Optimizing Gridding Parameters in a Parallel Multiscale Reservoir Characterization Approach
Abstract/Contents
- Abstract
- A method for history matching combined with unstructured non-uniform grids and grid optimization is proposed. History matching has a significant impact on reservoir characterization. Conditioning realizations to well log and seismic alone is not sufficient for reducing the uncertainties in the production forecasts. It is now well understood that the integration of production history into geostatistical models is necessary to obtain a reliable reservoir description. The major challenge of this data integration problem lies in the fact that each datum has its own area of coverage and resolution. Fine scale heterogeneities can have significant effects on the flow response. Large numbers of grid blocks are required to depict such fine scale heterogeneities. However, commercial flow simulators can not handle such huge numbers of grid cells. The method used to attack this problem is upscaling the fine scale geostatistical models to a coarse scale, and then performing the flow simulations on this coarse model which requires less CPU demand. This upscaling can be done uniformly or non-uniformly. In this study we propose utilizing a flexible gridding algorithm 3DDEGA1 (1990, Garcia et al.). This algorithm allows flexible corner point geometry grid generation which is to be used for the coarse model. The unstructured corner point geometries can capture the curvilinear shapes such as high perm sand channels in a clastic oil reservoir. 3DDEGA performs the upscaling by static (permeability) or dynamic (flow response) information or both. The 3DDEGA method aims at preserving the geology by minimizing the within block heterogeneities in a given coarse grid block. During the history matching process we utilize an optimization algorithm which optimizes the gridding parameters of 3DDEGA without performing full flow simulations. Approximating the actual flow model, a fast streamline simulation is used to minimize the mismatch between the flow responses of the fine scale and the corresponding coarse scale models. The applicability of this method is investigated through some realistic 2D and 3D synthetic reservoir models.
Description
| Type of resource | text |
|---|---|
| Date created | June 2004 |
Creators/Contributors
| Author | Karacali, Ozgur |
|---|---|
| Primary advisor | Caers, Jef K. |
| Degree granting institution | Stanford University, Department of Petroleum Engineering |
Subjects
| Subject | School of Earth Energy & Environmental Sciences |
|---|---|
| Genre | Thesis |
Bibliographic information
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Preferred citation
- Preferred Citation
- Karacali, Ozgur. (2004). Optimizing Gridding Parameters in a Parallel Multiscale Reservoir Characterization Approach. Stanford Digital Repository. Available at: https://purl.stanford.edu/gq442mg9885
Collection
Master's Theses, Doerr School of Sustainability
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