Application of multidimensional interpolation and random forest regression to enhanced oil recovery modeling-Reference-Cited by-同舟云学术

Application of multidimensional interpolation and random forest regression to enhanced oil recovery modeling

Published:2017-10-20 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 13th Central & Eastern European Software Engineering Conference in Russia
language:
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Author:

Krasnov Fedor¹,Glavnov Nikolay¹,Sitnikov Alexander¹

Affiliation:

1. Gazpromneft STC, Russia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3166094.3166096

Reference20 articles.

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2. Optimising Gas Injection in Carbonate Reservoirs Using High-Resolution Outcrop Analogue Models

3. Jurij Nikolaevich Bahvalov Leonid Leonidovich Malygin and Pavel Sergeevich Cherkass. 2012. Metod mashinnogo obuchenija na osnove algoritma mnogomernoj interpoljacii i approksimacii sluchajnyh funkcij. Vestnik Cherepoveckogo gosudarstvennogo universiteta 2 2 (39) (2012). Jurij Nikolaevich Bahvalov Leonid Leonidovich Malygin and Pavel Sergeevich Cherkass. 2012. Metod mashinnogo obuchenija na osnove algoritma mnogomernoj interpoljacii i approksimacii sluchajnyh funkcij. Vestnik Cherepoveckogo gosudarstvennogo universiteta 2 2 (39) (2012).

4. Leo Breiman. 2001. Random forests. Machine learning 45 1 (2001) 5--32. 10.1023/A:1010933404324 Leo Breiman. 2001. Random forests. Machine learning 45 1 (2001) 5--32. 10.1023/A:1010933404324

5. Paul Dierckx. 1995. Curve and surface fitting with splines. Oxford University Press. Paul Dierckx. 1995. Curve and surface fitting with splines. Oxford University Press.

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