Towards BBN based risk modelling of process plants

• A method is developed to integrate human and technical factors into a Bow-Tie using Bayesian Belief Nets.
• A systematic way of handling uncertainties is provided.
• A method is developed to describe time dependencies.
• A method to estimate human incentives towards safety is presented.

Recent disasters in high hazard industries such as Oil and Gas Exploration (The Deepwater Horizon) and Petrochemical production (Texas City) have been found to have causes that range from direct technical failures through organizational shortcomings right up to weak regulation and inappropriate company cultures. Risk models have generally concentrated upon technical failures, which are easier to construct and for which there is more concrete data. The primary causes lie firmly rooted in the culture of the organization and determine the way in which individuals go about risky activities. Modelling human activities, especially collectively rather than individual human errors as is done in most human models, is a quite different proposition, in which complex interactions between different individuals and levels change over time as success and failure alter the pattern of payoffs.This paper examines the development of a dynamic integrated model for risk in a real-time environment for the hydrocarbon industry. It is based originally on the CATS model for commercial aviation safety, which first attempted to address some of these problems in a relatively simple way. Aviation is, however, a relatively simple activity, with large numbers of common components in a constrained environment. The Oil and Gas industry is significantly more diverse, covering the gamut from exploration, drilling, production, transport, refining and chemical production, each with its own potential for large scale disaster, but in the case of an integrated oil company all run by individuals within a common company culture.