| Applications of artificial intelligence techniques in the petroleum industry A Hemmati-Sarapardeh, A Larestani, NA Menad, S Hajirezaie Gulf Professional Publishing, 2020 | 78 | 2020 |
| Modeling of methane adsorption capacity in shale gas formations using white-box supervised machine learning techniques MN Amar, A Larestani, Q Lv, T Zhou, A Hemmati-Sarapardeh Journal of Petroleum Science and Engineering 208, 109226, 2022 | 52 | 2022 |
| Predicting formation damage of oil fields due to mineral scaling during water-flooding operations: Gradient boosting decision tree and cascade-forward back-propagation network A Larestani, SP Mousavi, F Hadavimoghaddam, A Hemmati-Sarapardeh Journal of Petroleum Science and Engineering 208, 109315, 2022 | 49 | 2022 |
| Predicting viscosity of CO2–N2 gaseous mixtures using advanced intelligent schemes A Naghizadeh, A Larestani, MN Amar, A Hemmati-Sarapardeh Journal of Petroleum Science and Engineering 208, 109359, 2022 | 42 | 2022 |
| 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 … A Hashemizadeh, A Maaref, M Shateri, A Larestani, ... Journal of Petroleum Science and Engineering 207, 109132, 2021 | 42 | 2021 |
| Modelling minimum miscibility pressure of CO2-crude oil systems using deep learning, tree-based, and thermodynamic models: Application to CO2 sequestration and enhanced oil … Q Lv, R Zheng, X Guo, A Larestani, F Hadavimoghaddam, M Riazi, ... Separation and Purification Technology 310, 123086, 2023 | 39 | 2023 |
| Modeling of wax disappearance temperature (WDT) using soft computing approaches: Tree-based models and hybrid models B Amiri-Ramsheh, M Safaei-Farouji, A Larestani, R Zabihi, ... Journal of Petroleum Science and Engineering 208, 109774, 2022 | 36 | 2022 |
| Predicting the surfactant-polymer flooding performance in chemical enhanced oil recovery: Cascade neural network and gradient boosting decision tree A Larestani, SP Mousavi, F Hadavimoghaddam, M Ostadhassan, ... Alexandria Engineering Journal 61 (10), 7715-7731, 2022 | 29 | 2022 |
| On the evaluation of permeability of heterogeneous carbonate reservoirs using rigorous data-driven techniques M Mahdaviara, A Larestani, MN Amar, A Hemmati-Sarapardeh Journal of Petroleum Science and Engineering 208, 109685, 2022 | 24 | 2022 |
| Experimental measurement and compositional modeling of bubble point pressure in crude oil systems: Soft computing approaches, correlations, and equations of state A Larestani, A Hemmati-Sarapardeh, A Naseri Journal of Petroleum Science and Engineering 212, 110271, 2022 | 16 | 2022 |
| Chapter 1: Introduction A Hemmati-Sarapardeh, A Larestani, NA Menad, S Hajirezaie Applications of artificial intelligence techniques in the petroleum industry …, 2020 | 10 | 2020 |
| Compositional modeling of the oil formation volume factor of crude oil systems: application of intelligent models and equations of state A Larestani, A Hemmati-Sarapardeh, Z Samari, M Ostadhassan ACS omega 7 (28), 24256-24273, 2022 | 8 | 2022 |
| Chapter 2: Intelligent models A Hemmati-Sarapardeh, A Larestani, NA Menad, S Hajirezaie Applications of Artificial Intelligence Techniques in the Petroleum Industry …, 2020 | 6 | 2020 |
| Chapter 4: Application of intelligent models in reservoir and production engineering A Hemmati-Sarapardeh, A Larestani, NA Menad, S Hajirezaie Applications of artificial intelligence techniques in the petroleum industry …, 2020 | 4 | 2020 |
| Chapter 3: Training and optimization algorithms A Hemmati-Sarapardeh, A Larestani, NA Menad, S Hajirezaie Applications of artificial intelligence techniques in the petroleum industry …, 2020 | 4 | 2020 |
| Toward reliable prediction of CO2 uptake capacity of metal–organic frameworks (MOFs): implementation of white-box machine learning A Larestani, A Jafari-Sirizi, F Hadavimoghaddam, S Atashrouz, ... Adsorption 30 (8), 1985-2003, 2024 | 2 | 2024 |
| White-box machine-learning models for accurate interfacial tension prediction in hydrogen–brine mixtures Q Lv, J Xue, X Li, F Rezaei, A Larestani, S Norouzi-Apourvari, H Abdollahi, ... Clean Energy 8 (5), 252-264, 2024 | 2 | 2024 |
| Predictive modeling of CO2 solubility in piperazine aqueous solutions using boosting algorithms for carbon capture goals MR Mohammadi, A Larestani, M Schaffie, A Hemmati-Sarapardeh, ... Scientific Reports 14 (1), 22112, 2024 | 2 | 2024 |
| Chapter 6: Application of intelligent models in exploration engineering A Hemmati-Sarapardeh, A Larestani, NA Menad, S Hajirezaie Applications of artificial intelligence techniques in the petroleum industry …, 2020 | 2 | 2020 |
| Toward accurate prediction of carbon dioxide (CO2) compressibility factor using tree-based intelligent schemes (XGBoost and LightGBM) and equations of state B Amiri-Ramsheh, A Larestani, S Atashrouz, E Nasirzadeh, ... Results in Engineering 25, 104035, 2025 | | 2025 |
Abdolhossein Hemmati-Sarapardeh ع...Associate Professor, Department of Petroleum Engineering, Shahid Bahonar University of KermanVerified email at uk.ac.ir
