Advanced Pipeline Inspection and Predictive Maintenance for Saudi Hydrocarbon Distribution Networks: Integrating Engineering Risk Assessment, Digital Monitoring, and Asset Integrity Management

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@article{1724868,
      author = {Shafiqur Rehman Shaikh},
      title = {Advanced Pipeline Inspection and Predictive Maintenance for Saudi Hydrocarbon Distribution Networks: Integrating Engineering Risk Assessment, Digital Monitoring, and Asset Integrity Management},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {10},
      number = {5},
      pages = {1486-1498},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1724868.pdf},
      abstract = {Hydrocarbon distribution pipelines require inspection strategies capable of detecting damage before it compromises containment, while avoiding maintenance activity that delivers little reduction in risk. This review examines how advanced in-line inspection, distributed monitoring, predictive modelling and asset integrity governance can be combined for Saudi Arabian distribution networks. A structured, critical synthesis of peer-reviewed studies published during 2020–2025 distinguishes validated engineering methods from promising but incompletely demonstrated digital applications. Evidence indicates that magnetic flux leakage and ultrasonic inspection remain essential for characterising material loss, whereas acoustic, hydraulic and fibre-optic systems provide complementary surveillance between inspection campaigns. Bayesian degradation models and machine-learning predictions can improve maintenance prioritisation when measurement uncertainty, operating changes and failure consequences are represented explicitly. However, high classification accuracy in controlled studies cannot establish field reliability, and algorithmic outputs cannot substitute for fitness-for-service assessment. The proposed framework connects threat registers, inspection coverage, data quality, uncertainty-aware prognosis and documented intervention decisions through an auditable feedback process. Particular attention is given to the implications of sour service, variable operating regimes, remote corridors and increasing infrastructure interdependence in Saudi Arabia. The contribution is a practical decision architecture that treats digital monitoring as additional evidence for engineering judgement, rather than an autonomous guarantee of safety. The review identifies requirements for field validation, accountable model governance and risk-sensitive deployment that can support reliable energy infrastructure under Vision 2030.},
      keywords = {Hydrocarbon pipelines; in-line inspection; predictive maintenance; asset integrity; Bayesian risk assessment; digital twins; Saudi Arabia},
      month = {November},
      doi = {https://doi.org/10.64388/ire1724868}
  }