Evidence map›Paper›PMID 40802673›Full record

ArticlePloS one2025

An improved mathematical model for hypothetical oil reservoir for optimum oil recovery using magnetic nanomaterials.

Mudasar Zafar, Hamzah Sakidin, Abida Hussain, Ahmed Daabo, Farman Ullah, Rajasegeran Ramasamy, Roslinda Nazar, Mikhail Sheremet, Abdullah Al-Yaari, Iliyas Karim Khan

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Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Mudasar ZafarSchool of Mathematics, Actuarial and Quantitative Studies (SOMAQS), Asia Pacific University of Technology and Innovation (APU), Bukit Jalil, Kuala Lumpur, Malaysia.ORCID https://orcid.org/0000-0002-5669-5839
Hamzah SakidinDepartment of Fundamental and Applied Sciences, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Perak, Malaysia.
Abida HussainDepartment of Fundamental and Applied Sciences, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Perak, Malaysia.
Ahmed DaaboMining Engineering Department, College of Petroleum and Mining Engineering, The University of Mosul, Mosul, Iraq.
Farman UllahDepartment of Physics, University of Science and Technology, Bannu, Khyber Pakhtunkhwa, Pakistan.
Rajasegeran RamasamySchool of Mathematics, Actuarial and Quantitative Studies (SOMAQS), Asia Pacific University of Technology and Innovation (APU), Bukit Jalil, Kuala Lumpur, Malaysia.
Roslinda NazarDepartment of Mathematical Sciences, Faculty of Science & Technology, Universiti Kebangsaan Malaysia, UKM Bangi, Selangor, Malaysia.
Mikhail SheremetLaboratory on Convective Heat and Mass Transfer, Tomsk State University, Tomsk, Russia.
Abdullah Al-YaariDepartment of Mathematics, Faculty of Applied Science, Thamar University, Dhamar, Yemen.
Iliyas Karim KhanDepartment of Fundamental and Applied Sciences, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Perak, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the oil and gas industry, enhanced oil recovery (EOR) strategies for unconventional reservoirs, characterized by complex geometries, differ significantly from those used in conventional reservoirs. This research focuses on the impact of 3D hexagonal prism geometries on EOR in hypothetical oil reservoirs using silicon dioxide (SiO₂) magnetic nanoparticles under liquid-phase flow conditions, a topic not extensively explored in existing literature. We developed an improved magnetohydrodynamic (MHD) mathematical models to simulate oil recovery processes in these geometries, using ANSYS Fluent for finite volume analysis. We developed an improved magnetohydrodynamic (MHD) model by incorporating magnetic field-induced pressure terms, nanoparticle transport losses, and a 3D hexagonal prism geometry that reflects complex reservoir behavior. These enhancements extend beyond traditional Darcy-based models by integrating magnetic permeability, viscosity alteration, and magnetic field-pore interactions. The model evaluates the impact of key reservoir parameters including porosity (ϕ = 0.1-0.4), injection flow rate (0.01-0.05 mL/min), and nanoparticle concentration (Ψ = 0.01-0.04), under different magnetic field configurations. Porosity and flow rate were also found to significantly influence recovery performance, highlighting the practical adaptability of the model for diverse reservoir conditions. Findings indicate that proximity of a magnetic field to cavity structures enhances oil recovery rates, with a significant 29.08% increase in recovery from nanoflooding compared to water flooding.Future research will extend this framework to study green, eco-friendly nanoparticles under elevated temperature and pressure, aiming to improve thermal stability, reduce environmental risks, and enhance recovery efficiency in more extreme reservoir conditions.

Indexed as

Magnetite NanoparticlesModels, TheoreticalNanostructuresPetroleumHydrodynamicsMagnetic FieldsOil and Gas IndustryPorositySilicon DioxideMagnetite NanoparticlesPetroleumSilicon Dioxide

Identifiers

PMID40802673
PMCPMC12349132

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.