首页> 外文会议> >Chaotic Neural Network Model for Output Prediction of Polymer Flooding
【24h】

Chaotic Neural Network Model for Output Prediction of Polymer Flooding

机译:聚合物驱产量预测的混沌神经网络模型

获取原文

摘要

In order to predict the dynamic targets of water ratio and oil output in situation of polymer flooding accurately, Chaotic Neural Network(CNN) prediction model on output varied rules of polymer flooding was established, the method of predict water cut and oil output is found, and the prediction results are analyzed. The results show that the prediction relative error of accumulative oil output on polymer flooding is 3.25 percent, which is much lower than the required prediction error.
机译:为了准确预测聚合物驱情况下水比和出油量的动态目标,建立了基于聚合物驱产量变化规律的混沌神经网络(CNN)预测模型,找到了预测含水率和出油量的方法,并分析了预测结果。结果表明,聚合物驱的累计产油量预测相对误差为3.25%,远低于要求的预测误差。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号