Using a drone to capture high precision underground utility location data up to 15 meters deep

For a long time it has been a dream of underground utility locators to deploy a drone based system for mapping underground utility infrastructure. The advantages of such a system are speed of execution – drone-based system can gather field data much quicker than traditional land-based technology. .The second advantage is safety – no boots on the pavement allows the field operator to remain safe at all times, regardless of terrain conditions. The third advantage is precision providing cm accuracy at a depth of 15 meters.

With respect to spatial positioning we support GNSS and RTK. But we can have either a fixed reference point on the ground upon which we work or have a satellite correction of our positioning. And this is how we’re able to have such a high level of accuracy in our mapping.

A most important general application of Skipper NDT technology is, as opposed to traditional methods, soil conditions have no impact on our measurements, meaning that if the soil is humid, or if you have different soil types, it will have no impact on our measurements. And the proof is that we can even see through water. A specialized Skipper NDT application is river crossings, being able to detect utilities under water is a rare capability.

A third application is an out-of-straightness assessment. The Skipper NDT technology has proven to be as precise as an invasive pipeline tool to measure the mechanical deformation of pipelines.

A caveat is that we are more suited for rural areas than urban due to the regulation for drone fight, but also due to the EM noise that can be prevalent in those areas, which is very important. We do require the standard permits to fly drones in different locations which can vary from country to country. We’re more of a rural-based technology applicable for both energy and utility segments. Electromagnetic noise is one of the competitive advantages that we’ve developed through time.  We’re able to filter those EM noises out of the signal that is required in order to have the cleanest magnetic environment. We filter interferences that could be created due to high voltage lines or metallic objects in the proximity of the pipeline.

Two main operators have validated this application, one being GRTgaz, the incumbent French gas operator, and the other one being Veolia, the large utility company. We’ve done operations in Europe, US, Asia and Africa. We have collaborated with prime operators such as TotalEnergies, GRTgaz, Patronus, US-based operators such as Kinder-Morgan, as well as operators in the field of utilities, such as Veolia. It is particularly interesting for markets in Europe, where there is a regulation that obliges all operators, energy or utility, to map their entire infrastructure with the inch precision by 2032.

Hardware payload

The Skipper NDT is a four-kilogram payload enabling a high-precision pipeline mapping. It is composed of several sensors, magnetic, but also centimetric GPS and IMU, sensors that calculate the distance between the drone and the ground to provide the depth of cover, and an electronic card, which interpolates all this data. The result is an acquisition pace which is three times higher than traditional methods. The device can collect data at up to 12 kilometers per hour with a data density that is up to 1,000 times more than traditional tools with a point every centimetre, if required. In addition we perform magnetometer compensation that allow us to increase by 25 times the native resolution of our magnetometers to have very high-precision data. We can detect pipelines that are metallic, so no PVC, but we can also detect active cables, cables in which a current is being transmitted. We have been actually tested on pipes going from a diameter of 80 millimetres to 1.2 meters, meaning we can go from very small to the largest pipeline seamlessly

We are drone agnostic, meaning that the drone we are showing is the DJIM 600. But we can integrate our payload on any tool being able to carry our payload. The way we market this product is either directly with operators which know us now or to service providers that might have already have a drone able to carry out payload.

In terms of software, we apply several algorithms to the data to have the cleanest magnetic information. These include field data level control, which compensate the movement of the acquisition vector that could cause potential false positive, or at least complicate the analysis of the data. But we also we filter EM interferences that could be created due to high voltage lines or metallic objects in the proximity of the pipeline. We also have several algorithms patented, which will process this data in order to provide the operator with the cleanest and most precise information.

Operational process

Skipperndt data acquisitionHere, we describe the operational process of data gathering through the Skipper NDT technology. We’ve simplified the process so that operator in the field will input two points and will then deploy the drone, which will go back and forth over the area. The objective is to hover over a zone with a width of 10 meters around the pipeline location. to collect data. We will then apply different magnetic acquisition filters in order to provide a magnetic map from which we will derive a number of points that will be provided to the operator within the format that suits best their system.  In this example a seven-inch diameter,gas pipeline was measured over a distance of 207 feet over 32. The number of profiles that were done by the drone was five to cover the entire magnetic anomaly. And the acquisition time for this coverage was of six minutes. The results of this acquisition were compared against an open ditch measurement, and the two tables describe basically the performance that was obtained with the Skipper technology. We can see that laterally, we have an average precision of 5.2 inches and a standard deviation of four inches. And horizontally, meaning depth of cover, we have an average precision of 1.6 inch with a standard deviation of 2.1 inch. We see here that the data is fairly constrained, meaning that there is a high degree of certitude on the data that is provided by the Skipper NDT algorithms. This shows why it is important that we gather the entire magnetic signal. We can see that on one of the pipelines that was measured, two different magnetic interferences were gathered, both in the low frequency map and a high frequency map. Skipperndt detecting new pipeAnd this was highlighted by our algorithms. Those kind of interferences are characteristic of a metallic object. Our analysts that reviewed the data suggested that there might be an abandoned line crossing the existing line. After further investigation, it was confirmed that an abandoned line was actually crossing the new line that was built. This constitute a serious hazard potential, and hence the data was then integrated into the global information system of the client. This is why we insist on gathering a large magnetic map that allows us to gather not only the magnetic signal of the pipeline, but also of its environment.

This post is based on Luigi Kassir’s (Skipper NDT) talk at Subsurface Utility Mapping Strategy Forum (SUMSF).

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