For decades, the typical inline inspection (ILI) process remained largely unchanged: run the tool, analyze the data, and deliver the results—often in the form of a spreadsheet.
The operator was then responsible for coordinating those results with previous inspection reports, alignment sheets, repair records, static maps, and other asset information. Integrity engineers had to bring these separate sources together to build the complete story of a pipeline segment: where it has been, what condition it is in today, and what challenges may lie ahead.
That process is changing—and GIS is helping change it quickly.
From Static Reports to Living Data
ILI deliverables have evolved considerably over the years.
During the 1980s and 1990s, analysts used magnifying glasses to examine paper logs. Inspection results were compiled into binders and shipped to the operator as hard-copy reports.
The early 2000s introduced digital signals and electronic reporting. Instead of receiving binders of paper, operators could receive inspection results in an Excel spreadsheet delivered directly to their inbox. This made the data easier to store, search, and share, but it remained largely static and contained limited spatial context.
During the 2010s, inertial measurement units, or IMUs, became increasingly common on ILI tools. This introduced the ability to associate XYZ positioning with the pipeline and individual anomalies. At the same time, more operators began developing GIS environments and manually loading ILI spreadsheets into their systems.
For the first time, integrity teams could more easily view inspection results alongside the pipeline and other relevant assets.
The addition of spatial information represented a major advancement in the way integrity engineers evaluate ILI data. Instead of relying entirely on rows and columns, they could begin seeing where anomalies were located and how those locations related to the surrounding pipeline environment.
ILI Data Should Not Be Evaluated in Isolation
ILI results rarely tell the complete story on their own.
Integrity decisions require an understanding of what is happening around each anomaly. A nearby road crossing, geohazard, previous repair, high consequence area, or other pipeline feature may affect how an inspection result is evaluated and prioritized.
When ILI data and GIS information remain separated, engineers must cross-reference spreadsheets, alignment sheets, maps, and historical records to assemble that context. This can be time-consuming, and the process may need to be repeated each time new inspection data is received.
Bringing ILI results into a GIS environment allows the inspection data and surrounding asset information to be viewed together. Instead of rebuilding the story across separate files, integrity teams can see more of that story in one place—and potentially as soon as the final ILI report is delivered.
The Multi-Vendor Data Problem
Data fragmentation is one of the most persistent challenges pipeline operators face.
ILI results collected over many years and across multiple vendors rarely tell the story in exactly the same way. Reports may use different formats, field names, naming conventions, data structures, and levels of spatial precision.
Each report may be useful on its own. However, combining the reports into one reliable view of the pipeline’s condition over time can become a separate project from the integrity work itself.
This is one reason the industry is moving toward more standardized and structured data models. A common schema does more than make a single report easier to interpret. It helps operators compare inspection results across different years, inspection technologies, and vendors without rebuilding the data structure from the beginning each time.
ILI vendors face the other side of this same problem. Every operator may maintain a different GIS structure and have different delivery requirements.
An ILI vendor serving multiple operators can quickly find itself supporting nearly as many delivery formats as it has clients.
More consistent data structures can make information easier to deliver, integrate, compare, and use—regardless of where or when the inspection was completed.
Why This Is a GIS Conversation, Not Just a Data Conversation
At first glance, this may appear to be primarily a data management issue. In practice, the shift is also visual and spatial.
Integrity engineers and analysts can make faster, better-informed decisions when they can see the complete context surrounding an inspection result. An interactive, queryable GIS map allows users to evaluate ILI anomalies alongside repairs, crossings, HCAs, geohazards, and other relevant pipeline information.
This does not mean spreadsheets are no longer valuable. It means integrity teams no longer have to rely on spreadsheets alone.
Instead of repeatedly cross-referencing separate files and documents, users can interact with the information spatially, query specific features, apply filters, and better understand how different pieces of pipeline data relate to one another.
What This Means for Integrity Teams
Bringing ILI results into a GIS environment can reduce the time spent locating, formatting, and cross-referencing information stored across separate systems.
Integrity teams can evaluate anomalies alongside nearby pipeline features without manually rebuilding the context for each inspection. The information may also be easier to communicate to other departments and decision-makers who do not work directly from detailed ILI spreadsheets every day.
The result is not simply a different way to display ILI data. It is a more efficient way to review inspection results, communicate findings, and support integrity decisions.
Preparing Pipeline Data for What Comes Next
Structured, consistent, and spatially enabled data also creates opportunities for more advanced analysis.
When relevant pipeline information is organized and accessible in one environment, operators are better positioned to explore tools such as artificial intelligence, risk modeling, corrosion growth analysis, and other predictive techniques.
However, these tools depend on the quality and consistency of the information they receive. AI is only as useful as the data behind it. Establishing clear data structures and improving the way information is integrated are important early steps toward developing more advanced integrity models in the future.
Where Enduro Fits
Enduro has listened to operators and experienced these challenges alongside them. We have built our GIS services to support the industry’s shift toward more structured, spatially enabled ILI data.
Every Enduro ILI report now includes a live, Esri-native Hosted Feature Layer alongside the standard inspection reporting. We are not replacing the tried-and-true spreadsheets operators are accustomed to receiving. We are providing an additional way to move that information directly into the GIS environment where integrity teams are already working.
For clients using a PODS data model, inspection data can also be delivered as a PODS-compatible geodatabase, with custom schema mapping available when needed.
The goal is not to add another deliverable to the pile. It is to make the story contained within the inspection data usable from the moment it arrives—visual, structured, and ready to sit alongside the other information the operator already tracks.
That means integrity teams can spend less time rebuilding the story and more time using it.
Want to see how ILI results can be delivered directly into your GIS environment?
Contact Enduro’s GIS team
to view an example Hosted Feature Layer and discuss the delivery options available for your next ILI project.
