Application of SiO2–water nanofluid to enhance oil recovery

Ramezanpour, Milad; Siavashi, Majid

doi:10.1007/s10973-018-7156-4

Cited by 53 publications

(12 citation statements)

References 56 publications

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“…By professional solid waste treatment companies, the generated waste drilling chips and waste drilling fluids are transported away from the drilling site to a centralized treatment plant. is method can eliminate the drilling fluid sinkhole, oil-based drilling waste management is mostly used in this method, and the treatment cost of this method is determined according to the degree of the environmental impact of pollutants and the size of the hazard [10]. e cost of this method varies according to the degree of environmental impact and hazard, and it has a greater economic advantage and industrial value for blocks with more concentrated drilling operations.…”

Section: Related Research Workmentioning

confidence: 99%

[Retracted] Application of Computer Simulation Optimization Algorithm in Waste Treatment of Drilling Engineering

Shu

Zhang²

2021

Complexity

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The existing computer technology is used to conduct an in-depth study and analysis of drilling waste treatment, and the results are analyzed by computer simulation optimization algorithms. Based on the system theory, we define the research system, combine the unique characteristics of the technological innovation mechanism of drilling waste treatment, and use the internal and external factors affecting the technological innovation dynamics of drilling waste treatment, such as drilling waste treatment capacity, from the current actual situation. On this basis, factor analysis is used to analyze the factors affecting technological innovation dynamics from both internal and external aspects of the system, establish a system model of technological innovation dynamics of drilling waste disposal, and give the initial values of the simulation model. This will reduce the pollution of the environment and enhance the competitiveness of enterprises. Drilling waste treatment technology is getting increased attention, but at this stage, there is no suitable technology innovation mechanism for drilling waste treatment. Through the simulation trend chart obtained by sensitivity analysis, the key factors in the system are found, and the innovation power mechanism of drilling waste treatment technology is constructed, which provides a basis for the formulation of enterprise technological innovation strategies and the development of technological innovation activities. Research on the dynamic mechanism of drilling waste treatment technology innovation explores a waste treatment mechanism suitable for the drilling industry, so as to promote the steady development of the drilling industry and at the same time provide theoretical support for the treatment of drilling engineering waste.

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Section: Related Research Workmentioning

confidence: 99%

[Retracted] Application of Computer Simulation Optimization Algorithm in Waste Treatment of Drilling Engineering

Shu

Zhang²

2021

Complexity

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“…Ferrofluids, also known as ferromagnetic fluids, are an innovative class of nanofluids which comprises magnetic nanoparticles suspended into the base fluids like water, EG, and oil [1]. For the past decades, a lot of research has been done on these fluids which revealed that the ferrofluids are beneficial for heat transfer applications, i.e., oil recovery [2], heat exchanger [3], power generation [4], electronics cooling [5], and solar systems [6] because of their unique chemical, thermal, physical, mechanical, and magnetic properties [1]. These ferromagnetic nanomaterials embody maghemite (Fe 2 O 3 or γ-Fe 2 O 3 ), magnetite (Fe 3 O 4 ), and ferrites composed of nickel (Ni), cobalt (Co), Manganese (Mn), silver (Ag), barium (Ba), lithium (Li), chromium (Cr), and zinc (Zn) [7].…”

Section: Introductionmentioning

confidence: 99%

Stability Analysis of Fe₃O₄‐OA‐MWCNT Nanocomposite‐Based Nanofluid

Nadeem

Purree

Ashiq

et al. 2022

Journal of Nanomaterials

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The aim of this project is to fabricate a highly stable Fe3O4-OA-MWCNT composite and its colloidal suspension in polyalphaolefin (PAO) base fluid for heat transfer applications. The nanocomposite was produced in three mass ratios (0.5 : 1, 1 : 1, and 1.5 : 1) to explore the concentration effects on the stability of the nanocomposite. XRD analysis and FTIR spectroscopy were conducted to inspect the phase and composition of the synthesized nanocomposite. The crystallite sizes (3.75 nm, 7.74 nm, and 7.52 nm) and dislocation densities of each composite were calculated, and it was revealed that the samples with high concentration of iron oxide nanoparticles showed small defects in their lattices. Dispersion stability of ferrofluids was also examined by natural deposition method for 365 days. The ferrofluids displayed high stability for more than one year with no sign of sedimentation. Thermal conductivity of the nanofluid was also measured via. A transient plane source method and a linear trend with slight deviation were observed.

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“…Researchers have investigated various methods of modeling and simulation to predict the thermal and rheological behavior of NFs. Due to the importance of fossil energy and the need of communities for it, some researchers investigated the effect of adding nanoparticles to oil reservoirs numerically and studied the rate of oil recovery 41–47 . The results of modeling can be used in other studies to reduce the cost of testing 48,49 .…”

Section: Introductionmentioning

confidence: 99%

Optimization and modeling of thermal conductivity and viscosity of Cu/engine oil nanofluids by NSGA‐II using RSM

Esfe

Motallebi

2020

Math Methods in App Sciences

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This study provides the optimization of the thermophysical properties of Cu/engine oil nanofluid. In this optimization, the objective functions were determined using response surface methodology (RSM) to analyze the experimental data of nanofluid viscosity and thermal conductivity (TC). Two equations are presented for the accurate prediction of TC and viscosity data. The nondominated sorting genetic algorithm II (NSGA‐II) method was used for multi‐objective optimization (Mo‐O), and Pareto's front was introduced to study optimal viscosity and TC. According to the results, the highest TC and the lowest viscosity occur when the temperature and solid volume fraction of the nanofluid are at their maximum values.

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Application of SiO2–water nanofluid to enhance oil recovery

Cited by 53 publications

References 56 publications

[Retracted] Application of Computer Simulation Optimization Algorithm in Waste Treatment of Drilling Engineering

[Retracted] Application of Computer Simulation Optimization Algorithm in Waste Treatment of Drilling Engineering

Stability Analysis of Fe₃O₄‐OA‐MWCNT Nanocomposite‐Based Nanofluid

Optimization and modeling of thermal conductivity and viscosity of Cu/engine oil nanofluids by NSGA‐II using RSM

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Application of SiO2–water nanofluid to enhance oil recovery

Cited by 53 publications

References 56 publications

[Retracted] Application of Computer Simulation Optimization Algorithm in Waste Treatment of Drilling Engineering

[Retracted] Application of Computer Simulation Optimization Algorithm in Waste Treatment of Drilling Engineering

Stability Analysis of Fe3O4‐OA‐MWCNT Nanocomposite‐Based Nanofluid

Optimization and modeling of thermal conductivity and viscosity of Cu/engine oil nanofluids by NSGA‐II using RSM

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Stability Analysis of Fe₃O₄‐OA‐MWCNT Nanocomposite‐Based Nanofluid