Articles | Volume 9, issue 2
Solid Earth, 9, 385–402, 2018
https://doi.org/10.5194/se-9-385-2018
Solid Earth, 9, 385–402, 2018
https://doi.org/10.5194/se-9-385-2018
Method article
06 Apr 2018
Method article | 06 Apr 2018

Monte Carlo simulation for uncertainty estimation on structural data in implicit 3-D geological modeling, a guide for disturbance distribution selection and parameterization

Evren Pakyuz-Charrier et al.

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Cited articles

Aldiss, D. T., Black, M. G., Entwisle, D. C., Page, D. P., and Terrington, R. L.: Benefits of a 3-D geological model for major tunnelling works: an example from Farringdon, east-central London, UK, Q. J. Eng. Geol. Hydroge., 45, 405–414, https://doi.org/10.1144/qjegh2011-066, 2012.
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Bagchi, P.: Bayesian analysis of directional data, University of Toronto, Ottawa, Ont: National Library of Canada, 1987.
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Short summary
MCUE is a method that produces probabilistic 3-D geological models by sampling from distributions that represent the uncertainty of the initial input dataset. This process generates numerous plausible datasets used to produce a range of statistically plausible 3-D models which are combined into a single probabilistic model. In this paper, improvements to distribution selection and parameterization for input uncertainty are proposed.