刘宁^1,,
符力耘^2,,,
曹呈浩³,
刘建林²
1. 北京化工大学机电工程学院, 北京 100029
2. 中国石油大学(华东)深层油气重点实验室, 青岛 266580
3. 南京工业大学交通运输工程学院, 南京 210009

基金项目: 国家自然科学基金（41804134）、中国科学院战略性先导科技专项（B类）（XDB10010401）、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），中央高校基本科研业务费专项（ZY2009），中国博士后科学基金面上项目（2018M640176）和中国科学院青年创新促进会基金（2019069）联合资助


详细信息

作者简介: 刘宁, 女, 1988年生, 副教授, 硕士生导师, 主要从事岩石物理、计算力学及结构动力学等方面研究.E-mail:nicolaliu@buaa.edu.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: P313

收稿日期:2019-06-09
修回日期:2019-09-25
上线日期:2020-07-25

Research on numerical modeling method of LSM-RVM and TOC content influence for digital core from Longmaxi Formation shale

LIU Ning^1,,
FU LiYun^2,,,
CAO ChengHao³,
LIU JianLin²
1. College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing 100029, China
2. Key Laboratory of Deep Oil and Gas, China University of Petroleum(East China), Qingdao 266580, China
3. School of Transportation Engineering, Nanjing Tech University, Nanjing 210009, China


More Information

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

MSC: P313

--> Received Date: 09 June 2019
Revised Date: 25 September 2019
Available Online: 25 July 2020


摘要
摘要:页岩气储层中含有大量有机碳（TOC），其丰度与成熟度对页岩力学特性有重要影响.建立包含TOC的精细数值模型，将有助于探索页岩微结构与矿物组分含量对等效弹性模量的作用程度，是"甜点区"预测的重要理论基础.本文提出了一种离散数值建模方法，基于高精度成像技术，采用晶格弹簧-随机孔隙耦合模型（LSM-RVM）模拟包含多种矿物组分及不同成熟度干酪根的数字岩心，分析TOC成熟度及含量对弹性参数的影响.在该模型中，参数设置（数值阻尼与加载应变速率）至关重要，选取不当会对计算精度造成一定影响.研究结果表明，LSM-RVM能够生成符合TOC及多种矿物实际分布特征的数值模型，是一种精细数值建模方法.
关键词: 龙马溪组页岩/
TOC含量/
数字岩心/
晶格弹簧模型(LSM)/
随机孔隙模型(RVM)/
弹性模量

Abstract:Shale gas reservoirs contain a large amount of organic carbon (TOC), and its abundance and maturity have significant effects on the mechanical properties. An accurate numerical model regarding TOC helps to analyze the effects of shale microstructure and mineral composition contents on the effective elastic moduli. It serves as an important theoretical basis for the prediction of "sweet spot". In this paper, a numerical modeling method based on discrete concepts is proposed. The lattice spring model and random void model are combined to simulate the digital cores from X-ray micro-CT imaging. This LSM-RVM coupling model takes various mineral components and different maturity kerogens into consideration. Then, the effect of maturity and content of TOC on the effective elasticity is analyzed. Here, model parameters (e.g., numerical damping and loading strain rate) settings are critical. An improper selection might lead to low accuracy. As a result, the LSM-RVM model could capture the real distribution characteristics of TOC and various minerals, which confirms it is an accurate numerical elastic modeling scheme.
Key words:Longmaxi Formation shale/
TOC content/
Digital core/
Lattice Spring Model (LSM)/
Random Void Model (RVM)/
Elastic moduli



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