eprintid: 19092
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/90/92
datestamp: 2024-06-04 14:11:32
lastmod: 2024-06-04 14:11:32
status_changed: 2024-06-04 14:04:51
type: book
metadata_visibility: show
creators_name: Sahith Sayani, J.K.
creators_name: Lal, B.
title: Machine Learning in Oil and Gas Industry
ispublished: pub
note: cited By 0
abstract: In the chapter, the use of machine learning in the oil and gas industry is briefly presented with emphases on the current trends in the oil and gas models. Also, the use of machine learning in the oil and gas upstream is discussed with highlights on the recent advancement on the use of AI in the oil and gas industry. The challenges facing the application of machine learning in the oil and gas industry is also presented. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.
date: 2023
publisher: Springer Nature
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174779179&doi=10.1007%2f978-3-031-24231-1_2&partnerID=40&md5=c79c9a2fb94df592ea7665ab070e66ff
id_number: 10.1007/978-3-031-24231-1₂
full_text_status: none
publication: Machine Learning and Flow Assurance in Oil and Gas Production
pagerange: 7-26
refereed: TRUE
isbn: 9783031242311; 9783031242304
citation:   Sahith Sayani, J.K. and Lal, B.  (2023) Machine Learning in Oil and Gas Industry.     Springer Nature, pp. 7-26.  ISBN 9783031242311; 9783031242304