Risk models are prominent pipeline integrity management (PIM) tools used to make data-driven decisions. With the growth in computing power and data acquisition methods, risk models have become more complex. Understanding the impact of data uncertainty on risk model outcomes is crucial to effectively and ethically apply the model in any decision-making process. In the United States, 49 CFR 192.917(4)c specifies Sensitivity Analysis (SA) implementation on factors characterizing both the likelihood and consequence of failure for gas pipelines.

This white paper provides a brief review of local and global SA techniques, identifying critical gaps. Additionally, it offers a comprehensive comparative study, delving into the key criteria for technique selection and it includes two detailed case studies showcasing the practical application of global simulation-based SA methods in quantitative risk models.

Date Published: March 27, 2024