多模型油藏闭环管理

 针对目前基于单一模型进行油藏闭环管理的局限性,结合油藏数值模拟技术,提出了一种基于多模型实现的油藏闭环管理方法。利用集合卡尔曼滤波(EnKF)法通过拟合实测数据对地质模型进行实时更新,并以更新后模型的经济净现值的期望值作为目标函数,通过随机扰动近似算法(SPSA)进行油田生产优化。计算实例显示,应用该方法进行油藏闭环管理能够降低油藏模型的不确定性,给出更为合理的地质模型估计,所得控制方案相比常规方案明显改善了注水开发效果、提高了经济效益、降低了开发的风险性。

Closed-loop Reservoir Management with Multi-geological Models

In view of the limitations of performing closed-loop reservoir management with single model, a novel approach for closed-loop management based on multi-geological realizations is proposed with the combination of reservoir numerical simulation technique. A set of realizations are sequentially updated by the ensemble kalman filter (EnKF) method to honor the measurement data. Then taking the expected NPV of the updated realizations as the objective function, the production optimization process is implemented by the simultaneous perturbation stochastic approximation (SPSA) algorithm. The example application indicates that the proposed method for closed-loop reservoir management can decrease the actual geological uncertainty and provide a reasonable estimate reservoir model, and the calculated optimal controls significantly improve the effect of waterflooding with a higher economic benefits and lower developing risks than normal operation strategies.