| Removing the outlier from the production data for the decline curve analysis of shale gas reservoirs: a comparative study using machine learning T Yehia, H Khattab, M Tantawy, I Mahgoub ACS omega 7 (36), 32046-32061, 2022 | 23 | 2022 |
| A comprehensive review of deterministic decline curve analysis for oil and gas reservoirs T Yehia, MM Abdelhafiz, GM Hegazy, SA Elnekhaily, O Mahmoud Geoenergy Science and Engineering 226, 211775, 2023 | 20 | 2023 |
| Improving the Shale Gas Production Data Using the Angular-Based Outlier Detector Machine Learning Algorithm T Yehia, H Khattab, M Tantawy, I Mahgoub Journal of University of Shanghai for Science and Technology 24 (8), 52-72, 2022 | 13 | 2022 |
| Suitability of different machine learning outlier detection algorithms to improve shale gas production data for effective decline curve analysis T Yehia, A Wahba, S Mostafa, O Mahmoud Energies 15 (23), 8835, 2022 | 13 | 2022 |
| Machine learning outlier detection algorithms for enhancing production data analysis of shale gas T Yehia, A Wahba, S Mostafa, O Mahmoud Fundamental Research and Application of Physical Science 4, 127-163, 2023 | 8 | 2023 |
| Probabilistic decline curve analysis: state-of-the-art review T Yehia, A Naguib, MM Abdelhafiz, GM Hegazy, O Mahmoud Energies 16 (10), 4117, 2023 | 6 | 2023 |
| Comparative analysis of machine learning techniques for predicting drilling rate of penetration (ROP) in geothermal wells: A case study of FORGE site T Yehia, M Gasser, H Ebaid, N Meehan, ER Okoroafor Geothermics 121, 103028, 2024 | 5 | 2024 |
| Machine Learning Models to Predict Total Skin Factor in Perforated Wells S Thabet, A Elhadidy, M Elshielh, A Taman, A Helmy, H Elnaggar, T Yehia SPE Western Regional Meeting, D011S004R007, 2024 | 3 | 2024 |
| Preliminary hydraulic fracturing campaign strategies for unconventional and tight reservoirs of UAE: Case studies and lessons learned. GM Hegazy, T Yehia, O Mahmoud AIMS Energy 11 (6), 2023 | 3 | 2023 |
| Prediction of Total Skin Factor in Perforated Wells Using Models Powered by Deep Learning and Machine Learning S Thabet, HM Zidan, A Elhadidy, A Helmy, T Yehia, H Elnaggar, ... SPE Gas & Oil Technology Showcase and Conference, D011S004R001, 2024 | 2 | 2024 |
| Machine Learning Models to Predict Production Rate of Sucker Rod Pump Wells S Thabet, H Zidan, A Elhadidy, A Taman, A Helmy, H Elnaggar, T Yehia SPE Western Regional Meeting, D011S004R008, 2024 | 2 | 2024 |
| A review on clay reactivity with brine and its impact on fluid flow through porous media H Elnagger, M Sobhy, O Elagab, A Saeed, T Yehia IOGP Conference and Exhibition, 2023 | 2 | 2023 |
| A comparative analysis of machine learning techniques for geothermal wells’ drilling rate of penetration (ROP) prediction T Yehia, M Gasser, H Ebaid, N Meehan, ER Okoroafor Unconventional Resources Technology Conference, 17–19 June 2024, 429-448, 2024 | 1 | 2024 |
| Next-Gen Proppant Cleanout Operations: Machine Learning for Bottom-Hole Pressure Prediction SA Thabet, AA Elhadidy, M Heikal, A Taman, TA Yehia, H Elnaggar, ... Mediterranean Offshore Conference, D021S012R008, 2024 | 1 | 2024 |
| Application of Machine Learning and Deep Learning to Predict Production Rate of Sucker Rod Pump Wells SA Thabet, HA Zidan, AA Elhadidy, AG Helmy, TA Yehia, H Elnaggar, ... SPE Gas & Oil Technology Showcase and Conference, D021S035R001, 2024 | 1 | 2024 |
| Enhancing Oil Recovery in Heterogeneous Reservoirs with CO2 Flooding: A Simulation Study H Ebaid, M Gasser, T Yehia, ER Okoroafor SPE/AAPG/SEG Carbon, Capture, Utilization, and Storage Conference and …, 2024 | 1 | 2024 |
| A Technoeconomic, Policy, and Regulation Assessment of an Integrated Campus Geothermal Energy System GC Carter, M Gasser, Z Albabawat, R Vijapurapu, E Alharbi, T Yehia, ... | | 2025 |
| Investigating curve smoothing techniques for enhanced shale gas production data analysis T Yehia, S Mostafa, M Gasser, MM Abdelhafiz, N Meehan, O Mahmoud Journal of Natural Gas Geoscience 9 (6), 431-458, 2024 | | 2024 |
| Innovative Approach of Generative AI for Automating Technical Bid Evaluations in Oil Companies OE Abdelaziem, AN Khafagy, TA Yehia Mediterranean Offshore Conference, D021S012R003, 2024 | | 2024 |
| Nano-enhanced drilling fluids: Effects of MgO and ZnO nanoparticles on rheological properties and ANN modeling for predictive analysis M Gasser, T Yehia, H Ebaid, N Meehan, O Mahmoud SEG International Exposition and Annual Meeting, SEG-2024-4101073, 2024 | | 2024 |
Omar MahmoudAssociate Professor of Petroleum Engineering, Future University in Egypt (FUE); PhD-Texas A&Mfue.edu.eg üzerinde doğrulanmış e-posta adresine sahip
