The Citing articles tool gives a list of articles citing the current article. The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).
A further study in the prediction of viscosity for Iranian crude oil reservoirs by utilizing a robust radial basis function (RBF) neural network model
Mohammad Soleimani Lashkenari, Mohammad Bagheri, Afshin Tatar, Hadi Rezazadeh and Mustafa Inc Neural Computing and Applications 35(14) 10663 (2023) https://doi.org/10.1007/s00521-023-08256-y
Prediction of the equivalent circulation density using machine learning algorithms based on real-time data
Prediction of penetration rate in drilling operations: a comparative study of three neural network forecast methods
Ehsan Brenjkar, Ebrahim Biniaz Delijani and Kasra Karroubi Journal of Petroleum Exploration and Production Technology 11(2) 805 (2021) https://doi.org/10.1007/s13202-020-01066-1
Experimental measurement and modeling of water-based drilling mud density using adaptive boosting decision tree, support vector machine, and K-nearest neighbors: A case study from the South Pars gas field
Abbas Hashemizadeh, Ahmad Maaref, Mohammadhadi Shateri, Aydin Larestani and Abdolhossein Hemmati-Sarapardeh Journal of Petroleum Science and Engineering 207 109132 (2021) https://doi.org/10.1016/j.petrol.2021.109132
An insight into the estimation of drilling fluid density at HPHT condition using PSO-, ICA-, and GA-LSSVM strategies
S. M. Alizadeh, Issam Alruyemi, Reza Daneshfar, Mohammad Mohammadi-Khanaposhtani and Maryam Naseri Scientific Reports 11(1) (2021) https://doi.org/10.1038/s41598-021-86264-5
Machine Learning Models for Equivalent Circulating Density Prediction from Drilling Data
A systematic review of data science and machine learning applications to the oil and gas industry
Zeeshan Tariq, Murtada Saleh Aljawad, Amjed Hasan, et al. Journal of Petroleum Exploration and Production Technology 11(12) 4339 (2021) https://doi.org/10.1007/s13202-021-01302-2
COVID-19 prediction analysis using artificial intelligence procedures and GIS spatial analyst: a case study for Iraq
Artificial neural network model for predicting the density of oil-based muds in high-temperature, high-pressure wells
Okorie E. Agwu, Julius U. Akpabio and Adewale Dosunmu Journal of Petroleum Exploration and Production Technology 10(3) 1081 (2020) https://doi.org/10.1007/s13202-019-00802-6
Effect of a modified nano clay and nano graphene on rheology, stability of water-in-oil emulsion, and filtration control ability of oil-based drilling fluids: a comparative experimental approach
Vahid Nooripoor and Abdolnabi Hashemi Oil & Gas Science and Technology – Revue d’IFP Energies nouvelles 75 40 (2020) https://doi.org/10.2516/ogst/2020032
