Machine learning model to predict the contact of angle using mineralogy, TOC and process parameters in shale

Saved in:
Bibliographic Details
Main Authors: Ameenuddin Irfan, S., Fadhli, M.Z., Padmanabhan, E.
Format: Conference or Workshop Item
Published: European Association of Geoscientists and Engineers, EAGE 2021
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111074226&doi=10.3997%2f2214-4609.202171009&partnerID=40&md5=c18a347bae53151fc765613596b5e658
http://eprints.utp.edu.my/23995/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utp.eprints.23995
record_format eprints
spelling my.utp.eprints.239952021-08-19T14:59:29Z Machine learning model to predict the contact of angle using mineralogy, TOC and process parameters in shale Ameenuddin Irfan, S. Fadhli, M.Z. Padmanabhan, E. European Association of Geoscientists and Engineers, EAGE 2021 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111074226&doi=10.3997%2f2214-4609.202171009&partnerID=40&md5=c18a347bae53151fc765613596b5e658 Ameenuddin Irfan, S. and Fadhli, M.Z. and Padmanabhan, E. (2021) Machine learning model to predict the contact of angle using mineralogy, TOC and process parameters in shale. In: UNSPECIFIED. http://eprints.utp.edu.my/23995/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
format Conference or Workshop Item
author Ameenuddin Irfan, S.
Fadhli, M.Z.
Padmanabhan, E.
spellingShingle Ameenuddin Irfan, S.
Fadhli, M.Z.
Padmanabhan, E.
Machine learning model to predict the contact of angle using mineralogy, TOC and process parameters in shale
author_facet Ameenuddin Irfan, S.
Fadhli, M.Z.
Padmanabhan, E.
author_sort Ameenuddin Irfan, S.
title Machine learning model to predict the contact of angle using mineralogy, TOC and process parameters in shale
title_short Machine learning model to predict the contact of angle using mineralogy, TOC and process parameters in shale
title_full Machine learning model to predict the contact of angle using mineralogy, TOC and process parameters in shale
title_fullStr Machine learning model to predict the contact of angle using mineralogy, TOC and process parameters in shale
title_full_unstemmed Machine learning model to predict the contact of angle using mineralogy, TOC and process parameters in shale
title_sort machine learning model to predict the contact of angle using mineralogy, toc and process parameters in shale
publisher European Association of Geoscientists and Engineers, EAGE
publishDate 2021
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111074226&doi=10.3997%2f2214-4609.202171009&partnerID=40&md5=c18a347bae53151fc765613596b5e658
http://eprints.utp.edu.my/23995/
_version_ 1738656551110967296
score 13.214268