饶颖^1,2,,
符力耘^3,,,
吴玉¹,
BOATENGCyril D.³
1. 中国科学院油气资源研究重点实验室, 中国科学院地质与地球物理研究所, 北京 100029
2. 中国科学院大学, 北京 100049
3. 中国石油大学(华东)深层油气重点实验室, 山东青岛 266580

基金项目: 中国科学院战略性先导科技专项（B类）（XDB10010401）和国家科技重大专项课题"页岩气勘探地球物理技术研究"（2017ZX05036-005）联合资助


详细信息

作者简介: 饶颖, 女, 1993年生, 博士研究生, 2015年获中国石油大学(北京)勘查技术与工程专业学士学位, 现于中国科学院地质与地球物理研究所攻读固体地球物理学专业博士学位, 主要从事页岩"甜点"识别、储层参数反演方面的研究.E-mail:raoying@mail.iggcas.ac.cn

通讯作者: 符力耘, 男, 1964年生, 教授, 博士生导师, 主要从事岩石物理、地震成像等相关领域研究工作和教学.E-mail:lfu@mail.iggcas.ac.cn

中图分类号: P631

收稿日期:2019-02-22
修回日期:2019-05-21
上线日期:2020-07-25

Heterogeneous characteristic analysis of shale based on multi-component and multi-scale random media method

RAO Ying^1,2,,
FU LiYun^3,,,
WU Yu¹,
BOATENG Cyril D.³
1. Key Laboratory of Petroleum Resource Research, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China
2. University of Chinese Academy of Sciences, Beijing 100049, China
3. Key Laboratory of Deep Oil and Gas, China University of Petroleum(East China), Shandong Qingdao 266580, China


More Information

Corresponding author: FU LiYun,E-mail:lfu@mail.iggcas.ac.cn

MSC: P631

--> Received Date: 22 February 2019
Revised Date: 21 May 2019
Available Online: 25 July 2020


摘要
摘要:页岩储层矿物颗粒、孔/裂隙、干酪根等微观结构呈现明显的尺度化分布特征，常规的单结构单尺度随机介质模拟方法难以完整描述和重构微观尺度的页岩储层介质，本文提出了一种微结构-尺度双分解的随机介质模拟方法.基于龙马溪组页岩数字岩心，将岩心切片按照占比分解为脆性矿物、孔隙、干酪根及背景介质四种类型，对脆性矿物、孔隙和干酪根三种微结构进行尺度分解，通过优化随机介质模型参数，实现精确模拟不同尺度的微结构组分，再按占比进行微结构-尺度双合成.结果表明，微结构-尺度双分解随机介质模拟大幅度提高强非均质页岩储层介质的建模精度.
关键词: 龙马溪组页岩/
数字岩心/
随机介质模拟/
微结构-尺度双分解

Abstract:The microstructure such as mineral particles, pores or fractures and kerogen in shale reservoirs displays obvious scaled distribution characteristics. It is difficult to fully depict and reconstruct the micro-scale shale by conventional single-structure and single-scale random media simulation method. In this paper, we proposed a multi-component and multi-scale random media method. Based on the digital core of Longmaxi Formation shale, the slice is decomposed into four types: brittle minerals, pore, kerogen and background media according to the proportion of each type. Three microstructures, brittle minerals, pore and kerogen, are then decomposed according to scales. By optimizing the parameters of random media model, it is possible to accurately simulate the microstructures of different scales. Then we do the microstructure-scale double synthesis according to the proportion. The results show that the multi-component and multi-scale random media method greatly improves the modeling accuracy of strong heterogeneous shale reservoir media.
Key words:Longmaxi Formation shale/
Digital core/
Random media method/
Multi-component and multi-scale



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