Optimization Techniques for History Matching Using Streamline-Based Geostatistical Constraints
Abstract/Contents
- Abstract
- History-matching can be used to enhance reservoir description and modeling. Field flow responses supply convoluted local information concerning rock properties, fluid properties, and rock-fluid interactions, that serve to refine reservoir models. Obtaining a match by adjusting the reservoir model under realistic constraints improves the predictive power of the technique. A first step towards predictive history matching consists in integration of available information, as constraints to the matching problem. Integrating geostatistical constraints with respect to the permeability field, for instance, bounds the search for reservoir models. Such history-matching methods improve the reservoir model, de.ned with geostatistics, and tested with streamline simulations. The search for the best reservoir model must be carried out with proper optimization tools, because of the ill-posedness of the problem. Stochastic search and multi-zone gradual deformation methods have been used to converge to a better permeability field description, honoring all prior geostatistical information. This method is validated by working on 3D synthetic fields, as well as on a real field.
Description
| Type of resource | text |
|---|---|
| Date created | June 2003 |
Creators/Contributors
| Author | Gross, Hervé |
|---|---|
| Primary advisor | Kovscek, Anthony R. |
| Degree granting institution | Stanford University, Department of Petroleum Engineering |
Subjects
| Subject | School of Earth Energy & Environmental Sciences |
|---|---|
| Subject | Stanford University Petroleum Research Institute |
| Genre | Thesis |
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Preferred citation
- Preferred Citation
- Gross, Hervé. (2003). Optimization Techniques for History Matching Using Streamline-Based Geostatistical Constraints. Stanford Digital Repository. Available at: https://purl.stanford.edu/fh029yr7753
Collection
Master's Theses, Doerr School of Sustainability
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