调整碳氢化合物工作流程,实现高效、快速的CO2储存潜力筛选

Q3 Earth and Planetary Sciences
Joss Smith, Ashley Uren, Joe Jennings, Thomas Butt, Craig Lang
{"title":"调整碳氢化合物工作流程,实现高效、快速的CO2储存潜力筛选","authors":"Joss Smith, Ashley Uren, Joe Jennings, Thomas Butt, Craig Lang","doi":"10.3997/1365-2397.fb2023081","DOIUrl":null,"url":null,"abstract":"Identifying and screening subsurface carbon storage options requires knowledge of numerous elements that can be costly and time consuming to assess at the regional scale. To remediate this, we use Neftex® Predictions which has automated the process of screening its global geological content so that carbon storage fairway extents and storage resources can be readily assessed and compared. This frees the geoscientist from the burden of time-consuming data cleaning and geoprocessing workflows. Attributes that indicate suitability of the storage option are based on a bespoke Carbon Storage Adequacy Index, developed to assess the reservoir, seal and operational factors. This automated workflow enables rapid portfolio generation and comparison, with high ranked fairways being prioritised for further investigation. Once prioritised, areas within fairways that have the greatest storage potential are useful to identify, here termed ‘sweet spots’. An example of how to do this by creating distribution maps of volumetric Prospective Storage Resource is presented. This shows how the Neftex Predictions datasets, alongside third-party data, can enhance screening map generation, especially when inferring beyond available data control. Examples from the North Sea, the Mediterranean, and the Gulf of Mexico demonstrate the global applicability of the workflows.","PeriodicalId":35692,"journal":{"name":"First Break","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adapting Hydrocarbon Workflows to Enable Efficient and Rapid Screening for CO2 Storage Potential\",\"authors\":\"Joss Smith, Ashley Uren, Joe Jennings, Thomas Butt, Craig Lang\",\"doi\":\"10.3997/1365-2397.fb2023081\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Identifying and screening subsurface carbon storage options requires knowledge of numerous elements that can be costly and time consuming to assess at the regional scale. To remediate this, we use Neftex® Predictions which has automated the process of screening its global geological content so that carbon storage fairway extents and storage resources can be readily assessed and compared. This frees the geoscientist from the burden of time-consuming data cleaning and geoprocessing workflows. Attributes that indicate suitability of the storage option are based on a bespoke Carbon Storage Adequacy Index, developed to assess the reservoir, seal and operational factors. This automated workflow enables rapid portfolio generation and comparison, with high ranked fairways being prioritised for further investigation. Once prioritised, areas within fairways that have the greatest storage potential are useful to identify, here termed ‘sweet spots’. An example of how to do this by creating distribution maps of volumetric Prospective Storage Resource is presented. This shows how the Neftex Predictions datasets, alongside third-party data, can enhance screening map generation, especially when inferring beyond available data control. Examples from the North Sea, the Mediterranean, and the Gulf of Mexico demonstrate the global applicability of the workflows.\",\"PeriodicalId\":35692,\"journal\":{\"name\":\"First Break\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"First Break\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3997/1365-2397.fb2023081\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Earth and Planetary Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"First Break","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3997/1365-2397.fb2023081","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Earth and Planetary Sciences","Score":null,"Total":0}
引用次数: 0

摘要

识别和筛选地下碳储存方案需要了解许多要素,这些要素在区域范围内进行评估可能既昂贵又耗时。为了解决这个问题,我们使用了Neftex®预测,该预测自动化了筛选其全球地质含量的过程,以便可以很容易地评估和比较碳储存通道的范围和储存资源。这将地球科学家从耗时的数据清理和地理处理工作流程中解放出来。表明储层选择是否合适的属性是基于定制的碳储存充足性指数,该指数用于评估储层、密封和操作因素。这种自动化的工作流程可以快速生成和比较组合,并优先考虑排名较高的球道,以便进一步调查。一旦确定了优先级,球道内存储潜力最大的区域就可以被识别出来,这里称之为“最佳区域”。给出了如何通过创建容量预期存储资源的分布图来实现这一点的示例。这表明Neftex预测数据集与第三方数据一起可以增强筛选地图的生成,特别是在推断可用数据控制之外的情况下。北海、地中海和墨西哥湾的例子证明了该工作流程的全球适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adapting Hydrocarbon Workflows to Enable Efficient and Rapid Screening for CO2 Storage Potential
Identifying and screening subsurface carbon storage options requires knowledge of numerous elements that can be costly and time consuming to assess at the regional scale. To remediate this, we use Neftex® Predictions which has automated the process of screening its global geological content so that carbon storage fairway extents and storage resources can be readily assessed and compared. This frees the geoscientist from the burden of time-consuming data cleaning and geoprocessing workflows. Attributes that indicate suitability of the storage option are based on a bespoke Carbon Storage Adequacy Index, developed to assess the reservoir, seal and operational factors. This automated workflow enables rapid portfolio generation and comparison, with high ranked fairways being prioritised for further investigation. Once prioritised, areas within fairways that have the greatest storage potential are useful to identify, here termed ‘sweet spots’. An example of how to do this by creating distribution maps of volumetric Prospective Storage Resource is presented. This shows how the Neftex Predictions datasets, alongside third-party data, can enhance screening map generation, especially when inferring beyond available data control. Examples from the North Sea, the Mediterranean, and the Gulf of Mexico demonstrate the global applicability of the workflows.
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
First Break
First Break Earth and Planetary Sciences-Geophysics
CiteScore
1.40
自引率
0.00%
发文量
98
×
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