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Journal Articles

Machine Learning Models for Acoustic Data Prediction During Drilling Composite Lithology Formations

Vagif Suleymanov, Hany Gamal, Salaheldin Elkatatny, Guenther Glatz, Abdulazeez Abdulraheem
Journal: Journal of Energy Resources Technology
Publisher: ASME
Article Type: Research Papers
J. Energy Resour. Technol. October 2022, 144(10): 103201.
Paper No: JERT-21-2104
https://doi.org/10.1115/1.4053846
Published Online: March 3, 2022
View Article titled, Machine Learning Models for Acoustic Data Prediction During Drilling Composite Lithology Formations
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Topics: Acoustics, Drilling, Machine learning, Sensitivity analysis, Support vector machines, Testing, Composite materials, Shear (Mechanics), Wells
Journal Articles

Intelligent Model for Predicting Downhole Vibrations Using Surface Drilling Data During Horizontal Drilling

Ramy Saadeldin, Hany Gamal, Salaheldin Elkatatny, Abdulazeez Abdulraheem
Journal: Journal of Energy Resources Technology
Publisher: ASME
Article Type: Research Papers
J. Energy Resour. Technol. August 2022, 144(8): 083002.
Paper No: JERT-21-1799
https://doi.org/10.1115/1.4052794
Published Online: November 12, 2021
View Article titled, Intelligent Model for Predicting Downhole Vibrations Using Surface Drilling Data During Horizontal Drilling
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Topics: Artificial neural networks, Drilling, Vibration, Machine learning
Journal Articles

Applying Different Artificial Intelligence Techniques in Dynamic Poisson’s Ratio Prediction Using Drilling Parameters

Osama Siddig, Hany Gamal, Salaheldin Elkatatny, Abdulazeez Abdulraheem
Journal: Journal of Energy Resources Technology
Publisher: ASME
Article Type: Research Papers
J. Energy Resour. Technol. July 2022, 144(7): 073006.
Paper No: JERT-21-1643
https://doi.org/10.1115/1.4052185
Published Online: September 3, 2021
View Article titled, Applying Different Artificial Intelligence Techniques in Dynamic Poisson’s Ratio Prediction Using Drilling Parameters
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Topics: Drilling, Machine learning, Poisson ratio, Support vector machines, Algorithms, Testing, Wells, Rocks
Journal Articles

Estimating the Total Organic Carbon for Unconventional Shale Resources During the Drilling Process: A Machine Learning Approach

Ahmed Abdulhamid Mahmoud, Hany Gamal, Salaheldin Elkatatny, Ahmed Alsaihati
Journal: Journal of Energy Resources Technology
Publisher: ASME
Article Type: Research Papers
J. Energy Resour. Technol. April 2022, 144(4): 043004.
Paper No: JERT-21-1539
https://doi.org/10.1115/1.4051737
Published Online: July 19, 2021
View Article titled, Estimating the Total Organic Carbon for Unconventional Shale Resources During the Drilling Process: A Machine Learning Approach
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Topics: Algorithms, Carbon, Machine learning, Testing, Gamma rays, Fuzzy neural nets, Potassium, Uranium, Drilling
Journal Articles

Predicting the Rock Sonic Logs While Drilling by Random Forest and Decision Tree-Based Algorithms

Hany Gamal, Ahmed Alsaihati, Salaheldin Elkatatny
Journal: Journal of Energy Resources Technology
Publisher: ASME
Article Type: Research Papers
J. Energy Resour. Technol. April 2022, 144(4): 043203.
Paper No: JERT-21-1527
https://doi.org/10.1115/1.4051670
Published Online: July 16, 2021
View Article titled, Predicting the Rock Sonic Logs While Drilling by Random Forest and Decision Tree-Based Algorithms
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Topics: Algorithms, Drilling, Machine learning, Rocks, Testing
Journal Articles

The Utilization of Steelmaking Industrial Waste of Silicomanganese Fume as Filtration Loss Control in Drilling Fluid Application

Waseem Razzaq, Salaheldin Elkatatny, Hany Gamal, Ariffin Samsuri
Journal: Journal of Energy Resources Technology
Publisher: ASME
Article Type: Research Papers
J. Energy Resour. Technol. February 2022, 144(2): 023004.
Paper No: JERT-20-1880
https://doi.org/10.1115/1.4051197
Published Online: May 31, 2021
View Article titled, The Utilization of Steelmaking Industrial Waste of Silicomanganese Fume as Filtration Loss Control in Drilling Fluid Application
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Topics: Drilling, Filtration, Fluids, Silicomanganese, Iron and steel making, Water
Journal Articles

Rock Strength Prediction in Real-Time While Drilling Employing Random Forest and Functional Network Techniques

Hany Gamal, Ahmed Alsaihati, Salaheldin Elkatatny, Saleh Haidary, Abdulazeez Abdulraheem
Journal: Journal of Energy Resources Technology
Publisher: ASME
Article Type: Research Papers
J. Energy Resour. Technol. September 2021, 143(9): 093004.
Paper No: JERT-20-1898
https://doi.org/10.1115/1.4050843
Published Online: May 3, 2021
View Article titled, Rock Strength Prediction in Real-Time While Drilling Employing Random Forest and Functional Network Techniques
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Topics: Artificial intelligence, Drilling, Principal component analysis, Rocks, Testing, Errors, Reservoirs, Compressive strength, Petroleum industry