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Produktbild: Machine Learning and Flow Assurance in Oil and Gas Production
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Machine Learning and Flow Assurance in Oil and Gas Production

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Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

12.03.2023

Abbildungen

VII, 177 p. 35 illus., 28 illus. in color.

Herausgeber

Bhajan Lal + weitere

Verlag

Springer

Seitenzahl

177

Maße (L/B/H)

24,1/16/1,6 cm

Gewicht

401 g

Auflage

2023

Sprache

Englisch

ISBN

978-3-031-24230-4

Beschreibung

Portrait

Dr. Bhajan Lal, chartered chemist, is a senior lecturer (2013-conti..) in Chemical Engineering Department and a core research member of CO2 Research Centre in Institute of Contaminant Management (ICM) at the Universiti Teknologi PETRONAS-Malaysia. After receiving M.Sc., Ph.D. degree (Physical Chemistry) in 2004 from JMI Central University, New Delhi, India, Dr. Lal worked as a postdoc fellow and research scientist in USA, Canada, South Africa, Turkey, and Malaysia (2004-2013). His main areas of research interests are CO2 hydrates and its application in CO2 capture and storage, desalination, and flow assurance. He graduated 6 M.Sc., 5 Ph.D., 2 postdocs, and more than 60 chemical engineering undergrads FYPI students since 2013. Dr. Lal has published 4 books related to oil and gas industry, 120 peer-reviewed journal papers, 50 conference papers, and 4 book chapters (H-index 36, i-10 index 93, no of being cited 3825). In addition, as a project leader, he has secured 18 gas hydrate-related research projects worth RM 3.4 million from oil and gas industries, UTP, and Malaysian Government. He achieved Gold Medal in ITEX2021, EREKA 2022 -Malaysia for his novel gas hydrate-based desalination product exhibition. He delivered customized online/face-to-face short courses in flow assurance, machine learning, and gas hydrate related to oil and gas industry.



Cornelius Borecho Bavoh is a researcher and academician. He worked at the Phase Separation Laboratory of the Research Center for CO2 Capture (RCCO2C) in the Chemical Engineering Department of Universiti Teknologi PETRONAS (UTP), Seri Iskandar, Perak Darul Ridzuan, Malaysia. He has more than 5 years of experience in tutoring and research at the Universiti Teknologi PETRONAS, Malaysia. He has worked on several industrial and fundamental projects related to drilling, gas hydrate, and CO2 capture and separation, and published more than 30 scientific papers in peer-reviewed journals, conferences, and book chapters. Bavoh holds Ph.D. and M.Sc. degrees in chemical engineering and B.Sc. (Hons) degree in petroleum engineering. His research expertise includes thermodynamics and kinetics of reservoir fluid phase modeling and characterization, gas hydrate in flow assurance, production of naturally deposited methane hydrates, and application of gas hydrate-based technology in CO2 capture and natural gas storage and transportation, drilling fluid technology, rheology, and cuttings transport. Bavoh is a member of the Society of Petroleum Engineers (SPE).



Dr. Jai Krishna Sahith graduated in mechanical engineering department from University Technology PETRONAS, Malaysia, and currently doing postdoc in University College Dublin (UCD). Previously, he completed his masters from Jawaharlal Nehru Technological University Kakinada, India. He filed the IP and patent on gas hydrate-related applications. At present, he is working on gas hydrate-based desalination process. He has published hisresearch work in peer-reviewed journals and book chapters.





Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

12.03.2023

Abbildungen

VII, 177 p. 35 illus., 28 illus. in color.

Herausgeber

Verlag

Springer

Seitenzahl

177

Maße (L/B/H)

24,1/16/1,6 cm

Gewicht

401 g

Auflage

2023

Sprache

Englisch

ISBN

978-3-031-24230-4

Herstelleradresse

Springer-Verlag GmbH
Europaplatz 3
69115 Heidelberg
DE

Email: ProductSafety@springernature.com

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  • Produktbild: Machine Learning and Flow Assurance in Oil and Gas Production
  • Chapter 1: Machine Learning and Flow Assurance Issues.- Chapter 2: Machine Learning in Oil and Gas Industry.- Chapter 3: Multiphase Flow Systems and Potential of Machine Learning Approaches in Cutting Transport and Liquid Loading Scenarios.- Chapter 4: Machine Learning in Corrosion.- Chapter 5: Machine Learning in Asphaltenes Mitigation.- Chapter 6: Machine learning for Scale deposition in oil and gas industry.- Chapter 7: Machine Learning in CO2 sequestration.- Chapter 8: Machine Learning in Wax Deposition.- Chapter 9: Machine Learning Application in Gas Hydrates.- Chapter 10: Machine Learning Application Guidelines in Flow Assurance.