World Pipelines Magazine Features Dexon’s UT-CS Hawk ILI System in the 2023 Integrity Issue 

The technical article entitled “Crack Tip Diffraction Smart Pigging” covers Dexon’s use of a high-density sensor array and angle beam tip diffraction intelligent pigging for the detection and sizing of cracks and crack-like features in oil and gas pipelines. The technology is a big leap forward for the industry offering advanced accuracy and detection capabilities to better ensure the integrity of these fundamental assets. 

Read the article here (See Page 19) or read below. 

Online Flip Book: https://bit.ly/46Owzam 
Downloadable PDF: https://bit.ly/40oAS9V 

Crack Tip Diffraction Smart Pigging

Introduction: Pipeline Integrity   

Pipelines play a crucial role in the safe and efficient transportation of oil, gas, and other hydrocarbons over long distances. However, like all infrastructure, pipelines are susceptible to defects that can compromise their integrity and pose risks to the environment and public safety. Detecting and addressing these defects early is essential to prevent costly and potentially disastrous consequences. Oil and gas pipelines are prone to various defects that can affect their structural integrity and cause failures, posing a threat to human lives and the environment. Defects can be categorized into the following groups. Corrosion, geometric anomalies, and cracking and crack-like features.   

The Objective  

Dexon Technology (Dexon) set out to develop a market-leading smart PIG for the detection and sizing of sub 1.0 mm cracks and crack-like features in pipelines, combined with high-resolution wall thickness measurements.  

Cracking in Oil and Gas Pipelines  

Cracks are a common problem in oil and gas pipelines reducing their ability to withstand pressure. Cracking can be caused by a variety of factors including mechanical stress, corrosion, fatigue, and external forces leading to structural integrity issues. Detection and repair of these defects are crucial before they lead to significant damage or catastrophic failure. While current technology allows for the accurate detection and measurement of corrosion and geometric anomalies, tools for the detection and sizing of critical cracking have been less developed. The issue is exacerbated by the need to detect cracking in the early stages due to the rapid increase in growth rates as the anomaly enlarges. Cracks often form at the site of pre-existing flaws and grow during operation. For example, fatigue crack growth can occur due to cyclic applied loading or hostile chemical environments.   

Factors affecting growth rate can include pipe material, material condition, mechanical forces, pressure, temperature, and product. Integrity assessments may forecast defect growth rates using mathematical algorithms. However, these assessments require highly accurate crack dimensions.    

The figure below shows how the crack growth rate increases as the crack size increases. This is because the stress intensity factor at the crack tip is dependent on the crack size. With the crack continuing to grow until it reaches a critical size, leading to the failure of the asset. The crack grows very slowly in the initial stages, with growth accelerating substantially as the size of the crack increases. 

Figure 1: The crack growth curve depicts the crack size, a, as a function of the applied load cycles, N. The instantaneous slope of this curve is represented by da/dN, which indicates the rate of crack growth.  

Intelligent Pigging  

Smart pigging (PIGs) uses non-destructive testing techniques via specialized tools to internally evaluate the condition of a pipeline. PIG’s are commonly propelled through pipelines using the flow of transported products and are able to cover hundreds of kilometers in a single inspection. When compared to traditional methods of pipeline inspection, intelligent pigging can offer several advantages in terms of accuracy, speed, and cost-effectiveness.   

Conventional non-destructive testing (NDT) techniques are limited to accessible areas of pipeline or dig sites. In-line inspection (ILI) enables PIGs to examine vast underground pipe sections as well as areas covered by coatings or insulation allowing for a comprehensive examination. Without the use of ILI these pipe sections would be inconvenient to inspect requiring excavation for manual inspection which poses logistical difficulties and increased costs.  

The three most common technologies used in smart pigging are Ultrasound, Magnetic Flux Leakage, and geometric in-line inspection. Ultrasonic (UT) smart pigging utilizes high-frequency sound waves to detect and measure wall thickness, cracking, and geometric anomalies. Magnetic Flux Leakage (MFL) uses powerful magnets and triaxial hall sensors to detect changes in wall thickness. While geometric smart PIGs use a series of mechanical arms that measure geometric anomalies and changes in pipe ovality.  

The Solution: Ultra High-Density Sensor Array  

To achieve the objective Dexon’s R&D team designed a high-density sensor array with a combination of angle beam and pipe thickness transducers. Dexon’s UT-CS Hawk ILI system collects uses an arrangement of both zero-degree transducers for the collection of wall thickness measurements and angle beam/shear transducers (angled around the circumference of the pipe) for the collection of angle beam tip diffraction crack data.   

High-Density Sensor Array and Sampling Resolution  

A high-density sensor array was used to increase sampling resolution and in turn the accuracy of detection and sizing capabilities. A total of 768 specially designed transducers were used in the development of the initial 8” PIG producing a sampling density of 1,000,000 direct measurements per square meter of piping.   

Circumferential and Axial Sampling Density 

The below table illustrates the number of data samples generated based on the axial and circumferential sampling distribution. The probability of detection and accuracy of sizing are directly related to the number of data samples collected for a given defect. When measuring axial defects, the axial sampling rate (data samples along the length of the pipeline) directly correlates to the measurement of defect length while the circumferential sampling rate directly correlates to the accuracy of through-wall height measurement in axially oriented cracking.    

Figure 2: The number of data points collected at the following sampling resolutions are as follows, 10.0 mm X 1.0 mm – 100,000, 5.0 mm X 1.0 mm – 200,000, and 1.0 mm X 1.0 mm – 1,000,000. 

The figure below shows a graphic representation of clockwise and anticlockwise angled circumferential sampling density. As the number of circumferential samples is increased and the distance between samples is reduced, the sampling resolution is increased.  

Figure 3: Graphic representation of varying circumferential sampling resolutions (10.0 mm X 1.0 mm, 5.0 mm X 1.0 mm, and 1.0 mm X 1.0 mm) 

Axial sampling density is directly dependent on tool speed which is set in accordance with pipeline operating conditions and client inspection requirements. Increased PIG velocities result in a possible reduction of axial sampling rates if acquisition electronics are unable to compensate.   

Probability of Detection and Dimensioning  

As sampling density increases the probability of detection and accuracy of sizing also increases. The three columns below (Figure 4) show increases in the number of data samples collected for a 3.0 mm simulated seam weld crack as sampling density increases. Improving circumferential sampling from 10.0 mm to 1.0 mm results in a ten-fold gain in ultrasonic data collection. This additional data aids in the analysis of crack dimensions allowing for greater accuracy in through-wall measurement.   

Figure 4: Ultrasonic Sampling Resolutions Compared 

Angle Beam Tip Diffraction  

As data sampling increases across the face of a crack, the ability to employ tip-diffraction sizing increases. Tip-diffraction has been shown to provide a high degree of through-wall sizing accuracy in comparison to other methods such as amplitude sizing. Amplitude-based sizing methods are highly dependent on defect orientation matching calibration reflector orientation to ensure sizing accuracy. Angle-beam tip diffraction uses time of flight data from ultrasonic sound waves without regard to amplitude. This data shows defect signals recorded from the crack base to the tip as seen in the figure below (Figure 5). Six individual data points indicate separate geometric reflectors marked by different colored circles on both the A-Scan data and the graphic representation of the crack. Tip signals appear first due to their closer proximity to the transducer. The difference in time of flight between the crack base and the crack tip can be used to calculate the through-wall dimension of the crack.  

Figure 5: The image on the left shows ultrasonic shear wave signals entering the pipe wall and returning 6 direct measurements. The middle image shows A-Scan data points for the 6 direct measurements collected in Dexon’s proprietary UT data analysis software, Dexon Studio. The image on the right shows each measurement collected in relation to through-wall height.  

Crack Inspection Verification  

Inspection verification and testing were performed using natural and artificial defects in an 8” test loop at Dexon’s test yard. A test loop system allows a PIG to run continuously through a closed loop pipeline and provides valuable data concerning the probability of detection, sizing accuracy, inspection repeatability, tool reliability, and the effect of tool wear on inspection results.   

Numerous artificial defect shapes were tested including rectangular, elliptical, varying through-wall height, tilted, skewed, ID / OD connected, and multi-angular. In addition, a major oil and gas company provided two natural flaws removed from service piping. These flaws were inspected by Dexon without prior information concerning position, through-wall height, or orientation. The following two tables define the shape and orientation of the artificial defects, with all notch dimensions and locations being confirmed by manual inspection.   

Artificial Crack Shapes  

Figure 6: Rectangular, Elliptical, variable, and multi-angular artificial crack defect shapes. 

NEWS

Crack Tip Diffraction Smart Pigging | World Pipelines

01
Dec

World Pipelines Magazine Features Dexon’s UT-CS Hawk ILI System in the 2023 Integrity Issue 

The technical article entitled “Crack Tip Diffraction Smart Pigging” covers Dexon’s use of a high-density sensor array and angle beam tip diffraction intelligent pigging for the detection and sizing of cracks and crack-like features in oil and gas pipelines. The technology is a big leap forward for the industry offering advanced accuracy and detection capabilities to better ensure the integrity of these fundamental assets. 

Read the article here (See Page 19) or read below. 

Online Flip Book: https://bit.ly/46Owzam 
Downloadable PDF: https://bit.ly/40oAS9V 

Crack Tip Diffraction Smart Pigging

Introduction: Pipeline Integrity   

Pipelines play a crucial role in the safe and efficient transportation of oil, gas, and other hydrocarbons over long distances. However, like all infrastructure, pipelines are susceptible to defects that can compromise their integrity and pose risks to the environment and public safety. Detecting and addressing these defects early is essential to prevent costly and potentially disastrous consequences. Oil and gas pipelines are prone to various defects that can affect their structural integrity and cause failures, posing a threat to human lives and the environment. Defects can be categorized into the following groups. Corrosion, geometric anomalies, and cracking and crack-like features.   

The Objective  

Dexon Technology (Dexon) set out to develop a market-leading smart PIG for the detection and sizing of sub 1.0 mm cracks and crack-like features in pipelines, combined with high-resolution wall thickness measurements.  

Cracking in Oil and Gas Pipelines  

Cracks are a common problem in oil and gas pipelines reducing their ability to withstand pressure. Cracking can be caused by a variety of factors including mechanical stress, corrosion, fatigue, and external forces leading to structural integrity issues. Detection and repair of these defects are crucial before they lead to significant damage or catastrophic failure. While current technology allows for the accurate detection and measurement of corrosion and geometric anomalies, tools for the detection and sizing of critical cracking have been less developed. The issue is exacerbated by the need to detect cracking in the early stages due to the rapid increase in growth rates as the anomaly enlarges. Cracks often form at the site of pre-existing flaws and grow during operation. For example, fatigue crack growth can occur due to cyclic applied loading or hostile chemical environments.   

Factors affecting growth rate can include pipe material, material condition, mechanical forces, pressure, temperature, and product. Integrity assessments may forecast defect growth rates using mathematical algorithms. However, these assessments require highly accurate crack dimensions.    

The figure below shows how the crack growth rate increases as the crack size increases. This is because the stress intensity factor at the crack tip is dependent on the crack size. With the crack continuing to grow until it reaches a critical size, leading to the failure of the asset. The crack grows very slowly in the initial stages, with growth accelerating substantially as the size of the crack increases. 

Figure 1: The crack growth curve depicts the crack size, a, as a function of the applied load cycles, N. The instantaneous slope of this curve is represented by da/dN, which indicates the rate of crack growth.  

Intelligent Pigging  

Smart pigging (PIGs) uses non-destructive testing techniques via specialized tools to internally evaluate the condition of a pipeline. PIG’s are commonly propelled through pipelines using the flow of transported products and are able to cover hundreds of kilometers in a single inspection. When compared to traditional methods of pipeline inspection, intelligent pigging can offer several advantages in terms of accuracy, speed, and cost-effectiveness.   

Conventional non-destructive testing (NDT) techniques are limited to accessible areas of pipeline or dig sites. In-line inspection (ILI) enables PIGs to examine vast underground pipe sections as well as areas covered by coatings or insulation allowing for a comprehensive examination. Without the use of ILI these pipe sections would be inconvenient to inspect requiring excavation for manual inspection which poses logistical difficulties and increased costs.  

The three most common technologies used in smart pigging are Ultrasound, Magnetic Flux Leakage, and geometric in-line inspection. Ultrasonic (UT) smart pigging utilizes high-frequency sound waves to detect and measure wall thickness, cracking, and geometric anomalies. Magnetic Flux Leakage (MFL) uses powerful magnets and triaxial hall sensors to detect changes in wall thickness. While geometric smart PIGs use a series of mechanical arms that measure geometric anomalies and changes in pipe ovality.  

The Solution: Ultra High-Density Sensor Array  

To achieve the objective Dexon’s R&D team designed a high-density sensor array with a combination of angle beam and pipe thickness transducers. Dexon’s UT-CS Hawk ILI system collects uses an arrangement of both zero-degree transducers for the collection of wall thickness measurements and angle beam/shear transducers (angled around the circumference of the pipe) for the collection of angle beam tip diffraction crack data.   

High-Density Sensor Array and Sampling Resolution  

A high-density sensor array was used to increase sampling resolution and in turn the accuracy of detection and sizing capabilities. A total of 768 specially designed transducers were used in the development of the initial 8” PIG producing a sampling density of 1,000,000 direct measurements per square meter of piping.   

Circumferential and Axial Sampling Density 

The below table illustrates the number of data samples generated based on the axial and circumferential sampling distribution. The probability of detection and accuracy of sizing are directly related to the number of data samples collected for a given defect. When measuring axial defects, the axial sampling rate (data samples along the length of the pipeline) directly correlates to the measurement of defect length while the circumferential sampling rate directly correlates to the accuracy of through-wall height measurement in axially oriented cracking.    

Figure 2: The number of data points collected at the following sampling resolutions are as follows, 10.0 mm X 1.0 mm – 100,000, 5.0 mm X 1.0 mm – 200,000, and 1.0 mm X 1.0 mm – 1,000,000.  

The figure below shows a graphic representation of clockwise and anticlockwise angled circumferential sampling density. As the number of circumferential samples is increased and the distance between samples is reduced, the sampling resolution is increased.  

Figure 3: Graphic representation of varying circumferential sampling resolutions (10.0 mm X 1.0 mm, 5.0 mm X 1.0 mm, and 1.0 mm X 1.0 mm) 

Axial sampling density is directly dependent on tool speed which is set in accordance with pipeline operating conditions and client inspection requirements. Increased PIG velocities result in a possible reduction of axial sampling rates if acquisition electronics are unable to compensate.   

Probability of Detection and Dimensioning  

As sampling density increases the probability of detection and accuracy of sizing also increases. The three columns below (Figure 4) show increases in the number of data samples collected for a 3.0 mm simulated seam weld crack as sampling density increases. Improving circumferential sampling from 10.0 mm to 1.0 mm results in a ten-fold gain in ultrasonic data collection. This additional data aids in the analysis of crack dimensions allowing for greater accuracy in through-wall measurement.   

Figure 4: Ultrasonic Sampling Resolutions Compared 

Angle Beam Tip Diffraction  

As data sampling increases across the face of a crack, the ability to employ tip-diffraction sizing increases. Tip-diffraction has been shown to provide a high degree of through-wall sizing accuracy in comparison to other methods such as amplitude sizing. Amplitude-based sizing methods are highly dependent on defect orientation matching calibration reflector orientation to ensure sizing accuracy. Angle-beam tip diffraction uses time of flight data from ultrasonic sound waves without regard to amplitude. This data shows defect signals recorded from the crack base to the tip as seen in the figure below (Figure 5). Six individual data points indicate separate geometric reflectors marked by different colored circles on both the A-Scan data and the graphic representation of the crack. Tip signals appear first due to their closer proximity to the transducer. The difference in time of flight between the crack base and the crack tip can be used to calculate the through-wall dimension of the crack.  

Figure 5: The image on the left shows ultrasonic shear wave signals entering the pipe wall and returning 6 direct measurements. The middle image shows A-Scan data points for the 6 direct measurements collected in Dexon’s proprietary UT data analysis software, Dexon Studio. The image on the right shows each measurement collected in relation to through-wall height.  

Crack Inspection Verification  

Inspection verification and testing were performed using natural and artificial defects in an 8” test loop at Dexon’s test yard. A test loop system allows a PIG to run continuously through a closed loop pipeline and provides valuable data concerning the probability of detection, sizing accuracy, inspection repeatability, tool reliability, and the effect of tool wear on inspection results.   

Numerous artificial defect shapes were tested including rectangular, elliptical, varying through-wall height, tilted, skewed, ID / OD connected, and multi-angular. In addition, a major oil and gas company provided two natural flaws removed from service piping. These flaws were inspected by Dexon without prior information concerning position, through-wall height, or orientation. The following two tables define the shape and orientation of the artificial defects, with all notch dimensions and locations being confirmed by manual inspection.   

Artificial Crack Shapes  

Figure 6: Rectangular, Elliptical, variable, and multi-angular artificial crack defect shapes.  

Defect Orientation 

Figure 7: Artificial crack defect through wall height and orientation.  

Verification of Detection and Sizing Results  

In total 54 defects were placed in the Dexon test loop. Inspection verification data from the above defects show a high probability of detection. All defects with a minimum through-wall height of 0.50 mm were detected. 94% of all defects were accurately sized to within ±1.0 mm of actual through-wall height. Sizing deviations for all defects produced a minimum of 0.00 mm, an average of 0.49 mm, and a maximum of 1.40 mm. Defects producing the largest deviation tended to be highly tilted. Both natural crack flaws were detected, oriented, and sized within ±1.0 mm. Verification of the natural flaw characteristics was performed with a combination of phased array, full matrix capture, three-dimensional metrology (third party), and macro-etching. Each verification method agreed with PIG inspection results.   

Conclusion  

By notably increasing the sampling density of pipeline inspection the tip diffraction sizing method can be employed for in-line inspection. The UT-CS Hawk ILI System has produced high-quality ultrasonic data confirming the ability to detect, place, and size defects with a high degree of accuracy. The tip diffraction sizing method combined with high-density sensor arrays proved to be accurate regardless of defect orientation, placement, or through-wall dimension.   

Dexon Technology PLC  

Dexon Technology PLC is a technology company that provides intelligent pigging and asset integrity management services globally. With close to 500 staff spread over 5 continents, Dexon provides cutting-edge inspection solutions to a diverse range of industries. Extensive in-house Research and Development and testing facilities allow for the continual development of inspection technology as well as modification of existing technology to meet individual client inspection requirements.