RobotX: Robotic digital X-ray scanning system for deep water flexible riser inspection
Background
The boundaries of oil and gas exploration continue to push production facilities into deeper water creating many new challenges for operators to provide adequate integrity assurance of their assets. Operating in deep water hostile environments, flexible risers are used to bring oil from oil wells deep underwater to the surface, where it can be processed by Floating Production, Storage and Off Loading (FPSO) installations. Today, there are over 270 vessels worldwide as oil FPSOs with generally 5-30 riser slots.
A flexible riser consists of a number of layers of steel and polymer that have a complex structure and some layers are shielded by others, making non-destructive testing (NDT) particularly difficult. Further challenging condition arise from corrosive environments, higher pressures and temperatures. The inspection techniques currently available in the market consist of only irregular diver or Remotely Operated Vehicle (ROV) inspections and are able to inspect only the near side layers for wire disruptions, with the far side layers remaining uninspected.
The RobotX project will investigate the feasibility of a robotic digital X-ray scanning system to solve the needs and challenge of deep water flexible risers’ inspection.
Objectives
The RobotX system will perform a see-through quick scan as it crawls and process the data using innovative image processing methods and categorise them using machine learning.
If defects are detected the robotic system will be able to turn around the riser and perform a more thorough scan. The defect will be correctly identified, using image taken at several angles. The robot and digital radiography equipment would have to withstand harsh environmental conditions i.e. high pressure (100bar).
Several enabling technologies will be explored and feasibility assessed for the deep-water riser inspection applications.
The project will develop:
A Robot crawler capable of moving along the subsea riser and revolve about the axis thereby allowing a complete series of continuous radiographic images;
Image Processing methods to improve image focusing and resolution on real life radiographic images (presence of bio-fouling, repair clamps etc.). New innovative feature analysis methods will be investigated to model observations and reduce effect of noise under extreme adverse conditions;
Innovative machine learning methods, e.g. deep learning, support vector machine etc., to carry out automated defect detection, classification and autonomous decision making for further inspection and intervention.
Benefits
The innovations of RobotX will allow the detection, and location, of the defects, and classify them according to an existing historical database, automatically deciding on bespoke scans for assessing the severity and needs for future intervention. This autonomous and adaptive scanning methodology will allow cost-effective, fast and comprehensive robotic inspections of flexible risers especially at higher depths (>1000m), where the only technology is based on extremely costly ROV deployed from surface ships.
The project results will feed also into other applications like the inspection of wind or aircraft turbine blades.
Project Partners
- CIT
- InnoTecUK
- London SouthBank University
Meet the Principal Investigator(s) for the project
Professor Tat-Hean Gan - Professional Qualifications CEng. IntPE (UK), Eur Ing BEng (Hons) Electrical and Electronics Engg (Uni of Nottingham) MSc in Advanced Mechanical Engineering (University of Warwick) MBA in International Business (University of Birmingham) PhD in Engineering (University of Warwick) Languages English, Malaysian, Mandarin, Cantonese Professional Bodies Fellow of the British Institute of NDT Fellow of the Institute of Engineering and Technology Tat-Hean Gan has 10 years of experience in Non-Destructive Testing (NDT), Structural Health Monitoring (SHM) and Condition Monitoring of rotating machineries in various industries namely nuclear, renewable energy (eg Wind, Wave ad Tidal), Oil and Gas, Petrochemical, Construction and Infrastructure, Aerospace and Automotive. He is the Director of BIC, leading activities varying from Research and development to commercialisation in the areas of novel technique development, sensor applications, signal and image processing, numerical modelling and electronics hardware. His experience is also in Collaborative funding (EC FP7 and UK TSB), project management and technology commercialisation.
Related Research Group(s)
Brunel Innovation Centre - A world-class research and technology centre that sits between the knowledge base and industry.
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Project last modified 02/03/2021