Prediction of permeability from well logs using a new hybrid machine learning algorithm

Matinkia, Morteza; Hashami, Romina; Mehrad, Mohammad; Hajsaeedi, Mohammad Reza; Velayati, Arian

doi:10.1016/j.petlm.2022.03.003

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Prediction of permeability from well logs using a new hybrid machine learning algorithm

Author(s): Morteza Matinkia , Romina Hashami , Mohammad Mehrad , Mohammad Reza Hajsaeedi , Arian Velayati

Publication date Created: March 2022

Publication date (Print): March 2022

Journal: Petroleum

Publisher: Elsevier BV

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Comparison of machine learning methods for estimating permeability and porosity of oil reservoirs via petro-physical logs

Mohammad Ahmadi, Zhangxing Chen (2018)

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Permeability estimation: The various sources and their interrelationships

U Ahmed, S. Crary, G Coates … (1991)

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Prediction of Shear Wave Velocity Using Artificial Neural Network Technique, Multiple Regression and Petrophysical Data: A Case Study in Asmari Reservoir (SW Iran)

Habib Akhundi, Mohammad Ghafoori, Gholam-Reza Lashkaripour (2014)

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Mohammad Mehrad: (View ORCID Profile)

Mohammad Reza Hajsaeedi: (View ORCID Profile)

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Title: Petroleum

Abbreviated Title: Petroleum

Publisher: Elsevier BV

ISSN (Print): 24056561

Publication date Created: March 2022

Publication date (Print): March 2022

Article

DOI: 10.1016/j.petlm.2022.03.003

SO-VID: 85577fe1-115e-4361-9f43-531c620fdf34

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https://www.elsevier.com/tdm/userlicense/1.0/

http://creativecommons.org/licenses/by-nc-nd/4.0/

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Prediction of permeability from well logs using a new hybrid machine learning algorithm

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Most cited references 3

Comparison of machine learning methods for estimating permeability and porosity of oil reservoirs via petro-physical logs

Permeability estimation: The various sources and their interrelationships

Prediction of Shear Wave Velocity Using Artificial Neural Network Technique, Multiple Regression and Petrophysical Data: A Case Study in Asmari Reservoir (SW Iran)

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