Modeling the Viscoelastic Behavior of Quartz and Clay Minerals in Shale by Nanoindentation Creep Tests

Abstract

The viscoelastic behavior of minerals in shales is important in predicting the macroscale creep behavior of heterogeneous bulk shale. In this study, in situ indentation measurements of two major constitutive minerals (i.e., quartz and clay) in Longmaxi Formation shale from the Sichuan Basin, South China, were conducted using a nanoindentation technique and high-resolution optical microscope. Firstly, quartz and clay minerals were identified under an optical microscope based on their morphology, surface features, reflection characteristics, particle shapes, and indentation responses. Three viscoelastic models (i.e., three-element Voigt, Burger’s, and two-dashpot Kelvin models) were then used to fit the creep data for both minerals. Finally, the effects of peak load on the viscoelastic behavior of quartz and clay minerals were investigated. Our results show that the sizes of the residual imprints on clay minerals were larger than that of quartz for a specific peak load. Moreover, the initial creep rates and depths in clay minerals were higher than those in quartz. However, the creep rates of quartz and clay minerals displayed similar trends, which were independent of peak load. In addition, all three viscoelastic models produced good fits to the experimental data. However, due to the poor fit in the initial holding stage of the three-element Voigt model and instability of the two-dashpot Kelvin model, Burger’s model is best in obtaining the regression parameters. The regression results indicate that the viscoelastic parameters obtained by these models are associated with peak load, and that a relatively small peak load is more reliable for the determination of viscoelastic parameters. Furthermore, the regression values for the viscoelastic parameters of clay minerals were lower than those of quartz and the bulk shale, suggesting the former facilitates the viscoelastic deformation of shale. Our study provides a better understanding of the nanoscale viscoelastic properties of shale, which can be used to predict the time-dependent deformation of shale.