PHD at Texas A&M University, United States
Ahmed Farid Ibrahim, based in Houston, USA, is an accomplished petroleum engineer with over 13 years of expertise in CO2 sequestration, sustainability, and machine learning applications. As an assistant professor, he has spearheaded numerous funded projects focusing on CO2 sequestration and enhanced hydrocarbon recovery. He holds a PhD from Texas A&M University and has a robust background in reservoir modeling, production performance analysis, and technical evaluation of oil and gas assets. Ahmed’s work, recognized through various awards, has been published in peer-reviewed journals and presented at international conferences. He is also an active member of professional organizations like SPE and EAGE. Petroleum Energy
Professional Profiles
Education
PhD, Petroleum Engineering Institution: Texas A&M University, College Station Graduation Date: December 2017 GPA: 4.0/4.0 Topic: CO2 Applications in Unconventional Reservoirs Graduate Advisor: Dr. Hisham Nasr-El-Din MSc, Petroleum Engineering Institution: Cairo University, Egypt Graduation Date: June 2011 Thesis: Development of an Integrated Model for History Matching and Predicting Reservoir Performance of Gas Condensate Wells Advisor: Dr. Ahmed El-Banbi GPA: 4.0/4.0 BSc, Petroleum Engineering Institution: Cairo University, Egypt Graduation Date: July 2009 Grade: Distinction with honor degree, First place/150. Petroleum Energy
Professional Experience
Assistant Professor Institution: KFUPM Dates: 2021 – present Status: Full-Time Post Doc. Researcher Institution: Texas A&M University Dates: 2017-2018 Status: Full-Time Research Assistant Institution: Texas A&M University Dates: 2013-2017 Status: Full-Time Teaching Assistant Institution: Cairo University Dates: 2009-2013 Status: Full-Time Teaching Courses: Reservoir Engineering, Natural Gas Engineering, Well Test Analysis, Reservoir Description and Characterization, Water Flooding, Machine Learning Applications in Oil and Gas Industry. Petroleum Energy
Filed Patents
Ibrahim, Ahmed Farid. “SYSTEM AND METHODS FOR DETERMINING THE EFFECT OF FRACTURE INTERFERENCE ON SHALE WELL PERFORMANCE.” U.S. Patent Application 18/357,638, filed March 7, 2024. De Paulo, J.M., et al. “Viscoelastic compositions for matrix acidizing.” U.S. Patent Application 17/417,668, filed March 3, 2022.
Computer Skills
Reservoir Simulation Software: CMG, ECLIPSE Programming Languages: Python, Spotfire, FORTRAN, Visual Basic, Labview Microsoft Office: Word, Excel, PowerPoint Public Datasets: Drilling info
Honors and Awards
OGAPS Grant, Texas A&M University, 2015 2021 Reviewers of the Year, ASME Journal of Energy Resources Technology SPE Student Paper Contest, Ranked First Place in the Subregional Middle East Level Schlumberger Distinguished Student Award, 2007 and 2008
Research Focus
Ahmed Farid Ibrahim’s research focuses on enhancing hydrocarbon recovery and CO2 sequestration in both conventional and unconventional reservoirs. His work integrates experimental and numerical simulation studies, with a particular emphasis on machine learning applications. His research encompasses reservoir modeling, the effects of water salinity on coal wettability, mobility control using nanoparticle-stabilized CO2 foam, and the development of innovative friction-reducing agents for hydraulic fracturing. His contributions also include acid diversion in carbonate reservoirs, diagnostics in unconventional formations, and stability improvements for CO2 foam. Ahmed’s extensive publication record highlights his significant contributions to petroleum engineering and environmental sustainability.
Publications
- Optimizing Recovery of Fracturing Fluid in Unconventional and Tight Gas Reservoirs Through Innovative Environmentally Friendly Flowback Additives, Publication date: 2024.
- Optimizing cluster spacing in multistage hydraulically fractured shale gas wells: balancing fracture interference and stress shadow impact, Publication date: 2024.
- Real-Time Identification of Geological Factuals by Integrating Formation Micro Resistivity Imaging Logs With Computer Vision, Publication date: 2024.
- Impact of Injection Velocity on Wormhole Generation Due to CO2 Sequestration, Publication date: 2024.
- Data Analytics and Machine Learning Application for Reservoir Potential Prediction in Vuggy Carbonate Reservoirs Using Conventional Well Logging, Publication date: 2024.
- Advancing Reservoir Understanding: Integrating Deep Learning into Automated Formation Micro-Imaging Log Interpretation for Enhanced Reservoir Characterization and Management, Publication date: 2024.
- Real-Time Prediction of Petrophysical Properties Using Machine Learning Based on Drilling Parameters, Publication date: 2024.
- Optimizing Completion Design for Delaware Basin Wells with Real-Time Performance Monitoring, Publication date: 2024.
- SYSTEM AND METHODS FOR DETERMINING THE EFFECT OF FRACTURE INTERFERENCE ON SHALE WELL PERFORMANCE, Publication date: 2024.
- Cluster Spacing Effect on the Fracture Interference Including Stress Shadow, Publication date: 2024.
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