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

Pakyuz-Charrier, Evren; Lindsay, Mark; Ogarko, Vitaliy; Giraud, Jeremie; Jessell, Mark

doi:https://doi.org/10.5194/se-9-385-2018

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

Data sets

Basic graben GeoModeller model and relevant MCUE outputs E. Pakyuz-Charrier https://doi.org/10.5281/zenodo.854730

Mansfield (Victoria, Australia) area original GeoModeller model and relevant MCUE outputs E. Pakyuz-Charrier and Intrepid Geophysics https://doi.org/10.5281/zenodo.848225

"GeoModeller API" Intrepid Geophysics|Home of GeoModeller, Intrepid, Jetstream and Sea-g|Gravity, Magnetics, Radiometrics, FTG Intrepid Geophysics http://www.intrepid-geophysics.com/ig/index.php?page=geomodeller-api

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.