Causes of bias and uncertainty in fracture network analysis
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.
113-128
Peacock, David C.p.
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Sanderson, David J.
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Bastesen, Eivind
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Rotevatn, Atle
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Storstein, Tor H.
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24 April 2019
Peacock, David C.p.
6a9e5a6a-445c-4412-8afa-053bcb1cc9cb
Sanderson, David J.
5653bc11-b905-4985-8c16-c655b2170ba9
Bastesen, Eivind
351f796e-0fde-4470-9bc3-e0321f2c6353
Rotevatn, Atle
a5811643-0e5c-4b86-9145-54f5810fbe4c
Storstein, Tor H.
e593fbad-5d78-4f38-9d70-f6a3aa545fb0
Peacock, David C.p., Sanderson, David J., Bastesen, Eivind, Rotevatn, Atle and Storstein, Tor H.
(2019)
Causes of bias and uncertainty in fracture network analysis.
Norwegian Journal of Geology, 99 (1), .
(doi:10.17850/njg99-1-06).
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.
Text
NJG_Vol99_Nr1_Art6_Peacock
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More information
Accepted/In Press date: 2 March 2019
Published date: 24 April 2019
Identifiers
Local EPrints ID: 444430
URI: http://eprints.soton.ac.uk/id/eprint/444430
ISSN: 2387-5844
PURE UUID: 04627f4f-636c-47a1-8c50-97ecbcfe305f
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Date deposited: 19 Oct 2020 16:31
Last modified: 17 Mar 2024 03:13
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Author:
David C.p. Peacock
Author:
Eivind Bastesen
Author:
Atle Rotevatn
Author:
Tor H. Storstein
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