Articles | Volume 12, issue 7
Geosci. Model Dev., 12, 2941–2960, 2019
https://doi.org/10.5194/gmd-12-2941-2019
Geosci. Model Dev., 12, 2941–2960, 2019
https://doi.org/10.5194/gmd-12-2941-2019

Development and technical paper 15 Jul 2019

Development and technical paper | 15 Jul 2019

Efficiency and robustness in Monte Carlo sampling for 3-D geophysical inversions with Obsidian v0.1.2: setting up for success

Richard Scalzo et al.

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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Anna Mirena Feist-Polner on behalf of the Authors (14 Jun 2019)  Author's response
ED: Publish as is (15 Jun 2019) by Thomas Poulet
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Short summary
Producing 3-D models of structures under the Earth's surface based on sensor data is a key problem in geophysics (for example, in mining exploration). There may be multiple models that explain the data well. We use the open-source Obsidian software to look at the efficiency of different methods for exploring the model space and attaching probabilities to models, leading to less biased results and a better idea of how sensor data interact with geological assumptions.