致密油藏水平井压裂后产能预测方法

PRODUCTIVITY PREDICTING METHOD OF THE FRACTURED HORIZONTAL WELLS IN THE TIGHT OIL RESERVOIRS

以松辽盆地南部红岗北水平井开发目标区扶余油层水平井压裂后各项参数为基础,首先采用灰色关联分析方法对扶余致密油藏压裂水平井产能参数的影响程度进行排序,优选出主要影响参数;然后对研究区压裂水平井进行模糊聚类分析,将研究区压裂水平井分成4类;最后将水平井分类结果与影响参数一起加入到BP神经网络输入端,以日产能指标为硬数据,建立预测压裂后水平井产能的神经网络模型,并利用检验数据对模型进行验证。结果表明,基于水平井类型控制的神经网络模型产能预测效果要优于传统神经网络模型,可以作为有效的水平井压裂后产能预测方法。

Based on all parameters of the fractured horizontal wells in Fuyu oil layers in the horizontal well development target block of North Honggang in South Songliao Basin,the method of grey relational analysis is adopted first to sequence the influence degrees of the productivity parameters of the fractured horizontal wells in the layers,and then the major impacting parameters are selected; secondly,the fuzzy clustering analysis is applied to categorize and research the wells in the study area into four kinds; finally the classified results and influencing parameters are input into BP neural network to built the neural network model to predict the horizontal wells' productivity after being fractured,and moreover the testing data are adopted to verify the model. The results show that the predicted effects of the neural network model based on the control of the types of the horizontal well are well better than those of the traditional neural network model,so the productivity predicting method for the fractured horizontal wells is proven to be effective.