## 5 The Measurement Methods for Microscale Mechanical Parameters and Deformation Quantities in Shale
### In Situ Strain Measurement Method for Shale  
In macroscopic rock mechanics experiments, strain gauges and displacement sensors are commonly employed to quantitatively characterize the deformation process of rocks, providing insights into their fracturing mechanisms based on the evolution of strain [82; 83]. However, in the microscopic domain, how can strain information be obtained quantitatively while microfractures are propagating? This poses a challenge as traditional measurement techniques such as strain sensors cannot be used due to the inability to cover the sample surface during in situ observation of fracture propagation. Currently, the main methods for microscale strain characterization include digital image correlation (DIC) and electron backscatter diffraction (EBSD) techniques [84; 85]. DIC is a non-contact strain measurement technique that has been widely used in various fields such as medicine, materials science, and aerospace due to its wide application range and high precision. In the field of macroscopic rock mechanics experiments, DIC has been extensively applied to measure the deformation and strain during rock fracturing processes, and theoretical analyses have been conducted [86; 87; 88]. However, applying this method in microscale rock mechanics experiments presents some challenges. If the rock surface is left untreated and only relies on natural speckles, it may result in low contrast, leading to insufficient accuracy in calculating the strain field [89]. Using traditional black and white spray coatings during the speckle production process can result in larger and unevenly distributed particles. This restricts the use of high magnification scanning electron microscopy (SEM) observation, making it difficult to obtain accurate microscale strain information at high magnifications (Figure 7) [90; 91]. In addition to SEM, some researchers have attempted to combine computed tomography (CT) with DIC to quantitatively analyze the initiation, closure, shear, and accumulation features of microfractures in rocks during different loading stages. However, this study still relies on natural speckles on the rock surface, resulting in less accurate strain information [92]. Electron backscatter diffraction (EBSD) is a technique used for point-by-point and line-by-line automated orientation measurements on the surface of a sample, with the acquired data stored [93]. By combining the coordinates of each point in the sample coordinate system and using crystal orientation as imaging criteria, image reconstruction known as orientation imaging microscopy can be achieved. Characterizing and quantitatively analyzing crystal orientation changes during crystal deformation processes contribute to a deeper understanding of the inherent connection between plastic deformation behavior and the initiation and propagation of microfractures. When materials undergo plastic deformation, dislocations are generated within the crystals, along with low-angle dislocation boundaries. Although EBSD cannot directly observe dislocations, it can measure orientation changes caused by a large number of crystal dislocations, and the extent of these changes (misorientation) reflects the degree of crystal deformation. Specifically, this orientation change  
Figure 6: **(a)** Shale nanoindentation testing [80]. **(b)** The distribution of Young’s modulus of potassium feldspar measured by AFM [81]. can be studied through Euler angles, pattern quality, small angle grain boundaries, inverse pole figures, and misorientation [94]. Quantitative characterization of crystal deformation behavior can be achieved by studying the changes in grain orientation, misorientation angles, and Schmid factor evolution during in situ loading processes. This technique is widely applied in materials science, and in the field of microscale rock deformation. It has only been utilized in tectonic geology to investigate structural deformations in rocks and infer their geological evolution history (Figure 7) [95].