Particle Image Velocimetry (PIV) in Flow Assurance: Fundamentals, Applications, and Future Research Directions

Flow assurance remains a critical concern in the safe and efficient operation of energy transport systems, including oil and gas pipelines, carbon capture and storage, and emerging hydrogen (H₂) infrastructure. Complex phenomena such as hydrate formation, wax and asphaltene deposition, solid particle transport, and multiphase instabilities can severely disrupt flow, leading to operational downtime and safety hazards. Traditional measurement techniques, while useful, are often limited in their ability to capture the high-resolution, time-dependent behavior of such complex flow systems. Particle image velocimetry (PIV) has emerged as a versatile, non-intrusive optical measurement technique capable of resolving velocity fields across entire flow domains. Its ability to visualize and quantify transient, multiphase, and near-wall flows makes it particularly valuable for addressing longstanding challenges in flow assurance. This review systematically explores the fundamentals of PIV, including its working principles, hardware components, and major variants such as stereo-PIV, time-resolved PIV, and micro-PIV. A comprehensive assessment is presented of how PIV has been applied to visualize slug flow, hydrate and wax deposition, barite sag, sand transport, and interfacial phenomena in emulsions and foams. Further, the review highlights the integration of PIV with computational fluid dynamics, artificial intelligence (AI), and digital-twin frameworks for model validation, hybrid data assimilation, and predictive analytics. Representative case studies from oil, gas, CO₂, and H₂ pipelines are compared to showcase practical insights and experimental setups. Experimental limitations related to optical access, seeding fidelity, and data processing are critically discussed, along with potential mitigation strategies. Finally, the review outlines future directions including real-time PIV integration in smart flow loops, AI-assisted image processing, and miniaturized systems for downhole or opaque environments. By synthesizing current knowledge and identifying key research gaps, this work positions PIV as a strategic enabler for next-generation flow assurance diagnostics in both conventional and green energy systems.