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Aydin Larestani

Observed name: Larestani, Aydin
ORCID: 0000-0002-8320-0176
Observed ORCID: 0000-0002-8320-0176
OpenAlex ID: A5037841609
Predicting formation damage of oil fields due to mineral scaling during water-flooding operations: Gradient boosting decision tree and cascade-forward back-propagation network
2021 · Aydin Larestani, Seyed Pezhman Mousavi, et al. · Journal of Petroleum Science and Engineering · 69
Modeling of methane adsorption capacity in shale gas formations using white-box supervised machine learning techniques
2021 · Menad Nait Amar, Aydin Larestani, et al. · Journal of Petroleum Science and Engineering · 69
Predicting viscosity of CO2–N2 gaseous mixtures using advanced intelligent schemes
2021 · Arefeh Naghizadeh, Aydin Larestani, et al. · Journal of Petroleum Science and Engineering · 64
Modelling minimum miscibility pressure of CO2-crude oil systems using deep learning, tree-based, and thermodynamic models: Application to CO2 sequestration and enhanced oil recovery
2023 · Qichao Lv, Rong Zheng, et al. · Separation and Purification Technology · 56
Experimental measurement and modeling of water-based drilling mud density using adaptive boosting decision tree, support vector machine, and K-nearest neighbors: A case study from the South Pars gas field
2021 · Abbas Hashemizadeh, Ahmad Maaref, et al. · Journal of Petroleum Science and Engineering · 53
Modeling of wax disappearance temperature (WDT) using soft computing approaches: Tree-based models and hybrid models
2021 · Behnam Amiri-Ramsheh, Majid Safaei-Farouji, et al. · Journal of Petroleum Science and Engineering · 46
Predicting the surfactant-polymer flooding performance in chemical enhanced oil recovery: Cascade neural network and gradient boosting decision tree
2022 · Aydin Larestani, Seyed Pezhman Mousavi, et al. · Alexandria Engineering Journal · 44
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On the evaluation of permeability of heterogeneous carbonate reservoirs using rigorous data-driven techniques
2021 · Mehdi Mahdaviara, Aydin Larestani, et al. · Journal of Petroleum Science and Engineering · 33
Predictive modeling of CO2 solubility in piperazine aqueous solutions using boosting algorithms for carbon capture goals
2024 · Mohammad-Reza Mohammadi, Aydin Larestani, et al. · Scientific Reports · 28
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Toward accurate prediction of carbon dioxide (CO2) compressibility factor using tree-based intelligent schemes (XGBoost and LightGBM) and equations of state
2025 · Behnam Amiri-Ramsheh, Aydin Larestani, et al. · Results in Engineering · 20
White-box machine-learning models for accurate interfacial tension prediction in hydrogen–brine mixtures
2024 · Qichao Lv, Jinglei Xue, et al. · Clean Energy · 20
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Experimental measurement and compositional modeling of bubble point pressure in crude oil systems: Soft computing approaches, correlations, and equations of state
2022 · Aydin Larestani, Abdolhossein Hemmati-Sarapardeh, et al. · Journal of Petroleum Science and Engineering · 20
Toward reliable prediction of CO2 uptake capacity of metal–organic frameworks (MOFs): implementation of white-box machine learning
2024 · Aydin Larestani, Ahmadreza Jafari-Sirizi, et al. · Adsorption · 14
Introduction
2020 · Abdolhossein Hemmati-Sarapardeh, Aydin Larestani, et al. · Elsevier eBooks · 14
Compositional Modeling of the Oil Formation Volume Factor of Crude Oil Systems: Application of Intelligent Models and Equations of State
2022 · Aydin Larestani, Abdolhossein Hemmati-Sarapardeh, et al. · ACS Omega · 12
Training and optimization algorithms
2020 · Abdolhossein Hemmati-Sarapardeh, Aydin Larestani, et al. · Elsevier eBooks · 11
Compositional modeling of solution gas–oil ratio (Rs): a comparative study of tree-based models, neural networks, and equations of state
2025 · Aydin Larestani, Sara Sahebalzamani, et al. · Scientific Reports · 8
Micromechanical variation of organic matter (kerogen type I) under controlled thermal maturity progression
2024 · Bo Liu, Aydin Larestani, et al. · Journal of Rock Mechanics and Geotechnical Engineering · 6
Leveraging advanced ensemble learning techniques for methane uptake prediction in metal organic frameworks
2025 · Aydin Larestani, Behnam Amiri-Ramsheh, et al. · Scientific Reports · 5
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Intelligent models
2020 · Abdolhossein Hemmati-Sarapardeh, Aydin Larestani, et al. · Elsevier eBooks · 5
Application of intelligent models in reservoir and production engineering
2020 · Abdolhossein Hemmati-Sarapardeh, Aydin Larestani, et al. · Elsevier eBooks · 4
Contrasting mechanical evolution of bakken shale under hydrous and anhydrous pyrolysis: A nanoindentation-based assessment
2026 · Mengdi Sun, Jiajun Fu, et al. · International Journal of Rock Mechanics and Mining Sciences · 3
Application of intelligent models in exploration engineering
2020 · Abdolhossein Hemmati-Sarapardeh, Aydin Larestani, et al. · Elsevier eBooks · 2
Weaknesses and strengths of intelligent models in petroleum industry
2020 · Abdolhossein Hemmati-Sarapardeh, Aydin Larestani, et al. · Elsevier eBooks · 2
Application of intelligent models in drilling engineering
2020 · Abdolhossein Hemmati-Sarapardeh, Aydin Larestani, et al. · Elsevier eBooks · 1
Works count: 27
Citation count: 609
H-index: 14
I10-index: 16
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