eprintid: 17509 rev_number: 2 eprint_status: archive userid: 1 dir: disk0/00/01/75/09 datestamp: 2023-12-19 03:23:53 lastmod: 2023-12-19 03:23:53 status_changed: 2023-12-19 03:08:10 type: article metadata_visibility: show creators_name: Ishak, M.A. creators_name: Ismail, I. creators_name: Al-qutami, T.A.H. title: Virtual Multiphase Flow Meter using combination of Ensemble Learning and first principle physics based ispublished: pub note: cited By 0 abstract: This paper describes a Virtual Flow Meter (VFM) to estimate oil, gas and water flow rate by combining two distinct approaches i.e., datadriven Ensemble Learning algorithm and first principle physics-based transient multiphase flow simulator. The VFM uses a common real-time sensor readings and the estimated flow rates were then combined using a new combiner approach which provides confidence decay and historical performance factors to assign confidence and contribution weights to the base estimators, and then aggregates their estimates to deliver more accurate flow rate estimates. This technique was tested for over 6 months at an offshore oil facility having two oil wells. The technique successfully delivered a 50 improvement in measurement performance compared to stand-alone VFMs. This combiner technique will be of great benefit to surveillance engineers by providing additional real-time production monitoring in addition to acting as a verification tool for physical multiphase flow meters (MPFMs). © 2022 Authors. This work is licensed under the Creative Commons Attribution-Non-Commercial-NoDerivs 4.0 License https://creativecommons.org/licenses/by-nc-nd/4.0/. All Rights Reserved. date: 2022 publisher: Sciendo official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139007799&doi=10.2478%2fijssis-2022-0010&partnerID=40&md5=7d637e797be4069c4dec1c30a4541e4c id_number: 10.2478/ijssis-2022-0010 full_text_status: none publication: International Journal on Smart Sensing and Intelligent Systems volume: 15 number: 1 pagerange: 1-21 refereed: TRUE issn: 11785608 citation: Ishak, M.A. and Ismail, I. and Al-qutami, T.A.H. (2022) Virtual Multiphase Flow Meter using combination of Ensemble Learning and first principle physics based. International Journal on Smart Sensing and Intelligent Systems, 15 (1). pp. 1-21. ISSN 11785608