The book aims to provide comprehensive knowledge and information pertaining to application or implementation of big data in the petroleum industry and its operations (such as exploration, production, refining and finance).
The book covers intricate aspects of big data such as 6Vs, benefits, applications, implementation, research work and real-world implementation pertaining to each petroleum-associated operation in a concise manner that aids the reader to apprehend the overview of big data's role in the industry.
The book resonates with readers who wish to understand the intricate details of working with big data (along with data science, machine learning and artificial intelligence) in general and how it affects and impacts an entire industry. As the book builds various concepts of big data from scratch to industry level, readers who wish to gain big data-associated knowledge of industry level in simple language from the very fundamentals would find this a wonderful read.
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Für die Erwachsenenbildung
Academic, Adult education, Postgraduate, Professional, Professional Practice & Development, Undergraduate Advanced, and Undergraduate Core
Illustrationen
25 s/w Tabellen, 54 s/w Zeichnungen, 54 s/w Abbildungen
25 Tables, black and white; 54 Line drawings, black and white; 54 Illustrations, black and white
Maße
Höhe: 246 mm
Breite: 174 mm
Dicke: 10 mm
Gewicht
ISBN-13
978-1-032-02901-6 (9781032029016)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Mr. Jay Gohil is pursuing Bachelor of Technology in Information and Communication Technology at Pandit Deendayal Energy University. He has authored three research papers, two conference papers, two book chapters and a book (this) during his academic study. His research interests include Big Data, Data Science, Machine Learning, Deep Learning, Data Mining and Artificial Intelligence, and he has communicated research work in esteemed journals in these areas. He has been a research intern at ISRO (Indian Space Research Organization, Ahmedabad, India) and Ryerson University (Toronto, Canada). He is also a Google DSC Lead, Microsoft Learn Student Ambassador, Intel Student Ambassador for IoT, IBM Z Ambassador, AWS Community Builder and deeplearning.ai Event Ambassador.
Dr. Manan Shah has a B.E. in Chemical Engineering from LD College of Engineering and an M.Tech. in Petroleum Engineering from School of Petroleum Technology, PDPU. He has completed his Ph.D. in the area of exploration and exploitation of Geothermal Energy in the state of Gujarat. He is currently Assistant Professor in the Department of Chemical Engineering, School of Technology (SOT), PDPU, and Research Scientist in Centre of Excellence for Geothermal energy (CEGE). One of his areas of research is power generation from low enthalpy geothermal reservoirs using Organic Rankine Cycle. He was also involved in the designing of a Geothermal Space Heating and Cooling system at Dholera and doing research on hybrid setup in the renewable energy sector. Dr. Shah has received the Young Scientist Award from the Science and Engineering Research Board (SERB). He has published several articles in reputed international journals in the areas of renewable energy, petroleum engineering, water quality and chemical engineering. He serves as an active reviewer for several Springer and Elsevier international journals.
Autor*in
Pandit Deendayal Petroleum University, India
Pandit Deendayal Petroleum Uni, India
1 Introduction; 2 Petroleum Operations; 3 Big Data's 6Vs; 4 Benefits of Big Data; 5 Applications of Big Data; 6 Implementation of Big Data; 7 Big Data Platforms; 8 AI Algorithms; 9 Research on Big Data; 10 Real-World Implementation of Big Data; 11 Traits of Companies with Superior Big Data Implementation; 12 Challenges of Big Data; 13 Future Scope of Big Data; 14 Conclusion
