计算机与现代化 ›› 2022, Vol. 0 ›› Issue (12): 60-66.
出版日期:
2023-01-04
发布日期:
2023-01-04
作者简介:
张晓东(1979—),男,黑龙江大庆人,讲师,硕士生导师,博士,研究方向:大数据分析,人工智能,E-mail: 1240902174@qq.com; 通信作者:王栩颖 (1997—),女,山东威海人,硕士研究生,研究方向:大数据分析,机器学习,E-mail: wangxuyingz@163.com; 秦子轩(1998—),男,硕士研究生,研究方向:大数据分析,E-mail: 1164010672@qq.com
基金资助:
Online:
2023-01-04
Published:
2023-01-04
摘要: 检泵周期是反映抽油机井工作情况的重要指标,准确预测检泵周期对提高油井产能和经济效益具有重要意义。针对油田检泵周期预测准确率低等问题,提出一种基于特征融合抽油机井检泵周期预测方法。该方法引入SVR提取油田数据的静态特征,利用卷积神经网络学习油田数据的动态特征,引入多模态压缩双线性池化对静态特征和动态特征进行融合,利用判别模型训练融合特征实现检泵周期的准确预测。实验结果验证了该模型的有效性和可行性。
张晓东, 王栩颖, 秦子轩. 基于特征融合的抽油机井检泵周期预测[J]. 计算机与现代化, 2022, 0(12): 60-66.
ZHANG Xiao-dong, WANG Xu-ying, QIN Zi-xuan. Pump Detection Period Predicting of Pump Well Based on Feature Fusion[J]. Computer and Modernization, 2022, 0(12): 60-66.
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