Identification of aquifer heterogeneity through inverse methods
The paper underlines the contributions of Ghislain deMarsily (GdM) to the identification of aquifers heterogeneity using inverse methods mainly for modeling subsurface flow. Inverse methods require an objective function to express the goodness of fit of the chosen model, a parameterization to describe the spatial distribution of model parameters, and aminimization algorithm. The resulting inverse problem, which consists in seeking model parameters' values that render model outputs close to the observations, is usually unstable. GdM developed seminal ideas for the two key inversion issues that are: to stabilize the inverse problem through regularization, and to parameterize it to reproduce the natural heterogeneity of the subsurface with a limited number of parameters. GdM conducted pioneering works that are the basis of current parameterization methods relying upon adaptive zonation and/or interpolation based on pilot points. We take here the opportunity to highlight the GdM's contributions inspiring currently used techniques.
| Main Authors: | , , |
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| Format: | artículo biblioteca |
| Published: |
Académie des Sciences. Institut de France
2022
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| Online Access: | http://hdl.handle.net/10261/309373 |
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| Summary: | The paper underlines the contributions of Ghislain deMarsily (GdM) to the identification of aquifers heterogeneity using inverse methods mainly for modeling subsurface flow. Inverse methods require an objective function to express the goodness of fit of the chosen model, a parameterization to describe the spatial distribution of model parameters, and aminimization algorithm. The resulting inverse problem, which consists in seeking model parameters' values that render model outputs close to the observations, is usually unstable. GdM developed seminal ideas for the two key inversion issues that are: to stabilize the inverse problem through regularization, and to parameterize it to reproduce the natural heterogeneity of the subsurface with a limited number of parameters. GdM conducted pioneering works that are the basis of current parameterization methods relying upon adaptive zonation and/or interpolation based on pilot points. We take here the opportunity to highlight the GdM's contributions inspiring currently used techniques. |
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