预测石油储层初始含水饱和度的人工神经网络模型

Anthony Ogbaegbe Chikwe, O. Nwanwe, Jude Emeka Odo, Aliene Chibuike Patrick, Ifeanyichukwu Michael Onyejekwe, Christian Emelu Okalla
{"title":"预测石油储层初始含水饱和度的人工神经网络模型","authors":"Anthony Ogbaegbe Chikwe, O. Nwanwe, Jude Emeka Odo, Aliene Chibuike Patrick, Ifeanyichukwu Michael Onyejekwe, Christian Emelu Okalla","doi":"10.9734/jerr/2024/v26i31093","DOIUrl":null,"url":null,"abstract":"Initial Water saturation is the water saturation of a reservoir before production commences. It enables the reservoir engineer to properly estimate the correct volume of Oil or gas reserves and to produce without water. And over the years over estimation or under estimation had caused major changes in the decision making of oil companies. New techniques are developed as technology advances to measure water saturation. These are the most widely used techniques for determining water saturation, nevertheless. Measurements obtained directly from a sealed core, which are more expensive, or calculations made using the Archie equation on sample well logs, which are less expensive. In this Project, Artificial Neural Network (ANN) model is the sole purpose of the modelling. The datasets are gathered, processed, trained, tested and validated.","PeriodicalId":508164,"journal":{"name":"Journal of Engineering Research and Reports","volume":"104 3‐4","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Artificial Neural Network Model for Predicting Initial Water Saturation of Petroleum Reservoirs\",\"authors\":\"Anthony Ogbaegbe Chikwe, O. Nwanwe, Jude Emeka Odo, Aliene Chibuike Patrick, Ifeanyichukwu Michael Onyejekwe, Christian Emelu Okalla\",\"doi\":\"10.9734/jerr/2024/v26i31093\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Initial Water saturation is the water saturation of a reservoir before production commences. It enables the reservoir engineer to properly estimate the correct volume of Oil or gas reserves and to produce without water. And over the years over estimation or under estimation had caused major changes in the decision making of oil companies. New techniques are developed as technology advances to measure water saturation. These are the most widely used techniques for determining water saturation, nevertheless. Measurements obtained directly from a sealed core, which are more expensive, or calculations made using the Archie equation on sample well logs, which are less expensive. In this Project, Artificial Neural Network (ANN) model is the sole purpose of the modelling. The datasets are gathered, processed, trained, tested and validated.\",\"PeriodicalId\":508164,\"journal\":{\"name\":\"Journal of Engineering Research and Reports\",\"volume\":\"104 3‐4\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Engineering Research and Reports\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.9734/jerr/2024/v26i31093\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Engineering Research and Reports","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.9734/jerr/2024/v26i31093","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

初始含水饱和度是指开始生产前储层的含水饱和度。它使储层工程师能够正确估计石油或天然气储量,并在不含水的情况下进行生产。多年来,估算过高或过低都给石油公司的决策带来了重大变化。随着技术的进步,人们开发出了测量含水饱和度的新技术。然而,这些都是最广泛使用的确定含水饱和度的技术。直接从密封岩心中获取的测量值成本较高,或使用阿奇方程在样本测井记录上进行的计算,成本较低。在本项目中,人工神经网络(ANN)模型是建模的唯一目的。对数据集进行收集、处理、训练、测试和验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Artificial Neural Network Model for Predicting Initial Water Saturation of Petroleum Reservoirs
Initial Water saturation is the water saturation of a reservoir before production commences. It enables the reservoir engineer to properly estimate the correct volume of Oil or gas reserves and to produce without water. And over the years over estimation or under estimation had caused major changes in the decision making of oil companies. New techniques are developed as technology advances to measure water saturation. These are the most widely used techniques for determining water saturation, nevertheless. Measurements obtained directly from a sealed core, which are more expensive, or calculations made using the Archie equation on sample well logs, which are less expensive. In this Project, Artificial Neural Network (ANN) model is the sole purpose of the modelling. The datasets are gathered, processed, trained, tested and validated.
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