{"title":"基于神经网络系统识别理论的地层压力预测研究","authors":"Cheng Liang, S. Lijun","doi":"10.1109/ITCA52113.2020.00151","DOIUrl":null,"url":null,"abstract":"The traditional formation pressure calculation mostly uses the system identification method of empirical formula and fitting formula. It can not get satisfactory identification results. In this paper, neural network is applied to system identification. A neural network identification model and improved error back propagation algorithm are researched. It is applied to the formation pressure prediction of injection production system. The process of system identification is the process of directly learning the input and output data of the system. The experimental results show that the neural network is effective in system identification.","PeriodicalId":103309,"journal":{"name":"2020 2nd International Conference on Information Technology and Computer Application (ITCA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Formation Pressure Prediction Based on Neural Network System Identification Theory\",\"authors\":\"Cheng Liang, S. Lijun\",\"doi\":\"10.1109/ITCA52113.2020.00151\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The traditional formation pressure calculation mostly uses the system identification method of empirical formula and fitting formula. It can not get satisfactory identification results. In this paper, neural network is applied to system identification. A neural network identification model and improved error back propagation algorithm are researched. It is applied to the formation pressure prediction of injection production system. The process of system identification is the process of directly learning the input and output data of the system. The experimental results show that the neural network is effective in system identification.\",\"PeriodicalId\":103309,\"journal\":{\"name\":\"2020 2nd International Conference on Information Technology and Computer Application (ITCA)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 2nd International Conference on Information Technology and Computer Application (ITCA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITCA52113.2020.00151\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 2nd International Conference on Information Technology and Computer Application (ITCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITCA52113.2020.00151","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Formation Pressure Prediction Based on Neural Network System Identification Theory
The traditional formation pressure calculation mostly uses the system identification method of empirical formula and fitting formula. It can not get satisfactory identification results. In this paper, neural network is applied to system identification. A neural network identification model and improved error back propagation algorithm are researched. It is applied to the formation pressure prediction of injection production system. The process of system identification is the process of directly learning the input and output data of the system. The experimental results show that the neural network is effective in system identification.