遗留数据-隐藏的机会

K. Reeves
{"title":"遗留数据-隐藏的机会","authors":"K. Reeves","doi":"10.1080/22020586.2019.12073241","DOIUrl":null,"url":null,"abstract":"Summary As oil prices have rebounded, operators look for new exploration opportunities. A new paradigm, however, is the increased focus on investor return rather than relentless expansion at all costs. This value-focused exploration looks for cost effective approaches and methods to leverage prior expenditures. Exploration driven by legacy data is one cost effective approach that is rising. Examination of resource discoveries are presented","PeriodicalId":8502,"journal":{"name":"ASEG Extended Abstracts","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Legacy data – hidden opportunity\",\"authors\":\"K. Reeves\",\"doi\":\"10.1080/22020586.2019.12073241\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Summary As oil prices have rebounded, operators look for new exploration opportunities. A new paradigm, however, is the increased focus on investor return rather than relentless expansion at all costs. This value-focused exploration looks for cost effective approaches and methods to leverage prior expenditures. Exploration driven by legacy data is one cost effective approach that is rising. Examination of resource discoveries are presented\",\"PeriodicalId\":8502,\"journal\":{\"name\":\"ASEG Extended Abstracts\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ASEG Extended Abstracts\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/22020586.2019.12073241\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ASEG Extended Abstracts","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/22020586.2019.12073241","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

随着油价的回升,油公司开始寻找新的勘探机会。然而,一种新的模式是越来越关注投资者回报,而不是不惜一切代价进行无情的扩张。这种以价值为中心的探索寻找具有成本效益的方法和方法来利用先前的支出。由遗留数据驱动的勘探是一种成本有效的方法。介绍了对资源发现的检查
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Legacy data – hidden opportunity
Summary As oil prices have rebounded, operators look for new exploration opportunities. A new paradigm, however, is the increased focus on investor return rather than relentless expansion at all costs. This value-focused exploration looks for cost effective approaches and methods to leverage prior expenditures. Exploration driven by legacy data is one cost effective approach that is rising. Examination of resource discoveries are presented
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
期刊最新文献
The Forrestania and Nepean electromagnetic test ranges, Western Australia – a comparison of airborne systems Smart stitching: adding lateral priors to ensemble inversions as a post-processing step X-ray computerised tomography for fracture and facies characterisation and slab orientation in cores stored within aluminium tubes Geophysical characterization of the remanent anomaly in the Paleo/Mesoproteozoic Araí Intracontinental Rift, Brazil Viability of long-short term memory neural networks for seismic refraction first break detection – a preliminary study
×
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