第 31 卷 第 8 期 电子测量与仪器学报 Vol. 31 No. 8 · production，dynamic and changing working conditions during operations may lead to failure of the soft sensor model． In order to solve this problem，a small amount of patrol-measuring data of the dynamic liquid levelis used to evaluate the original model，and then the similarity principle is used to add new data on the basis of the original model． And on this basis the weight of the new data is used to update the weak learning machine to become the strong learning machine model to dynamically adapt to the new production conditions． The simulation results using the real operation data of the oil well show that the proposed method has strong adaptive ability for fluctuation in production and can improve the generalization ability and the prediction accuracy of the soft sensor model． Keywords�ensemble learning algorithm� dynamic modeling�error rate� dynamic liquid level� generalization ability 到有效应用，以至于动液面数据无法实时准确测量，导致 0 引 言 油田生产过程中措施调整滞后，油井长期处在非最佳工 作状态，工程人员利用井下静态参数、示功图数据、井口 油田生产过程中地下环境复杂，传统传感器无法得 压力等可测参数结合机理过程计算动液面，但过程中无 收稿日期�2017-02
