Demonstration of a Multianalytic Risk Management Tool for the California Pipeline Industry

Maintaining natural gas pipeline safety involves making decisions based on multiple sources of information. Integrating information from these diverse sources – real-time data from sensors, older data stored in databases, incident reports, and expert knowledge – into a single framework can be very difficult. To address this challenge, DNV GL created a Multi-Analytic Risk Visualization method to combine information, regardless of its source or degree of uncertainty, to help comprehensively anticipate, prioritize, and manage threats to natural gas pipeline systems in California.
This report provides the activities for modeling two threats chosen by the project’s industry partner, Southern California Gas Company. DNV GL, University of California, Los Angeles (UCLA) and Southern California Gas Company selected two pipelines to test the MARV™ method and identified the data needed for the models. DNV GL then developed an external corrosion Bayesian (a type of statistical model) threat model and UCLA developed a Bayesian third-party damage threat model for gas transmission pipelines. The industry partner’s confidential data was used for the models to identify the leading indicators: parameters that should be monitored to control the threat.