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Volume 6, Issue 1
Challenges and Technologies in Reservoir Modeling

Larisa V. Branets, Sartaj S. Ghai, Stephen L. Lyons & Xiao-Hui Wu

Commun. Comput. Phys., 6 (2009), pp. 1-23.

Published online: 2009-06

[An open-access article; the PDF is free to any online user.]

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  • Abstract

Reservoir modeling is playing an increasingly important role in developing and producing hydrocarbon reserves. In this paper, we provide a brief overview of some main challenges in reservoir modeling, i.e., accurate and efficient modeling of complex reservoir geometry and heterogeneous reservoir properties. We then present modeling techniques we recently developed in addressing these challenges, including a method for generating constrained Voronoi grids and a generic global scale-up method. We focus on the Voronoi gridding method, which is based on a new constrained Delaunay triangulation algorithm and a rigorous method of adapting Voronoi grids to piecewise linear constraints. The global scale-up method based on generic flows is briefly described. Numerical examples are provided to demonstrate the techniques and the advantage of combining them in constructing accurate and efficient reservoir models.

  • AMS Subject Headings

37M05, 76S05, 86A60, 65M50, 65N50

  • Copyright

COPYRIGHT: © Global Science Press

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@Article{CiCP-6-1, author = {Larisa V. Branets, Sartaj S. Ghai, Stephen L. Lyons and Xiao-Hui Wu}, title = {Challenges and Technologies in Reservoir Modeling}, journal = {Communications in Computational Physics}, year = {2009}, volume = {6}, number = {1}, pages = {1--23}, abstract = {

Reservoir modeling is playing an increasingly important role in developing and producing hydrocarbon reserves. In this paper, we provide a brief overview of some main challenges in reservoir modeling, i.e., accurate and efficient modeling of complex reservoir geometry and heterogeneous reservoir properties. We then present modeling techniques we recently developed in addressing these challenges, including a method for generating constrained Voronoi grids and a generic global scale-up method. We focus on the Voronoi gridding method, which is based on a new constrained Delaunay triangulation algorithm and a rigorous method of adapting Voronoi grids to piecewise linear constraints. The global scale-up method based on generic flows is briefly described. Numerical examples are provided to demonstrate the techniques and the advantage of combining them in constructing accurate and efficient reservoir models.

}, issn = {1991-7120}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/cicp/7669.html} }
TY - JOUR T1 - Challenges and Technologies in Reservoir Modeling AU - Larisa V. Branets, Sartaj S. Ghai, Stephen L. Lyons & Xiao-Hui Wu JO - Communications in Computational Physics VL - 1 SP - 1 EP - 23 PY - 2009 DA - 2009/06 SN - 6 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/cicp/7669.html KW - Reservoir modeling, grid generation, grid adaptation, global scale-up. AB -

Reservoir modeling is playing an increasingly important role in developing and producing hydrocarbon reserves. In this paper, we provide a brief overview of some main challenges in reservoir modeling, i.e., accurate and efficient modeling of complex reservoir geometry and heterogeneous reservoir properties. We then present modeling techniques we recently developed in addressing these challenges, including a method for generating constrained Voronoi grids and a generic global scale-up method. We focus on the Voronoi gridding method, which is based on a new constrained Delaunay triangulation algorithm and a rigorous method of adapting Voronoi grids to piecewise linear constraints. The global scale-up method based on generic flows is briefly described. Numerical examples are provided to demonstrate the techniques and the advantage of combining them in constructing accurate and efficient reservoir models.

Larisa V. Branets, Sartaj S. Ghai, Stephen L. Lyons and Xiao-Hui Wu. (2009). Challenges and Technologies in Reservoir Modeling. Communications in Computational Physics. 6 (1). 1-23. doi:
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