{"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}
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.