SUN Xian-hang, XU Ming-hai, GONG Liang, JIA Xin-xin, ZHOU Hui. A Fast POD-Based Method for Predicting Oil and Water Flow in Water-Drive Reservoir[J]. Applied Mathematics and Mechanics, 2015, 36(12): 1228-1237. doi: 10.3879/j.issn.1000-0887.2015.12.002
Citation: SUN Xian-hang, XU Ming-hai, GONG Liang, JIA Xin-xin, ZHOU Hui. A Fast POD-Based Method for Predicting Oil and Water Flow in Water-Drive Reservoir[J]. Applied Mathematics and Mechanics, 2015, 36(12): 1228-1237. doi: 10.3879/j.issn.1000-0887.2015.12.002

A Fast POD-Based Method for Predicting Oil and Water Flow in Water-Drive Reservoir

doi: 10.3879/j.issn.1000-0887.2015.12.002
Funds:  The National Natural Science Foundation of China(51276199); The National Science and Technology Major Project of China(2011ZX05017_004_HZ01)
  • Received Date: 2015-06-11
  • Rev Recd Date: 2015-09-30
  • Publish Date: 2015-12-15
  • A fast method based on the proper orthogonal decomposition (POD) technique for predicting oil and water flow in water-drive reservoir was proposed. The reduced order model of oil and water flow in water-drive reservoir was generated with the POD. An ensemble of 100 samples of pressure and water saturation snapshots in the time range of [0 d, 500 d] with an interval step of 5 d for the 2D water-drive reservoir model was obtained through numerical reservoir simulation, and the POD was applied to extract a reduced set of POD basis functions from these snapshots. After the injection and production parameters were changed continuously, the obtained POD basis functions combined with the reduced order model were used to predict the new physical fields. The research results show that fast and accurate predictions can be achieved with the proposed POD-based method, for the given example, the prediction errors of pressure and water saturation are less than 1.2% and 1.5%, respectively. What’s more, this POD-based method is 50 times faster in calculation than the traditional numerical reservoir simulation.
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