73-energies-10-00540" class="html-bibr">73</a>] (with permission from SPE, 2017).</p> Full article ">Figure 23
<p>Samples of α-Al<sub>2</sub>O<sub>3</sub> nanofluids (without any stabilizer) stability change with time [<a href="#B74-energies-10-00540" class="html-bibr">74</a>] (with permission from Elsevier, 2009).</p> Full article ">
7189 KiB  
Review
Application of Nanoparticles in Enhanced Oil Recovery: A Critical Review of Recent Progress
by Xiaofei Sun, Yanyu Zhang, Guangpeng Chen and Zhiyong Gai
Energies 2017, 10(3), 345; https://doi.org/10.3390/en10030345 - 11 Mar 2017
Cited by 470 | Viewed by 29720
Abstract
The injected fluids in secondary processes supplement the natural energy present in the reservoir to displace oil. The recovery efficiency mainly depends on the mechanism of pressure maintenance. However, the injected fluids in tertiary or enhanced oil recovery (EOR) processes interact with the [...] Read more.
The injected fluids in secondary processes supplement the natural energy present in the reservoir to displace oil. The recovery efficiency mainly depends on the mechanism of pressure maintenance. However, the injected fluids in tertiary or enhanced oil recovery (EOR) processes interact with the reservoir rock/oil system. Thus, EOR techniques are receiving substantial attention worldwide as the available oil resources are declining. However, some challenges, such as low sweep efficiency, high costs and potential formation damage, still hinder the further application of these EOR technologies. Current studies on nanoparticles are seen as potential solutions to most of the challenges associated with these traditional EOR techniques. This paper provides an overview of the latest studies about the use of nanoparticles to enhance oil recovery and paves the way for researchers who are interested in the integration of these progresses. The first part of this paper addresses studies about the major EOR mechanisms of nanoparticles used in the forms of nanofluids, nanoemulsions and nanocatalysts, including disjoining pressure, viscosity increase of injection fluids, preventing asphaltene precipitation, wettability alteration and interfacial tension reduction. This part is followed by a review of the most important research regarding various novel nano-assisted EOR methods where nanoparticles are used to target various existing thermal, chemical and gas methods. Finally, this review identifies the challenges and opportunities for future study regarding application of nanoparticles in EOR processes. Full article
(This article belongs to the Special Issue Nanotechnology for Oil and Gas Applications)
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<p>The categories of available EOR technologies.</p> Full article ">Figure 2
<p>FESEM images of some commonly used NPs: (<b>a</b>) TiO<sub>2</sub>; (<b>b</b>) Al<sub>2</sub>O<sub>3</sub>; (<b>c</b>) NiO; (<b>d</b>) SiO<sub>2</sub> [<a href="#B16-energies-10-00345" class="html-bibr">16</a>].</p> Full article ">Figure 3
<p>A schematic diagram of NPs with high surface to volume ratio.</p> Full article ">Figure 4
<p>The schematic of the EOR mechanisms of nanofluids.</p> Full article ">Figure 5
<p>The simulated shape of the meniscus profile in the wedge region [<a href="#B21-energies-10-00345" class="html-bibr">21</a>].</p> Full article ">Figure 6
<p>The schematic of two mechanisms causing pore channels plugging: (<b>a</b>) mechanical entrapment; (<b>b</b>) log-jamming.</p> Full article ">Figure 7
<p>Influence parameters of viscosities of SiO<sub>2</sub> nanofluids [<a href="#B28-energies-10-00345" class="html-bibr">28</a>].</p> Full article ">Figure 8
<p>A schematic diagram of rock wettability conditions of a rock-brine/nanofluid-oil system [<a href="#B41-energies-10-00345" class="html-bibr">41</a>].</p> Full article ">Figure 9
<p>Relative permeability curves. The symbols are experimental data. The notation AT and BT indicates that measurements were carried out after or before nanofluid treatment [<a href="#B37-energies-10-00345" class="html-bibr">37</a>].</p> Full article ">Figure 10
<p>SEM images of the measured calcite surface: (<b>A</b>) before; (<b>B</b>) after nano-modification; (<b>C</b>) high resolution; and (<b>D</b>) maximum resolution; (<b>E</b>) EDX analysis of carbonate rocks aged in fluids [<a href="#B28-energies-10-00345" class="html-bibr">28</a>].</p> Full article ">Figure 11
<p>Atomic force microscopy (AFM) images of the measured calcite surface: (<b>a</b>) before; (<b>b</b>) after nano-modification [<a href="#B28-energies-10-00345" class="html-bibr">28</a>].</p> Full article ">Figure 12
<p>Emulsions observed in the micromodel experiments during nanofluid flooding processes [<a href="#B34-energies-10-00345" class="html-bibr">34</a>].</p> Full article ">Figure 13
<p>Particle size analysis of crude oil under an optical microscope at X200 magnification: (<b>a</b>) mixed with 30,000 ppm saline water; (<b>b</b>) mixed with the Al<sub>2</sub>O<sub>3</sub> nanofluid [<a href="#B16-energies-10-00345" class="html-bibr">16</a>].</p> Full article ">Figure 14
<p>The advantages with the usage of nanocatalysts compared with traditional catalysts.</p> Full article ">Figure 15
<p>The schematic diagram of the nano-assisted steam-assisted gravity drainage (SAGD) process.</p> Full article ">Figure 16
<p>Micrometer-scale quantification of emulsion sizes: (<b>a</b>) images of o/w and w/o emulsions produced by a CO<sub>2</sub> flood and a NP-stabilized CO<sub>2</sub> foam flood; (<b>b</b>) size distribution of oil-in-water emulsions; (<b>c</b>) size distribution of water-in-oil emulsions [<a href="#B137-energies-10-00345" class="html-bibr">137</a>].</p> Full article ">Figure 16 Cont.
<p>Micrometer-scale quantification of emulsion sizes: (<b>a</b>) images of o/w and w/o emulsions produced by a CO<sub>2</sub> flood and a NP-stabilized CO<sub>2</sub> foam flood; (<b>b</b>) size distribution of oil-in-water emulsions; (<b>c</b>) size distribution of water-in-oil emulsions [<a href="#B137-energies-10-00345" class="html-bibr">137</a>].</p> Full article ">

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Correction: Hu, Z.; et al. Transport and Deposition of Carbon Nanoparticles in Saturated Porous Media. Energies 2017, 10, 1151
by Zhongliang Hu, Jin Zhao, Hui Gao, Ehsan Nourafkan and Dongsheng Wen
Energies 2017, 10(10), 1681; https://doi.org/10.3390/en10101681 - 24 Oct 2017
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Abstract
The author wishes to correct Figure 1b in this paper [1][...] Full article
(This article belongs to the Special Issue Nanotechnology for Oil and Gas Applications)
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<p>(<b>b</b>) TEM picture for carbon dots at ~5 nm.</p> Full article ">
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