Journal of Thermal Analysis and Calorimetry

, Volume 135, Issue 1, pp 565–580 | Cite as

Application of SiO2–water nanofluid to enhance oil recovery

A new hybrid optimization approach using pattern search and PSO algorithms
  • Milad Ramezanpour
  • Majid SiavashiEmail author


The present study aims to investigate effects of nanofluid flooding on EOR and also compares its performance with water flooding in field scale using the published experimental data provided from core-scale studies. The nanofluid is based on water including silica nanoparticles. The relative permeability curves of water, nanofluid and oil for a light crude oil core sample obtained in an experimental study are used in this numerical investigation. A 2D heterogeneous reservoir model is constructed using the permeability and porosity of the last layer of SPE-10 model. It has been shown that nanofluid flooding can substantially improve the oil recovery in comparison with the water flooding case. Afterward, the operational parameters of the 13 injection and production wells have been optimized in order to meet the maximum cumulative oil production. First, pattern search (PS) algorithm was implemented which has a good convergence speed, but with a high probability of trapping in local optimum points. Particle swarm optimization (PSO) approach has also been employed, which requires a large number of population (to approach the global optimum) with so many simulations. Accordingly, a hybrid PSO–PS algorithm with confined domain is proposed. The hybrid algorithm starts with PSO and depending on the distribution density of the values of each parameter, confines the searching domain and provides a proper initial guess to be used by PS. It is concluded that the hybrid PSO–PS method could obtain the optimal solution with a high convergence speed and reduced possibility of trapping in local optimums.


Nanofluid Enhanced oil recovery (EOR) Optimization Pattern search (PS) Particle swarm optimization (PSO) Hybrid 


  1. 1.
    Negin C, Ali S, Xie Q. Application of nanotechnology for enhancing oil recovery—a review. Petroleum. 2016;2(4):324–33.Google Scholar
  2. 2.
    Bell AT. The impact of nanoscience on heterogeneous catalysis. Science. 2003;299(5613):1688.Google Scholar
  3. 3.
    Perez JM. Iron oxide nanoparticles: hidden talent. Nat Nanotechnol. 2007;2(9):535–6.Google Scholar
  4. 4.
    Esfe MH, Saedodin S, Bahiraei M, Toghraie D, Mahian O, Wongwises S. Thermal conductivity modeling of MgO/EG nanofluids using experimental data and artificial neural network. J Therm Anal Calorim. 2014;118(1):287–94.Google Scholar
  5. 5.
    Barkalina N, Charalambous C, Jones C, Coward K. Nanotechnology in reproductive medicine: emerging applications of nanomaterials. Nanomed Nanotechnol Biol Med. 2014;10(5):e921–38.Google Scholar
  6. 6.
    Thines RK, Mubarak NM, Nizamuddin S, Sahu JN, Abdullah EC, Ganesan P. Application potential of carbon nanomaterials in water and wastewater treatment: A review. J Taiwan Inst Chem Eng. 2017;72(Supplement C):116–33.Google Scholar
  7. 7.
    Socas-Rodríguez B, González-Sálamo J, Hernández-Borges J, Rodríguez-Delgado MÁ. Recent applications of nanomaterials in food safety. TrAC Trends Anal Chem. 2017;96:172–200.Google Scholar
  8. 8.
    Ananthakumar S, Ramkumar J, Babu SM. Semiconductor nanoparticles sensitized TiO2 nanotubes for high efficiency solar cell devices. Renew Sustain Energy Rev. 2016;57(Supplement C):1307–21.Google Scholar
  9. 9.
    Wang L, Zhang F. Preparation and optical properties of Sn- and Ga-doped indium oxide semiconductor nanoparticles. Ceram Int. 2017;43(13):9723–8.Google Scholar
  10. 10.
    Mahian O, Kianifar A, Kalogirou SA, Pop I, Wongwises S. A review of the applications of nanofluids in solar energy. Int J Heat Mass Transf. 2013;57(2):582–94.Google Scholar
  11. 11.
    Zhang Z, Yuan Y, Ouyang L, Sun Q, Cao X, Alelyani S. Enhanced thermal properties of Li2CO3–Na2CO3–K2CO3 nanofluids with nanoalumina for heat transfer in high-temperature CSP systems. J Therm Anal Calorim. 2017;128(3):1783–92.Google Scholar
  12. 12.
    Bellos E, Tzivanidis C. Thermal efficiency enhancement of nanofluid-based parabolic trough collectors. J Therm Anal Calorim. 2018. Scholar
  13. 13.
    Stalin PMJ, Arjunan TV, Matheswaran MM, Sadanandam N. Experimental and theoretical investigation on the effects of lower concentration CeO2/water nanofluid in flat-plate solar collector. J Therm Anal Calorim. 2017. Scholar
  14. 14.
    Rashidi S, Eskandarian M, Mahian O, Poncet S. Combination of nanofluid and inserts for heat transfer enhancement. J Therm Anal Calorim (2018). Scholar
  15. 15.
    Motamedi P, Bargozin H, Pourafshary P. Management of implementation of nanotechnology in upstream oil industry: An analytic hierarchy process analysis. J Energy Resour Technol. 2017;140(5):052908.Google Scholar
  16. 16.
    Al-Malki N, Pourafshary P, Al-Hadrami H, Abdo J. Controlling bentonite-based drilling mud properties using sepiolite nanoparticles. Pet Explor Dev. 2016;43(4):717–23.Google Scholar
  17. 17.
    Shakib JT, Kanani V, Pourafshary P. Nano-clays as additives for controlling filtration properties of water–bentonite suspensions. J Pet Sci Eng. 2016;138:257–64.Google Scholar
  18. 18.
    Kong X, Ohadi M. Applications of micro and nano technologies in the oil and gas industry-overview of the recent progress. In: Abu Dhabi international petroleum exhibition and conference (2010).Google Scholar
  19. 19.
    Thomas S. Enhanced oil recovery-an overview. Oil Gas Sci Technol Rev IFP. 2008;63(1):9–19.Google Scholar
  20. 20.
    Rahman Arifur, Happy Fatema Akter, Ahmed Salim, Hossain M Enamul. Development of scaling criteria for enhanced oil recovery: a review. J Pet Sci Eng. 2017;158(Supplement C):66–79.Google Scholar
  21. 21.
    Shafiei A, Dusseault MB, Zendehboudi S, Chatzis I. A new screening tool for evaluation of steamflooding performance in Naturally Fractured Carbonate Reservoirs. Fuel. 2013;108(Supplement C):502–14.Google Scholar
  22. 22.
    Lv M, Wang S. Pore-scale modeling of a water/oil two-phase flow in hot water flooding for enhanced oil recovery. RSC Adv. 2015;5(104):85373–82.Google Scholar
  23. 23.
    Giacchetta G, Leporini M, Marchetti B. Economic and environmental analysis of a Steam Assisted Gravity Drainage (SAGD) facility for oil recovery from Canadian oil sands. Appl. Energy. 2015;142(Supplement C):1–9.Google Scholar
  24. 24.
    Changfeng X, Wenlong G, Jihong H. Research and application of fire-flooding technologies in post-steam injected heavy oil reservoir. In: Presented at the international petroleum technology conference (2013).Google Scholar
  25. 25.
    Sayyafzadeh M, Keshavarz A. Optimisation of gas mixture injection for enhanced coalbed methane recovery using a parallel genetic algorithm. J Nat Gas Sci Eng. 2016;33:942–53.Google Scholar
  26. 26.
    Negin C, Ali S, Xie Q. Most common surfactants employed in chemical enhanced oil recovery. Petroleum. 2017;3(2):197–211.Google Scholar
  27. 27.
    Lu J, et al. New surfactant developments for chemical enhanced oil recovery. J Pet Sci Eng. 2014;120(Supplement C):94–101.Google Scholar
  28. 28.
    Joonaki E, Erfani Gahrooei HR, Ghanaatian S. Experimental study on adsorption and wettability alteration aspects of a new chemical using for enhanced oil recovery in carbonate oil reservoirs. J Unconv Oil Gas Resour. 2016;15(Supplement C):11–21.Google Scholar
  29. 29.
    Ehtesabi H, Ahadian MM, Taghikhani V, Ghazanfari MH. Enhanced heavy oil recovery in sandstone cores using TiO2 nanofluids. Energy Fuels. 2014;28(1):423–30.Google Scholar
  30. 30.
    Ayatollahi S, Zerafat MM. Nanotechnology-assisted EOR techniques: new solutions to old challenges. In: Presented at the SPE international oilfield nanotechnology conference and exhibition (2012).Google Scholar
  31. 31.
    Mothé CG, Correia DZ, de França FP, Riga AT. Thermal and rheological study of polysaccharides for enhanced oil recovery. J Therm Anal Calorim. 2006;85(1):31–6.Google Scholar
  32. 32.
    Raffa P, Broekhuis AA, Picchioni F. Polymeric surfactants for enhanced oil recovery: A review. J Pet Sci Eng. 2016;145(Supplement C):723–33.Google Scholar
  33. 33.
    Moradi B, Pourafshary P, Jalali F, Mohammadi M, Emadi MA. Experimental study of water-based nanofluid alternating gas injection as a novel enhanced oil-recovery method in oil-wet carbonate reservoirs. J Nat Gas Sci Eng. 2015;27:64–73.Google Scholar
  34. 34.
    Hasannejad R, Pourafshary P, Vatani A, Sameni A. Application of silica nanofluid to control initiation of fines migration. Pet Explor Dev. 2017;44(5):850–9.Google Scholar
  35. 35.
    Bera A, Belhaj H. Application of nanotechnology by means of nanoparticles and nanodispersions in oil recovery—a comprehensive review. J Nat Gas Sci Eng. 2016;34(Supplement C):1284–309.Google Scholar
  36. 36.
    Alomair OA, Matar KM, Alsaeed YH. Experimental study of enhanced-heavy-oil recovery in Berea sandstone cores by use of nanofluids applications. SPE Reserv Eval Eng. 2015;18(03):387–99.Google Scholar
  37. 37.
    Hendraningrat L, Torsaeter O. Unlocking the potential of metal oxides nanoparticles to enhance the oil recovery. In: Presented at the offshore technology conference-Asia (2014).Google Scholar
  38. 38.
    Al-Farsi H, Pourafshary P, Al-Maamari RS. Application of nanoparticles to improve the performance of microwave assisted gravity drainage (MWAGD) as a thermal oil recovery method. In: Presented at the SPE EOR conference at oil and gas west Asia (2016).Google Scholar
  39. 39.
    Assef Y, Arab D, Pourafshary P. Application of nanofluid to control fines migration to improve the performance of low salinity water flooding and alkaline flooding. J Pet Sci Eng. 2014;124:331–40.Google Scholar
  40. 40.
    Parvazdavani M, Masihi M, Ghazanfari MH. Monitoring the influence of dispersed nano-particles on oil–water relative permeability hysteresis. J Pet Sci Eng. 2014;124:222–31.Google Scholar
  41. 41.
    Salmachi A, Sayyafzadeh M, Haghighi M. Infill well placement optimization in coal bed methane reservoirs using genetic algorithm. Fuel. 2013;111:248–58.Google Scholar
  42. 42.
    Sayyafzadeh M. Reducing the computation time of well placement optimisation problems using self-adaptive metamodelling. J Pet Sci Eng. 2017;151:143–58.Google Scholar
  43. 43.
    Azamipour V, Assareh M, Mittermeir GM. An improved optimization procedure for production and injection scheduling using a hybrid genetic algorithm. Chem Eng Res Des. 2017. Scholar
  44. 44.
    Siavashi M, Doranehgard MH. Particle swarm optimization of thermal enhanced oil recovery from oilfields with temperature control. Appl Therm Eng. 2017;123:658–69.Google Scholar
  45. 45.
    Siavashi M, Garusi H, Derakhshan S. Numerical simulation and optimization of steam-assisted gravity drainage with temperature, rate, and well distance control using an efficient hybrid optimization technique. Numer Heat Transf Part Appl. 2017;72(9):721–44.Google Scholar
  46. 46.
    Bjørnar E. The potential of hydrophilic silica nanoparticles for EOR purposes. Master Thesis. Norwegian University of Science and Technology; 2012.Google Scholar
  47. 47.
    Youssif MI, El-Maghraby RM, Saleh SM, Elgibaly A. Silica nanofluid flooding for enhanced oil recovery in sandstone rocks. Egypt J Pet. 2017. Scholar
  48. 48.
    Wasan D, Nikolov A, Kondiparty K. The wetting and spreading of nanofluids on solids: role of the structural disjoining pressure. Curr Opin Colloid Interface Sci. 2011;16(4):344–9.Google Scholar
  49. 49.
    Mcelfresh PM, Holcomb DL, Ector D. Application of nanofluid technology to improve recovery in oil and gas wells. In: Presented at the SPE international oilfield nanotechnology conference and exhibition (2012).Google Scholar
  50. 50.
    Chengara A, Nikolov AD, Wasan DT, Trokhymchuk A, Henderson D. Spreading of nanofluids driven by the structural disjoining pressure gradient. J Colloid Interface Sci. 2004;280(1):192–201.Google Scholar
  51. 51.
    Dahle GS. Investigation of how hydrophilic silica nanoparticles affect oil recovery in Berea sandstone: an experimental study. Master Thesis. Norwegian University of Science and Technology; 2014. Google Scholar
  52. 52.
    Roustaei A, Moghadasi J, Bagherzadeh H, Shahrabadi A. An experimental investigation of polysilicon nanoparticles’ recovery efficiencies through changes in interfacial tension and wettability alteration. In: SPE international oilfield nanotechnology conference and exhibition (2012).Google Scholar
  53. 53.
    Li S, Hendraningrat L, Torsaeter O. Improved oil recovery by hydrophilic silica nanoparticles suspension: 2 phase flow experimental studies. In: IPTC 2013: international petroleum technology conference (2013).Google Scholar
  54. 54.
    Li S, Torsæter O. An experimental investigation of EOR mechanisms for nanoparticles fluid in glass micromodel. In: Presented at the paper SCA2014-022 was prepared for presentation at the international symposium of the society of core analysts held in Avignon, France, pp 8–11 (2014).Google Scholar
  55. 55.
    Parvazdavani M, Masihi M, Ghazanfari MH, Sherafati M, Mashayekhi L. Investigation of the effect of water based nano-particles addition on hysteresis of oil-water relative permeability curves. In: SPE international oilfield nanotechnology conference and exhibition (2012).Google Scholar
  56. 56.
    Marini F, Walczak B. Particle swarm optimization (PSO). A tutorial. Chemom Intell Lab Syst. 2015;149:153–65.Google Scholar
  57. 57.
    France van den Bergh. An analysis of particle swarm optimizers. Ph.D. Thesis, University of Pretoria (2011).Google Scholar
  58. 58.
    Du K-L, Swamy MNS. Search and optimization by metaheuristics. New York: Springer; 2016.Google Scholar
  59. 59.
    Venter G, Sobieszczanski-Sobieski J. Particle swarm optimization. AIAA J. 2003;41(8):1583–9.Google Scholar
  60. 60.
    Christie MA, Blunt MJ. Tenth SPE comparative solution project: a comparison of upscaling techniques. In: SPE reservoir simulation symposium (2001).Google Scholar

Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2018

Authors and Affiliations

  1. 1.Applied Multi-Phase Fluid Dynamics Lab., School of Mechanical EngineeringIran University of Science and TechnologyTehranIran

Personalised recommendations