Experimental Investigations and MD Simulation on Nanoparticle-Enhanced CO2-Responsive Foam (NECRF): Implications on CO2-EOR
Source abstract
Abstract
CO 2 -responsive foam (CRF) is a highly promising candidate for CO 2 -enhanced oil recovery (CO 2 -EOR) because it displays higher stability than the surfactant-stabilized foam owing to the formation of robust wormlike micelles (WLMs) upon exposure to CO 2 . In this work, the nanoparticle-enhanced CO 2 -responsive foam (NECRF) was properly prepared using lauryl ether sulfate sodium (LES)/diethylenetriamine/nano-SiO 2, and its interfacial properties and EOR potential were experimentally and numerically assessed, aiming to explore the feasibility and effectiveness of NECRF as a novel CO 2 -EOR technique. It was found that the interfacial expansion elastic modulus increased 6-fold after CO 2 stimulation. The modulus continued to increase with the introduction of nano-SiO 2 owing to the pronounced synergistic effect of WLMs and nanoparticles. In addition to increasing the viscosity of the foaming liquid, WLMs and nano-SiO 2 enhanced the shearing resistance of the NECRF as well. Calculations demonstrated that both the coarsening rate and the size distribution uniformity coefficient of NECRF were markedly lower than that of the LES foam, which subsequently inhibited NECRF decay and greatly improved its dynamic stability. Besides, molecular dynamics simulation revealed that adding inorganic salts to NECRF could notably enhance the foaming performance due to the intensified hydration of surfactant head groups and reduced binding energy of neighboring molecules. Nuclear magnetic resonance-assisted core flooding experiments validated the exceptional capacity of NECRF to sweep the low-permeability region and improve the conformance profile. Overall, these findings may provide valuable insights into the development and application of novel materials and strategies for the CO 2 -EOR.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Enhanced Oil Recovery Techniques · Pickering emulsions and particle stabilization · Hydrocarbon exploration and reservoir analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Key Laboratory of Oil & Gas Exploration and Development Theory and Technology, China University of Geosciences (Wuhan), Wuhan, Hubei Province 430074, PR China
School of Earth Resources, China University of Geosciences (Wuhan), Wuhan 430074, PR China
School of Mining and Petroleum, Department of Civil and Environmental Engineering, University of Alberta, Edmonton T6G 1H9, Canada
Funding
Natural Science Foundation of Hubei Province · China Scholarship Council
References (70)
Show source-provided references
1. Liao G. Z. · 1999
2. Bond, D.; Holbrook, O. Gas drive oil recovery process. U.S. Patent 2,866,507 A 1958.
3. 10.1021/ie201872v10.1021/ie201872v ↗
4. 10.1021/acs.energyfuels.1c0003510.1021/acs.energyfuels.1c00035 ↗
5. 10.1016/j.jcis.2018.03.09010.1016/j.jcis.2018.03.090 ↗
6. Rossen W. R. · 1996
7. 10.2118/199821-PA10.2118/199821-PA ↗
8. Olukoga, T. A.; Feng, Y. Machine learning models for predicting the rheology of nanoparticle-stabilized-CO2-foam fracturing fluid in reservoir conditions. In SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, Virtual, 2021.10.15530/AP-URTEC-2021-208308 ↗
9. 10.2118/56396-PA10.2118/56396-PA ↗
10. 10.2118/170840-PA10.2118/170840-PA ↗
11. Schramm L. L. · 2012
12. 10.1016/j.cej.2022.13945410.1016/j.cej.2022.139454 ↗
13. 10.1016/j.jcou.2014.12.00910.1016/j.jcou.2014.12.009 ↗
14. 10.1016/j.cej.2023.14452410.1016/j.cej.2023.144524 ↗
15. Telmadarreie, A. Evaluating the potential of CO2 foam and CO2 polymer enhanced foam for heavy oil recovery in fractured reservoirs: pore-scale and core-scale studies, Doctor of Philosophy, University of Alberta, 2017.10.2118/193785-MS ↗
16. 10.1021/acs.energyfuels.0c0204810.1021/acs.energyfuels.0c02048 ↗
17. Kaminsky, R. D.; Wattenbarger, R. C.; Szafranski, R. C.; Coutee, A. S. Guidelines for Polymer Flooding Evaluation and Development; European Association of Geoscientists & Engineers: Dubai, U.A.E, 2007.10.2523/IPTC-11200-MS ↗
18. Nguyen, D.; Sadeghi, N. Stable emulsion and demulsification in chemical EOR flooding: challenges and best practices. In SPE EOR Conference at Oil and Gas West Asia: Muscat, Oman, 2012.10.2118/154044-MS ↗
19. 10.1021/acsami.2c0222810.1021/acsami.2c02228 ↗
20. 10.1021/acsami.1c0844510.1021/acsami.1c08445 ↗
21. Telmadarreie, A.; Trivedi, J. J. Evaluating the performance of CO2 foam and CO2 polymer enhanced foam for heavy oil recovery: laboratory experiments in unconsolidated and consolidated porous media. In SPE International Heavy Oil Conference and Exhibition, Kuwait City, Kuwait, 2018.10.2118/193785-MS ↗
22. 10.1016/j.petrol.2017.08.01810.1016/j.petrol.2017.08.018 ↗
23. 10.1039/c7ta02038d10.1039/c7ta02038d ↗
24. 10.1021/acs.jpclett.9b0102310.1021/acs.jpclett.9b01023 ↗
25. 10.1016/j.fuel.2021.12030610.1016/j.fuel.2021.120306 ↗
26. 10.1021/la400051a10.1021/la400051a ↗
27. 10.1021/la702855910.1021/la7028559 ↗
28. 10.1039/c0sm00874e10.1039/c0sm00874e ↗
29. 10.1021/am500711310.1021/am5007113 ↗
30. 10.1021/acsami.2c0898610.1021/acsami.2c08986 ↗
31. 10.1021/acs.langmuir.5b0129510.1021/acs.langmuir.5b01295 ↗
32. 10.1016/j.cherd.2015.06.02610.1016/j.cherd.2015.06.026 ↗
33. 10.1021/acs.langmuir.8b0118710.1021/acs.langmuir.8b01187 ↗
34. 10.1016/j.ces.2019.05.03310.1016/j.ces.2019.05.033 ↗
35. 10.1016/j.jcis.2021.10.05810.1016/j.jcis.2021.10.058 ↗
36. 10.1021/acs.langmuir.1c0083210.1021/acs.langmuir.1c00832 ↗
37. 10.1021/acs.langmuir.1c0011210.1021/acs.langmuir.1c00112 ↗
38. 10.1016/j.jcis.2022.10.10210.1016/j.jcis.2022.10.102 ↗
39. 10.1021/acs.langmuir.1c0334710.1021/acs.langmuir.1c03347 ↗
40. 10.1016/j.jcis.2020.07.11010.1016/j.jcis.2020.07.110 ↗
41. 10.1021/acs.jced.6b0013510.1021/acs.jced.6b00135 ↗
42. 10.1016/j.jcis.2015.08.03110.1016/j.jcis.2015.08.031 ↗
43. 10.1016/j.petrol.2017.08.01810.1016/j.petrol.2017.08.018 ↗
44. 10.1016/j.colsurfa.2019.03.08710.1016/j.colsurfa.2019.03.087 ↗
45. 10.1021/la034747p10.1021/la034747p ↗
46. 10.1016/j.softx.2015.06.00110.1016/j.softx.2015.06.001 ↗
47. 10.1063/1.240842010.1063/1.2408420 ↗
48. 10.1103/PhysRevLett.90.07550310.1103/PhysRevLett.90.075503 ↗
49. 10.1016/0263-7855(96)00018-510.1016/0263-7855(96)00018-5 ↗
50. Lu, T. Sobtop, version [1.0(dev3.1)]. http://sobereva.com/soft/Sobtop (accessed Sep 20, 2023).
51. 10.1021/cm500365c10.1021/cm500365c ↗
52. 10.1021/acs.energyfuels.3c0496410.1021/acs.energyfuels.3c04964 ↗
53. Hunter R. J. · 2013
54. 10.1016/j.jconrel.2016.06.01710.1016/j.jconrel.2016.06.017 ↗
55. Tadros T. · 2007
56. 10.1016/j.cocis.2010.04.00110.1016/j.cocis.2010.04.001 ↗
57. 10.1016/0927-7757(95)03492-710.1016/0927-7757(95)03492-7 ↗
58. 10.1007/s00396-010-2227-510.1007/s00396-010-2227-5 ↗
59. 10.1016/j.colsurfa.2016.12.00410.1016/j.colsurfa.2016.12.004 ↗
60. Rothstein J. P. · Rheol. Rev. · 2008 · 2008 · 1
61. 10.1039/b705775j10.1039/b705775j ↗
62. Yuan L. · 2022
63. 10.1016/j.petrol.2021.10969810.1016/j.petrol.2021.109698 ↗
64. 10.1021/jz101365h10.1021/jz101365h ↗
65. 10.1021/la203952p10.1021/la203952p ↗
66. 10.1016/j.petrol.2020.10803910.1016/j.petrol.2020.108039 ↗
67. 10.1016/j.cocis.2010.05.01010.1016/j.cocis.2010.05.010 ↗
68. 10.1016/j.colsurfa.2015.11.01210.1016/j.colsurfa.2015.11.012 ↗
69. 10.1021/jp907438x10.1021/jp907438x ↗
70. 10.1016/j.molliq.2022.12040410.1016/j.molliq.2022.120404 ↗