Application of BP Neural Network in Oil Field Production Prediction

Lei Sun, Yange Bi, Guorong Lu
{"title":"Application of BP Neural Network in Oil Field Production Prediction","authors":"Lei Sun, Yange Bi, Guorong Lu","doi":"10.1109/WCSE.2010.101","DOIUrl":null,"url":null,"abstract":"This paper introduces a new Neural Network model which is suitable for oil production prediction with training parameter set. From the comparison between prediction of oil production and real production, the precision of prediction meets the requirements quite well. In addition, this new model offers better self-adaptive ability and can be used in multi-cycle and multi-descending production forecast. In general, BP Neural Network is an ideal mean for oil production prediction.","PeriodicalId":376358,"journal":{"name":"2010 Second World Congress on Software Engineering","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Second World Congress on Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCSE.2010.101","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

This paper introduces a new Neural Network model which is suitable for oil production prediction with training parameter set. From the comparison between prediction of oil production and real production, the precision of prediction meets the requirements quite well. In addition, this new model offers better self-adaptive ability and can be used in multi-cycle and multi-descending production forecast. In general, BP Neural Network is an ideal mean for oil production prediction.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
BP神经网络在油田产量预测中的应用
本文介绍了一种新的神经网络模型,该模型适用于具有训练参数集的石油产量预测。从预测产油量与实际产油量的对比来看,预测精度达到了要求。该模型具有较好的自适应能力,可用于多周期、多递减的产量预测。总的来说,BP神经网络是一种理想的石油产量预测手段。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Justification of Free Software and its Enlightenment An Integrated Software for the Performance Study of PET Detector with Neural Network Position Estimators Browser/Server Based Individual Well Profit Evaluation System Color Analysis of Soybean Leaves Based on Computer Vision Design of Power Grid Environment Monitoring System Based on WLAN
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1