eprintid: 19091
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/90/91
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: Bavoh, C.B.
creators_name: Lal, B.
title: Machine Learning and Flow Assurance Issues
ispublished: pub
note: cited By 1
abstract: This chapter briefly discusses the main challenges facing the flow assur­ance related areas in the oil and gas industry. It also provide simple fundamental definitions to machine learning vocabulary to introduce to machine learning terms. © 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-s2.0-85174780226&doi=10.1007%2f978-3-031-24231-1_1&partnerID=40&md5=41c08fee0b50c9684bb30c65588c4d21
id_number: 10.1007/978-3-031-24231-1₁
full_text_status: none
publication: Machine Learning and Flow Assurance in Oil and Gas Production
pagerange: 1-5
refereed: TRUE
isbn: 9783031242311; 9783031242304
citation:   Bavoh, C.B. and Lal, B.  (2023) Machine Learning and Flow Assurance Issues.     Springer Nature, pp. 1-5.  ISBN 9783031242311; 9783031242304