Articles | Volume 10, issue 5
https://doi.org/10.5194/se-10-1469-2019
© 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-10-1469-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
How can geologic decision-making under uncertainty be improved?
Cristina G. Wilson
CORRESPONDING AUTHOR
Department of Psychology, College of Arts and Sciences, Temple University, Philadelphia, PA, USA
Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
Clare E. Bond
Department of Geology and Petroleum Geology, School of Geosciences, University of Aberdeen, Kings College, Aberdeen, UK
Thomas F. Shipley
Department of Psychology, College of Arts and Sciences, Temple University, Philadelphia, PA, USA
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Cited
19 citations as recorded by crossref.
- Towards a definition of a spatial geochemical compatibility: workflow, validation, and application M. Zuccolini et al. https://doi.org/10.1016/j.apgeochem.2024.106260
- The application of Tobler's hiking function in data-driven traverse modelling for planetary exploration A. Goodwin et al. https://doi.org/10.1016/j.actaastro.2024.12.005
- Explicit Instruction of Scientific Uncertainty in an Undergraduate Geoscience Field-Based Course K. Bateman et al. https://doi.org/10.1007/s11191-022-00345-z
- 3D multiple-point geostatistical simulation of joint subsurface redox and geological architectures R. Madsen et al. https://doi.org/10.5194/hess-25-2759-2021
- Fracture and fault characterization in the era of artificial intelligence C. Li & Y. Chen https://doi.org/10.1016/j.earscirev.2026.105504
- Cognitive Bias Mitigation in Executive Decision-Making: A Data-Driven Approach Integrating Big Data Analytics, AI, and Explainable Systems L. Theodorakopoulos et al. https://doi.org/10.3390/electronics14193930
- Spatial uncertainty constraints reduce overfitting for potential field geophysical inversion M. Lindsay et al. https://doi.org/10.1093/gji/ggag133
- Multi‐scenario Interpretations From Sparse Fault Evidence Using Graph Theory and Geological Rules G. Godefroy et al. https://doi.org/10.1029/2020JB020022
- Antarctic Sedimentary Basins and Their Influence on Ice‐Sheet Dynamics A. Aitken et al. https://doi.org/10.1029/2021RG000767
- Mapping hydrodynamic structure with sparse or no well data S. Stewart https://doi.org/10.1144/geoenergy2023-028
- Introduction: Handling uncertainty in the geosciences: identification, mitigation and communication L. Pérez-Díaz et al. https://doi.org/10.5194/se-11-889-2020
- Examining Rock Engineering Knowledge through a Philosophical Lens D. Elmo et al. https://doi.org/10.3390/geosciences12040174
- Understanding Human Dynamic Sampling Objectives to Enable Robot-assisted Scientific Decision Making S. Liu et al. https://doi.org/10.1145/3623383
- Fiber Arts Require Spatial Skills: How a Stereotypically Feminine Practice Can Help Us Understand Spatial Skills and Improve Spatial Learning G. Bennett-Pierre & E. Gunderson https://doi.org/10.1007/s11199-022-01340-y
- Geology and inquiry-based learning. The case of sliding rocks J. Roldán Muñoz https://doi.org/10.1080/20004508.2023.2267266
- Spatially and temporally distributed data foraging decisions in disciplinary field science C. Wilson et al. https://doi.org/10.1186/s41235-021-00296-z
- Effective dipole extraction from noisy magnetic field image data using deep convolutional neural networks J. Feinstein et al. https://doi.org/10.1063/5.0299028
- An interactive sequential-decision benchmark from geosteering S. Alyaev et al. https://doi.org/10.1016/j.acags.2021.100072
- Deformation history of a foredeep basin during the incorporation of its deposits within an advancing orogenic wedge: The case of the Oligocene-Early Miocene Macigno Costiero Formation, southern Tuscany, northern Apennines, Italy E. Tavarnelli et al. https://doi.org/10.1016/j.jsg.2021.104347
19 citations as recorded by crossref.
- Towards a definition of a spatial geochemical compatibility: workflow, validation, and application M. Zuccolini et al. https://doi.org/10.1016/j.apgeochem.2024.106260
- The application of Tobler's hiking function in data-driven traverse modelling for planetary exploration A. Goodwin et al. https://doi.org/10.1016/j.actaastro.2024.12.005
- Explicit Instruction of Scientific Uncertainty in an Undergraduate Geoscience Field-Based Course K. Bateman et al. https://doi.org/10.1007/s11191-022-00345-z
- 3D multiple-point geostatistical simulation of joint subsurface redox and geological architectures R. Madsen et al. https://doi.org/10.5194/hess-25-2759-2021
- Fracture and fault characterization in the era of artificial intelligence C. Li & Y. Chen https://doi.org/10.1016/j.earscirev.2026.105504
- Cognitive Bias Mitigation in Executive Decision-Making: A Data-Driven Approach Integrating Big Data Analytics, AI, and Explainable Systems L. Theodorakopoulos et al. https://doi.org/10.3390/electronics14193930
- Spatial uncertainty constraints reduce overfitting for potential field geophysical inversion M. Lindsay et al. https://doi.org/10.1093/gji/ggag133
- Multi‐scenario Interpretations From Sparse Fault Evidence Using Graph Theory and Geological Rules G. Godefroy et al. https://doi.org/10.1029/2020JB020022
- Antarctic Sedimentary Basins and Their Influence on Ice‐Sheet Dynamics A. Aitken et al. https://doi.org/10.1029/2021RG000767
- Mapping hydrodynamic structure with sparse or no well data S. Stewart https://doi.org/10.1144/geoenergy2023-028
- Introduction: Handling uncertainty in the geosciences: identification, mitigation and communication L. Pérez-Díaz et al. https://doi.org/10.5194/se-11-889-2020
- Examining Rock Engineering Knowledge through a Philosophical Lens D. Elmo et al. https://doi.org/10.3390/geosciences12040174
- Understanding Human Dynamic Sampling Objectives to Enable Robot-assisted Scientific Decision Making S. Liu et al. https://doi.org/10.1145/3623383
- Fiber Arts Require Spatial Skills: How a Stereotypically Feminine Practice Can Help Us Understand Spatial Skills and Improve Spatial Learning G. Bennett-Pierre & E. Gunderson https://doi.org/10.1007/s11199-022-01340-y
- Geology and inquiry-based learning. The case of sliding rocks J. Roldán Muñoz https://doi.org/10.1080/20004508.2023.2267266
- Spatially and temporally distributed data foraging decisions in disciplinary field science C. Wilson et al. https://doi.org/10.1186/s41235-021-00296-z
- Effective dipole extraction from noisy magnetic field image data using deep convolutional neural networks J. Feinstein et al. https://doi.org/10.1063/5.0299028
- An interactive sequential-decision benchmark from geosteering S. Alyaev et al. https://doi.org/10.1016/j.acags.2021.100072
- Deformation history of a foredeep basin during the incorporation of its deposits within an advancing orogenic wedge: The case of the Oligocene-Early Miocene Macigno Costiero Formation, southern Tuscany, northern Apennines, Italy E. Tavarnelli et al. https://doi.org/10.1016/j.jsg.2021.104347
Saved (final revised paper)
Latest update: 28 May 2026
Short summary
In this paper, we outline the key insights from decision-making research about how, when faced with uncertainty, humans constrain decisions through the use of heuristics (rules of thumb), making them vulnerable to systematic and suboptimal decision biases. We also review existing strategies to debias decision-making that have applicability in the geosciences, giving special attention to strategies that make use of information technology and artificial intelligence.
In this paper, we outline the key insights from decision-making research about how, when faced...