Simulation of defect detection for the buried petroleum pipe by the X-ray backscatter imaging

Abstract

Ensuring the integrity, safety, and compliance of oil pipelines is crucial for operators. Two significant factors affecting pipeline integrity are metal loss due to corrosion or air gouging and the presence of cracks. This paper introduces an X-ray backscatter nondestructive testing model on a smart pig(an intelligent robot) for internal inspection of petroleum pipelines. The paper investigates the X-ray source and detection system, essential components of the backscatter imaging technology, to provide technical guidance for model design. The imaging system’s layout is modeled using GEANT4, and its performance in detecting defects of various formats on pipe walls is studied. The research demonstrates the feasibility of using X-ray backscatter imaging for pipeline inspection and provides insights into different defect detection. The findings contribute to designing and optimizing the robot’s scanning head for effective pipeline inspection.