Aerial data-driven change detection

The oil and gas sector can choose to use high-quality aerial data to identify and monitor changes in old pipelines, make corrections, and, if necessary, replace pipeline portions with valve-fitted new segments, as required by the DOT. The 400-page ARC study’s impact will be to increase aerial data collection and analysis. This article provides the FAA with detailed and practical regulatory suggestions to expand UAS BVLOS operations safely and affordably. Simply explained, the FAA has the necessary fuel for BVLOS. Companies seeking cost-effective strategies to protect pipeline and asset integrity, as well as prevent product loss, will benefit directly.

Reading between the lines of the DOT rule

Addressing congressional mandates from the Pipeline Safety Act of 2011 and longer-standing recommendations from the National Transportation Safety Board (NTSB), the DOT regulation was created through the Pipeline and Hazardous Materials Safety Administration (PHMSA) with industry input. It requires firms to install emergency valves that can immediately cut down the flow of oil, natural gas, or other hazardous fuels when pipelines burst. In fact, personnel or technology must isolate a broken pipeline portion within 30 minutes. In 2010, petroleum poured into the Kalamazoo River for 17 hrs before the pipeline was shut down, and in San Bruno, California, a 90 min. fatal natural gas leak decimated an entire town, both triggers for the regulation. The aims are to improve pipeline safety for people (including first responders), limit environmental damage, and reduce oil and gas loss.

But this obligation only applies to new or rebuilt pipeline segments. Why? Retrofitting hundreds of thousands of kilometres of old pipeline at once is unreasonably costly and disruptive. The law allows industry to replace older pipes in stages, starting with those most susceptible to corrosion and deterioration. That strategy seeks to balance immediate needs with long-term preservation of people, land, and assets.

We know that 40 - 50 year old pipelines have problem areas. The most efficient and reliable way to scan for those is to use long-range, high-precision aerial mapping and data analytics in an ongoing and systematic manner, with data fed into software designed specifically to examine pipelines and large-scale assets. SkyVision 2.0 is an example of technology that does this.

It’s purpose-built to detect what other inspection methods can’t detect well: pooling, puddling, leaks, cracks, vegetation encroachment, erosion, and unauthorised – sometimes nefarious – third-party activity, all over long distances and repeatedly through time. It’s a system that can integrate data from other sources, like satellite or sensor data or data acquired from a company’s own drones or ground crews, and easily export it into GIS applications.

Change detection data means getting ahead of problems

With ageing pipelines, a quick examination isn’t adequate. Creating a cost-effective process and pattern yields actionable data and insights. Software-enabled change detection uses granular aerial data, annotated with natural and human activities in regions of interest, layered over time. RGB and LiDAR images, orthomosaics, and 3D modelling are all possible. Companies may follow changes throughout pipeline segments and prioritise concerns as data is gathered and stacked. Early change detection and prioritisation decrease mishaps, guaranteeing product safety and preventing product loss.

It’s important to consider, too, that, as companies implement aerial data-driven change detection, this will ultimately lead to their ability to use predictive AI models to better understand their assets. The only way to build an AI model for a pipeline is to actually capture the overlapping visual data and metrics of that pipeline repeatedly through time. Companies that want to fully engage in the digital transformation of their pipelines should put AI on their roadmaps, to set themselves up for long-term financial success and public acceptance.

Protecting against product loss

It’s apparent from working outside the US, that the amount of product loss that happens along a pipeline, alone, constitutes a strong argument for the meticulous and responsible adoption of modern, aerial data-based change detection systems. On one end, an oil and gas company pumps in 100% fuel, but on the other end, only 70% is coming out, with the other 30% spilling or being stolen in a jungle or wilderness. That kind of loss happens every day and it can happen anywhere.

Accessing more distant pipelines becomes simpler and more cost-effective when UAVs can fly BVLOS. Drone operators may deploy their airborne vehicles dozens, even hundreds of kilometers away, monitoring them using sensors, cameras, and software. SkyX, for example, already accomplishes this globally, in areas where flight approval is less stringent. Companies save a lot of money. A pivot in aviation for UAVs, but also for the oil and gas business, is coming – employing BVLOS to reduce product loss, preserve the environment, and go along the digital path the DOT regulation is pointing.

The DOT and FAA actions aren’t the only forward-looking measures coming out of the US government to improve safety and promote digital transformation for pipelines. Another federal action – expansion of the Joint Cyber Defence Collaborative (JCDC) to include industrial control systems (ICS) experts like security vendors, integrators and distributors will “further increase US government focus on the cybersecurity and resilience of industrial control systems and operational technology (ICS/OT)”, according to the CISA.

While that expansion covers many industries and kinds of infrastructure, there’s a recognition of vulnerabilities and threats that require technology-driven public/private partnerships to solve. The DOT rule and ARC report embrace the same perspective, in essence, urging industry to proactively approach threats to infrastructure, whatever their source, and scale in smart ways.

Read the article online at: https://www.worldpipelines.com/special-reports/23092022/aerial-data-driven-change-detection/