Optimal Model-Based Reservoir Management with Model Parameter Uncertainty Updates

摘要：

The objective of this work is to manage water flooding of a reservoir to achieve optimal oil production by employing an optimal model-based control framework that uses uncertain parameter updating and a particular reduced-order model. A Markov chain Monte Carlo method is used to update the proposed distributions of the uncertain parameters. To avoid excessive simulations of the complex reservoir model, the techniques of partial least square regression and the Karhunen-Lo` eve expansion are used to find the relationships between the uncertain parameters and the system state. To demonstrate this approach, the optimal control of an oil producing reservoir is compared against an uncontrolled reservoir.

作者: Yingying Chen Karlene A. Hoo

作者单位: Chemical Engineering, Texas Tech University,Lubbock, TX 79416-3121, USA,

会议类型: 国际会议

会议名称: 2011 International Symposium on Advanced Control of Industrial Processes(2011工业过程先进控制技术国际研讨会)

会议地点: 杭州

会议语种:英文

页码: 439-444

在线出版日期: 2011-05-01（万方平台首次上网日期，不代表论文的发表时间）