石油学报 ›› 2021, Vol. 42 ›› Issue (4): 508-522.DOI: 10.7623/syxb202104008
人工智能在测井地层评价中的应用现状及前景
李宁1, 徐彬森1,2,3, 武宏亮1, 冯周1, 李雨生1, 王克文1, 刘鹏1
- 1. 中国石油勘探开发研究院 北京 100083;
2. 中国石油大学(北京)地球物理学院 北京 102249;
3. 中国石油大学(北京)人工智能学院 北京 102249
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收稿日期:2020-02-07修回日期:2021-01-20出版日期:2021-04-25发布日期:2021-05-11 -
通讯作者:徐彬森,男,1992年7月生,2015年获北京交通大学学士学位,现为中国石油大学(北京)博士研究生,主要从事云计算、机器学习、大数据、测井、人工智能等方面的研究。Email:xbs150@163.com -
作者简介:李宁,男,1958年7月生,1982年获华东石油学院学士学位,1989年获中国石油勘探开发研究院博士学位,现为中国石油勘探开发研究院教授级高级工程师、中国工程院院士、博士生导师,主要从事测井、软件等方面研究与教学工作。Email:ln@petrochina.com.cn -
基金资助:中国石油天然气集团公司科技项目（2018D-5010-16）和中国工程院战略咨询项目（2019-XZ-17）资助。
Application status and prospects of artificial intelligence in well logging and formation evaluation
Li Ning1, Xu Binsen1,2,3, Wu Hongliang1, Feng Zhou1, Li Yusheng1, Wang Kewen1, Liu Peng1
- 1. PetroChina Research Institute of Petroleum Exploration and Development, Beijing 100083, China;
2. College of Geophysics, China University of Petroleum, Beijing 102249, China;
3. College of Artificial Intelligence, China University of Petroleum, Beijing 102249, China
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Received:2020-02-07Revised:2021-01-20Online:2021-04-25Published:2021-05-11
摘要： 测井是求取储层物性参数、发现与评价油气藏、预测油气储量的重要手段。测井技术更新换代、测井技术种类发展多样化、测井数据管理方式多元化等多重因素导致测井信息具有测量种类多、数据量大和多源异构等大数据特征。人工智能技术的快速发展为解决测井地层评价中的多解性、不确定性等难题提供了新的思路和方法，"测井＋人工智能"也是一个亟待探索的新领域。在系统回顾人工智能在测井领域的研究现状和进展基础上，重点讨论了有监督机器学习和半监督机器学习、神经网络和深度学习等人工智能技术在测井曲线重构、岩相预测和物性参数计算等测井地层评价中的应用。受样本数量有限、处理流程不完善和自我调节能力较差等因素制约，人工智能在流体研究、储层综合评价等测井领域具有较大的发展空间和广阔的应用前景。
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引用本文
李宁, 徐彬森, 武宏亮, 冯周, 李雨生, 王克文, 刘鹏. 人工智能在测井地层评价中的应用现状及前景[J]. 石油学报, 2021, 42(4): 508-522.
Li Ning, Xu Binsen, Wu Hongliang, Feng Zhou, Li Yusheng, Wang Kewen, Liu Peng. Application status and prospects of artificial intelligence in well logging and formation evaluation[J]. Acta Petrolei Sinica, 2021, 42(4): 508-522.
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