Automating Pipeline Monitoring for Superior Corrosion Tracking

rusted above ground pipeline

Pipeline corrosion is an unstoppable force, albeit a slow-moving one at times. Corrosion accounts for nearly 10% of all significant pipeline incidents over the past 20 years, according to PHMSA, putting it among the top contributors to leaks. Furthermore, corrosion-related costs to monitor, replace, and maintain assets is approximately $5.8 billion annually 1. Implementing a preventative maintenance strategy and best practice could save you as much as 25 – 30% of annual corrosion-related costs 2.

Operators have tools in their arsenal to stall this kind of damage to their infrastructure in the form of steel-protective coatings and the application of cathodic electrical currents to override the corrosion process, but these are only time-buying measures.

While you may find yourself constantly reacting to remediate incidents that stem from undetected or unmanaged corrosion, the good news is that there are proactive measures you can implement today to better manage this pesky problem and it can be defined in one word. Data.

Actually, two words. Predictive data.

Let’s explore how different data sets need to come together to feed predictive models to generate actionable insights.

Predictive Analytics: Getting Ahead of Those Pesky Oxygen Ions

In leveraging critical points of data analytics over time, you, or your friendly neighborhood data processing partner, can develop an effective predictive model. Analyzing occurrences of corrosion and corrosion-inducing issues, where and when they occur, and how it’s developing over time is the stuff that accurate predictions are built on.

In the case of an above-ground pipeline, the value is quite simple. Track your active cases of corrosion and how they’re growing over time. Before it hits a severe integrity compromising level, tackle it with preventative maintenance. Boom. Done.

However, on an underground pipeline the value comes from a beautiful symbiosis of different data sets, that come together to paint a holistic picture of how corrosion is developing on your asset:

Aerial Data

You can pinpoint key indicators of corrosion for both above-ground and buried pipelines with aerial data.

In the case of an above-ground pipeline this would take the form of:

  • Rust and other types of discolouration on the pipeline
  • Clustering of pits on the pipeline
  • Active areas of galvanized and pitted corrosion
  • Specific changes in pipeline temperature
  • Localized corrosion around welds and flanges

In the case of underground pipelines, you can identify environmental corrosion risks and leaks indicative of corrosion-related damage:

  • Soil erosion that is likely to expose the pipe to the elements
  • Water pooling and flooding on the ROW
  • Abnormal ground discoloration indicative of a leak
  • Abnormal condensation near the line indicative of a leak
  • Abnormal vegetation loss indicative of a leak

Each detected anomaly and change from each inspection can be used to develop visualization models of what’s likely to happen on your pipeline and ROW. However, this visual data can also be used to derive greater meaning alongside the other data sources in your arsenal.

In-House Data

Your SCADA network, the in-line sensor readings, PIG inspections, and any other systems you use to collect data on your pipeline. All of these readings are valuable to a predictive model. In particular, ultrasonic analysis techniques can detect corrosion-related openings in the line, while magnetic analysis can measure the integrity of the pipeline walls. Vital readings for corrosion monitoring. However, many in-line inspection techniques can be locationally-vague, so augmenting them with visual data on your ROW can help pinpoint potential issues that these systems are flagging.

External Data

Name a major external factor that can have a huge impact on pipeline corrosion, that is entirely out your’s, mine, or anyone’s control? You guessed it, weather. While we can’t promise you control over the weather, we can help you use data about it to your advantage. Things like humidity, rainfall, or even flooding can be used to make estimations about potential corrosion, but the aerial data can help you focus it.

Is a part of your ROW particularly susceptible to erosion during heavy rainfalls? Does part of the pipeline reside in a lowland where water will frequently pool over the soil? Or is part of your pipeline going to be submerged for weeks on end by a flood? The aerial monitoring process can help you understand how weather affects your pipeline and how you should interpret weather data accordingly.

AI Shines a Spotlight on Corrosion-Related Issues

While Artificial Intelligence (AI) can detect anomalies and even classify them to an extent, the acronym AI should really be ASI (Artificial Slightly Intelligent). This technology is great at doing the grunt work, but when it comes time to make a firm decision, it’s not the best choice. So, with a small verification step by a human subject matter expert, you can be 100% sure all the key data points are in fact actionable. As you approve and discard anomalies the AI will get an even better understanding of what to look for. Think of it as your naive robo-protege.

Equally valuable to getting eyes on new anomalies, AI can cross-reference your most recent inspection against your historical data sets, and with change detection, identify growth in active corrosion on the pipeline or risky environmental factors along your ROW.

With a thorough understanding of how corrosion is forming on your pipeline and areas of future concern, you can focus your teams on preventative maintenance that keeps product flowing to its final destination, rather than out the side of your pipe.

Automating your pipeline inspection with a state-of-the-art data solution not only provides greater cost-efficiencies by reducing the manpower and resources required for inspection but also unlocks a new layer of visual data that perfectly complements the existing corrosion prevention toolset. With much of the arduous inspection relegated to an automated system, you can focus your personnel on valuable efforts like preventative maintenance, where their skills are best serving the organization.

Have questions about how high-quality aerial data can elevate your organization?

Contact our team to discuss your unique challenges and data requirements.

References

  1. Wright, Ruishu F. et al (2019) “Corrosion Sensors for Structural Health Monitoring of Oil and Natural Gas Infrastructure: A Review”
  2. Ibid