There are more than 2.6 million miles of natural gas and hazardous liquid transmission lines in the United States, and most of that infrastructure is decades old. A significant portion is actually more than a century old. Aging mains and service lines are more susceptible to failures, which can lead to catastrophic events like the rupture in San Bruno, California in 2010 that destroyed a neighborhood. That explosion was so large, it registered as an earthquake on seismic sensors, killing several people and injuring dozens.
The San Bruno explosion prompted federal action on the risks associated with gas infrastructure. The Department of Transportation’s Pipeline and Hazardous Materials Safety Administration (PHMSA) began issuing new safety guidance to utilities soon after the San Bruno incident and issued additional rules in the subsequent years to prevent more disasters caused by aging infrastructure. These rules mandated a comprehensive set of higher standards for assessing and enhancing the safety of underground pipelines. In August of last year, PHMSA expanded the mandate with additional safety requirements for natural gas pipelines.
These mandates require utilities to conduct more intensive assessments of their infrastructure in order to mitigate vulnerabilities from aging pipes, valves and other equipment that may have corroded or weakened over time. To comply with those regulations, utilities need to have far more accurate information about the exact location of all parts of their infrastructure, including service lines that connect mains to residential and commercial buildings.
Mapping service lines is tricky though, because information about their location is scattered in so many different places and formats. Many utilities have been unable to dedicate the significant resources required to extract information from those disparate sources. Instead, they estimate service locations by drawing a short line from the main toward the customer – a “whisker line.” Drawing these whiskers has been a common practice for a couple of decades (well before the PHMSA mandate), but it is an outdated practice that does little to deliver a precise map of infrastructure.
There is a better way, and it involves integrating the disparate information that many utilities dismiss as too scattered, incomplete and messy to have value for service line mapping. All of that disparate data has a story to tell. It just takes the right methodology to get it to speak.
There are myriad sources of information about service lines in utilities’ IT systems and archives: data from multiple GIS systems, recent and “vintage” service cards, tabular data, leak survey data, GPS-confirmed coordinates of known infrastructure, street-level imagery, aerial imagery, archived maps, data from CIS, AMR, Parcels/Landbase databases and much more. That can be an intimidating number of sources of data to gather and analyze, which is where automation and experience become so important. Locana has worked with a number of utilities and developed a blueprint for how the industry can extract usable information from all of those sources to create highly-accurate service line maps.
The process begins with a full inventory of the available sources of data in both electronic and paper formats. This initial step is a difficult one for utilities to tackle on their own, which is why it is important to have an experienced partner. There are so many types of data in different formats, and the raw sources are often frustrating to work with. It takes an experienced hand to evaluate each of these data sources to determine which have information that can play a role in improving the accuracy of service line locations. A key step in this process is to rank each data source for the relative value it will deliver for enhancing the accuracy of the service line maps. This ranking is a key component of the algorithm that is the centerpiece of the automated data analysis.
The data preparation process continues when we begin layering those data sources upon one another to create a cohesive overall body of data that can collectively deliver insights that no one data source could achieve in isolation. This integrated database of internal information is then augmented with other external data sources such as GPS information (which can be updated over time as new external data is available).
Using the ranking process above, we configure our service line mapping application to analyze the available data. The application then provides the basis for converting the integrated data sources into service line features. We typically start the process with a pilot project for a limited geographic area, which allows us to test and finetune the algorithm. The final step is to expand the analysis to a utility’s entire geography. The process produces not only a map of service lines, but also valuable information about the statistical confidence level we have about each aspect of the map.
Utilities often think they don’t have the right data to be able to conduct this kind of project, but the reality is that they do. They just don’t realize it. By using this methodology to mine those data sources, build and refine an algorithm for analyzing that data, and translate that into visual data, utilities are creating more accurate service line maps. The result is not only a highly accurate snapshot of service line locations, but a process that the utilities can continue to use and enhance as they get updated internal and external data.
The benefits of accurate service line mapping go well beyond PHMSA. They improve maintenance efficiency and accountability, worker safety, and infrastructure planning. However, the most important additional benefit will be helping utilities respond to growing regulatory requirements around emissions.
Regulatory mandates around emissions will place a heavy burden on utilities to measure, monitor and mitigate emissions. These mandates are impossible to meet without the information that comes from the highly precise service line maps produced by the data-driven process outlined above. Drawing whiskers won’t be enough. Only data-driven processes will produce key information not only about the location of lines, but whether they are connected to high-pressure or low-pressure transmission lines, and other vital information. Getting your data to tell you the story of your service lines is therefore not only important for PHMSA compliance, but also for successfully tackling other major challenges over the next two decades.
About the Author
Bruce Taylor is a Partner and the Utilities Industry Lead at Locana, a location and mapping technology company whose software products and services solve the world’s most pressing infrastructure, sustainability, business and social challenges. In his role, he leads Locana’s utility delivery and go-to-market initiatives, collaborating with clients and partners to develop innovative and effective location-based solutions to address the utility industry's challenges. He has more than two decades of experience in the geospatial industry, including his role as Project Manager for Locana, providing geospatial thought leadership through the development of strategic plans, developing solution architectures and evaluating the impact of emerging technology. Prior to his time at Locana, he was the Project Manager for CH2M HILL.