An approximate dynamic programming method for the optimal control of Alkai-Surfactant-Polymer flooding. (April 2018)
- Record Type:
- Journal Article
- Title:
- An approximate dynamic programming method for the optimal control of Alkai-Surfactant-Polymer flooding. (April 2018)
- Main Title:
- An approximate dynamic programming method for the optimal control of Alkai-Surfactant-Polymer flooding
- Authors:
- Ge, Yulei
Li, Shurong
Chang, Peng - Abstract:
- Highlights: An ADP idea is presented to solve the optimal control of ASP flooding. The Actor-Critic algorithm is adopted to search the optimal injection strategy. A linear basis function construction method is introduced. The TD error is used to train and predict the control and value function. The solving effect is good on the optimal control of ASP flooding. Abstract: Since the complexity, coupling, distributed parameter, etc. of alkali-surfactant-polymer (ASP) flooding, common optimization methods cannot acquire the optimal solutions well. This paper brings an optimal control method for ASP flooding based on approximate dynamic programming (ADP). At first, take the net present value (NPV) as the performance index. Then the Actor-Critic algorithm based on gradient descent method is adopted to get the optimal injection strategy, in which Actor and Critic are used to approximate the control and value function, respectively. To improve the approximation performance, the linear approximation basis function based on system characteristic is constructed. Furthermore, to train and predict the control and value function in next step, a temporal difference (TD) learning algorithm is introduced to update the weight coefficients. Then, the control in ADP is generated according to the Gauss function and its weight is updated according to the sigmoid function of TD error, so that the optimal control can be searched. At last, the enhanced oil recovery problem of ASP flooding with fourHighlights: An ADP idea is presented to solve the optimal control of ASP flooding. The Actor-Critic algorithm is adopted to search the optimal injection strategy. A linear basis function construction method is introduced. The TD error is used to train and predict the control and value function. The solving effect is good on the optimal control of ASP flooding. Abstract: Since the complexity, coupling, distributed parameter, etc. of alkali-surfactant-polymer (ASP) flooding, common optimization methods cannot acquire the optimal solutions well. This paper brings an optimal control method for ASP flooding based on approximate dynamic programming (ADP). At first, take the net present value (NPV) as the performance index. Then the Actor-Critic algorithm based on gradient descent method is adopted to get the optimal injection strategy, in which Actor and Critic are used to approximate the control and value function, respectively. To improve the approximation performance, the linear approximation basis function based on system characteristic is constructed. Furthermore, to train and predict the control and value function in next step, a temporal difference (TD) learning algorithm is introduced to update the weight coefficients. Then, the control in ADP is generated according to the Gauss function and its weight is updated according to the sigmoid function of TD error, so that the optimal control can be searched. At last, the enhanced oil recovery problem of ASP flooding with four injection wells and nine production wells is solved by the proposed method to test the effect of proposed method. … (more)
- Is Part Of:
- Journal of process control. Volume 64(2018)
- Journal:
- Journal of process control
- Issue:
- Volume 64(2018)
- Issue Display:
- Volume 64, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 64
- Issue:
- 2018
- Issue Sort Value:
- 2018-0064-2018-0000
- Page Start:
- 15
- Page End:
- 26
- Publication Date:
- 2018-04
- Subjects:
- ASP flooding -- Approximate dynamic programming -- Actor-Critic algorithm -- Temporal difference learning algorithm -- TD error -- Linear basis function
Process control -- Periodicals
Fabrication -- Contrôle -- Périodiques
Process control
Periodicals
Electronic journals
660.281 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09591524 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.jprocont.2018.01.010 ↗
- Languages:
- English
- ISSNs:
- 0959-1524
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5042.645000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 6225.xml