天然气管道黑色粉末粒度分布模型评价研究

doi:10.11885/j.issn.1674-5086.2018.03.05.01

西南石油大学学报(自然科学版) ›› 2018, Vol. 40 ›› Issue (4): 177-186.DOI: 10.11885/j.issn.1674-5086.2018.03.05.01

• 石油机械与油田化学 • 上一篇

天然气管道黑色粉末粒度分布模型评价研究

秦云松^1,2, 张吉军¹, 安建川³, 黄昕², 郑达⁴

1. 西南石油大学经济管理学院, 四川成都 610500;
2. 中国石油化工股份有限公司天然气分公司, 北京朝阳 100029;
3. 中国石油西南油气田分公司, 四川成都 610000;
4. 西南石油大学石油与天然气工程学院, 四川成都 610500

收稿日期:2018-03-05 出版日期:2018-08-01 发布日期:2018-08-01
通讯作者: 秦云松,E-mail:qinys.trqi@sinopec.com
作者简介:秦云松,1972年生,男,汉族,河南濮阳人,博士研究生,主要从事天然气产业、安全生产技术方面的研究工作。E-mail:qinys.trqi@sinopec.com;张吉军,1963年生,男,汉族,四川南充人,教授,博士生导师,主要从事石油工程管理、风险管理和决策分析方面的研究和教学工作。E-mail:yyjy7@sina.cn;安建川,1970年生,男,汉族,四川广安人,高级工程师,主要从事天然气生产经营方面的研究与管理工作。E-mail:anjc@petrochina.com.cn;黄昕,1982年生,男,汉族,江苏高邮人,硕士研究生,主要从事天然气项目管理、天然气储运系统安全生产、管道完整性方面的研究工作。E-mail:huangx.trqi@sinopec.com;郑达,1992年生,男,汉族,四川成都人,硕士研究生,主要从事天然气管道黑色粉末问题方面的研究工作。E-mail:frankzheng999@126.com
基金资助:
国家自然科学基金青年基金（51704253）；中国石油化工股份有限公司重点研发项目（2014314103）

Assessment of Particle Size Distribution Models for Black Powders in Natural Gas Pipelines

QIN Yunsong^1,2, ZHANG Jijun¹, AN Jianchuan³, HUANG Xin², ZHENG Da⁴

1. School of Economics and Management, Southwest Petroleum University, Chengdu, Sichuan 610500, China;
2. SINOPEC Gas Company, Chaoyang, Beijing 100029, China;
3. Southwest Oil and Gas Field, PetroChina, Chengdu, Sichuan 610000, China;
4. School of Oil & Gas Engineering, Southwest Petroleum University, Chengdu, Sichuan 610500, China

Received:2018-03-05 Online:2018-08-01 Published:2018-08-01

摘要/Abstract

摘要： 掌握天然气管道黑色粉末粒度分布（PSD）信息对于解决黑色粉末问题十分关键。如今常用的颗粒PSD模型较多，但缺乏较为成熟的模型评价机制。基于某一实际天然气管道内的黑色粉末数据，引入了S_RMSE、R²、I^AIC等评价指标和混淆矩阵、ROC曲线分别对7种常见PSD模型的拟合优度和预测能力进行了评价，结果显示，对数正态模型兼具描述集中分布和平均分布的能力而在拟合优度方面更具优势；同时，对数正态模型在颗粒全尺寸范围内[0.30 μm，7.25 μm]都有有效的预测效果。因此，该模型是一种综合预测能力最强的分布模型。

关键词: 天然气管道, 黑色粉末, PSD模型, 混淆矩阵, ROC曲线

Abstract: Understanding the particle size distribution (PSD) of black powders in natural gas pipelines is critical to resolving the black powder issue. There are now many PSD models available; however, there is a lack of established methods for assessing them. In this study, seven common PSD models were assessed for their goodness of fit and prediction capacities, on the basis of black powder data of a real natural gas pipeline, by employing assessment indexes such as S_RMSE, R², and I^AIC as well as a confusion matrix and ROC curve. The results showed that the log-normal model not only is capable of both concentrated and even distribution, but also exhibits better goodness of fit. In addition, the log-normal model is capable of effective prediction in the full range of particle sizes (0.30~7.25 μm). Therefore, it is the PSD model with the most comprehensive prediction capability.

Key words: natural gas pipeline, black powder, PSD model, confusion matrix, ROC curve

中图分类号:

TE89

秦云松, 张吉军, 安建川, 黄昕, 郑达. 天然气管道黑色粉末粒度分布模型评价研究[J]. 西南石油大学学报(自然科学版), 2018, 40(4): 177-186.

QIN Yunsong, ZHANG Jijun, AN Jianchuan, HUANG Xin, ZHENG Da. Assessment of Particle Size Distribution Models for Black Powders in Natural Gas Pipelines[J]. 西南石油大学学报(自然科学版), 2018, 40(4): 177-186.

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天然气管道黑色粉末粒度分布模型评价研究

Assessment of Particle Size Distribution Models for Black Powders in Natural Gas Pipelines

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