Making smarter decisions for network longevity

The Picarro solution combines data analytics with a vehicle-based methane emissions data collection platform to assist with capital pipeline replacement decisions as one of its many use case applications. 

The vehicle mounted Picarro systems conduct multiple patrols through a natural gas infrastructure, collecting methane plume data, wind, atmospheric and GPS data and sending it to the Picarro cloud. The data is later processed by Picarro’s algorithms to detect and localise leaks and calculate methane emission rates.  Here, the analytics transform the data into actionable results for a number of applications – from leak survey to pipeline replacement optimization to emissions reduction and more.

This leads to significant O&M cost savings through avoided leak repair by prioritising replacements of pipelines with high leak or emissions densities. 

Picarro’s Director of Gas Sales & Marketing, Doug Ward, says when this data is combined with traditional risk (DIMP) models, such benefits are maximised, including optimised capital project prioritisation, accelerated risk reduction, emissions reduction, and reduction in odour calls. 

“The solution has its greatest economic benefit when used in applications where 

locating specific leaks is not the goal. In the latter, using methane data collected along pipelines, Picarro’s analytics estimate leak density (leaks per kilometre or area) and measure the actual, aggregated methane emissions (flow rate) along pipe segments or areas rather than identifying individual leaks,” Ward says. 

Picarro pioneered over a decade ago the Advanced Leak Detection concept that utilises the wind to bring methane plumes to Picarro’s vehicle-based methane and atmospheric sensing platform. 

The company’s data collection methodology is based on the ability of the Picarro system to detect methane emissions below as well as at distances of hundreds of metres away from the vehicle when the methane emission point is upwind of the vehicle. 

The reach of Picarro’s Field of View (FOVTM) coverage area is calculated at each point along the vehicle path to provide documented record of survey coverage. In this way, both mains, services, and gas meters can effectively be surveyed. 

Outlined in a recent case study of a 276-mile distribution system in Northeastern US, Picarro enabled the customer to remediate the number of leaks, avoid repair costs, and optimise pipe replacement by making slight changes to the planned replacement projects.

Ward says Picarro’s optimisation enable the customer to remediate 2x the leaks per mile as compared to the existing replacement strategy (5.7/2.8 leaks per mile = 2x). 

“Looking at the case study closer, over the 276 miles they had an average leak density of 1.2 leaks per mile,” he says. 

“What the client had selected with their DIMP model was going to extract and remediate sections of pipes that had 2.8 leaks per mile. But if we could select pipes to replace based on methane data, the leakage rate and emissions rate, we could achieve 5.7 leaks per mile being remediated for that same amount of mileage.

“For example, if it was 10 miles of pipe replacement in the 276 miles, the DIMP model would remediate 28 leaks. But in our model, with the same budget and length, we would have mitigated twice as many leaks compared to what the DIMP model had suggested.” 

Ward says leaks are a large indicator of the integrity of the pipe and future failures. He says overall, a lot of utilities are using Picarro’s data to understand their network better.

By scheduling repairs instead of doing emergency repairs, Ward says customers can find leaks before they become an issue, and potentially avoid sending emergency repair crews out after normal working hours, reducing overtime. 

“Instead, by having a Picarro program they can replace the most hazardous and dangerous pipes which then leads to system risk reductions, reduced costs and less unplanned work,” Ward says. 

“From a capital expenditure point of view, companies can prioritise those decisions and improve the accuracy of DIMP models because there is more real-time data about the assets.”

For more information visit Picarro.

This article featured in the May edition of The Australian Pipeliner. 

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