In-Line Service For Internal Inspection Of Unpiggable Buried Oil Pipelines Using Long Range Ultrasound Guided Waves In Fifty Metre Segments
The PIGWaves project targets at developing an in-service pipe inspection tool capable of inspecting both piggable and currently unpiggable oil pipelines of steel construction and internal diameter 150-350mm that provides 100% volume inspection for features such as hard spots, stress corrosion cracking, corrosion and erosion. Long Range Ultrasound Guided Waves (LRUG) will be employed by the robot in order to produce a map of the circumferential and axial pipe corrosion and cracks. Moreover, total volume inspection of the pipeline will be achieved far more rapidly, accurately and cheaply than state-of-the-art magnetic and ultrasonic pigs. After project ends the system will be scaled up to inspect pipelines of diameters 500-1000mm.
The PIGWaves system will comprise of a robot that will be capable of working in pipelines that carry liquids, and particularly oil. The PIGWaves robot will float down the pipeline in a non-inspecting mode. Every 50m it will expand a flexible probe collar to lock itself to the circumference of the pipe. The collar will employ Long Range Ultrasound Guided waves technology (LRUG) to inspect a pipe segment of 50m in both directions. It will then retract the collar and move another 50m before inspecting the next 50m. The robot will communicate with base station at entry point to send NDT data and locate the position of the robot. The robotic system will be designed to float freely past dents, sharp bends, debris, valves and changing pipe diameters. Moreover, in the presence of no flow at the pipe, the robot will actively swim past these obstructions.
The aim is to perform total volume inspection far more rapidly and accurately than current methods of ultrasonic NDT inspection. In the field of pipeline inspection LRUG presents the benefit that the probes would only need to be adjusted every 50m, the typical attainable propagation range of LRUG in pipelines, thus making the adaptation more feasible.
1) To develop an innovative flexible LRUG collar that adapts to typical steel pipes used in the Oil & Gas pipeline construction with wall thicknesses ranging from 7-47mm and diameters 150-350mm with one size of LRUG collar and also 500-1000mm diameters with another collar. The collar will bring sufficient number of NDT sensors that will be required to detect corrosion defects with cross sectional area greater than 1cm2 and thinning greater than 10% of wall thickness.
2) To develop an adaptive locking mechanism to allow the robot to become stationary at the data collection points and remain at that location till NDT operations are completed.
3) To develop an innovative umbilical free swimming robot, 50-60% smaller than the diameter of the pipe to be inspected. The robot will be able to passively floats past restrictions, sharp bends, dents, valves and debris using pipeline flow pressure where available or actively swims using thrusters where a pipe has little or no flow. Every 50m the robot will expand and engage with the pipe wall to send and receive LRUG waves down the pipe in order to assess the condition of 50m pipe segments.
4) To develop a robust sensor/communication system that wirelessly transmits NDT data over distances of 1000m with minimum on-board circuitry and power requirements.
5) To develop a navigation system, as part of the sensor/communication system, capable of measuring the distance travelled by the robot through the pipeline to activate its locking mechanisms, stop the robot every 50m and perform the NDT inspection.
6) To develop a Supervisory Control and Data Acquisition System capable of displaying defect data with spatial mapping of defects. Target robot position determination accuracy: ±0.25m in a pipeline, target defect detection performance: detection of all corrosion defects greater than 10% of wall thickness.
The PigWaves Robot is able to inspect pipelines with diameter reductions caused by obstacles, sharp bends, and little or no flow. It also reduces the on-board data storage requirements by orders of magnitude compared with present inspection methods deployed by existing smart pigs. This also results in increased speed of coverage as compared to pigs that gather data with ultrasonic compression probes which have to make contact with the pipe wall every few millimetres. Reduced data enables faster subsequent defect analysis and reporting.
PigWaves is a result of a research project funded by the European Commission Research Programme under grant no. 315232.