Drilling rate prediction from petrophysical logs and mud logging data using an optimized multilayer perceptron neural network von Anemangely, Mohammad, Ramezanzadeh, Ahmad, Tokhmechi, Behzad, Molaghab, Abdollah, Mohammadian, Aram

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A machine learning approach to predict drilling rate using petrophysical and mud logging data von Sabah, Mohammad, Talebkeikhah, Mohsen, Wood, David A., Khosravanian, Rasool, Anemangely, Mohammad, Younesi, Alireza

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Application of hybrid artificial neural networks for predicting rate of penetration (ROP): A case study from Marun oil field von Ashrafi, Seyed Babak, Anemangely, Mohammad, Sabah, Mohammad, Ameri, Mohammad Javad

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Machine learning technique for the prediction of shear wave velocity using petrophysical logs von Anemangely, Mohammad, Ramezanzadeh, Ahmad, Amiri, Hamed, Hoseinpour, Seyed-Ahmad

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Geomechanical parameter estimation from mechanical specific energy using artificial intelligence von Anemangely, Mohammad, Ramezanzadeh, Ahmad, Mohammadi Behboud, Mohammad

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Shear wave travel time estimation from petrophysical logs using ANFIS-PSO algorithm: A case study from Ab-Teymour Oilfield von Anemangely, Mohammad, Ramezanzadeh, Ahmad, Tokhmechi, Behzad

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Development of a new rock drillability index for oil and gas reservoir rocks using punch penetration test von Anemangely, Mohammad, Ramezanzadeh, Ahmad, Tokhmechi, Behzad, Molaghab, Abdollah, Mohammadian, Aram

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