Oil and Gas Processing Equipment: Risk Assessment with Bayesian Networks

Oil and gas industries use Bayesian Networks (BNs) to assess and mitigate risks, modeling cause and effect of process hazards with probabilistic nature, conditional probability, and Bayesian thinking. This book covers the development of BNs for typical equipment, accident case studies, and their use alongside conventional risk assessment methods. It aims at professionals in the industry, providing a systematic approach to setting up models, populating them with data, and simulating practical cases.

\n Format: Hardback
\n Length: 138 pages
\n Publication date: 15 September 2020
\n Publisher: Taylor & Francis Ltd
\n

The oil and gas industries employ a range of techniques to evaluate and manage the risks associated with their operations. In this context, the application of Bayesian Networks (BNs) to risk assessment presents a distinct probabilistic approach to causal reasoning. By incorporating the probabilistic nature of hazards, conditional probability, and Bayesian thinking, the book delves into the modeling of cause and effect relationships in process hazards using BNs. It discusses the development of large BNs from basic building blocks and their application in assessing risks for typical equipment in the industry, including accident case studies. The book is specifically designed for professionals working in the oil and gas industry, safety engineering, risk assessment, and related fields. It offers a comprehensive overview of Bayesian theory, Bayesian Networks, and their applications to process safety hazards and risk assessment. The book provides a step-by-step guide for setting up BNs, populating them with data, and simulating them for practical cases in a systematic manner. It includes a comprehensive list of sources of failure data and valuable tips on modeling and simulation of large and complex networks. Furthermore, the book showcases the modeling and simulation of loss of containment scenarios for actual equipment in the oil and gas industry, such as separators, storage tanks, pipelines, compressors, and risk assessments. Case studies are presented to demonstrate the practicality and effectiveness of using Bayesian Networks in routine risk assessments. By leveraging the power of probabilistic reasoning and statistical analysis, this book empowers professionals to make informed decisions and implement effective risk management strategies in the oil and gas industry.

\n Weight: 380g\n
Dimension: 161 x 241 x 16 (mm)\n
ISBN-13: 9780367254407\n \n