基于灰色关联分析法的页岩储层脆性影响因素研究

Study on the influence factors of shale reservoir brittleness based on grey correlation analysis

针对页岩脆性影响因素多、权重分配模糊的问题,利用RTR-1000岩石三轴测试系统对鄂尔多斯盆地南部延长组长7段的15块页岩岩芯进行应力-应变曲线测试。通过线性回归和灰度关联法对10个影响页岩脆性的因素进行了定性和定量化表征,结果表明:围压、泊松比、弹性模量与页岩脆性呈正相关关系,峰值应变、峰值应力、破裂时间、残余应力、残余应变、差应力、破裂面条数与页岩脆性呈负相关关系;峰值应变对页岩脆性影响最大,残余应力,残余应变等次之,弹性模量对页岩脆性影响最小;峰值处的力学参数(峰值应变、峰值应力、破裂时间、差应力)对页岩脆性影响最大,峰后力学参数(残余应力、残余应变、破裂面条数)次之,峰前力学参数(弹性模量、泊松比、围压)对脆性影响最小,峰前、峰值处、峰后的力学参数对页岩脆性影响权重比例为0.181∶0.499∶0.319。对页岩脆性影响因素权重的分析,不仅可以简化脆性评价公式,同时可以提高脆性评价的准确性。

Many factors affect the shale brittleness,and their weight distribution is fuzzy.Considering that,this paper uses 15 shale samples from Yanchang formation of southern Erdos Basin to test the stress-strain curve,and use linear regression and gray correlation method on the 10 factors which affect the brittleness of the shale to have the qualitative and quantitative analysis.Finally,10 factors weight allocation can be calculated in the brittleness evaluation.The results show that confining pressure,Poisson ratio,modulus of elasticity are positively associated with shale brittleness,and peak strain,peak stress,rupture time,residual stress,residual strain,differential stress,numbers of surfaces of rupture are negatively related with the shale brittleness;the peak strain has the greatest impact on the shale brittleness,and residual stress,residual strain,etc are the secondary,and modulus of elasticity with the minimal impact on shale brittleness;the mechanical parameters(peak strain,peak stress,fracture time and differential stress)at the peak have the greatest impact on the shale brittleness,and the after-peak mechanical parameters(residual stress,residual strain,broken noodles number)are the secondary,and pre-peak mechanical parameters(elastic modulus,Poisson ratio and confining pressure)have the minimal impact on brittleness three weight ratio of 0.181∶0.499∶0.319.The weight analysis of the influence factors of shale brittleness can not only simplify the formula of brittleness evaluation,but also improve the accuracy of brittleness evaluation.