| Real time prediction of drilling fluid rheological properties using Artificial Neural Networks visible mathematical model (white box) Salaheldin Elkatatny, Zeeshan Tariq, Mohamed Mahmoud Journal of Petroleum Science and Engineering 146, 1202–1210, 2016 | 189 | 2016 |
| New insights into the prediction of heterogeneous carbonate reservoir permeability from well logs using artificial intelligence network S Elkatatny, M Mahmoud, Z Tariq, A Abdulraheem Neural Computing and Applications 30, 2673-2683, 2018 | 151 | 2018 |
| A systematic review of data science and machine learning applications to the oil and gas industry Z Tariq, MS Aljawad, A Hasan, M Murtaza, E Mohammed, A El-Husseiny, ... Journal of Petroleum Exploration and Production Technology, 1-36, 2021 | 140 | 2021 |
| Relative contribution of wettability Alteration and interfacial tension reduction in EOR: A critical review X Deng, Z Tariq, M Murtaza, S Patil, M Mahmoud, MS Kamal Journal of Molecular Liquids 325, 115175, 2021 | 98 | 2021 |
| An integrated approach for estimating static Young’s modulus using artificial intelligence tools S Elkatatny, Z Tariq, M Mahmoud, A Abdulraheem, I Mohamed Neural Computing and Applications 31, 4123-4135, 2019 | 93 | 2019 |
| Optimization of rate of penetration using artificial intelligent techniques SM Elkatatny, Z Tariq, MA Mahmoud, A Al-AbdulJabbar ARMA US Rock Mechanics/Geomechanics Symposium, ARMA-2017-0429, 2017 | 83 | 2017 |
| A new artificial intelligence based empirical correlation to predict sonic travel time Z Tariq, S Elkatatny, M Mahmoud, A Abdulraheem International Petroleum Technology Conference, D012S057R001, 2016 | 76 | 2016 |
| New insights into porosity determination using artificial intelligence techniques for carbonate reservoirs S Elkatatny, Z Tariq, M Mahmoud, A Abdulraheem Petroleum 4 (4), 408-418, 2018 | 75 | 2018 |
| Development of new mathematical model for compressional and shear sonic times from wireline log data using artificial intelligence neural networks (white box) S Elkatatny, Z Tariq, M Mahmoud, I Mohamed, A Abdulraheem Arabian Journal for Science and Engineering 43 (11), 6375-6389, 2018 | 75 | 2018 |
| A new technique to develop rock strength correlation using artificial intelligence tools Z Tariq, S Elkatatny, M Mahmoud, AZ Ali, A Abdulraheem SPE Reservoir Characterisation and Simulation Conference and Exhibition …, 2017 | 75 | 2017 |
| A review on non-aqueous fracturing techniques in unconventional reservoirs S Kalam, C Afagwu, J Al Jaberi, OM Siddig, Z Tariq, M Mahmoud, ... Journal of Natural Gas Science and Engineering 95, 104223, 2021 | 71 | 2021 |
| Machine learning derived correlation to determine water saturation in complex lithologies MR Khan, Z Tariq, A Abdulraheem SPE Kingdom of Saudi Arabia annual technical symposium and exhibition, SPE …, 2018 | 67 | 2018 |
| Development of a new correlation for bubble point pressure in oil reservoirs using artificial intelligencetechnique S Elkatatny, R Aloosh, Z Tariq, M Mahmoud, A Abdulraheem SPE Kingdom of Saudi Arabia Annual Technical Symposium and Exhibition …, 2017 | 66 | 2017 |
| A new approach to predict failure parameters of carbonate rocks using artificial intelligence tools Z Tariq, S Elkatatny, M Mahmoud, AZ Ali, A Abdulraheem SPE Kingdom of Saudi Arabia Annual Technical Symposium and Exhibition …, 2017 | 64 | 2017 |
| Machine learning application for oil rate prediction in artificial gas lift wells MR Khan, S Alnuaim, Z Tariq, A Abdulraheem SPE middle east oil and gas show and conference, D032S085R002, 2019 | 59 | 2019 |
| Data-driven machine learning approach to predict mineralogy of organic-rich shales: An example from Qusaiba Shale, Rub’al Khali Basin, Saudi Arabia A Mustafa, Z Tariq, M Mahmoud, AE Radwan, A Abdulraheem, ... Marine and Petroleum Geology 137, 105495, 2022 | 48 | 2022 |
| Application of artificial intelligence to estimate oil flow rate in gas-lift wells MR Khan, Z Tariq, A Abdulraheem Natural Resources Research 29 (6), 4017-4029, 2020 | 46 | 2020 |
| Real-time prognosis of flowing bottom-hole pressure in a vertical well for a multiphase flow using computational intelligence techniques Z Tariq, M Mahmoud, A Abdulraheem Journal of Petroleum Exploration and Production Technology 10, 1411-1428, 2020 | 46 | 2020 |
| Application of artificial intelligent techniques to determine sonic time from well logs SM Elkatatny, T Zeeshan, M Mahmoud, A Abdulazeez, IM Mohamed ARMA US Rock Mechanics/Geomechanics Symposium, ARMA-2016-755, 2016 | 46 | 2016 |
| Gas adsorption and reserve estimation for conventional and unconventional gas resources AE Radwan, DA Wood, M Mahmoud, Z Tariq Sustainable geoscience for natural gas subsurface systems, 345-382, 2022 | 44 | 2022 |
Mohamed A. MahmoudKFUPMZweryfikowany adres z kfupm.edu.sa