西安石油大学学报（自然科学版）2024，Vol.39Issue(4)：83-89,7.DOI:10.3969/j.issn.1673-064X.2024.04.012
基于YOLOv5的油气井套管接箍检测方法
YOLOv5-based Detection Method for Oil and Gas Well Casing Joints
摘要
Abstract
At present,in the field of visual logging,the manual identification and depth calibration of casing joints from logging videos results in low detection efficiency and high detection error.To address this issue,a intelligent casing joint detection method based on YOLOv5 algorithm is proposed.Firstly,the image of the downhole casing joint is collected.In the absence of a publicly available data-set,a casing joint dataset is created through data enhancement method,and the enhanced dataset is labeled using the labelimg tool.Then,the labeled dataset is fed into the YOLOv5 network for training.Finally,the casing joints are recognized and counted using the trained optimal weights.The test results show that this method can accurately identify the casing joints in the current logging video,with a 100％accuracy in counting of the casing joints,and there is high detection efficiency,with an average detection time of 15 ms per frame.关键词
套管接箍/YOLOv5/目标检测/油气井检测Key words
casing joint/YOLOv5/target detection/oil and gas well detection分类
能源科技引用本文复制引用
张家田,赵耀,严正国,任星,张志威..基于YOLOv5的油气井套管接箍检测方法[J].西安石油大学学报（自然科学版）,2024,39(4):83-89,7.基金项目
国家科技重大专项(2016ZX05060) （2016ZX05060）
陕西省教育厅重点实验室项目(15JS097 （）
11JS051) （）
陕西省光电传感测井重点实验室开放基金(09JS042) （09JS042）
西安石油大学研究生创新与实践能力培养计划项目(YCS22113137) （YCS22113137）
