By Béla Lipták, PE, Columnist
In the previous article, I have described the fracking process and its safety concerns. In the coming articles of this series, I will describe the automatic controls that can improve the safety of fracking, oilshale and pipelining processes. In this article, I will concentrate on pipelining safety and on how automation could have prevented such accidents as the rupturing of the ExxonMobil pipeline running under the Yellowstone River in Montana last summer.
According to the U.S. Department of Transportation Pipeline and Hazardous Materials Safety Administration, gas-transmission-line accidents increased 72% from the 1990s to the 2000s, and are still rising because the distribution network is old. Roughly 60% of gas-transmission lines in the United States were installed before 1970, and some date back to the Great Depression in the 1930s.
As we will see—like the Deepwater Horizon or Fukushima practices—the main cause of pipelining accidents is not the lack of availability of the sensors needed to detect unsafe conditions, nor is it the inability to know what needs to be done when unsafe conditions occur. No, it is the manual nature of all of these operations. In other words, the pipelining operations are also manually controlled, meaning that the detection of an unsafe condition does not shut down the pumping or compressor stations automatically (Figure 1).
The main concerns in pipelining safety are mechanical damage, construction flaws, cracking and corrosion of large pipelines. Stress corrosion cracking (SCC) and top-of-the-line corrosion (TLC), which is caused by droplets of condensed natural gas, are the most likely natural causes of accidents in gas pipelines. The progress of these forms of corrosion and the condition of oil and gas pipelines must be checked continuously through the use of in-line inspection (ILI) instruments. These instruments can test pipe thickness, roundness, check for corrosion, detect minute leaks and any other defects along the interior of the pipeline that may either impede the flow of oil or gas, or pose a potential safety risk to the operation.
Smart Pipeline Inspection Gauges (PIGs)
Smart PIGs are intelligent robotic devices that are propelled down pipelines by the flowing gas or liquid to evaluate the condition of the pipe's interior to find locations of rust, weak seams, coating, thinning walls, etc. They go where people can't, but controlling them can be challenging because most depend solely on the pressurized fluid in the pipe for propulsion, and it's very difficult to stop a PIG in specific locations. Most PIGs use magnetic flux leakage methods of inspection, but some also depend on ultrasound or the combination of the two to perform inspections. Figure 2 illustrates the magnetic flux leakage type design.
In this design, a strong magnetic field is established in the pipe wall using either magnets, or by injecting electrical current into the steel (the flux loop in Figure 2). Because the damaged areas of the pipe can't support as much magnetic flux as undamaged areas, the magnetic flux leaks out of the pipe wall at the damaged areas, thereby identifying their locations. An array of sensors is provided around the circumference of the PIG to detect the magnetic flux leaks and identify their locations.
PIGs can also operate with ultrasound sensors. These PIG designs are provided with an array of transducers that emit high-frequency sound pulses perpendicular to the pipe wall and receive echo signals from both the inner and outer surface of the pipe. The tool measures the time interval between the arrival of the reflected echo from the inner surface and outer surface to calculate the wall thickness. The electromagnetic acoustic transducer (EMAT) is a combination of the above two designs and represents a major advance in crack detection in both oil and gas pipelines.
A third of the 1.3 million miles of natural-gas pipeline in the United States are "unpiggable" because their diameters vary, or the pipe has sharp bends. Yet as these pipes age and corrode, the need to inspect them becomes more urgent.
Recently, PIG designs have been improved at Carnegie Mellon University, where Explorer II, a 66-pound, eight-foot-long wireless robot was developed that looks like a series of sausage links (Figure 3). It twists and turns with ease, and because it has a drive train, it also allows operators to precisely control where it starts and stops, instead of being propelled by the oil or gas flow, as is the case with previously discussed PIGs. In addition, the use of permanent magnets slows down the movement of the previous PIG designs. In contrast, Explorer II replaces permanent magnets with a compact electromagnetic coil, and thereby eliminates the reduction of the speed.
On some pipelines it's easier to use remote visual inspection equipment to assess the condition of the pipe. Robotic crawlers of all shapes and sizes have been developed to navigate pipes. Typically, the video signal so obtained is fed to a truck, where an operator reviews the images and controls the robot. A recent advance is to use special paints that change color if leakage occurs at pipe joints, and this color change then can be detected automatically through remote inspection, including the use of drones.
Controlling the PIGs
ILI PIGs go where people can't, but controlling them requires good process control because most depend solely on the pipe's pressurized fluid for propulsion, and therefore it is difficult to stop the ILI at specific points. Good speed control requires the measurement of velocity, drag, pressure drop and flow. On in-compressible oil service, it's relatively easy to make these measurements to control speed. On incompressible gas service, it is not.
What we would need for automatic velocity control is a cascade loop, where the master controller is velocity, and the slave is a flow controller through a bypass valve (BPV) in the nose of the ILI (Figure 4). This valve provides a path for the process fluid to pass through the core of the ILI, so that if the PIG speeds up, the BPV opens up further, and if it slows, it closes a bit. What makes such a cascade loop interesting is that the flow sensor element and the control valve in this loop are the same. The flow is measured by the differential pressure across the BPV (or the whole rig), while the control valve whose opening is being manipulated is the BPV itself.
Speed control via a bypass valve
In the coming articles in this series, I will elaborate on PIG control and other control systems serving pipeline safety and then go into fracking and oil-sand safety automation.