王 通,陈延彬.基于改进生成对抗网络的动液面建模数据扩充[J].电子测量与仪器学报,2023,37(2):99-109 |
基于改进生成对抗网络的动液面建模数据扩充 |
Dynamic liquid level modeling data augmentation based onimproved generative adversarial networks |
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DOI: |
中文关键词: 数据扩充 动液面 生成对抗网络 |
英文关键词:data augmentation dynamic liquid level generative adversarial networks |
基金项目:国家自然科学基金(62173073)项目资助 |
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中文摘要: |
针对采用生成对抗网络进行油井生产参数数据生成时,部分生成数据不符合油井生产过程特性,导致动液面软测量建
模质量不高的问题,提出一种基于专家诊断的生成对抗网络油井动液面软测量建模数据扩充方法。 在判别器基于真实数据与
生成数据得到原始损失值后,结合油井生产的机理过程对生成数据的合理性进行专家诊断,检测判别器判别结果。 对错误结果
进行补偿并加入生成器与判别器的损失函数中进行后续对抗训练,从而生成较优的符合油井生产过程特性的动液面软测量建
模样本数据。 通过仿真实验,生成数据补充到软测量建模的训练数据中能够提高动液面的预测精度,均方根误差降低了
5. 99%。 表明加入专家诊断模块后生成器生成数据质量更高,能够更好地满足油田生产需求。 |
英文摘要: |
In using generative adversarial networks to generate oil well production parameter data, this method causes the inconsistency
between partially generated data characteristics and characteristics of oil well production process, which leads to the low quality of soft
sensor modeling of dynamic liquid level. This paper presents an expansion method of soft sensor modeling data of oil well dynamic liquid
level based on expert diagnosis-wasserstein generative adversarial networks. After the discriminator obtains the original loss value based
on the real data and generated data, the rationality of the generated data is diagnosed by the expert diagnosis module in combination with
the mechanism process of oil well production, and the discriminator judgment results are detected. The error results are compensated and
added to the loss functions of the generator and discriminator for subsequent confrontation training, thus the better soft sensor modeling
sample data of dynamic liquid level which consistent with the characteristics of oil well production process is generated. Through
simulation experiments, the prediction accuracy of the dynamic liquid level improved by adding the generated data to the training data of
soft sensor modeling, and the root mean square error is reduced by 5. 99%. It shows that the data generated by the generator after adding
the expert diagnosis module has higher quality and can better meet the production needs of the oilfield. |
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