Productivity Prediction of Tight Sandstone Reservoir Based on BP Neural Network

Yulei Wang
{"title":"Productivity Prediction of Tight Sandstone Reservoir Based on BP Neural Network","authors":"Yulei Wang","doi":"10.3968/9476","DOIUrl":null,"url":null,"abstract":"To survey He-8 member tight sand reservoir with low porosity and permeability in Mizhi gas field in Ordos basin, using the conventional well log data, this paper proposes the tight sand reservoir productivity prediction model and classification criterion based on BP neural network, getting quick classification of gas well productivity. We can predict sand reserve quantitatively instead qualitatively with the methods.Applications show that the methods of productivity prediction are effective and practical.","PeriodicalId":313367,"journal":{"name":"Advances in Petroleum Exploration and Development","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Petroleum Exploration and Development","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3968/9476","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

To survey He-8 member tight sand reservoir with low porosity and permeability in Mizhi gas field in Ordos basin, using the conventional well log data, this paper proposes the tight sand reservoir productivity prediction model and classification criterion based on BP neural network, getting quick classification of gas well productivity. We can predict sand reserve quantitatively instead qualitatively with the methods.Applications show that the methods of productivity prediction are effective and practical.
基于BP神经网络的致密砂岩储层产能预测
以鄂尔多斯盆地米脂气田河8段低孔低渗致密砂岩储层为研究对象,利用常规测井资料,提出了基于BP神经网络的致密砂岩储层产能预测模型和分类标准,实现了气井产能的快速分类。利用该方法可以定量预测砂储量,而不是定性预测。应用表明,生产率预测方法是有效的、实用的。
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 求助全文
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:481959085
Book学术官方微信