致密低渗油藏压裂井网气驱深度学习预测模型
TE341%TE348; 压裂井网气驱将油藏压裂与注气井网驱油结合,是当前致密低渗油藏提高采收率有效技术之一.水力裂缝及多相流动复杂性,使得基于精细油藏数值模拟的压裂井网气驱效果预测变得困难且耗时.提出一种基于均方根传播(root mean square propagation,RMSProp)深度学习的压裂井网气驱效果预测方法.通过建立压裂直井/水平井混合井网气驱数值模拟模型,引入高斯函数定量表征压裂水平井多级裂缝分布特征.利用正交试验筛选试验样本方案,自主编程实现数值模拟结果自动提取与数据处理,建立致密低渗油藏压裂井网气驱样本数据库.基于随机森林算法,筛选油藏地质、裂缝、生产等关键参数重要...
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| Published in | 深圳大学学报（理工版） Vol. 39; no. 5; pp. 559 - 566 |
|---|---|
| Main Authors | , , , , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
中国石油大学(华东)石油工程学院,山东青岛266580%中国石油塔里木油田实验检测研究院油气分析测试中心,新疆库尔勒841009
01.09.2022
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1000-2618 |
| DOI | 10.3724/SP.J.1249.2022.05559 |
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| Abstract | TE341%TE348; 压裂井网气驱将油藏压裂与注气井网驱油结合,是当前致密低渗油藏提高采收率有效技术之一.水力裂缝及多相流动复杂性,使得基于精细油藏数值模拟的压裂井网气驱效果预测变得困难且耗时.提出一种基于均方根传播(root mean square propagation,RMSProp)深度学习的压裂井网气驱效果预测方法.通过建立压裂直井/水平井混合井网气驱数值模拟模型,引入高斯函数定量表征压裂水平井多级裂缝分布特征.利用正交试验筛选试验样本方案,自主编程实现数值模拟结果自动提取与数据处理,建立致密低渗油藏压裂井网气驱样本数据库.基于随机森林算法,筛选油藏地质、裂缝、生产等关键参数重要性特征,通过误差逆传播(back propagation,BP)神经网络、长短期记忆单元(long short-term memory,LSTM)、双向长短期记忆单元(bi-directional long short-term memory,BiLSTM)等深度学习算法,建立日产油、地层压力和采出程度预测代理模型,通过与油藏数值模拟对比,验证模型准确性.结果表明,BiLSTM算法在预测压裂井网气驱和压裂衰竭开发时效果最好.所提出的基于RMSProp的深度学习方法有效兼顾了模型实用性与精确性,为致密低渗油藏压裂井网气驱模拟预测提供了新途径. |
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| AbstractList | TE341%TE348; 压裂井网气驱将油藏压裂与注气井网驱油结合,是当前致密低渗油藏提高采收率有效技术之一.水力裂缝及多相流动复杂性,使得基于精细油藏数值模拟的压裂井网气驱效果预测变得困难且耗时.提出一种基于均方根传播(root mean square propagation,RMSProp)深度学习的压裂井网气驱效果预测方法.通过建立压裂直井/水平井混合井网气驱数值模拟模型,引入高斯函数定量表征压裂水平井多级裂缝分布特征.利用正交试验筛选试验样本方案,自主编程实现数值模拟结果自动提取与数据处理,建立致密低渗油藏压裂井网气驱样本数据库.基于随机森林算法,筛选油藏地质、裂缝、生产等关键参数重要性特征,通过误差逆传播(back propagation,BP)神经网络、长短期记忆单元(long short-term memory,LSTM)、双向长短期记忆单元(bi-directional long short-term memory,BiLSTM)等深度学习算法,建立日产油、地层压力和采出程度预测代理模型,通过与油藏数值模拟对比,验证模型准确性.结果表明,BiLSTM算法在预测压裂井网气驱和压裂衰竭开发时效果最好.所提出的基于RMSProp的深度学习方法有效兼顾了模型实用性与精确性,为致密低渗油藏压裂井网气驱模拟预测提供了新途径. |
| Author | 刘秀磊 朱璇 袁彬 赵明泽 郑贺 同元辉 |
| AuthorAffiliation | 中国石油大学(华东)石油工程学院,山东青岛266580%中国石油塔里木油田实验检测研究院油气分析测试中心,新疆库尔勒841009 |
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| Author_FL | ZHU Xuan YUAN Bin LIU Xiulei ZHENG He TONG Yuanhui ZHAO Mingze |
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| Keywords | 致密油藏 气驱 代理模型 井网 油田开发 深度学习 水平井 压裂 提高采收率 |
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| Publisher | 中国石油大学(华东)石油工程学院,山东青岛266580%中国石油塔里木油田实验检测研究院油气分析测试中心,新疆库尔勒841009 |
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| Snippet | TE341%TE348; 压裂井网气驱将油藏压裂与注气井网驱油结合,是当前致密低渗油藏提高采收率有效技术之一.水力裂缝及多相流动复杂性,使得基于精细油藏数值模拟的压裂井网气驱效果预测变得困难且耗时.提出一种基于均方根传播(root mean square... |
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| Title | 致密低渗油藏压裂井网气驱深度学习预测模型 |
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