IoT for Smart Operations in the Oil and Gas Industry

IoT for Smart Operations in the Oil and Gas Industry

From Upstream to Downstream

1st Edition - October 1, 2022

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  • Authors: Razin Farhan Hussain, Ali Mokhtari, Ali Ghalambor, Mohsen Amini Salehi
  • Paperback ISBN: 9780323911511

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The oil and gas industry look for ways to utilize machine learning, AI, and more advanced computing technologies to improve their operations. IoT for Smart Operations in the Oil and Gas Industry elaborates on how the synergy between state-of-the-art computing platforms, such as Internet of Things (IOT), cloud computing and artificial intelligence, in particular modern machine learning methods, can be harnessed to serve the purpose of a more efficient oil and gas industry. The reference explores the operations performed in each sector of the industry and then introduces the computing platforms and advanced technologies that can enhance the operation, lower costs, and lower carbon footprint. Safety and security content is included, in particular, cybersecurity and potential threats to smart oil and gas solutions, focusing on adversarial effects of smart solutions, problems resulted from interference of smart solutions, and problems related to the interoperability of human-machine intelligence in the context of oil and gas industry. Detailed case studies are included throughout to learn and research for further application. Covering the latest topics and solutions, IoT for Smart Operations in the Oil and Gas Industry delivers a much-needed reference for the engineer and manager to understand upcoming computing technologies for the oil and gas industry.

Key Features

  • Follow a systematic and categorical taxonomy of the upstream, midstream, and downstream processes paired with cutting-edge technologies that benefit both the computer scientist and engineer
  • Understand advanced computing technologies to reduce the costs of existing operations and carbon footprint
  • Deep dive into case studies that cover the entire oil and gas spectrum and explain bridges into application


Oil and gas industry engineer and researcher working either in exploration, drilling, completions, production, midstream, and downstream operations

Table of Contents

  • 1. Introduction to Smart O&G Industry
    2. Smart Upstream Sector
    3. Smart Midstream of O&G Industry
    4. Smart Downstream Sector of O&G Industry
    5. Threats and Side-Effects of Smart Solutions in Oil and Gas Industry
    6. Designing a Disaster Management System for Smart Oil Fields
    7. Case Study I: Analysis of Oil Spill Detection Using Deep Neural Networks
    8. Case Study II: Evaluating DNN Applications in Smart O&G Industry

Product details

  • No. of pages: 200
  • Language: English
  • Copyright: © Gulf Professional Publishing 2022
  • Published: October 1, 2022
  • Imprint: Gulf Professional Publishing
  • Paperback ISBN: 9780323911511

About the Authors

Razin Farhan Hussain

Razin Farhan Hussain is currently a PhD candidate in computer science at the University of Louisiana at Lafayette. He works as a research assisstant at High Performance Cloud Computing (HPCC) Lab of computer science department. His research interest includes efficient utilization of fog computing for Industry 4.0 applications focusing Deep Neural Network models. He earned a M.Sc. in computer science from the University of Louisiana at Lafayette, and a Bachelor of Science in computer science and engineering from the Military Institute of Science and Technology at the Bangladesh University of Professionals.

Affiliations and Expertise

PhD Candidate, University of Louisiana at Lafayette, Lafayette, LA, USA

Ali Mokhtari

Ali Mokhtari is currently a researcher in the High-Performance Cloud Computing (HPCC) laboratory at the University of Louisiana at Lafayette. His main research interests are Artificial Intelligence (AI) and Edge-to-Cloud computing. He earned a M.Sc in aerospace engineering at Sharif University of Technology in Iran, and a B.Sc in mechanical engineering from Shiraz University in Iran.

Affiliations and Expertise

Researcher, High-Performance Cloud Computing (HPCC) Laboratory, University of Louisiana at Lafayette. Lafayette, LA, USA

Ali Ghalambor

Ali Ghalambor is currently an international consultant with more than 40 years of industrial and academic experience. He served as the API Endowed Professor, head of the petroleum engineering department, and director of the Energy Institute at the University of Louisiana at Lafayette. He has performed consulting and training services in 45 countries, authored 15 books and more than 230 technical papers. Ali received the SPE Distinguished Achievement Award for Petroleum Engineering Faculty in 2001, the Distinguished Member in 2006, Production and Operations Award in 2007, and Distinguished Service Award in 2008. Dr. Ghalambor earned a BS and MS degree, both in petroleum engineering from the University of Southwestern Louisiana, and a PhD in environmental sciences and engineering from Virginia Polytechnic Institute and State University. He is a registered professional engineer in the US, elected member of the Russian Academy of Natural Sciences, and recipient of its Nobel Laureate Physicists Kapitsa Gold Medal.

Affiliations and Expertise

Formerly Professor, University of Louisiana at Lafayette, Lafayette, LA, USA

Mohsen Amini Salehi

Mohsen Amini Salehi is currently Associate Professor at the School of Computing and Informatics, University of Louisiana at Lafayette. He is the director of High-Performance Cloud Computing (HPCC) laboratory where several researchers explore the applications of Cloud and Edge computing in Industry 4.0 use cases. He earned a PhD in computing and software engineering from Melbourne University, a M.Sc. in software engineering from Ferdowsi University, and a B.Sc. in software engineering from Azad University of Mashhad, Iran.

Affiliations and Expertise

Associate Professor, School of Computing and Informatics, University of Louisiana at Lafayette, Lafayette, LA, USA

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