Low-Cost Representative Sampling for a Natural Gas Distribution System in Transition

Area of Science:

• Engineering
• Materials Science
• Environmental Science

Background:

• Natural gas distribution systems are critical energy infrastructure in the US.
• Decarbonization efforts require understanding infrastructure adaptation to new operational modes like hydrogen or biogas blending.
• Current asset data is often incomplete, hindering predictive analysis.

Purpose of the Study:

• To assess the viability of opportunistic sampling for gathering crucial data on natural gas infrastructure.
• To determine if data from assets undergoing maintenance is representative of the entire asset base.
• To inform strategies for safe and reliable energy transition.

Main Methods:

• Analysis of a comprehensive dataset of service lines and leaks from a major natural gas utility.
• Statistical evaluation of samples from excavation-damaged lines against the overall asset base.
• Utilizing opportunistic sampling to estimate unknown plastic pipe types.

Main Results:

• Excavation damage sites yield a representative sample of plastic and steel service lines regarding age, pressure, and diameter.
• Opportunistic sampling can estimate the prevalence of key characteristics, such as plastic pipe type (unknown for 80% of plastic lines).
• Excavation damage is a major cause of hazardous leaks in plastic lines (75%), while corrosion dominates steel line leaks (47%).

Conclusions:

• Opportunistic sampling is a cost-effective method for collecting representative data on natural gas infrastructure.
• This approach supports data-driven decisions for managing aging infrastructure during the energy transition.
• Improved data collection is essential for ensuring the safety and reliability of a lower-emission natural gas system.