During the trial mining process, ground horizontal pipes are prone to generating hydrates due to pressure and temperature changes, leading to ice blockage. Hydrate inhibitors are usually added on-site to prevent freezing blockage. However, existing addition methods have limitations, including poor real-time performance, insufficient accuracy in the addition amount, and dependence on manual adjustment. In view of this, this paper aims to develop models to predict the throttling pressure and temperature for horizontal ground pipes, and to indicate the amount of ethylene glycol needed to prevent freezing blockage, thereby laying the foundation for accurate, real-time prediction of fluid pressure and temperature and for controlling the addition amount. By integrating data-driven technologies and mechanism models, this study developed intelligent prediction systems for ground horizontal pipe throttling pressure and temperature, and for suppression of freeze-blocking ethylene glycol addition. First, a three-phase throttling mechanism model for oil, gas, and water is established using the energy conservation equation to accurately predict the pressure and temperature at the throttling points along the process. At the same time, HYSYS software is used to simulate various operating conditions and to fit the ethylene glycol addition amount prediction model. Finally, edge computing equipment is integrated to enable real-time data collection, prediction, and dynamic adjustment and optimization. The field measurement data of Well A showed that the model’s prediction error of pressure and temperature before and after throttling is less than 6%, and the prediction error of the ethylene glycol addition amount is less than 5%, which provides key technical support for safe and efficient operation of the trial mining process as well as for cost reduction and efficiency improvement.
Peng et al. (Wed,) studied this question.