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}
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.
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.