A bibliometric analysis of the application of machine learning methods in the petroleum industry-Reference-Cited by-同舟云学术

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A bibliometric analysis of the application of machine learning methods in the petroleum industry

Published:2023-12 Issue: Volume:20 Page:101518
ISSN:2590-1230
Container-title:Results in Engineering
language:en
Short-container-title:Results in Engineering

Author:

Sadeqi-Arani Zahra,Kadkhodaie Ali^ORCID

Publisher

Elsevier BV

Subject

General Engineering

Reference57 articles.

1. The application of committee machine with intelligent systems to the prediction of permeability from petrographic image analysis and well logs data: a case study from the South Pars Gas field, south Iran;Ghiasi-Freez;Petrol. Sci. Technol.,2012

2. A fuzzy logic approach for estimation of permeability and rock type from conventional well log data: an example from the Kangan reservoir in the Iran Offshore Gas Field;Kadkhodaie Ilkhchi;J. Geophys. Eng.,2006

3. Estimation of NMR log parameters from conventional well log data using a committee machine with intelligent systems: a case study from the Iranian part of the South Pars gas field, Persian Gulf Basin;Labani;J. Petrol. Sci. Eng.,2010

4. A new method for permeability estimation in carbonate reservoirs using NMR T2 distribution features and data clustering;Parchekhari;Arabian J. Geosci.,2021

5. Permeability prediction using machine learning methods for the CO2 injectivity of the precipice sandstone in surat basin, Australia;Rezaee;Energies,2022

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