Journal article
A Hierarchical Multigrid Method for Oil Production Optimization
Department of Applied Mathematics and Computer Science, Technical University of Denmark1
Scientific Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark2
Center for Energy Resources Engineering, Centers, Technical University of Denmark3
Centre for oil and gas – DTU, Technical University of Denmark4
The large-scale optimization problems that arise from oil production optimization under geological uncertainty of industry-scale reservoir models poses a challenge even for modern computer architecture. In combination with ensemble-based methods for production optimization under uncertainty, gradient-based optimization algorithms provides a powerful approach that ensures a high convergence rate.
However, the spatial resolution and complexity of typical industry-scale models has a significant computational impact that renders the optimization problem intractable. To reduce the computational burden model reduction is essential. In this paper, we introduce a grid coarsening method that maintains the overall dynamics of the flow, by preserving the geological features of the model.
Furthermore, we present a hierarchical multigrid method for oil production optimization. The method utilizes a hierarchy of coarse level models based on the high-fidelity model. We present the workflow of the hierarchical multigrid optimization procedure and a numerical example that demonstrates the application of oil production optimization on a synthetic reservoir. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd.
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| Language: | English |
|---|---|
| Year: | 2019 |
| Pages: | 492-497 |
| Proceedings: | 12th IFAC Symposium on Dynamics and Control of Process Systems |
| ISSN: | 24058963 and 24058971 |
| Types: | Journal article |
| DOI: | 10.1016/j.ifacol.2019.06.110 |
| ORCIDs: | Hørsholt, Steen , Nick, Hamid and Jørgensen, John Bagterp |
