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Keywords: horizontal drilling
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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
....2019.05.021 [9] Mahmoud , A. A. , Elkatatny , S. , Al-AbdulJabbar , A. , Moussa , T. , Gamal , H. , and Shehri , D. A. , 2020 , “ Artificial Neural Networks Model for Prediction of the Rate of Penetration While Horizontally Drilling Carbonate Formations ,” Proceedings...
View Article titled, Intelligent Model for Predicting Downhole Vibrations Using Surface Drilling Data During <span class="search-highlight">Horizontal</span> <span class="search-highlight">Drilling</span>
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Topics: Artificial neural networks, Drilling, Vibration, Machine learning
Journal Articles

Estimation of the Rate of Penetration While Horizontally Drilling Carbonate Formation Using Random Forest

Hany Osman, Abdulwahab Ali, Ahmed Abdulhamid Mahmoud, Salaheldin Elkatatny
Journal: Journal of Energy Resources Technology
Publisher: ASME
Article Type: Research Papers
J. Energy Resour. Technol. September 2021, 143(9): 093003.
Paper No: JERT-20-2001
https://doi.org/10.1115/1.4050778
Published Online: April 29, 2021
...Hany Osman; Abdulwahab Ali; Ahmed Abdulhamid Mahmoud; Salaheldin Elkatatny Predicting the rate of penetration (ROP) is challenging especially during horizontal drilling. This is because there are many factors affecting ROP. Machine learning techniques are very promising in identifying...
View Article titled, Estimation of the Rate of Penetration While <span class="search-highlight">Horizontally</span> <span class="search-highlight">Drilling</span> Carbonate Formation Using Random Forest
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Topics: Artificial neural networks, Drilling, Machine learning, Regression models, Algorithms, Testing
Journal Articles

Use of Machine Learning and Data Analytics to Detect Downhole Abnormalities While Drilling Horizontal Wells, With Real Case Study

Ahmed Alsaihati, Salaheldin Elkatatny, Ahmed Abdulhamid Mahmoud, Abdulazeez Abdulraheem
Journal: Journal of Energy Resources Technology
Publisher: ASME
Article Type: Research Papers
J. Energy Resour. Technol. April 2021, 143(4): 043201.
Paper No: JERT-20-1090
https://doi.org/10.1115/1.4048070
Published Online: August 28, 2020
...@kfupm.edu.sa Email: aazeez@kfupm.edu.sa Contributed by the Petroleum Division of ASME for publication in the J ournal of E nergy R esources T echnology . 02 02 2020 10 07 2020 12 07 2020 28 08 2020 torque and drag horizontal drilling random forest Mahalanobis...
View Article titled, Use of Machine Learning and Data Analytics to Detect Downhole Abnormalities While Drilling Horizontal Wells, With Real Case Study
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Topics: Artificial neural networks, Drilling, Torque, Wells, Testing, Drag (Fluid dynamics), Pipes
Journal Articles

Numerical and Experimental Investigation on the Feasibility of Horizontal Drilling With a New Type of Jet Mill Bit

Tong Cao, Kaian Yu, Xuyue Chen, Deli Gao, Hongwu Zhu, YunQing Luo
Journal: Journal of Energy Resources Technology
Publisher: ASME
Article Type: Research-Article
J. Energy Resour. Technol. September 2019, 141(9): 093101.
Paper No: JERT-18-1794
https://doi.org/10.1115/1.4043246
Published Online: April 4, 2019
...Tong Cao; Kaian Yu; Xuyue Chen; Deli Gao; Hongwu Zhu; YunQing Luo Recently, a new type of jet mill bit (JMB) has been introduced to improve the cutting transport efficiency in horizontal drilling by comminuting cuttings into dust-like particles immediately after the cuttings are generated...
View Article titled, Numerical and Experimental Investigation on the Feasibility of <span class="search-highlight">Horizontal</span> <span class="search-highlight">Drilling</span> With a New Type of Jet Mill Bit
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Topics: Cutting, Drilling, Flow (Dynamics), Simulation analysis, Simulation results, Fluids, Stress, Simulation