A new optimization method for steam-liquid level intelligent control model in oil sands steam-assisted gravity drainage (SAGD) process

作者：Liang Guangyue^*; Liu Shangqi; Shen Pingping; Liu Yang; Luo Yanyan

来源：Petroleum Exploration and Development, 2016, 43(2): 301-307.

DOI：10.1016/s1876-3804(16)30034-9

• oil sand
• SAGD
• steam-liquid level
• steam chamber
• intelligent control model
• proportional-integral-derivative (PID) control function
• coefficients optimization method

In order to prevent steam breakthrough and improve thermal efficiency in the process of SAGD development of oil sands by real-time adjustment on injection-production temperature difference (Subcool) according to the growth situations of steam chamber along the wellbore, a series of studies were conducted on coefficients optimization of proportional-integral-derivative (PID) control equation for the steam-liquid level intelligent control model. According to heat conservation and material balance principles, a mathematical model for determining the coefficients of PID control equation was established with the liquid pool in the steam chamber as the objective and the Subcool as the control target. The intelligent steam-liquid level control model suitable for M Block in Canada was optimized using this mathematical model, together with the Ziegler-Nichols (Z-N) tuning method. Application effects of these PID control strategies were evaluated by reservoir numerical simulation. The results show, when the combination of PID proportional, integral and derivative coefficients are used, the time scale for Subcool to evolve to the set point is minimized and the convergence speed and robustness are improved. Compared with conventional steam injection process, the intelligent steam injection based on the PID coefficient optimization method is much better in the uniform conformance of steam chambers along the wellbore, higher in oil production and lower in steam-oil ratio (SOR). Both the model optimization method and the Ziegler-Nichols tuning method are similar in simulation results. Based on the former method, however, the optimization process of the intelligent control model is simplified greatly, so it can be implemented more conveniently and rapidly.

• 出版日期2016-4
• 单位中国石油天然气股份有限公司勘探开发研究院