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首页» 过刊浏览» 2021» Vol.6» Issue(3) 369-379     DOI : 10.3969/j.issn.2096-1693.2021.03.030
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基于流动单元分类的致密砂岩储层渗透率预测
鲁健康,郝彬,李程善,王维斌,王乾右 ,杨威
1 中国石油大学(北京)油气资源与探测国家重点实验室,北京 102249 2 中国石油大学(北京)非常规油气科学技术研究院,北京 102249 3 中国石油勘探开发研究院西北分院,兰州 730020 4 中国石油长庆油田分公司勘探事业部,西安 710018 5 利物浦大学地球海洋与生态科学系,英国利物浦 L69 3GP
Permeability prediction of tight sandstone reservoirs based on flow unit classification
LU Jiankang, HAO Bin , LI Chenshan, WANG Weibin, WANG Qianyou , YANG Wei
1 State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing 102249, China 2 Institute of Unconventional Natural Gas Research, China University of Petroleum. Beijing 102249, China 3 Research Institute of Exploration and Development-Northwest, PetroChina, Lanzhou 730020, China 4 Exploration Department, PetroChina Changqing Oilfield Company, Xi’an 710018, China 5 Department of Earth, Ocean and Ecological Sciences, University of Liverpool, Liverpool L69 3GP, UK

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摘要  渗透率是衡量岩石允许流体通过的畅通程度的参数,是反映储层渗流特性进行储层评价的关键参数之一。 鄂尔多斯盆地中南部地区长 6 致密砂岩储层由于受沉积环境、成岩作用和构造因素的综合影响,孔隙结构复杂、 非均质性强。岩心孔渗实验数据中,相同孔隙度数值的岩心渗透率数值相差 1 至 2 个数量级,利用常规解释方 法进行渗透率解释精度较低,不能满足储层评价要求。本论文运用FZI累积频率划分方法将研究区储层划分为 4 类,分类后的四类储层孔隙度、渗透性差异明显,且每一类储层孔隙结构、渗透性等特征基本一致,说明利用 FZI值划分储层类型的合理性。在此基础上建立了各类储层的渗透率精细解释模型,利用多元线性回归建模方法 建立孔隙度、FZI的测井响应多参数拟合方程,实现了FZI的连续定量评价,实现了研究区致密储层流动单元类 型的连续划分及其渗透率的测井评价;并将其应用于研究区典型单井的渗透率计算中,应用结果表明:新方法 计算渗透率与岩心分析数据吻合较好,该方法有效地提高了渗透率测井评价的准确度。该研究对于精确预测该 研究区长 6 致密砂岩储层渗透率的空间分布和陆相致密砂岩储层渗透率的详细评价提供理论依据。
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关键词 : 渗透率;孔隙度;流动单元;测井曲线;延长组;致密储层;鄂尔多斯盆地
Abstract
Permeability is a measure of the ability of a porous rock to allow fluids to pass through it. It is one of the key
parameters for reservoir evaluation to reflect the characteristics of reservoir seepage. Due to the comprehensive influence of  
sedimentary environment, diagenesis and tectonic factors, the tight sandstone reservoirs of the Upper Triassic Chang 6 member  
in the central-southern Ordos Basin have a complex pore structure and strong heterogeneity. In the core porosity and permeability  
test data, the core permeability values of the same porosity value differ by one to two orders of magnitude. Permeability  
prediction with methods used for conventional reservoirs cannot meet the requirements of unconventional reservoir evaluation.  
Hence, this study divided the Chang 6 reservoir into four types of flow units using the Flow Zone Indicator ( FZI ) cumulative  
frequency division method. The porosity and permeability of the four types of reservoirs after classification are obviously  
different, and the characteristics of the pore structure and permeability of each type of reservoir are basically the same. On this  
basis, a fine interpretation model for permeability of various reservoirs was established, and a multi-parameter fitting equation for  
porosity and FZI logging response was established by using multiple linear regression modeling methods to achieve continuous  
quantitative evaluation of FZI and to realize the continuous division of flow unit types in tight reservoirs in the area and the  
logging evaluation of permeability; and we applied it to the permeability calculation of typical single wells in the study area.  
The application results show that the new method calculates permeability which is in good agreement with the core analysis  
data .This method effectively improves the accuracy of permeability logging evaluation. This research is of great significance  
for accurately predicting the spatial distribution of permeability of Chang 6 tight sandstone reservoirs in the study area, and will  
provide a theoretical basis for the detailed evaluation of the permeability of continental tight sandstone reservoirs.


Key words: permeability; porosity; flow unit; log interpretation; Yanchang Formation tight reservoir; Ordos Basin
收稿日期: 2021-09-29     
PACS:    
基金资助:中国石油大学( 北京) 优秀青年学者科研启动基金项目(2462020QNXZ004)、国家科技重大专项“中生界陆相不同盆地类型页岩气赋存方式
与富集规律研究”(2016ZX05034001-005) 和国家科技重大专项“页岩气成藏要素匹配及综合评价”(2017ZX05035002-007)、中石油战略
合作科技专项(ZLZX2020-01-06-02) 联合资助
通讯作者: yangw@cup.edu.cn
引用本文:   
鲁健康, 郝彬, 李程善, 王维斌, 王乾右, 杨威. 基于流动单元分类的致密砂岩储层渗透率预测. 石油科学通报, 2021, 03: 369-379 LU Jiankang, HAO Bin, LI Chenshan, WANG Weibin, WANG Qianyou, YANG Wei. Permeability prediction of tight sandstone reservoirs based on flow unit classification. Petroleum Science Bulletin, 2021, 03: 369-379.
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