Applications of artificial intelligence techniques in the petroleum industry A Hemmati-Sarapardeh, A Larestani, NA Menad, S Hajirezaie Gulf Professional Publishing, 2020 | 51 | 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 | 28 | 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 | 27 | 2022 |
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 | 26 | 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 | 23 | 2021 |
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 | 20 | 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 | 15 | 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 | 9 | 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 | 9 | 2022 |
Chapter 2: Intelligent models A Hemmati-Sarapardeh, A Larestani, NA Menad, S Hajirezaie Applications of Artificial Intelligence Techniques in the Petroleum Industry …, 2020 | 7 | 2020 |
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 | 6 | 2023 |
Chapter 1: Introduction A Hemmati-Sarapardeh, A Larestani, NA Menad, S Hajirezaie Applications of artificial intelligence techniques in the petroleum industry …, 2020 | 4 | 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 | 3 | 2022 |
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 | 3 | 2020 |
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 | 3 | 2020 |
Chapter 7: Weaknesses and strengths of intelligent models in petroleum industry A Hemmati-Sarapardeh, A Larestani, NA Menad, S Hajirezaie Applications of artificial intelligence techniques in the petroleum industry …, 2020 | 2* | 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 | 2 | 2020 |
Chapter 5: Application of intelligent models in drilling engineering A Hemmati-Sarapardeh, A Larestani, NA Menad, S Hajirezaie Applications of artificial intelligence techniques in the petroleum industry …, 2020 | | 2020 |