Articles | Volume 10, issue 2
https://doi.org/10.5194/se-10-487-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/se-10-487-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Apr 2019
Research article |
| 11 Apr 2019
How do we see fractures? Quantifying subjective bias in fracture data collection
Billy J. Andrews
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering, University of
Strathclyde, Glasgow, G11XJ, Scotland
Jennifer J. Roberts
Department of Civil and Environmental Engineering, University of
Strathclyde, Glasgow, G11XJ, Scotland
Zoe K. Shipton
Department of Civil and Environmental Engineering, University of
Strathclyde, Glasgow, G11XJ, Scotland
Sabina Bigi
Department of Earth Science, Sapienza University of Rome, P.le Aldo
Moro, 5, 00185 Rome, Italy
M. Chiara Tartarello
Department of Earth Science, Sapienza University of Rome, P.le Aldo
Moro, 5, 00185 Rome, Italy
Gareth Johnson
Department of Civil and Environmental Engineering, University of
Strathclyde, Glasgow, G11XJ, Scotland
School of GeoSciences, University of Edinburgh, Edinburgh, EH93FE,
Scotland
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Cited
20 citations as recorded by crossref.
- Mapping the fracture network in the Lilstock pavement, Bristol Channel, UK: manual versus automatic C. Weismüller et al. 10.5194/se-11-1773-2020
- Adaptive Segmentation for Discontinuity Detection on Karstified Carbonate Outcrop Images From UAV-SfM Acquisition and Detection Bias Analysis A. Marques et al. 10.1109/ACCESS.2022.3151897
- An automated fracture trace detection technique using the complex shearlet transform R. Prabhakaran et al. 10.5194/se-10-2137-2019
- The growth of faults and fracture networks in a mechanically evolving, mechanically stratified rock mass: a case study from Spireslack Surface Coal Mine, Scotland B. Andrews et al. 10.5194/se-11-2119-2020
- Introduction: Handling uncertainty in the geosciences: identification, mitigation and communication L. Pérez-Díaz et al. 10.5194/se-11-889-2020
- Fracture distribution in a folded fluvial succession: The Puig-reig anticline (south-eastern Pyrenees) X. Sun et al. 10.1016/j.marpetgeo.2021.105169
- Geomechanical and Fracture Network Interpretation of a Devonian Outcrop S. McKean et al. 10.2118/206723-PA
- Surface and Subsurface Damage Caused by Bullet Impacts into Sandstone O. Campbell et al. 10.3390/geosciences11090395
- Application of the tilt derivative transform to bathymetric data for structural lineament mapping C. Yeomans et al. 10.1016/j.jsg.2021.104301
- How can geologic decision-making under uncertainty be improved? C. Wilson et al. 10.5194/se-10-1469-2019
- The Decollement Depth of Active Thrust Faults in Italy: Implications on Potential Earthquake Magnitude P. Petricca et al. 10.1029/2019TC005641
- Fault fictions: systematic biases in the conceptualization of fault-zone architecture Z. Shipton et al. 10.1144/SP496-2018-161
- Geometry and topology of tectonolineaments in the Gorce Mts. (Outer Carpathians) in Poland M. Kania & M. Szczęch 10.1016/j.jsg.2020.104186
- Large-scale natural fracture network patterns: Insights from automated mapping in the Lilstock (Bristol Channel) limestone outcrops R. Prabhakaran et al. 10.1016/j.jsg.2021.104405
- A cluster-based multiparametric similarity test for the compartmentalization of crystalline rocks into structural domains A. Abi et al. 10.1144/qjegh2021-136
- Effect of Density, Trace Length, Aperture, and Direction Angle on Permeability Performance of Fracture Networks B. Gao et al. 10.1061/(ASCE)GM.1943-5622.0001718
- Fluid-Rock Interactions in a Paleo-Geothermal Reservoir (Noble Hills Granite, California, USA). Part 2: The Influence of Fracturing on Granite Alteration Processes and Fluid Circulation at Low to Moderate Regional Strain J. Klee et al. 10.3390/geosciences11110433
- A new subsampling methodology to optimize the characterization of two-dimensional bedrock fracture networks N. Ovaskainen et al. 10.1016/j.jsg.2022.104528
- Fracture attribute scaling and connectivity in the Devonian Orcadian Basin with implications for geologically equivalent sub-surface fractured reservoirs A. Dichiarante et al. 10.5194/se-11-2221-2020
- Investigating the evolution of fractures in clay–based ceramics during repeated freeze-thawing cycles using X-ray micro-computed tomography and image analysis C. Porfido et al. 10.1016/j.matchar.2021.111185
20 citations as recorded by crossref.
- Mapping the fracture network in the Lilstock pavement, Bristol Channel, UK: manual versus automatic C. Weismüller et al. 10.5194/se-11-1773-2020
- Adaptive Segmentation for Discontinuity Detection on Karstified Carbonate Outcrop Images From UAV-SfM Acquisition and Detection Bias Analysis A. Marques et al. 10.1109/ACCESS.2022.3151897
- An automated fracture trace detection technique using the complex shearlet transform R. Prabhakaran et al. 10.5194/se-10-2137-2019
- The growth of faults and fracture networks in a mechanically evolving, mechanically stratified rock mass: a case study from Spireslack Surface Coal Mine, Scotland B. Andrews et al. 10.5194/se-11-2119-2020
- Introduction: Handling uncertainty in the geosciences: identification, mitigation and communication L. Pérez-Díaz et al. 10.5194/se-11-889-2020
- Fracture distribution in a folded fluvial succession: The Puig-reig anticline (south-eastern Pyrenees) X. Sun et al. 10.1016/j.marpetgeo.2021.105169
- Geomechanical and Fracture Network Interpretation of a Devonian Outcrop S. McKean et al. 10.2118/206723-PA
- Surface and Subsurface Damage Caused by Bullet Impacts into Sandstone O. Campbell et al. 10.3390/geosciences11090395
- Application of the tilt derivative transform to bathymetric data for structural lineament mapping C. Yeomans et al. 10.1016/j.jsg.2021.104301
- How can geologic decision-making under uncertainty be improved? C. Wilson et al. 10.5194/se-10-1469-2019
- The Decollement Depth of Active Thrust Faults in Italy: Implications on Potential Earthquake Magnitude P. Petricca et al. 10.1029/2019TC005641
- Fault fictions: systematic biases in the conceptualization of fault-zone architecture Z. Shipton et al. 10.1144/SP496-2018-161
- Geometry and topology of tectonolineaments in the Gorce Mts. (Outer Carpathians) in Poland M. Kania & M. Szczęch 10.1016/j.jsg.2020.104186
- Large-scale natural fracture network patterns: Insights from automated mapping in the Lilstock (Bristol Channel) limestone outcrops R. Prabhakaran et al. 10.1016/j.jsg.2021.104405
- A cluster-based multiparametric similarity test for the compartmentalization of crystalline rocks into structural domains A. Abi et al. 10.1144/qjegh2021-136
- Effect of Density, Trace Length, Aperture, and Direction Angle on Permeability Performance of Fracture Networks B. Gao et al. 10.1061/(ASCE)GM.1943-5622.0001718
- Fluid-Rock Interactions in a Paleo-Geothermal Reservoir (Noble Hills Granite, California, USA). Part 2: The Influence of Fracturing on Granite Alteration Processes and Fluid Circulation at Low to Moderate Regional Strain J. Klee et al. 10.3390/geosciences11110433
- A new subsampling methodology to optimize the characterization of two-dimensional bedrock fracture networks N. Ovaskainen et al. 10.1016/j.jsg.2022.104528
- Fracture attribute scaling and connectivity in the Devonian Orcadian Basin with implications for geologically equivalent sub-surface fractured reservoirs A. Dichiarante et al. 10.5194/se-11-2221-2020
- Investigating the evolution of fractures in clay–based ceramics during repeated freeze-thawing cycles using X-ray micro-computed tomography and image analysis C. Porfido et al. 10.1016/j.matchar.2021.111185
Discussed (final revised paper)
Discussed (final revised paper)
Latest update: 29 Mar 2023
Short summary
Rocks often contain fracture networks, which can strongly affect subsurface fluid flow and the strength of a rock mass. Through fieldwork and workshops we show that people report a different number of fractures from the same sample area of a fracture network. This variability results in significant differences in derived fracture statistics, which are often used as inputs for geological models. We suggest protocols to recognise, understand, and limit this effect on fracture data collection.
Rocks often contain fracture networks, which can strongly affect subsurface fluid flow and the...
