Pipeline Integrity Management and Data Science Blog

DIY or Software: Navigating the Evolving Pipeline Integrity Management Landscape

To succeed in the shifting landscape of pipeline regulations, you need an integrity system that adapts to changes.

An ideal solution is a software that’s purpose-built for pipelines and draws on the latest technology. Powerful management software helps you stay ahead of PHMSA’s rapidly moving compliance targets and, at the same time, saves hundreds of hours processing integrity information manually.

But as anyone who's ever tried developing a DIY software will tell you, it isn’t easy, cheap, or particularly effective.

A dedicated software solution provider is what’s needed to help you on your way.

Here’s how integrity management is evolving, plus three compelling reasons why Software-as-a-Service (SaaS) is an efficient—and comprehensive—way to handle pipeline threats.

How pipeline integrity management is evolving

It’s no secret that over the last few years, regulators have been pushing for change—just look at the demanding requirements of the Mega Rule.

Undoubtedly, PHMSA is shifting the rules to increase safety. But using the old ways to manage integrity isn’t going to be enough to meet the latest demands. In the new world order, operators with the ability to analyze massive amounts of data are going to have an easier time satisfying auditors.

Regulators want operators to apply all the integrity information they gather, but manual analysis of Big Data is overwhelming. To be effective, a dynamic threat management solution is needed. Technologies like machine learning and cloud computing have emerged to support complex integrity work.

SaaS Solutions: Offering innovation and value

Let your team focus on managing the pipeline while software experts handle the programming.

A pipeline operator’s expertise lies in managing, monitoring, and maintaining the integrity of their pipe. It’s not feasible for these organizations to, all of a sudden, become software experts. On the other hand, SaaS developers have the resources and expertise to grow their solution into the best integrity management product possible.

Risks of in-house DIY development

  • Keeping pace with programming technology from outside the software industry is unrealistic. In-house developers will have a hard time keeping up with changes.
  • Maintaining software functionality is a continuous expense. Patching software to accommodate regulatory or ILI-data changes involves complex programming, which drains budget dollars that could be better spent elsewhere.

Benefits of a SaaS Solution

  • A SaaS provider puts all of their time, effort, and money into developing software. They deliver the latest technologies along with professional support to keep their customers at the forefront of the industry.
  • Software companies are staffed with computing specialists engaged in the latest developments. A provider can tailor their product to your organization, and deliver a fantastic return on investment, right from the get-go.
  • Consistent updates are another benefit of engaging a Saas provider, as their business is focused on providing new and improved functionality for their product.

Machine Learning: Ready for any vendor’s dataset

Apply all the available data to get a comprehensive snapshot of your pipeline’s integrity, year-to-year, no matter the tool or vendor.

Trying to evaluate corrosion growth with data from multiple vendors is agony—the comparisons get complex, fast. Machine learning scales down the workforce effort using advanced algorithms, which learn for themselves.

This intuitive functionality correlates data between tools and vendors, and with powerful cloud computing, the program analyzes 100% of your pipeline data.

A Drawback of DIY Software Scripts

Most in-house software relies on basic ETL (extract, transform, load) scripts, requiring every condition to be written out. This process works all right for a single vendor’s data but is unsuited to multiple vendors, as each tool’s dataset needs a custom script.

A Benefit of Machine Learning

Machine learning normalizes data from any template you pour into it. The algorithm (largely unsupervised) learns to do QA & QC on its own. This ability is key, as it enables companies to compare vast volumes of data across an entire history of vendors.

Operators who apply machine learning to their analysis are free to choose and compare data from any tool. Machine learning also lets integrity departments maximize their historical data. Simply find a past dataset, drop it into the SaaS program, and it’s converted to useable information automatically.

OneBridge CIM: Do in minutes, what normally takes months

With a SaaS solution like Cognitive Integrity ManagementTM (CIM), the integrity team stays audit-ready, all the time.

CIM is a window into your pipeline’s entire history, making life (and analysis) easier for the integrity team. From a decade-old laser scan to last week’s EMAT run, CIM normalizes and stores all datasets and makes them accessible. Compliance work that takes months to complete manually (such as the PHMSA F&G report) can be generated in a matter of minutes.

  • Industry regulators require data-intensive reports from pipeline operators
  • In-house, legacy, solutions aren’t suitable for managing Big Data
  • CIM streamlines the entire integrity management process

We are helping pipeline operators eliminate uncertainty by applying every byte of integrity information they’ve paid to discover. Our fully integrated, enterprise-level solution learns from any vendor’s dataset to provide a complete overview of your pipeline system.

Contact one of our experts to learn more about how Cognitive Integrity Management™ can transform your integrity management program with minimal impact on day-to-day operations.