Guanghua Tong, Wang Jing, Gao Shan, Sun Yang, Wang Jinxiu, Zuo Jing
{"title":"Design of Automatic Layered Water Injection System Based on Internet of Things","authors":"Guanghua Tong, Wang Jing, Gao Shan, Sun Yang, Wang Jinxiu, Zuo Jing","doi":"10.1109/ICCSNT50940.2020.9304995","DOIUrl":null,"url":null,"abstract":"Layered water injection is a simple and effective way of secondary exploitation in oil fields. It can maintain the pressure of the oil layer and improve the effect of oilfield development, considered the basis for achieving stable and high production of crude oil. The traditional layered water injection method is inefficient and cannot meet the needs of mining. Therefore, this paper analyzes the current development of layered water injection technology and designs an automatic layered water injection system based on the Internet of Things. It is divided into perception recognition layer, network construction layer, and comprehensive application layer. Considering that the daily injection volume of water injection wells does not meet the standard caused by the actual water injection process, an automatic injection strategy of layered water injection is designed based on the K-means algorithm. Experiments demonstrate that the actual flow value of each layer after the automatic injection adjustment is completed is within the allowable error range of 10%, which meets the requirements of the qualified rate of layered water injection.","PeriodicalId":6794,"journal":{"name":"2020 IEEE 8th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"6 1","pages":"194-197"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 8th International Conference on Computer Science and Network Technology (ICCSNT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSNT50940.2020.9304995","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Layered water injection is a simple and effective way of secondary exploitation in oil fields. It can maintain the pressure of the oil layer and improve the effect of oilfield development, considered the basis for achieving stable and high production of crude oil. The traditional layered water injection method is inefficient and cannot meet the needs of mining. Therefore, this paper analyzes the current development of layered water injection technology and designs an automatic layered water injection system based on the Internet of Things. It is divided into perception recognition layer, network construction layer, and comprehensive application layer. Considering that the daily injection volume of water injection wells does not meet the standard caused by the actual water injection process, an automatic injection strategy of layered water injection is designed based on the K-means algorithm. Experiments demonstrate that the actual flow value of each layer after the automatic injection adjustment is completed is within the allowable error range of 10%, which meets the requirements of the qualified rate of layered water injection.