Using Common Models for Integrity Management and Investment Optimization in Gas

Using Common Models for Integrity Management and Investment Optimization in Gas Transmission & Distribution

Because of the potential hazards in operating a gas pipeline system, regulators mandate that natural gas utilities implement integrity management programs. For example, in the US, the Pipeline and Hazardous Materials Safety Administration (PHMSA) has published the Pipeline Safety Regulations (Title 49 CFR Part 192) and in the UK, the Office of Gas and Electricity Markets (Ofgem) recommends the Network Output Measures (NOMs) methodology.

The details of the regulations vary from jurisdiction to jurisdiction, but fundamentally such regulations are designed to make sure that the utility has a program in place for identifying existing and potential threats, evaluating and ranking risks, and proactively implementing measures to address those risks.

Gas distribution networks can have millions of assets and so identifying and quantifying the risks necessitates building mathematical models based on the attributes of the assets. For example, estimating the probability of failure of a steel main due to external corrosion is a function of numerous attributes of the main (e.g. age, protection, soil type). Similarly, the consequence of a failure is based on attributes such as class location. In addition, there are many different threats (e.g. internal corrosion, external corrosion or third-party damage) and the probability and consequence needs to be computed for every threat.

JANA has been providing risk modeling and integrity management consulting services to utilities in North America for nearly two decades. They are a pioneer in mechanistic-probabilistic risk modeling, specializing in using real-life data and proven statistical risk models to reliably predict how an asset’s risk profile will change over time.

JANA has developed quantitative risk models for gas distribution and transmission networks. These risk models compute the probability of different scenarios (e.g. ignition, explosion) and the consequence of those scenarios for 25 different threat types for various distribution assets (e.g. mains, services, risers, valves, etc.). JANA and Copperleaf have worked together to integrate these risk models into both the Copperleaf Integrity Management product (CIM) and the C55 Decision Analytics solution.

Integrity management programs identify the riskiest issues, but ultimately, trade-offs must be made between the recommendations of the integrity management program and other investments being made by the utility—such as system improvements, growth investments, IT, fleet, etc. C55 allows utilities to optimize their investments to provide the highest possible value—while respecting funding, resource and timing constraints.

Because the JANA risk models are quantitative risk models, the output of those models can be used to objectively determine the value of all investments. This allows integrity management investments to be automatically evaluated as part of the investment optimization process without requiring additional work by the project owners to rationalize or quantify the benefits of the investments. Through our partnership with JANA we have implemented their risk models in a number of utilities across North America, however, it is worth noting that similar benefits can be achieved with any quantitative risk model.

Utilizing the same quantitative risk models for integrity management and investment optimization reduces the effort to evaluate investments and allows for an objective optimization of integrity management investments against all other investments being considered by the utility.

If you are looking to implement a risk-informed integrity management strategy, please get in touch! In the meantime, feel free to download the Copperleaf Integrity Management brochure to learn more.

 

About the Author

Stan Coleman

With more than 25 years of high tech development and management experience, Stan is currently the CTO at Copperleaf.

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