Artificial neural network, support vector machine, decision tree, random forest, and committee machine intelligent system help to improve performance prediction of low salinity water injection in carbonate oil reservoirs-Reference-Cited by-同舟云学术

Artificial neural network, support vector machine, decision tree, random forest, and committee machine intelligent system help to improve performance prediction of low salinity water injection in carbonate oil reservoirs

Published:2022-12 Issue: Volume:219 Page:111046
ISSN:0920-4105
Container-title:Journal of Petroleum Science and Engineering
language:en
Short-container-title:Journal of Petroleum Science and Engineering

Author:

Shafiei Ali^ORCID,Tatar Afshin,Rayhani Mahsheed,Kairat Madiyar^ORCID,Askarova Ingkar^ORCID

Funder

Nazarbayev University

Publisher

Elsevier BV

Subject

Geotechnical Engineering and Engineering Geology,Fuel Technology

Reference111 articles.

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4. Evolving artificial neural network and imperialist competitive algorithm for prediction oil flow rate of the reservoir;Ahmadi;Appl. Soft Comput. J.,2013

5. Low-salinity flooding in a selected carbonate reservoir: experimental approach;Al-Attar;J. Pet. Explor. Prod. Technol.,2013

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