Beware the Ides of March
Beware the Ides of March
By Tom DeWitte and Tom Coolidge
Beware the Ides of March. Stated in less Shakespearean form, beware of March 15th. This statement was true for Julius Caesar and is true today for many GIS and compliance professionals across the United States natural gas industry.
In Roman times, March 15th was the deadline for settling debts. Today in the United States, March 15th is the deadline for submitting annual reports for gas distribution and transmission companies to the U.S. Department of Transportation (U.S. DOT) Pipeline and Hazardous Materials Safety Administration (PHMSA).
The submittal of the U.S. DOT PHMSA Annual Report for Gas Distribution (Form F 7100.1-1) and its sibling, the U.S. DOT PHMSA Annual Report for Gas Transmission and Gathering Pipeline Systems (F 7100.2-1), is an exercise in data mining. If your data is well organized and attuned to the data summarization requirements of these reports, gathering the information required to complete these forms is manageable. Suppose your data is not attuned to the data query, filtering, and summarization needs of these reports' data query, filtering, and summarization needs. In that case, this annual effort is scarier than having a best friend named Brutus.
Officially, PHMSA estimates that the time required to gather the data needed to complete these forms is 16 hours for Gas Distribution and 47 hours for the Gas Transmission and Gas Gathering form. This is achievable with a well-attuned geospatial dataset such as an ArcGIS data repository organized with the Utility and Pipeline Data Model (UPDM). If your data is poorly organized, this effort can take several months.
What does a well-attuned geospatial dataset look like?
Summarizing by Pipe Material
The first indication of a data model well attuned to these reports' data summarization needs is how material is defined. Part B of the Gas Distribution report does not ask for the specific material grade of the pipe (PE2708, Grade X42, etc.). It asks for a generic categorization of material (Plastic, Coated Steel, Bare Steel, Cast Iron, etc.).
Part D of the Gas Transmission and Gas Gathering report similarly asked for a generic categorization of the material instead of the specific grade.
The UPDM data model explicitly defines these categorizations of material in a data field called; AssetType. This AssetType data field has a set list of values which align with the categorization material values requested in the DOT reports.
A simple summarization of the assettype and cptraceability data fields will produce the data values needed for section B1 of the Gas Distribution Report.
A summarization of unique combinations of assettype, cptraceability, and regulatorytype will produce the data values needed for Part D of the Gas Transmission and Gas Gathering report.
These summarizations can be easily accomplished in ArcGIS with UPDM-organized data in minutes versus hours, days, and even weeks.
Summarizing Transmission By SMYS
Part K of the Gas Transmission and Gas Gathering Report asks for the miles of transmission pipe based on the operating pressure as a percent of specified minimum yield strength (SMYS) for a given DOT class designation. Storing engineering information about the pipe as descriptors about the pipe greatly simplifies summarizing this information for the Gas Transmission and Gas Gathering Report.
When the UPDM data fields for this engineering data are populated, this tabulation can be performed. The specific data fields within the pipelineline layer of UPDM are operatingpressure, SMYS, percentSMYS, dotclass and shape_length. Similar to the mileage by material table, a summarization of the unique combinations of percentSMYS, and dotclass, then summing the total length of pipe produces the information needed to populate this table.
Summarizing Leaks by Cause
UPDM and its optimization of data organization to support the reporting needs of the annual DOT reports extend beyond pipes. It is also attuned to the reporting requirements of leaks.
Part C of the Gas Distribution report asks for the number and severity of leaks on mains and services.
Here again, the P_GasLeaks featureclass in UPDM is intentionally organized to accommodate this categorization of leak cause and severity. The data field, leakcause includes a set list of valid values, which correlates to the Cause of Leak categories of the reporting table. The data field, revisedleakclass provides the leak severity distinction, and the leakstatus data field provides the indication of the status of the leak.
UPDM Alignment with DOT Reporting was no Accident
The fact that UPDM is so well aligned with the reporting needs of these annual reports is not an accident of data modeling. When UPDM was originally created, these DOT reports were studied. The intent way back in 2009 was to organize this information to not only address the daily engineering and operational needs of natural gas organizations but also to simplify this required annual reporting task. In the 15 years since the original release of UPDM, the gas team at Esri has continued to monitor the evolution of these compliance reports and, when needed modify UPDM to accommodate changes in reporting.
March 15th was a very bad day for Julius Caesar; it does not have to be a bad day for you.
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