利用机器学习对油气上游生产数据信息进行预测分析

A. K, R. Ramasree, M. Faisal
{"title":"利用机器学习对油气上游生产数据信息进行预测分析","authors":"A. K, R. Ramasree, M. Faisal","doi":"10.1109/ICCSP.2019.8698107","DOIUrl":null,"url":null,"abstract":"Machine learning is an area of knowledge, which supports many of the established and reliable techniques in Artificial intelligence. Oil and gas industry involve many sensors to collect data continuously. Especially the main focus, is on the Production data which will help the industry to perform Predictive analysis that will forecast what outputs we may get in future. The current research work focuses on the data produced from an oil well, over a month and then tries to predict the average oil rate, based on certain elements. In order to perform this, a predictive tool RapidMiner is used, and Regression model is applied. This research work helps in predicting the most dependent factor on the predictive variable, which is Average Oil Rate.","PeriodicalId":194369,"journal":{"name":"2019 International Conference on Communication and Signal Processing (ICCSP)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Performing Predictive Analysis using Machine Learning on the Information Retrieved from Production Data of Oil & Gas Upstream Segment\",\"authors\":\"A. K, R. Ramasree, M. Faisal\",\"doi\":\"10.1109/ICCSP.2019.8698107\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Machine learning is an area of knowledge, which supports many of the established and reliable techniques in Artificial intelligence. Oil and gas industry involve many sensors to collect data continuously. Especially the main focus, is on the Production data which will help the industry to perform Predictive analysis that will forecast what outputs we may get in future. The current research work focuses on the data produced from an oil well, over a month and then tries to predict the average oil rate, based on certain elements. In order to perform this, a predictive tool RapidMiner is used, and Regression model is applied. This research work helps in predicting the most dependent factor on the predictive variable, which is Average Oil Rate.\",\"PeriodicalId\":194369,\"journal\":{\"name\":\"2019 International Conference on Communication and Signal Processing (ICCSP)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Communication and Signal Processing (ICCSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSP.2019.8698107\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Communication and Signal Processing (ICCSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSP.2019.8698107","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

机器学习是一个知识领域,它支持人工智能中许多已建立和可靠的技术。石油和天然气行业需要使用许多传感器来连续收集数据。特别是主要的焦点是生产数据,这将有助于行业进行预测分析,预测我们未来可能得到的产出。目前的研究工作主要集中在油井一个多月的数据上,然后试图根据某些因素预测平均产油率。为了执行此操作,使用了预测工具RapidMiner,并应用了回归模型。本研究有助于预测平均产油量这一预测变量的最依赖因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performing Predictive Analysis using Machine Learning on the Information Retrieved from Production Data of Oil & Gas Upstream Segment
Machine learning is an area of knowledge, which supports many of the established and reliable techniques in Artificial intelligence. Oil and gas industry involve many sensors to collect data continuously. Especially the main focus, is on the Production data which will help the industry to perform Predictive analysis that will forecast what outputs we may get in future. The current research work focuses on the data produced from an oil well, over a month and then tries to predict the average oil rate, based on certain elements. In order to perform this, a predictive tool RapidMiner is used, and Regression model is applied. This research work helps in predicting the most dependent factor on the predictive variable, which is Average Oil Rate.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信