Cover Image

PARAMETRIC INVESTIGATION OF HPAM/GO-SIO2 THROUGH EXPERIMENTAL AND MACHINE LEARNING MODELING

In this paper, we focus on a conventional chemical enhanced oil recovery method, partially hydrolyzed polyacrylamide polymer flooding, augmented by SiO2 and graphene oxide nanoparticles to create a hybrid polymeric nanofluid to observe its effects on reducing interfacial tension in an oil-nanofluid...

Full description

Saved in:
Bibliographic Details
Main Author: KAMARUL AZMAN, MUHAMMAD HAKIM
Format: Final Year Project
Language:English
Published: 2021
Subjects:
QE Geology
Online Access:http://utpedia.utp.edu.my/id/eprint/25645/1/48_UTP21-3_PE48.pdf
http://utpedia.utp.edu.my/id/eprint/25645/
Tags: Add Tag
No Tags, Be the first to tag this record!
id oai:utpedia.utp.edu.my:25645
record_format eprints
spelling oai:utpedia.utp.edu.my:256452024-02-22T07:56:58Z http://utpedia.utp.edu.my/id/eprint/25645/ PARAMETRIC INVESTIGATION OF HPAM/GO-SIO2 THROUGH EXPERIMENTAL AND MACHINE LEARNING MODELING KAMARUL AZMAN, MUHAMMAD HAKIM QE Geology In this paper, we focus on a conventional chemical enhanced oil recovery method, partially hydrolyzed polyacrylamide polymer flooding, augmented by SiO2 and graphene oxide nanoparticles to create a hybrid polymeric nanofluid to observe its effects on reducing interfacial tension in an oil-nanofluid interface. 2021-05 Final Year Project NonPeerReviewed text en http://utpedia.utp.edu.my/id/eprint/25645/1/48_UTP21-3_PE48.pdf KAMARUL AZMAN, MUHAMMAD HAKIM (2021) PARAMETRIC INVESTIGATION OF HPAM/GO-SIO2 THROUGH EXPERIMENTAL AND MACHINE LEARNING MODELING. [Final Year Project] (Submitted)
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
language English
topic QE Geology
spellingShingle QE Geology
KAMARUL AZMAN, MUHAMMAD HAKIM
PARAMETRIC INVESTIGATION OF HPAM/GO-SIO2 THROUGH EXPERIMENTAL AND MACHINE LEARNING MODELING
description In this paper, we focus on a conventional chemical enhanced oil recovery method, partially hydrolyzed polyacrylamide polymer flooding, augmented by SiO2 and graphene oxide nanoparticles to create a hybrid polymeric nanofluid to observe its effects on reducing interfacial tension in an oil-nanofluid interface.
format Final Year Project
author KAMARUL AZMAN, MUHAMMAD HAKIM
author_facet KAMARUL AZMAN, MUHAMMAD HAKIM
author_sort KAMARUL AZMAN, MUHAMMAD HAKIM
title PARAMETRIC INVESTIGATION OF HPAM/GO-SIO2 THROUGH EXPERIMENTAL AND MACHINE LEARNING MODELING
title_short PARAMETRIC INVESTIGATION OF HPAM/GO-SIO2 THROUGH EXPERIMENTAL AND MACHINE LEARNING MODELING
title_full PARAMETRIC INVESTIGATION OF HPAM/GO-SIO2 THROUGH EXPERIMENTAL AND MACHINE LEARNING MODELING
title_fullStr PARAMETRIC INVESTIGATION OF HPAM/GO-SIO2 THROUGH EXPERIMENTAL AND MACHINE LEARNING MODELING
title_full_unstemmed PARAMETRIC INVESTIGATION OF HPAM/GO-SIO2 THROUGH EXPERIMENTAL AND MACHINE LEARNING MODELING
title_sort parametric investigation of hpam/go-sio2 through experimental and machine learning modeling
publishDate 2021
url http://utpedia.utp.edu.my/id/eprint/25645/1/48_UTP21-3_PE48.pdf
http://utpedia.utp.edu.my/id/eprint/25645/
_version_ 1792156973676888064
score 13.214268

Similar Items