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Articles | Volume 9, issue 2
Articles | Volume 9, issue 2
https://doi.org/10.5194/se-9-385-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/se-9-385-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 9, issue 2
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, Mark Lindsay, Vitaliy Ogarko, Jeremie Giraud, and Mark Jessell

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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.
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