A major manufacturer of hydraulic fracturing tools for the
oil and gas industry is using NVision's
HandHeld laser scanner to increase the performance and life of its products by
gaining a clearer picture of erosion patterns. The company previously used
ultrasonic sensors to measure discrete points in a gridded pattern after
erosion testing with proppant. The HandHeld Scanner provides a much clearer
understanding of erosion patterns by measuring millions of points and providing
a comparison of the geometry before and after testing with color deviation
models showing the amount of material that has been eroded in each area of the
tool. This information helps engineers gain an intuitive understanding of tool
performance, which in turn helps improve design and substantially increase tool
Hydraulic fracturing involves pumping a fracturing fluid
into a well bore at a high enough level of pressure to cause the formation to
crack, enhancing the flow of oil and gas from the formation to the well. A slurry
material called proppant, which commonly consists primarily of sand or ceramic
material, is then injected into the fracture to prop it open, thereby increasing
the flow of formation fluids. However, the proppant is highly abrasive and
erodes the casing and tools. After they have eroded to a certain point, the equipment
needs to be replaced, which is expensive in terms of labor and tool cost, but
most important delays the completion process.
After some investigation, the manufacturer decided to
perform the erosion measurements with the NVision HandHeld Scanner. A key
advantage of the HandHeld Scanner is that it is mounted on a mechanical arm so
it can move freely around tools of any size. The mechanical arm keeps track of
the scanner's location so all data is collected within the same coordinate
system. As technicians inspect the tool, the scanner generates a point cloud consisting
of millions points each with x, y, z coordinates and i, j, k vectors. The laser
scanner also provides accuracy to a few thousandths of an inch.
According to a study by the National Institute of Standards and Technology, one of the factors in the collapse of the original World Trade Center towers on Sept. 11, 2001, was the reduction in the yield strength of the steel reinforcement as a result of the high temperatures of the fire and the loss of thermal insulation.
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Robots are getting more agile and automation systems are becoming more complex. Yet the most impressive development in robotics and automation is increased intelligence. Machines in automation are increasingly able to analyze huge amounts of data. They are often able to see, speak, even imitate patterns of human thinking. Researchers at European Automation
call this deep learning.
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