岩性油气藏 ›› 2022, Vol. 34 ›› Issue (3): 117–130.doi: 10.12108/yxyqc.20220311

• 地质勘探 • 上一篇    下一篇

四川盆地泸州地区奥陶系五峰组—志留系龙马溪组页岩沉积微相划分及测井识别

邱晨1, 闫建平1,2, 钟光海3, 李志鹏4, 范存辉1,2, 张悦5, 胡钦红6, 黄毅7   

  1. 1. 西南石油大学 地球科学与技术学院, 成都 610500;
    2. 油气藏地质及开发工程国家重点实验室·西南石油大学, 成都 610500;
    3. 中国石油西南油气田公司 页岩气研究院, 成都 610500;
    4. 中国石化胜利油田分公司 勘探开发研究院, 山东 东营 257015;
    5. 河北省地球物理勘查院, 河北 廊坊 065000;
    6. 德克萨斯大学阿灵顿分校 地球与环境科学系, 美国 76019;
    7. 中国石油集团测井有限公司 西南分公司, 重庆 400021
  • 收稿日期:2021-09-13 修回日期:2021-11-28 出版日期:2022-05-01 发布日期:2022-05-12
  • 通讯作者: 闫建平(1980-),男,博士,教授,主要从事测井地质学及非常规储层测井评价方面的教学与研究工作。Email:yanjp_tj@163.com。
  • 作者简介:邱晨(1993-),男,西南石油大学在读硕士研究生,研究方向为测井地质学。地址:(610500)四川省成都市新都区西南石油大学地球科学与技术学院。Email:121511488@qq.com
  • 基金资助:
    中国石油-西南石油大学创新联合体科技合作项目“川南深层与昭通中浅层海相页岩气规模效益开发关键技术研究”（编号：2020CX020000）、国家自然科学基金项目“陆相页岩油在基质-裂缝体系中的多尺度运移机理研究”（编号：41830431）和高等学校学科创新引智计划（111计划）“深层海相页岩气高效开发学科创新引智基地”（编号：D18016）联合资助

Sedimentary microfacies division and logging identification of Ordovician Wufeng-Silurian Longmaxi shale in Luzhou area，Sichuan Basin

QIU Chen1, YAN Jianping1,2, ZHONG Guanghai3, LI Zhipeng4, FAN Cunhui1,2, ZHANG Yue5, HU Qinhong6, HUANG Yi7   

  1. 1. School of Geoscience and Technology, Southwest Petroleum University, Chengdu 610500, China;
    2. State Key Laboratory of Oil & Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu 610500, China;
    3. Shale Gas Research Institute, PetroChina Southwest Oil and Gas Field Company, Chengdu 610500, China;
    4. Research Institute of Exploration and Development, Shengli Oilfield Company, Sinopec, Dongying 257015, Shandong, China;
    5. Hebei Institute of Geophysical Exploration, Langfang 065000, Hebei, China;
    6. Department of Earth and Environmental Sciences, University of Texas at Arlington, Arlington, TX 76019, USA;
    7. Southwest Branch, CNPC Logging Company Limited, Chongqing 400021, China
  • Received:2021-09-13 Revised:2021-11-28 Online:2022-05-01 Published:2022-05-12

PDF (PC)

141

摘要： 通过X射线衍射分析、物性测试、薄片鉴定、地球化学分析以及测井资料，对川南泸州地区奥陶系五峰组—志留系龙马溪组深层页岩地层开展了沉积微相细分，明确了其测井响应特征及识别方法。研究结果表明：①泸州地区页岩沉积微相可细分为5个大类、8个小类，其中强还原富有机质富硅深水陆棚相物性好、含气量高、TOC含量高、脆性矿物含量高，是最优微相细分类型，主要分布于龙一段一亚段一小层； ②利用无铀伽马、自然伽马、钍含量、声波时差、中子、横波时差及钍铀比等7条敏感曲线，通过K-means的贝叶斯判别法划分的页岩地层微相细分类型，与取心结果的吻合率高于90.0%。

关键词: 深层页岩气, 微相细分, 测井识别, 贝叶斯判别法, “甜点”预测, 奥陶系五峰组—志留系龙马溪组, 泸州地区, 四川盆地

Abstract: Based on the data of XRD，physical properties，thin section， geochemistry and well logging，the microfacies subdivision of Ordovician Wufeng-Silurian Longmaxi shale in Luzhou area of southern Sichuan Basin was carried out，and the logging response characteristics and identification methods were defined. The results show that： （1）The microfacies of shale in Luzhou area can be subdivided into five categories and eight sub categories. Among them，the strong reduction rich organic matter and silicon-rich deep-water shelf facies is the best microfacies subdivision type with the characteristics of good physical properties and high contents of gas，TOC and brittle minerals，which is mainly distributed in the lower sublayer of Long-11 submember.（2）Using seven sensitive curves such as KTH，GR，Th， AC，CNL，DTS and Th/U，the microfacies subdivision types divided by the Bayesian discrimination method based on K-means are consistent with coring results with a coincidence rate greater than 90.0%.

Key words: deep shale gas, microfacies subdivision, logging identification, Bayesian discriminant method, sweet spot prediction, Ordovician Wufeng- Silurian Longmaxi Formation, Luzhou area, Sichuan Basin

中图分类号: 

  • TE122
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