裂缝网络分析中的偏差和不确定性的原因

IF 0.8 4区 地球科学 Q2 Earth and Planetary Sciences
D. Peacock, D. Sanderson, E. Bastesen, A. Rotevatn, Tor H. Storstein
{"title":"裂缝网络分析中的偏差和不确定性的原因","authors":"D. Peacock, D. Sanderson, E. Bastesen, A. Rotevatn, Tor H. Storstein","doi":"10.17850/NJG99-1-06","DOIUrl":null,"url":null,"abstract":"Fault and fracture networks are analysed to determine the deformation history and to help with such applications as engineering geology and fluidflow modelling. These analyses rely on quantifying such factors as length, frequency and connectivity. Measurements may, however, be influenced by a range of factors relating to resolution, geology, methods used and to the analyst(s). These factors mean that it can be difficult to obtain a single correct solution, with bias and uncertainty being introduced by different analysts, even for something as simple as counting the number of joint intersection points on a well-exposed bedding plane. These problems suggest there are significant issues in comparing databases, for example when using outcrop analogue data to model subsurface data. Our recommendation is that analysts and modellers should be aware of the potential pitfalls in their measurements of structures and, therefore, be more cautious with resultant analyses and models. We suggest that analysts assess their results by testing the reproducibility. Simple ways of doing this include: (1) checking for change in measurements (e.g., fracture frequencies) during the course of a study; (2) remeasuring part of the fracture network to check if the same results are obtained, and; (3) get one or more other analysts to blind-test the fracture network.","PeriodicalId":49741,"journal":{"name":"Norwegian Journal of Geology","volume":null,"pages":null},"PeriodicalIF":0.8000,"publicationDate":"2019-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Causes of bias and uncertainty in fracture network analysis\",\"authors\":\"D. Peacock, D. Sanderson, E. Bastesen, A. Rotevatn, Tor H. Storstein\",\"doi\":\"10.17850/NJG99-1-06\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fault and fracture networks are analysed to determine the deformation history and to help with such applications as engineering geology and fluidflow modelling. These analyses rely on quantifying such factors as length, frequency and connectivity. Measurements may, however, be influenced by a range of factors relating to resolution, geology, methods used and to the analyst(s). These factors mean that it can be difficult to obtain a single correct solution, with bias and uncertainty being introduced by different analysts, even for something as simple as counting the number of joint intersection points on a well-exposed bedding plane. These problems suggest there are significant issues in comparing databases, for example when using outcrop analogue data to model subsurface data. Our recommendation is that analysts and modellers should be aware of the potential pitfalls in their measurements of structures and, therefore, be more cautious with resultant analyses and models. We suggest that analysts assess their results by testing the reproducibility. Simple ways of doing this include: (1) checking for change in measurements (e.g., fracture frequencies) during the course of a study; (2) remeasuring part of the fracture network to check if the same results are obtained, and; (3) get one or more other analysts to blind-test the fracture network.\",\"PeriodicalId\":49741,\"journal\":{\"name\":\"Norwegian Journal of Geology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2019-04-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Norwegian Journal of Geology\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.17850/NJG99-1-06\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Earth and Planetary Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Norwegian Journal of Geology","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.17850/NJG99-1-06","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Earth and Planetary Sciences","Score":null,"Total":0}
引用次数: 20

摘要

对断层和裂缝网络进行分析,以确定变形历史,并有助于工程地质学和流体流动建模等应用。这些分析依赖于量化长度、频率和连通性等因素。然而,测量可能会受到与分辨率、地质、使用的方法和分析员有关的一系列因素的影响。这些因素意味着,即使是像计算暴露良好的层面上的节理交点数量这样简单的事情,也很难获得单一的正确解,因为不同的分析师会引入偏差和不确定性。这些问题表明,在比较数据库时存在重大问题,例如,在使用露头模拟数据对地下数据进行建模时。我们的建议是,分析师和建模者应该意识到他们对结构测量中的潜在陷阱,因此,对由此产生的分析和模型更加谨慎。我们建议分析员通过测试再现性来评估他们的结果。简单的方法包括:(1)在研究过程中检查测量值(例如断裂频率)的变化;(2) 重新测量裂缝网络的一部分,以检查是否获得相同的结果,以及;(3) 让一个或多个其他分析员对裂缝网络进行盲测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Causes of bias and uncertainty in fracture network analysis
Fault and fracture networks are analysed to determine the deformation history and to help with such applications as engineering geology and fluidflow modelling. These analyses rely on quantifying such factors as length, frequency and connectivity. Measurements may, however, be influenced by a range of factors relating to resolution, geology, methods used and to the analyst(s). These factors mean that it can be difficult to obtain a single correct solution, with bias and uncertainty being introduced by different analysts, even for something as simple as counting the number of joint intersection points on a well-exposed bedding plane. These problems suggest there are significant issues in comparing databases, for example when using outcrop analogue data to model subsurface data. Our recommendation is that analysts and modellers should be aware of the potential pitfalls in their measurements of structures and, therefore, be more cautious with resultant analyses and models. We suggest that analysts assess their results by testing the reproducibility. Simple ways of doing this include: (1) checking for change in measurements (e.g., fracture frequencies) during the course of a study; (2) remeasuring part of the fracture network to check if the same results are obtained, and; (3) get one or more other analysts to blind-test the fracture network.
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
Norwegian Journal of Geology
Norwegian Journal of Geology 地学-地球科学综合
CiteScore
1.60
自引率
25.00%
发文量
0
审稿时长
>12 weeks
期刊介绍: The Norwegian Journal of Geology publishes high-quality, fully peer-review papers from all geoscientific disciplines. Papers are commonly based on regional studies and should emphasise the development of understanding of fundamental geological processes. More specialised papers can also be submitted, but should be written in a way that is easily understood by nonspecialists, and illustrate the progress being made within that specific topic in geosciences. We also encourage initiatives for thematic issues within the scope of the Journal.
×
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