This paper first examines the evolution of pore-size distribution (PSD) in four types of reconstituted clays during one-dimensional (1D) compression, utilising mercury intrusion porosimetry. Central to this work, fractal theory is then applied to quantify the complexity of the pore structure through fractal dimensions, followed by being correlated with 1D compressibility. The key findings are as follows: (1) The 1D compressibility of the four clays exhibits significant variability, with montmorillonite demonstrating the highest compressibility and Shenzhen clay, dominated by chlorite, the lowest. This is associated with distinct pore size evolution patterns under 1D loading while also emphasising the crucial role of mesopores in macroscopic clay deformation. (2) Fractal dimensions increase with loading, reflecting the progressive refinement of the pore structure, with natural Shenzhen clay demonstrating the most pronounced change. (3) A mathematical relationship between fractal dimension and 1D compressibility is established for each clay type, providing a quantitative tool for predicting 1D compressibility based on fractal dimensions. (4) The testing procedures and methods to ensure the representativeness of pore structure analysis are elaborated, ensuring reliable PSD data. By employing fractal theory, this study provides new insights into the correlation between pore structure complexity and compressibility in reconstituted clays.

In this paper, the effects of strain softening of structural clay and the corresponding influencing factors are systematically analyzed by modifying the existing constitutive model to optimize energy extraction technology. Initially, the strain softening process and the existing constitutive model commonly used in the study of strain softening of structural clay are introduced. Then, through the construction of an analytical constitutive model, some simulations are designed on a virtual platform to investigate the strain softening process of structural clay. Finally, the strain softening effect of structural clay under various conditions is discussed. It is found that structural clays typically exhibit hardness at the top and softness at the bottom during energy extraction. To address this issue, this study optimizes the analytical formula for structural clay, considering factors such as upper hard clay thickness, lower soil strength, and soil strain softening effect. A predictive model is therefore developed to estimate the vertical ratio change of upper hard clay and lower soft clay, accounting for the strain softening effect of structural clay. Simulation results indicate a stress-softening fit of approximately 90% for the proposed constitutive model, which suggests that the model proves reliable and is effective in analyzing the strain-softening characteristics of structural clay. The research findings of this paper contribute to advancing existing energy extraction methods and serve as a reference for optimizing analytical approaches in studying the strain-softening effect and influencing factors of structural clay using constitutive models.

The process of geothermal energy development may cause induced seismic activities, posing a potential threat to the sustainable utilization and safety of geothermal energy. To effectively evaluate the danger of induced seismic activities, this paper establishes an artificial neural network model and selects nine influencing factors as the input parameters of the neurons. Based on the results of induced seismic activity under different parameter conditions, a sensitivity analysis is conducted for each parameter, and the influence degree of each parameter on the magnitude of induced seismic activity is ranked from largest to smallest as follows: in situ stress state, fault presence or absence, depth, degree of fracture aggregation, maximum in situ stress, distance to fault, injection volume, fracture dip angle, angle between fracture, and fault. Then, the weights of each parameter in the model are modified to improve the accuracy of the model. Finally, through data collection and the literature review, the Pohang EGS project in South Korea is analyzed, and the induced seismic activity influencing factors of the Pohang EGS site are analyzed and evaluated using the induced seismic activity evaluation model. The results show that the induced seismicity are all located below 3.7 km (drilling depth). As the depth increases, the seismicity magnitude also shows a gradually increasing trend. An increase in injection volume and a shortening of the distance from faults will also lead to an increase in the seismicity magnitude. When the injection volume approaches 10,000 cubic meters, the intensity of the seismic activity sharply increases, and the maximum magnitude reaches 5.34, which is consistent with the actual situation. This model can be used for the induced seismic evaluation of future EGS projects and provide a reference for project site selection and induced seismic risk warning.