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New insights into the prediction of heterogeneous carbonate reservoir permeability from well logs using artificial intelligence network.

, , , and . Neural Comput. Appl., 30 (9): 2673-2683 (2018)

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New insights into the prediction of heterogeneous carbonate reservoir permeability from well logs using artificial intelligence network., , , and . Neural Comput. Appl., 30 (9): 2673-2683 (2018)Application of Artificial Intelligence Techniques in Predicting the Lost Circulation Zones Using Drilling Sensors., , , , and . J. Sensors, (2020)An integrated approach for estimating static Young's modulus using artificial intelligence tools., , , , and . Neural Comput. Appl., 31 (8): 4123-4135 (2019)Photoelectric Factor Prediction Using Automated Learning and Uncertainty Quantification., , , and . CoRR, (2022)Newly Developed Correlations to Predict the Rheological Parameters of High-Bentonite Drilling Fluid Using Neural Networks., , , and . Sensors, 20 (10): 2787 (2020)Photoelectric factor prediction using automated learning and uncertainty quantification., , , and . Neural Comput. Appl., 35 (30): 22595-22604 (October 2023)Real-Time Prediction of Rate of Penetration in S-Shape Well Profile Using Artificial Intelligence Models.. Sensors, 20 (12): 3506 (2020)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., , , and . J. Sensors, (2022)Unconfined compressive strength (UCS) prediction in real-time while drilling using artificial intelligence tools., , and . Neural Comput. Appl., 33 (13): 8043-8054 (2021)Application of Various Machine Learning Techniques in Predicting Total Organic Carbon from Well Logs., , and . Comput. Intell. Neurosci., (2021)