Tel: + 966 (013) 860-1793

Location: Bldg. 76, Rm. 2160

Dr. Ashraf Hashim Ahmed

Post-Doc Researcher, Department of Petroleum Engineering

Dr. Ashraf Ahmed is a Postdoctoral Researcher at the Department of Petroleum Engineering. He joined KFUPM in 2019 as a Ph.D. student, during which he played a vital role in the Drilling Engineering Research Team within the Department of Petroleum Engineering.

Dr. Ahmed was a lecturer in the Department of Oil and Gas Engineering at the University of Khartoum, Sudan, from 2015 to 2019. During this time, he contributed to numerous petroleum engineering courses.

Dr. Ahmed has demonstrated expertise in drilling engineering, drilling fluid optimization, production engineering, artificial lifting, production optimization, well completion, and workover, as well as the application of artificial intelligence in petroleum engineering. He boasts a diverse range of publications and substantial experience in machine-learning applications and experimental work with drilling fluids. His research interests include artificial intelligence applications in petroleum engineering, hydrogen sulfide removal, and drilling fluid optimization.

Educational Qualification

  • D., Petroleum Engineering, KFUPM, Saudi Arabia, 2023.
  • S., Petroleum Engineering, KFUPM, Saudi Arabia, 2014.
  • B.S., Petroleum and Natural Gas Engineering, University of Khartoum, Sudan, 2009.

Research Interests

  • Drilling fluids optimization
  • Hydrogen sulfide scavengers
  • Nanotechnology in drilling fluids
  • Artificial intelligence applications in petroleum engineering

Selected Publications

  • Ahmed, A., Alsaihati, A., and Elkatatny, S. 2020. An Overview of the Common Water-Based Formulations Used for Drilling Onshore Gas Wells in The Middle East. Arabian Journal for Science and Engineering, https://doi.org/10.1007/s13369-020-05107-z
  • Ahmed, A., Elkatatny, S., Gamal, H., and Abdulraheem, A. 2021. Artificial Intelligence Models for Real-Time Bulk Density Prediction of Vertical Complex Lithology Using the Drilling Parameters, Arabian Journal for Science and Engineering, https://doi.org/10.1007/s13369-021-05537-3
  • Ahmed, A., Elkatatny, S., and Alsaihati, A. 2021. Applications of Artificial Intelligence for Static Poisson’s Ratio Prediction while Drilling. Computational Intelligence and Neuroscience, Article ID 9956128, 10 pages, https://doi.org/10.1155/2021/9956128
  • Ahmed, A., Basfar, S., Elkatatny, S., and Bageri, B. 2022. Vermiculite for enhancement of barite stability in water-based mud at elevated temperature. Powder Technology, 401, 117277, https://doi.org/10.1016/j.powtec.2022.117277
  • Ahmed, A., Elkatatny, S., and Onaizi, S. 2023. New application for Micromax in aqueous drilling fluids as a hydrogen sulfide scavenger. Geoenergy Science and Engineering, 229, 212137. https://doi.org/10.1016/j.geoen.2023.212137
  • Ahmed, A., Elkatatny, S., and Onaizi, S. 2022. Incorporating Steel-Industry Waste in Water Based Drilling Fluids for Hydrogen Sulfide Scavenging. Journal of Petroleum Science and Engineering, 216, 110818, https://doi.org/10.1016/j.petrol.2022.110818
  • Ahmed, A., Onaizi, S., and Elkatatny, S. 2022. Improvement of Hydrogen Sulfide Scavenging via the Addition of Mono-Ethanolamine to Water Based Drilling Fluids. ACS Omega, 7 (32), 28361-28368, https://doi.org/10.1021/acsomega.2c02890

Awards & Honors

  • Second Place, CPG Student Paper Contest,PhD Level, 2024
  • Outstanding Academic Performance during Undergraduate Studies, Schlumberger, Sudan, Academic Years 2005-2006, 2006-2007, 2007-2008 and 2008-2009.