A DAS-Based Approach for Predicting Liquid Flow Velocity in Pipelines

Accurate measurement of liquid flow velocity is crucial for pipeline management in the petroleum industry. Traditional flowmeters, such as ultrasonic, electromagnetic, and pressure-based devices, provide only point measurements and often require intrusive installation. Distributed Acoustic Sensing (DAS) offers a non-intrusive alternative by converting optical fibers into continuous acoustic sensors with meter-scale resolution. In this study, a High-Definition DAS system was applied in a laboratory flow loop to monitor single-phase liquid flow. The recorded signals were analyzed in both time and frequency domains. Results showed that the pump operating frequency dominated the spectral energy, accompanied by dispersive features. Power spectral density (PSD) increased linearly with flow rate, while Doppler-induced frequency shifts in the dominant component enabled velocity prediction. A regression model achieved a high coefficient of determination (R2 = 0.9928), confirming the strong predictive capability. These findings highlight DAS as a reliable and scalable solution for non-intrusive liquid flow monitoring in pipelines.