基于微结构-尺度双分解的页岩随机介质模拟和非均质特征分析

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.

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

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.