Gulf Professional Publishing IoT for Smart Operations in the Oil and Gas Industry: From Upstream to Downstream

Product Description 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. Review Learn the latest advances in IoT and AI solutions and technology to support the upstream, midstream, and downstream oil and gas industry From the Back Cover The oil and gas industry look for ways to utilize machine learning, AI, and more advanced computing technologies to improve their operations. <i>IoT for Smart Operations in the Oil and Gas Industry</i> 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, <i>IoT for Smart Operations in the Oil and Gas Industry</i> delivers a much-needed reference for the engineer and manager to understand upcoming computing technologies for the oil and gas industry. About the Author Razin Farhan Hussain is currently a PhD candidate in computer science at the University of Louisiana at Lafayette. 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. Previously, he was a Lead Engineer for Samsung R&D Institute Bangladesh and Trainee Programmer at Era InfoTech Ltd. Ali Mokhtari is currently a PhD candidate in computer science at the University of Louisiana at Lafayette. He earned a MS in aerospace engineering at Sharif University of Technology in Iran, and a BS in mechanical engineering from Shiraz University in Iran. 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 o