特种油气藏 ›› 2023, Vol. 30 ›› Issue (6): 16-22.DOI: 10.3969/j.issn.1006-6535.2023.06.003

• 地质勘探 • 上一篇    下一篇

基于聚类分析的砾岩储层分类方法及应用

刘明熹1, 宋考平1, 郭平2, 付虹1, 徐明霄3, 王龙鑫1, 帕提古丽·麦麦提4, 云庆庆4   

  1. 1.中国石油大学(北京),北京 102249;
    2.中国石油辽河油田分公司,辽宁 盘锦 124010;
    3.中国地质大学(北京),北京 100083;
    4.中国石油新疆油田分公司,新疆 克拉玛依 830023
  • 收稿日期:2023-03-07 修回日期:2023-10-13 出版日期:2023-12-25 发布日期:2024-01-19
  • 通讯作者: 宋考平(1962—),男,教授、博士生导师,孙越崎能源大奖与国务院特殊津贴获得者,1979年毕业于大庆石油学院油气田开发工程专业,1998年毕业于该校油气田开发工程专业,获博士学位,现从事油田开发理论研究、科技攻关和工程实践方面的研究工作。
  • 作者简介:刘明熹(1995—),男,2017年毕业于中国石油大学(北京)石油工程专业,现为该校石油与天然气工程专业在读博士研究生,研究方向为化学驱提高采收率和微观孔隙结构精细表征。
  • 基金资助:
    国家自然科学基金“驱替相自扩大波及体积提高采收率新方法”(51834005)

Classification Method and Application of Conglomerate Reservoir Based on ClusteringAnalysis

Liu Mingxi1, Song Kaoping1, Guo Ping2, Fu Hong1, Xu Mingxiao3, Wang Longxin1, Patiguri McMatty4, Yun Qingqing4   

  1. 1. China University of Petroleum (Beijing), Beijing 102249, China;
    2. PetroChinaLiaohe Oilfield Company, Panjin, Liaoning 124010, China;
    3. China University of Geosciences (Beijing), Beijing 100083, China;
    4. PetroChina Xinjiang Oilfield Company, Karamay, Xinjiang 830023, China
  • Received:2023-03-07 Revised:2023-10-13 Online:2023-12-25 Published:2024-01-19

摘要: 砾岩的岩相丰富多变,孔隙结构复杂,储层类型划分困难,且评价参数无法统一。以新疆克拉玛依油田七中区上—下克拉玛依组砾岩储层为研究对象,基于106组储层岩石高压压汞数据,利用聚类分析方法建立砾岩储层分类方案,通过方差计算等方法,简化并明确了砾岩储层的分类参数,最后利用判别分析法验证了该方法的有效性。结果表明:研究区砾岩随着储层物性变好,孔喉尺寸变大,非均质性反而加强,体现了砾岩孔隙结构的复杂性;数据预处理后的聚类分析可有效进行储层分类,类间差异显著;基于参数集中性和分散性的量化,优选出中值压力、平均孔喉半径等6个储层分类参数,经过判别分析验证,参数优选后分类准确率依然高达95.80%,表明该方法的分类准确性高,且不受地域限制,具有推广价值。

关键词: 克拉玛依组, 砾岩储层分类方法, 孔隙结构, 聚类分析, 判别分析, 参数优选

Abstract: The lithology of conglomerate is rich and variable, the pore structure is complex, the classification of reservoir type is difficult, without standardized evaluation parameters. Taking the conglomerate reservoirs of the Upper-Lower Karamay Formation in District Min-7 of Karamay Oilfield of Xinjiang as the object of study, based on the high-pressure mercury injection data of the reservoir rocks of the Formation 106, the classification scheme of the conglomerate reservoirs was established by using the clustering analysis method; the classification parameters of the conglomerate reservoirs were simplified and clarified by the methods such as the variance calculation and the validity of this method was verified by the use of the discriminant analysis in the end. The results show that the non-homogeneity of the conglomerate reservoir in the study area is strengthened as the physical properties become better and the pore-throat size becomes larger, reflecting the complexity of the conglomerate pore structure; the clustering analysis after data preprocessing can effectively classify the reservoirs, and there are significant differences between the classes; based on the quantification of parameter centralization and dispersion, six parameters for reservoir classification, such as the median pressure and the average pore-throat radius, are preferred; after the validation of the discriminant analysis, the accuracy of classification is still as high as 95.80% after the parameter preference, indicating that the method has high classification accuracy and is not geographically restricted, which makes it valuable for generalization.

Key words: Karamay Formation, conglomerate reservoir classification method, pore structure, clustering analysis, discriminant analysis, parameter preference

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