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| Content Provider | Springer Nature Link |
|---|---|
| Author | Aansen, Sigurd Ivar Eydiv, Dmitry |
| Copyright Year | 2006 |
| Abstract | A method for multiscale parameter estimation with application to reservoir history matching is presented. Starting from a given fine-scale model, coarser models are generated using a global upscaling technique where the coarse models are tuned to match the solution of the fine model. Conditioning to dynamic data is done by history-matching the coarse model. Using consistently the same resolution both for the forward and inverse problems, this model is successively refined using a combination of downscaling and history matching until model-matching dynamic data are obtained at the finest scale. Large-scale corrections are obtained using fast models, which, combined with a downscaling procedure, provide a better initial model for the final adjustment on the fine scale. The result is thus a series of models with different resolution, all matching history as good as possible with this grid. Numerical examples show that this method may significantly reduce the computational effort and/or improve the quality of the solution when achieving a fine-scale match as compared to history-matching directly on the fine scale. |
| Starting Page | 97 |
| Ending Page | 117 |
| Page Count | 21 |
| File Format | |
| ISSN | 14200597 |
| Journal | Computational Geosciences |
| Volume Number | 10 |
| Issue Number | 1 |
| e-ISSN | 15731499 |
| Language | English |
| Publisher | Springer Netherlands |
| Publisher Date | 2006-03-23 |
| Publisher Place | Dordrecht |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | parameter estimation history matching multiscale Soil Science & Conservation Hydrogeology Geotechnical Engineering Mathematical Modeling and Industrial Mathematics |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computers in Earth Sciences Computational Theory and Mathematics Computer Science Applications Computational Mathematics |
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