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Oil and gas industries apply several techniques for assessing and mitigating the risks that are inherent in its operations. In this context, the application of Bayesian Networks (BNs) to risk assessment offers a different probabilistic version of causal reasoning. Introducing probabilistic nature of hazards, conditional probability and Bayesian thinking, it discusses how cause and effect of process hazards can be modelled using BNs and development of large BNs from basic building blocks. Focus is on development of BNs for typical equipment in industry including accident case studies and its usage along with other conventional risk assessment methods. Aimed at professionals in oil and gas industry, safety engineering, risk assessment, this book
G. Unnikrishnan has over 40 years of experience in oil and gas industry. His experience spans the areas of process design, process safety, engineering & project management. He is currently on assignment as Engineering Specialist with a National Oil Company in the Middle East. He previously worked with engineering consultancy companies in India and abroad. His current work involves review and assessment of Front End Engineering Design and engineering management for upstream oil and gas projects.
He is keenly interested in optimization of process design and how it can be done with the highest process safety. He believes that much needs to be done in process plant design and operations to minimize accidents. He is an active researcher in the area and has presented and published papers on the subject in several international conferences and technical journals. He is a certified Functional Safety Engineer on Safety Instrumented Systems. He holds a degree in Chemical Engineering from Calicut University, MTech from Cochin University of Science & Technology and PhD from University of Petroleum and Energy Studies, Dehradun, India.
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