Articles | Volume 23, issue 1
https://doi.org/10.5194/hess-23-351-2019
https://doi.org/10.5194/hess-23-351-2019
Research article
 | 
21 Jan 2019
Research article |  | 21 Jan 2019

Contaminant source localization via Bayesian global optimization

Guillaume Pirot, Tipaluck Krityakierne, David Ginsbourger, and Philippe Renard

Model code and software

gpirot/BGICLP v1.0, Benchmark Generator Inspired by Contaminant Localization Problem G. Pirot https://doi.org/10.5281/zenodo.2476286

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Short summary
To localize the source of a contaminant in the subsurface, based on concentration observations at some wells, we propose to test different possible locations and minimize the misfit between observed and simulated concentrations. We use a global optimization technique that relies on an expected improvement criterion, which allows a good exploration of the parameter space, avoids the trapping of local minima and quickly localizes the source of the contaminant on the presented synthetic cases.