天然气管道清管过程动态预测软件开发及应用

1.中国石油西南油气田分公司集输工程技术研究所;2.中国石油西南油气田分公司川中油气矿;3.中国石油西南油气田分公司输气管理处

天然气管道;大口径;清管过程;动态预测;软件开发;现场应用

Development and application of dynamic prediction software for pigging process of natural gas pipelines
PENG Yang1,DAI Zhixiang1,HU Zixia2,DENG Lei3,DU Yan3,HE Jingran3,BIE Qin1

1.Gathering and Transmission Engineering Technology Research Institute, PetroChina Southwest Oil & Gas Field Company; 2.Central Sichuan Oil and Gas District, PetroChina Southwest Oil & Gas Field Company; 3.Gas Transmission Division, PetroChina Southwest Oil & Gas Field Company

natural gas pipeline, large-diameter, pigging process, dynamic prediction, software development, field application

DOI: 10.6047/j.issn.1000-8241.2024.03.011

备注

【目的】中国骨干天然气管网包含多条大口径、长距离天然气管道,对于天然气长输管道开展周期性清管作业是保障其安全、平稳、高效运行的重要手段。目前,清管作业仍是利用设立监听点和依靠操作人员经验方法来开展,无法提前模拟清管方案,并预测清管器运行速度、运行位置、到达时间以及管内压力变化等参数。【方法】为此,根据实际天然气清管作业特点,构建清管过程动态预测数学模型并求解,开发了天然气管道清管过程动态预测软件,并将其应用于某管道A—B、B—C、D—E输气管段的实际清管作业进行清管时间、清管速度预测。【结果】①基于改进的两相流瞬态清管模型和动态预测软件,能够准确预测清管过程中清管器运行速度、所处位置及到达各站时间等关键参数;②利用52次现场实际清管作业监测数据,验证了所用天然气管道清管过程动态预测软件的可靠性;③软件预测的清管时间、清管速度较实测数据的平均相对误差分别为5.94%、6.56%。【结论】应用该天然气管道清管过程动态预测软件,能够实现清管作业方案编制的高效性,降低清管人工负荷,保障清管过程的安全性,提升管道管理的智能化程度。(图3表6,参[28]
[Objective] China’s backbone natural gas pipeline network comprises numerous large-diameter and long-distance pipelines. Periodic pigging operations play a crucial role in ensuring the safe, stable and efficient operation of these pipelines. However, since current pigging operations rely heavily on operator experience and the establishment of monitoring points, the inability to simulate pigging schemes in advance prevents accurate prediction of parameters such as the operating speed, position and arrival time of the pig, and pressure changes in the pipe. [Methods] To address this challenge, a mathematical model for dynamic prediction of the pigging process was constructed and put into practice according to the characteristics of actual pigging operations. Subsequently, the software for dynamic prediction of the pigging process was developed and applied to the actual pigging operations of several sections (A-B, B-C and D-E) of a designated pipeline for predicting the pigging time and pigging speed. [Results] The improved two-phase flow transient pigging model and the dynamic prediction software accurately forecast critical parameters, including the running speed, position and arrival time at each station of the pig during the pigging process; The accuracy of the dynamic pigging prediction technology and the reliability of the software were verified using the monitoring data of 52 actual pigging operations; And compared with actual measurements, the software’s predictions had average relative errors of 5.94% for pigging time and 6.56% for pigging speed. [Conclusion] The utilization of the dynamic prediction technology and software enables efficient preparation of pigging operation schemes for natural gas pipelines, reduces manual workload, ensures pigging process safety, and enhances pipeline management intelligence. (3 Figures, 6 Tables, 28 References)
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