Leak detection has historically been a challenge for the oil and gas companies and is critical to the industry’s future. With current technology falling short, what happens when you bring cloud-based IoT architecture into the mix?
For owners and operators of pipelines carrying hazardous materials, including hydrocarbons, spontaneous leaks represent a significant environmental, health, and safety (EHS) risk that cannot be taken lightly. According to thePipeline and Hazardous Materials Safety Administration (PHMSA), pipeline incidents between 2005-2017 resulted in 168 fatalities, 592 injuries, and over $5.4 billion in total costs.
While the first line of defense in protecting against an unplanned product release in any pipeline is to ensure structural integrity through proactive measures,spontaneous leakswill inevitably occur. The key for operators is having the capability to detect the leak and determine its location quickly so that steps can be taken to minimize the impact on the environment. Unfortunately, this is something many companies across the oil and gas industry have struggled to do cost-effectively.
Today, a variety of methods and technologies are used forleak detection.
Mass-volume balance is one of the most widely used techniques, particularly for long-distance transmission lines. The method is based on the principle of mass-volume conservation, where the amount of product in the line is measured and compared at multiple meters along a route.
While simple to implement and cost-friendly, mass-volume balancing as a standalone solution does not constitute a comprehensive leak detection strategy, as it often fails to detect small product r releases. In some cases, as much as 1.5% - 4% of the volume in a line can be “lost” before a leak is triggered. For transmission lines where hundreds of thousands of barrels of liquid or millions of cubic feet of gas are transported on a daily basis, this can represent a substantial amount of product.
More advanced techniques, such as fiber-optic sensing, can resolve this problem. However, laying fiber-optic cable is often not feasible in many cases.
“Fiber-optic is very hard to deploy on what we call brownfield operations, or existing pipelines – and very expensive,” says Matthew Grimes, Business Owner for Spontaneous Leak Detection (SLD) at Siemens Energy. “In the U.S., it’s estimated that roughly half of the nation’s 2.6 million miles of oil and gas gathering, distribution, and transmission lines were commissioned more than half a century ago. It is very difficult for operators to justify large capital investments in these assets, as many have only limited years of service remaining.”
In 2020, Siemens Energy and Houston-based ProFlex Technologies partnered to develop a leak detection solution which overcomes many of the pain points of existing methods.
Offered to the market as “Siemens Energy Spontaneous Leak Detection (SLD) Service powered by ProFlex”, the system combines proven negative-pressure wave (NPW)-based sensing and advanced signal processing with Siemens Energy’s cloud-based IoT architecture to pinpoint the location of small leaks within seconds of their occurrence.
“Negative Pressure Wave (NPW)-based leak detection is a proven technique that has been in practice for decades,” said Nico van Rensburg, Head of Portfolio Innovation forOnshore Oil and Gasat Siemens Energy. “However, one of the most often cited issues in the past has been the high rate of false alarms caused by the errant noise in pipeline systems. One of the key differentiators with our SLD system is the algorithms we use to filter out that noise and determine what is truly a leak and what is not.”
Once a leak event has been identified, Siemens Energy’s cloud-basedIoT systemnotifiesusers through mobile devices, laptops, or desktop, or the pipeline’s SCADA system.Leak location in the form of latitude and longitude coordinates is presented on a pipeline asset map and has proven to be accurate to 20-50 feet.
The system uses existing block valves and risers and does not require excavations to deploy. Self-powered pressure and temperature transducers are tied in at access points. The system is then “trained” or “baselined” for about two weeks before becoming fully operational.
While Grimes and van Rensburg are based in Houston, their team includes members from ProFlex Technologies in Oklahoma and technicians in India, Germany, the Netherlands and Brazil. Covid-19 restrictions, as well as the physical distances meant that the 35 people on the team worked remotely to develop the system. “I’ve never met a large portion of our team face-to-face. We’ve all done this out of our garages, out of our attics, and got it to market and up and running,” says Grimes.
The SLD system is offered to customers on a subscription basis (i.e., as-a-service), making it highly scalable and economical to deploy on virtually any pipeline asset --new build or brownfield. It can also be used on lines carrying products other than oil and gas, such as produced water, hydrogen, or hazardous materials. Target applications included long-distance transmission lines, production gathering networks atwell sites, and offshore production risers.
Although it is possible to deploy the SLD system as a standalone solution, Siemens Energy often recommends using it as part of a multi-layered detection approach.
“There’s a very strong business case for this layered security approach that we advocate, particularly for pipelines that traverse highly sensitive areas like wetlands or cities,” Van Rensburg explains. “In such cases, our solution can be combined with traditional methods, such as mass-volume balancing or point pressure analysis to provide an added layer of protection, giving the operator peace of mind that any large unplanned product release can be avoided.”
The SLD system has undergone extensive testing at Siemens Energy’s dedicated leak test loop in Houston. The first field application took place in 2021 on an offshore production platform in the Gulf of Mexico, where it was used to monitor four steel crude oil flowline risers.
“The system has demonstrated excellent performance in several pilot tests and full-scale deployments,” says Rensburg. “As an example, we were able to detect a 1⁄2” leak in a 12” pipeline within a few seconds. Having this capability is enormously valuable tooil and gas companieswho are increasingly driving to improve ESG performance and reduce the environmental impact of their activities.”
April, 2022
Leane Cliftonis a New York City based TV producer, author and documentary filmmaker, with a focus on society, health and technology
Combined picture credits: Felix Sanchez
