龙马溪组页岩数字岩心LSM-RVM数值建模方法研究及TOC含量影响分析

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.

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

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.