A Mathematical Model of Imbibition Phenomenon in Homogeneous Porous Media

Choksi, Bhumika G.; Singh, Twinkle

doi:10.1615/specialtopicsrevporousmedia.2018021445

Special Topics Rev Porous Media

2019

DOI: 10.1615/specialtopicsrevporousmedia.2018021445

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A Mathematical Model of Imbibition Phenomenon in Homogeneous Porous Media

Bhumika G. Choksi

Twinkle Singh

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Cited by 6 publications

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Predictive modeling of oil and water saturation during secondary recovery with supervised learning

Sulaiman

Khan

2023

Physics of Fluids

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In the petroleum reservoir, the secondary oil recovery (SOR) process is employed by injecting water into wells to enhance the moment of oil toward the production wells. The SOR process gives rise to the instability (fingering) phenomena due to the injecting force and the difference in the wettability and viscosity of the oil and water at the common interface. Since the late 1800s, mathematical models of petroleum reservoirs have been extensively used in the oil and gas industry. In this paper, we investigated the saturation of two immiscible fluid (oil and water) flows through homogeneous porous media during the SOR process by solving the modeled partial differential equation using the supervised machine learning algorithm based on feedforward back-propagated neural networks (FFBNNs) and Levenberg–Marquardt (LM) optimization algorithm. The designed scientific computing technique (FFBNN-LMA) is further employed to study the detailed sensitivity analysis of the approximate solutions. Performance measures like average absolute deviations, Theils' inequality measure, regression, and Nash–Sutcliffe model efficiency coefficient.

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Predictive modeling of oil and water saturation during secondary recovery with supervised learning

Sulaiman

Khan

2023

Physics of Fluids

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Study of imbibition phenomenon in homogeneous porous medium model for oil recovery with temporal-fractional approach

Yadav,

Singh

2023

Journal of Applied Physics

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In this article, the phenomenon of countercurrent imbibition in a specific displacement method occurs within a dipping homogeneous porous medium. This phenomenon plays a vital role in the process of oil recovery, which motivates our analysis. To overcome the difficulties associated with the nonlinear partial differential equation governing the countercurrent imbibition phenomenon, we have been using two distinct methods: the natural transform decomposition method and the variational iteration transform method with their convergence analysis for solutions. These techniques give different perspectives and enable us to obtain approximate solutions. Notably, both the proposed methods demonstrate the potential for substantial production of oil during the secondary oil recovery process in the petroleum industry. The obtained results by the proposed methods show the efficiency in optimizing the oil recovery rate.

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Entropy-based analysis and economic scrutiny of magneto thermal natural convection enhancement in a nanofluid-filled porous trapezium-shaped cavity having localized baffles

Zidan

Tayebi

Dogonchi³

et al. 2022

Waves in Random and Complex Media

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A Mathematical Model of Imbibition Phenomenon in Homogeneous Porous Media

Cited by 6 publications

References 0 publications

Predictive modeling of oil and water saturation during secondary recovery with supervised learning

Predictive modeling of oil and water saturation during secondary recovery with supervised learning

Study of imbibition phenomenon in homogeneous porous medium model for oil recovery with temporal-fractional approach

Entropy-based analysis and economic scrutiny of magneto thermal natural convection enhancement in a nanofluid-filled porous trapezium-shaped cavity having localized baffles

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