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Proper Orthogonal Decomposition-Based Method for Predicting Flow and Heat Transfer of Oil and Water in Reservoir
- Source :
- J Energy Resour Technol
- Publication Year :
- 2019
- Publisher :
- American Society of Mechanical Engineers, 2019.
-
Abstract
- Calculation process of some reservoir engineering problems involves several passes of full-order numerical reservoir simulations, and this makes it a time-consuming process. In this study, a fast method based on proper orthogonal decomposition (POD) was developed to predict flow and heat transfer of oil and water in a reservoir. The reduced order model for flow and heat transfer of oil and water in the hot water-drive reservoir was generated. Then, POD was used to extract a reduced set of POD basis functions from a series of “snapshots” obtained by a finite difference method (FDM), and these POD basis functions most efficiently represent the dynamic characteristics of the original physical system. After injection and production parameters are changed constantly, the POD basis functions combined with the reduced order model were used to predict the new physical fields. The POD-based method was approved on a two-dimensional hot water-drive reservoir model. For the example of this paper, compared with FDM, the prediction error of water saturation and temperature fields were less than 1.3% and 1.5%, respectively; what is more, it was quite fast, where the increase in calculation speed was more than 70 times.
- Subjects :
- 0303 health sciences
Renewable Energy, Sustainability and the Environment
020209 energy
Mechanical Engineering
Flow (psychology)
Physical system
Finite difference method
Energy Engineering and Power Technology
Basis function
02 engineering and technology
Mechanics
Research Papers
03 medical and health sciences
Fuel Technology
Point of delivery
Geochemistry and Petrology
Principal component analysis
Heat transfer
Reservoir engineering
0202 electrical engineering, electronic engineering, information engineering
030304 developmental biology
Mathematics
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- J Energy Resour Technol
- Accession number :
- edsair.doi.dedup.....6b75a392752c0981af42b961ecea3a78