Petrophysical evaluation based on three-stream convolutional neural networks in the Berkine Basin, Algeria
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Elsevier BV
Reference47 articles.
1. Predicting log data by using artificial neural networks to approximate petrophysical parameters of formation;Baneshi;Pet. Sci. Technol.,2013
2. Artificial neural network model for reservoir petrophysical properties: porosity, permeability and water saturation prediction;Okon;Model. Earth Syst. Environ. Model. Earth Syst. Environ.,2021
3. Comparison of machine learning methods for estimating permeability and porosity of oil reservoirs via petro-physical logs;Ahmadi;Petroleum,2018
4. S. Singh, Permeability Prediction Using Artificial Neural Network (ANN): A Case Study of Uinta Basin. SPE Annual Technical Conference and Exhibition, Dallas, Texas, October 2005. SPE-99286-STU. 〈https://doi.org/10.2118/99286-STU〉 (2005).
5. Porosity and permeability prediction based on computational intelligences as artificial neural networks (ANNs) and adaptive neuro-fuzzy inference systems (ANFIS) in Southern carbonate reservoir of Iran;Zargari;Pet. Sci. Technol.,2013
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