Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Mohd Azmin Ishak"'
Publikováno v:
Day 3 Wed, February 23, 2022.
This paper introduces a multimodal virtual flow meter (VFM) that merges physics-driven multiphase flow simulations with machine learning models to accurately estimate flow rates in oil and gas wells. The combining algorithm takes advantage of the con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9d6b9da10c78e435102c9b76a61e4018
https://doi.org/10.2523/iptc-22431-ms
https://doi.org/10.2523/iptc-22431-ms
Publikováno v:
International Journal on Smart Sensing and Intelligent Systems. 15
This paper describes a Virtual Flow Meter (VFM) to estimate oil, gas and water flow rate by combining two distinct approaches i.e., data-driven Ensemble Learning algorithm and first principle physics-based transient multiphase flow simulator. The VFM
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4c47dbb4482903ff8ccf042c4d261d75
https://doi.org/10.2478/ijssis-2022-0010
https://doi.org/10.2478/ijssis-2022-0010
Autor:
Torgeir Ruden, Tareq Aziz Al-qutami Hasan, Mohd Azmin Ishak, Hatef Khaledi, Halvard Ellingsen
Publikováno v:
Day 2 Tue, November 03, 2020.
Production Well Testing is one of the major routines in the upstream oil and gas operations. It is an important oil & gas operation as it will be used to track the performance of individual well productivity, production planning, projection for futur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7a0855e63cdd8b4bc8f047d43a8a447d
https://doi.org/10.4043/30422-ms
https://doi.org/10.4043/30422-ms
Publikováno v:
Expert Systems with Applications. 93:72-85
Development of data-driven virtual flow meter (VFM) using diverse neural network ensembles.Adaptive simulated annealing is used for pruning and combining strategy selection.VFM can provide real-time monitoring for fields with common metering infrastr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::49eddee2d901a20ee8b97942fda9480b
https://doi.org/10.1016/j.eswa.2017.10.014
https://doi.org/10.1016/j.eswa.2017.10.014
Publikováno v:
International Journal on Smart Sensing and Intelligent Systems, Vol 10, Iss 1 (2017)
Scopus-Elsevier
Scopus-Elsevier
This paper proposes a soft sensor to estimate phase flow rates utilizing common measurements in oil and gas production wells. The developed system addresses the limited production monitoring due to using common metering facilities. It offers a cost-e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d9081bde2b74c430530e5e89490f31b
https://www.exeley.com/exeley/journals/in_jour_smart_sensing_and_intelligent_systems/10/1/pdf/10.21307_ijssis-2017-209.pdf
https://www.exeley.com/exeley/journals/in_jour_smart_sensing_and_intelligent_systems/10/1/pdf/10.21307_ijssis-2017-209.pdf
Publikováno v:
ICMLC
Estimation of individual phase flow rates in multiphase flow is of great significance to production optimization and reservoir management in oil and gas industry. This paper proposes radial basis function network to develop a virtual flow meter (VFM)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d3fc14df52060b2bc3c56c8d5c8fde0b
https://doi.org/10.1145/3055635.3056638
https://doi.org/10.1145/3055635.3056638