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基于改进U-Net卷积神经网络的储层预测

陈康 狄贵东 张佳佳 周游 吴尧 张广智

陈康, 狄贵东, 张佳佳, 周游, 吴尧, 张广智. 基于改进U-Net卷积神经网络的储层预测[J]. CT理论与应用研究, 2021, 30(4): 403-416. doi: 10.15953/j.1004-4140.2021.30.04.01
引用本文: 陈康, 狄贵东, 张佳佳, 周游, 吴尧, 张广智. 基于改进U-Net卷积神经网络的储层预测[J]. CT理论与应用研究, 2021, 30(4): 403-416. doi: 10.15953/j.1004-4140.2021.30.04.01
CHEN Kang, DI Guidong, ZHANG Jiajia, ZHOU You, WU Yao, ZHANG Guangzhi. Reservoir Prediction Based on Improved U-Net Convolutional Neural Network[J]. CT Theory and Applications, 2021, 30(4): 403-416. doi: 10.15953/j.1004-4140.2021.30.04.01
Citation: CHEN Kang, DI Guidong, ZHANG Jiajia, ZHOU You, WU Yao, ZHANG Guangzhi. Reservoir Prediction Based on Improved U-Net Convolutional Neural Network[J]. CT Theory and Applications, 2021, 30(4): 403-416. doi: 10.15953/j.1004-4140.2021.30.04.01

基于改进U-Net卷积神经网络的储层预测

doi: 10.15953/j.1004-4140.2021.30.04.01
基金项目: 

国家自然科学基金(42074136;41674130);中央高校基础研究业务费专项基金(18CX02061A);中国石油科技创新基金(2016D-5007-0301);中国石油科学研究与技术开发项目(2017D-3504)。

详细信息
    作者简介:

    陈康,男,中国石油西南油气田分公司勘探开发研究院工程师,主要从事地震资料解释与储层预测研究工作,E-mail:chenkang01@petrochina.com.cn;张佳佳*,男,中国石油大学(华东)地球科学与技术学院副教授,主要从事地震岩石物理及储层预测方面工作,E-mail:zhangjj@upc.edu.cn。

  • 中图分类号: TP183;P631

Reservoir Prediction Based on Improved U-Net Convolutional Neural Network

  • 摘要: 传统的U-Net卷积神经网络大多存在深层网络梯度消失的问题。本文在U-Net卷积神经网络中加入残差模块,提出了一种改进U-Net卷积神经网络。残差模块保证了U-Net卷积神经网络在误差反向传播过程中梯度的存在,在一定程度上可以缓解梯度消失的问题。最后将改进U-Net卷积神经网络应用于实际储层预测中,实际数据测试结果表明基于改进U-Net卷积神经网络在岩性识别以及“甜点”预测上均能取得较好的效果。

     

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出版历程
  • 收稿日期:  2020-12-20
  • 网络出版日期:  2021-09-24

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