石油钻采工艺2026，Vol.48Issue(4)：499-506,8.DOI:10.13639/j.odpt.202506023
基于K-means聚类的气井井筒积液程度定量划分与排液措施优化
K-means clustering-based quantitative classification of liquid loading severity in gas wells and drainage measures optimization
刘楠楠 1刘伟 1宋付权 1徐慧 1许守武 1彭浩平1
作者信息
- 1. 常州大学石油与天然气工程学院,江苏 常州 213164
- 折叠
摘要
Abstract
For the accurate identification of liquid loading severity in gas wellbores and the optimization of drainage gas recovery strategies,this study addresses the lack of quantitative classification criteria in field applications.By employing the K-means clustering algorithm,an improved silhouette coefficient method is proposed to determine the optimal number of clusters K with higher precision.Using production data from 86 wells in a certain oilfield,a dual classification criterion integrating tubing-casing pressure difference and daily gas production was established to categorize liquid loading levels.The results show that improved silhouette coefficient method achieved an accuracy rate of 94.6%in selecting the optimal K value.During the classification process,the severity of liquid loading is firstly divided into four main categories based on the tubing-casing pressure difference Δp:zero liquid loading(Δp＜2 MPa),mild liquid loading(2 MPa≤Δp＜3.41 MPa),moderate liquid loading(3.41 MPa≤Δp＜5 MPa),and severe liquid loading(Δp≥5 MPa).And then,for the three categories with liquid loading,the subdivision is made on the basis of daily gas production:mild liquid loading corresponds to daily gas production ranges of(1.15～1.38)×104 m3/d and(0.47～1.15)×104 m3/d,moderate liquid loading corresponds to(0.38～0.47)×104 m3/d and(0.35～0.38)×104 m3/d,and severe liquid loading corresponds to(0.26～0.35)×104 m3/d and(0～0.26)×104 m3/d.After applying this dual criterion,the accuracy of liquid loading severity identification has increased to 88.4%from 62.8%.This quantitative classification standard can effectively support the selection of drainage gas recovery technologies and parameters optimization,and plays guiding role in improving the effect of measures and the efficiency of fluid drainage.关键词
井筒积液/K-means聚类/改进轮廓系数/油套压差/日产气量/排水采气Key words
liquid loading/K-means clustering/improved silhouette coefficient/tubing-casing pressure difference/daily gas production/drainage gas recovery分类
能源科技引用本文复制引用
刘楠楠,刘伟,宋付权,徐慧,许守武,彭浩平..基于K-means聚类的气井井筒积液程度定量划分与排液措施优化[J].石油钻采工艺,2026,48(4):499-506,8.
