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.

Model code and software

Supporting data and code for: Efficiency and robustness in Monte Carlo sampling for 3-D geophysical inversions with Obsidian v0.1.2: Setting up for success R. Scalzo, D. Kohn, S. O'Callaghan, L. McCalman, and B. Simpson-Young https://doi.org/10.5281/zenodo.2580422

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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.