Alqahtani, F.; Ehsan, M.; Abdulfarraj, M.; Aboud, E.; Naseer, Z.; El-Masry, N.N.; Abdelwahed, M.F.
Machine Learning Techniques in Predicting Bottom Hole Temperature and Remote Sensing for Assessment of Geothermal Potential in the Kingdom of Saudi Arabia. Sustainability 2023, 15, 12718.
https://doi.org/10.3390/su151712718
AMA Style
Alqahtani F, Ehsan M, Abdulfarraj M, Aboud E, Naseer Z, El-Masry NN, Abdelwahed MF.
Machine Learning Techniques in Predicting Bottom Hole Temperature and Remote Sensing for Assessment of Geothermal Potential in the Kingdom of Saudi Arabia. Sustainability. 2023; 15(17):12718.
https://doi.org/10.3390/su151712718
Chicago/Turabian Style
Alqahtani, Faisal, Muhsan Ehsan, Murad Abdulfarraj, Essam Aboud, Zohaib Naseer, Nabil N. El-Masry, and Mohamed F. Abdelwahed.
2023. "Machine Learning Techniques in Predicting Bottom Hole Temperature and Remote Sensing for Assessment of Geothermal Potential in the Kingdom of Saudi Arabia" Sustainability 15, no. 17: 12718.
https://doi.org/10.3390/su151712718
APA Style
Alqahtani, F., Ehsan, M., Abdulfarraj, M., Aboud, E., Naseer, Z., El-Masry, N. N., & Abdelwahed, M. F.
(2023). Machine Learning Techniques in Predicting Bottom Hole Temperature and Remote Sensing for Assessment of Geothermal Potential in the Kingdom of Saudi Arabia. Sustainability, 15(17), 12718.
https://doi.org/10.3390/su151712718