From Prediction to Prevention: An Integrated Intelligent Solution for Hydrate Blockage in Gas Pipelines

Summary

Hydrate blockage poses a significant threat to the safe operation of natural gas pipelines, especially in desert environments with large diurnal temperature variations and undulating terrain. Current prevention strategies, often based on fixed-rate inhibitor injection, lack real-time responsiveness, leading to either chemical overuse or inadequate protection. In this study, we develop an integrated intelligent solution to shift from passive remediation to proactive prevention. A multifield coupling mathematical model was established to effectively predict hydrate formation location, time, and blockage degree by simulating gas/liquid flow, heat transfer, and hydrate kinetics. Furthermore, an intelligent feedback control algorithm was designed to dynamically adjust the inhibitor injection rate based on real-time pipeline pressure, temperature, and pressure-drop change rate. Field application in a 51.7-km desert pipeline demonstrated the model’s accuracy, with average prediction errors of 2.48% (absolute error = 0.15 MPa) for pressure and 4.35% (absolute error = 1.25°C) for temperature. The intelligent injection system reduced the average daily inhibitor consumption by approximately one-third (107.3 kg/d) while effectively preventing blockages. A comprehensive field deblocking scheme, combining depressurization, nitrogen-assisted methanol injection, gas/liquid separation, and pigging, successfully restored pipeline capacity by more than 30%. This integrated approach provides a reliable and economical strategy for hydrate management in long-distance gas pipelines.