Professor , University of Oklahoma , United States
Dr. Ramadan Ahmed is a distinguished professor and Mewbourne Chair in Petroleum Engineering at the University of Oklahoma 🇺🇸. With a PhD from NTNU 🇳🇴 and decades of international experience, he specializes in drilling technologies, wellbore hydraulics, and solids transport. Dr. Ahmed’s innovative research integrates machine learning 🤖 with traditional engineering principles to solve complex problems in energy systems and well control. A prolific author in top-tier journals 📚, he mentors students across undergraduate and graduate levels while advancing the science of safe, efficient, and sustainable drilling practices 🌍🛢️.
Professional Profile
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ORCID
Education & Experience
Dr. Ahmed earned his PhD 🥼 and MSc 📘 in Petroleum Engineering from NTNU, Norway 🇳🇴, after completing a BSc in Chemical Engineering from Addis Ababa University, Ethiopia 🇪🇹. He began his career as a Process Engineer 🏭 before moving into academia and consulting. His professional journey includes roles as Research Associate 🔬 and Senior Researcher at the University of Tulsa, and later as a full professor at the University of Oklahoma 🌟. With over three decades of experience in petroleum engineering 🚛, he has specialized in drilling simulation, cement degradation, and managed pressure drilling with both academic depth and industry insight 🛠️.
Professional Development
Dr. Ahmed’s professional journey reflects a commitment to continuous growth and knowledge dissemination 📈🎓. He integrates emerging technologies like AI and ML into traditional petroleum engineering systems 🤖, reshaping wellbore modeling and failure prediction. As a mentor and educator, he develops next-generation engineers by teaching advanced drilling technologies and simulation methods 👨🏫🛠️. He frequently publishes in prestigious journals 📚 and collaborates with global experts to tackle real-world drilling challenges 🌍🔧. His involvement in international research, peer review, and conference presentations 🎤 ensures he stays at the forefront of drilling innovation and professional development.
Research Focus
Dr. Ahmed’s research centers on drilling engineering, wellbore hydraulics, and multiphase flow systems 🛢️🔍. His interests include cuttings transport, fluid rheology, managed pressure drilling, and well control ⚙️💧. He also explores the integration of machine learning in predictive modeling, such as fatigue analysis of hydrogen pipelines and the degradation of cement and tubulars 🤖🧪. With a focus on simulation, instrumentation, and non-Newtonian fluid mechanics, his work supports safer and more efficient operations in deep and complex wells 🌐. His research bridges traditional petroleum engineering with digital innovation for modern energy solutions ⚡🔬.
Awards & Honors
🏆 Dr. Ahmed holds the prestigious Mewbourne Chair in Petroleum Engineering at the University of Oklahoma, a recognition of his excellence in research and teaching.
📚 He has published extensively in top journals like SPE Journal, Engineering Failure Analysis, and Geoenergy Science.
🎤 Regularly invited as a conference speaker at global petroleum engineering forums, he shares insights on drilling optimization and digital transformation.
🧠 His work on machine learning in energy systems and wellbore performance has earned peer recognition.
🌟 A global thought leader, Dr. Ahmed continues to shape the future of drilling engineering and sustainability.
Publication Top Notes
1. Novel Machine Learning Modeling Approach for Fatigue Failure of Hydrogen-Transporting Pipelines
Authors: Nayem Ahmed, Ramadan M. Ahmed, Catalin Teodoriu, Michael Gyaabeng
Journal: SPE Journal | Year: 2025 | Citations: 0
🔍 Summary:
This study introduces a novel machine learning (ML) framework for predicting fatigue failure in pipelines used for transporting hydrogen. The model leverages large-scale data and advanced feature selection techniques to evaluate pipeline structural integrity under cyclic stress. This approach significantly improves predictive accuracy and provides a safer, data-driven alternative to traditional fatigue analysis in hydrogen energy systems.
🤖🔧💥
2. Optimization of Radial Jet Drilling for Hard Formations Present in Deep Geothermal Wells
Authors: Ramadan M. Ahmed, Catalin Teodoriu
Journal: Geoenergy Science and Engineering | Year: 2024 | Citations: 2
🔍 Summary:
The paper explores the enhancement of radial jet drilling (RJD) in hard rock formations typically encountered in deep geothermal wells. Through experimental and computational analysis, the authors present techniques for improving nozzle efficiency, optimizing jet parameters, and reducing energy consumption. The study supports geothermal energy advancement by offering cost-effective drilling alternatives.
🌋🛠️🌡️
3. Effects of Clay Contamination on the Stability of Aqueous Foams at High Pressure
Authors: Oyindamola Obisesan, Ramadan M. Ahmed, Nayem Ahmed, Mahmood Amani
Journal: SPE Journal | Year: 2024 | Citations: 1
🔍 Summary:
This research examines how clay particles affect the structural stability and performance of aqueous foam systems under high-pressure conditions. The findings are vital for operations in managed pressure drilling and underbalanced drilling, where foam stability plays a crucial role in maintaining well control and cuttings transport efficiency.
🧪🌡️🌫️
4. Effects of Pipe Rotation on the Performance of Fibrous Water-Based Polymeric Fluids in Horizontal Well Cleanout
Authors: Sergio P. Garcia, Michael Mendez, Ramadan M. Ahmed, Mustafa S. Nasser, Ibnelwaleed A. Hussein
Journal: SPE Journal | Year: 2024 | Citations: 1
🔍 Summary:
This paper investigates the influence of pipe rotation on the performance of fibrous polymeric drilling fluids used during horizontal well cleanout. The study demonstrates that rotational motion enhances the fluid’s carrying capacity and improves debris transport efficiency in horizontal and deviated wellbores.
🔄🛢️🔬
5. Modeling of Necking Area Reduction of Carbon Steel in Hydrogen Environment Using Machine Learning Approach
Authors: Nayem Ahmed, Mohamed Aldaw, Ramadan M. Ahmed, Catalin Teodoriu
Journal: Engineering Failure Analysis | Year: 2024 | Citations: 6
🔍 Summary:
Utilizing ML techniques, this article models the behavior of carbon steel in hydrogen-rich environments—specifically necking and deformation before failure. This research is significant for hydrogen pipeline design and safety, offering predictive tools for hydrogen embrittlement mitigation.
🧠⚙️📉
6. Conference Paper: Novel ML Modeling Approach for Fatigue Failure of Hydrogen-Transporting Pipelines
Authors: Nayem Ahmed, Ramadan M. Ahmed, Catalin Teodoriu, Michael Gyaabeng
Conference Paper | Year: 2025 | Citations: 0
🔍 Summary:
A conference version of the journal article listed above, this paper presents the methodology and preliminary findings for the machine learning framework developed to predict fatigue in hydrogen-transporting pipelines.
🎤📊🔍
Conclusion
Dr. Ramadan M. Ahmed stands out as a leading figure in petroleum engineering 🛢️, combining academic excellence 🎓, extensive industry experience 🏭, and pioneering research 🔬. His contributions to drilling technology, machine learning applications 🤖, and hydrogen pipeline safety 💥 continue to shape the future of energy engineering. Through teaching, mentorship, and global collaboration 🌍, he exemplifies innovation and leadership in the field. With a strong educational foundation 📚 and a forward-thinking research portfolio 🚀, Dr. Ahmed remains a driving force in solving critical challenges in drilling and wellbore management technologies.