New insights into the prediction of heterogeneous carbonate reservoir permeability from well logs using artificial intelligence network. - Salaheldin Elkatatny; Mohamed Mahmoud; Zeeshan Tariq; Abdulazeez Abdulraheem (Neural Comput. Appl., 2018)

An integrated approach for estimating static Young's modulus using artificial intelligence tools. - Salaheldin Elkatatny; Zeeshan Tariq; Mohamed Mahmoud; Abdulazeez Abdulraheem; Ibrahim Mohamed (Neural Comput. Appl., 2019)

Application of Artificial Intelligence Techniques in Predicting the Lost Circulation Zones Using Drilling Sensors. - Abdulmalek Ahmed; Salaheldin Elkatatny; Abdulwahab Ali; Mahmoud Abughaban; Abdulazeez Abdulraheem (J. Sensors, 2020)

Real-Time Prediction of Rheological Properties of Invert Emulsion Mud Using Adaptive Neuro-Fuzzy Inference System. - Ahmed Alsabaa; Hany Gamal; Salaheldin Elkatatny; Abdulazeez Abdulraheem (Sensors, 2020)

Real-Time Prediction of Rate of Penetration in S-Shape Well Profile Using Artificial Intelligence Models. - Salaheldin Elkatatny (Sensors, 2020)

A New Model for Predicting Rate of Penetration Using an Artificial Neural Network. - Salaheldin Elkatatny; Ahmed Al-AbdulJabbar; Khaled Abdelgawad (Sensors, 2020)

Newly Developed Correlations to Predict the Rheological Parameters of High-Bentonite Drilling Fluid Using Neural Networks. - Ahmed Gowida; Salaheldin Elkatatny; Khaled Abdelgawad; Rahul Gajbhiye (Sensors, 2020)

Applications of Artificial Intelligence for Static Poisson's Ratio Prediction While Drilling. - Ashraf Ahmed; Salaheldin Elkatatny; Ahmed Alsaihati (Comput. Intell. Neurosci., 2021)

Intelligent Prediction for Rock Porosity While Drilling Complex Lithology in Real Time. - Hany Gamal; Salaheldin Elkatatny; Ahmed Alsaihati; Abdulazeez Abdulraheem (Comput. Intell. Neurosci., 2021)

Application of Various Machine Learning Techniques in Predicting Total Organic Carbon from Well Logs. - Osama Siddig; Ahmed Farid Ibrahim; Salaheldin Elkatatny (Comput. Intell. Neurosci., 2021)

Unconfined compressive strength (UCS) prediction in real-time while drilling using artificial intelligence tools. - Ahmed Gowida; Salaheldin Elkatatny; Hany Gamal (Neural Comput. Appl., 2021)

A Novel Artificial Neural Network-Based Correlation for Evaluating the Rate of Penetration in a Natural Gas Bearing Sandstone Formation: A Case Study in a Middle East Oil Field. - Ahmad Al-Abduljabbar; Ahmed Abdulhamid Mahmoud; Salaheldin Elkatatny; Mahmoud Abughaban (J. Sensors, 2022)

Photoelectric factor prediction using automated learning and uncertainty quantification. - Khalid L. Alsamadony; Ahmed Farid Ibrahim; Salaheldin Elkatatny; Abdulazeez Abdulraheem (Neural Comput. Appl., 2023)