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 et Abdolhossein Hemmati-Sarapardeh

Article de revue (2021)

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Département:	Département de génie informatique et génie logiciel
URL de PolyPublie:	https://publications.polymtl.ca/49126/
Titre de la revue:	Journal of Petroleum Science and Engineering (vol. 207)
Maison d'édition:	Elsevier
DOI:	10.1016/j.petrol.2021.109132
URL officielle:	https://doi.org/10.1016/j.petrol.2021.109132
Date du dépôt:	18 avr. 2023 14:59
Dernière modification:	08 avr. 2025 07:16

Citer en APA 7:	Hashemizadeh, A., Maaref, A., Shateri, M., Larestani, A., & Hemmati-Sarapardeh, A. (2021). 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. Journal of Petroleum Science and Engineering, 207, 109132 (10 pages). https://doi.org/10.1016/j.petrol.2021.109132

Citer en APA 7:

Hashemizadeh, A., Maaref, A., Shateri, M., Larestani, A., & Hemmati-Sarapardeh, A. (2021). 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. Journal of Petroleum Science and Engineering, 207, 109132 (10 pages). https://doi.org/10.1016/j.petrol.2021.109132

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