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.

Format: Paperback / softback
Length: 138 pages
Publication date: 25 September 2023
Publisher: Taylor & Francis Ltd

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, this book explores how the cause and effect of process hazards can be modeled using BNs and how large BNs can be constructed from basic building blocks. The focus lies in developing BNs for typical equipment in the industry, including accident case studies, and their integration with other conventional risk assessment methods. This book is specifically designed for professionals working in the oil and gas industry, safety engineering, risk assessment, and related fields. It serves as a comprehensive resource that brings together the fundamentals of Bayesian theory, Bayesian Networks, and their applications to process safety hazards and risk assessment within the oil and gas industry. The book provides a step-by-step guide for setting up a model, populating it with data, and simulating the model in a systematic manner for practical cases. It also includes a comprehensive list of sources of failure data and valuable tips on modeling and simulation of large and complex networks. Furthermore, the book delves into the modeling and simulation of loss of containment of 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 of using Bayesian Networks in routine risk assessments. By leveraging the power of probabilistic reasoning and Bayesian Networks, this book offers valuable insights and tools for professionals seeking to enhance their risk management strategies in the oil and gas industry.

Weight: 280g
Dimension: 234 x 156 (mm)
ISBN-13: 9780367541972