1.有色金属成矿预测与地质环境监测教育部重点实验室(中南大学)，湖南 长沙 410083;2.有色资源与地质灾害探查湖南省重点实验室，湖南 长沙 410083;3.中南大学地球科学与信息物理学院，湖南 长沙 410083;4.山河智能装备股份有限公司，湖南 长沙 410100
P634
中南大学研究生自主探索创新项目（编号：2024ZZTS0630）
- ZHANG Hangsheng 1,2,3
ZHANG Hangsheng
Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring;(Central South University), Ministry of Education, Changsha Hunan 410083, China;Key Laboratory of Non-Ferrous Resources and Geological Hazard Detection, Changsha Hunan 410083, China;School of Geosciences and Info-Physics, Central South University, Changsha Hunan 410083, China
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SUN Pinghe
Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring;(Central South University), Ministry of Education, Changsha Hunan 410083, China;Key Laboratory of Non-Ferrous Resources and Geological Hazard Detection, Changsha Hunan 410083, China;School of Geosciences and Info-Physics, Central South University, Changsha Hunan 410083, China
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在本站中查找 - ZHU Jianjun 4
- DENG Yingying 1,2,3
DENG Yingying
Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring;(Central South University), Ministry of Education, Changsha Hunan 410083, China;Key Laboratory of Non-Ferrous Resources and Geological Hazard Detection, Changsha Hunan 410083, China;School of Geosciences and Info-Physics, Central South University, Changsha Hunan 410083, China
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在本站中查找 - CAO Han 1,2,3
CAO Han
Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring;(Central South University), Ministry of Education, Changsha Hunan 410083, China;Key Laboratory of Non-Ferrous Resources and Geological Hazard Detection, Changsha Hunan 410083, China;School of Geosciences and Info-Physics, Central South University, Changsha Hunan 410083, China
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ZHANG Chen
Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring;(Central South University), Ministry of Education, Changsha Hunan 410083, China;Key Laboratory of Non-Ferrous Resources and Geological Hazard Detection, Changsha Hunan 410083, China;School of Geosciences and Info-Physics, Central South University, Changsha Hunan 410083, China
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在本站中查找 - ZHANG Xinxin 1,2,3
ZHANG Xinxin
Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring;(Central South University), Ministry of Education, Changsha Hunan 410083, China;Key Laboratory of Non-Ferrous Resources and Geological Hazard Detection, Changsha Hunan 410083, China;School of Geosciences and Info-Physics, Central South University, Changsha Hunan 410083, China
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在本站中查找 - PU Yingjie 1,2,3
PU Yingjie
Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring;(Central South University), Ministry of Education, Changsha Hunan 410083, China;Key Laboratory of Non-Ferrous Resources and Geological Hazard Detection, Changsha Hunan 410083, China;School of Geosciences and Info-Physics, Central South University, Changsha Hunan 410083, China
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1.Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring;(Central South University), Ministry of Education, Changsha Hunan 410083, China;2.Key Laboratory of Non-Ferrous Resources and Geological Hazard Detection, Changsha Hunan 410083, China;3.School of Geosciences and Info-Physics, Central South University, Changsha Hunan 410083, China;4.Sunward Intelligent Equipment Co., Ltd., Changsha Hunan 410100, China
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地层岩性的实时识别对及时调整钻井参数、有效控制井眼轨迹、寻找地下储层都具有十分重要的作用。与传统岩性识别方法相比，通过监测随钻参数变化进行岩性识别，具有便捷、高效、实时、准确、环保以及节能等优点。围绕基于随钻参数的地层岩性识别技术，按照煤矿勘探、油气藏开采等不同岩性识别应用领域对随钻参数进行分类；通过对随钻测控技术及装备的研究现状分析，介绍随钻参数采集及传输技术；介绍了机器学习算法、多元统计分析法、灰色关联法、交会图法的特点及应用情况；结合应用案例对4种基于随钻参数的地层识别方法进行对比分析。最终，归纳总结了随钻岩性识别研究的关键技术问题，分析了在研发及工程应用中存在的不足及面临的挑战，并给予建议。
Real-time recognition of formation lithology is critical for promptly adjusting drilling parameters， effectively controlling wellbore trajectory， and identifying subsurface reservoirs. Compared to traditional methods of identifying lithology， real-time recognition through monitoring parameters while drilling offers advantages such as convenience， efficiency， real-time accuracy， environmental compatibility， and energy efficiency. In this paper， around the lithology identification technology based on real-time parameters while drilling， the parameters according to different applications such as coal exploration and oil and gas reservoir exploitation are classified. Through the analysis of the current research status of drilling measurement and control technology and equipment， the technology for collecting and transmitting real-time parameters while drilling is introduced. Additionally， the characteristics and applications of machine learning algorithms， multivariate statistical analysis， grey relational analysis， and cross-plotting methods are also discussed. Through application cases， it compares and analyzes four types of lithology identification methods based on real-time parameters while drilling. Ultimately， the key technical issues in real-time lithology identification research is summarized， the deficiencies and challenges in development and engineering applications are analyzed， and the recommendations are provided.
引用本文
张航盛,孙平贺,朱建新,等.几种基于随钻参数地层识别方法的对比分析[J].钻探工程,2024,51(S1):10-15.
ZHANG Hangsheng, SUN Pinghe, ZHU Jianjun, et al. Comparative analysis of several formation identification methods based on parameters while drilling[J]. Drilling Engineering, 2024,51(S1):10-15.
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历史
- 收稿日期:2024-07-30
- 最后修改日期:2024-07-30
- 录用日期:2024-08-13
- 在线发布日期: 2024-11-08
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