Application of machine learning models for real-time prediction of the formation lithology and tops from the drilling parameters
Author:
Funder
King Fahd University of Petroleum and Minerals
Publisher
Elsevier BV
Subject
Geotechnical Engineering and Engineering Geology,Fuel Technology
Reference52 articles.
1. Real time determination of rheological properties of spud drilling fluids using a hybrid artificial intelligence technique;Abdelgawad;J. Energy Resour. Technol.,2019
2. New approach to evaluate the equivalent circulating density (ECD) using artificial intelligence techniques;Abdelgawad;Journal of Petroleum Exploration and Production Technology,2019
3. Toward connectionist model for predicting bubble point pressure of crude oils: application of artificial intelligence;Ahmadi;Petroleum,2015
4. Fracture pressure prediction using radial basis function;Ahmed,2019
5. Prediction of pore and fracture pressures using support vector machine;Ahmed,2019
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