The cycling performances for hollow SnO₂ microspheres, core–shell structured hollow SnO₂/21 wt% PPy nanocomposites, hollow SnO₂/21.5 wt% rGO nanocomposites and core–shell structured hollow SnO₂/21.5 wt% rGO/16.5 wt% PPy nanocomposites.

The logging evaluation of shale fracability is significant for the selection of high-quality reservoir targets and the construction of staged fracturing. The factors affecting shale fracability are complex, and the analysis and weight selection of the factors in traditional logging evaluation methods are obscure, thus resulting in low evaluation accuracy. In this paper, the shale oil reservoirs in the Liushagang Formation in the Weixinan Depression are divided into three types: the matrix type, texture type, and interlayer type. Then, a 3D digital core model is established to characterize the reservoirs in the Weixinan Depression. Through finite-element simulation, sensitivity analysis, and an analytic hierarchy process, the sensitivity and relative weights of the factors affecting the fracability of different types of shale oil reservoirs are determined. Finally, the evaluation model of fracability for different types of shale oil reservoirs is established, and the reliability of the model is verified by the comparison with fracturing data. The main factors affecting the fracability of target layers include mineral composition, textures, and fractures. The minerals with the most significant influence on elastic parameters are quartz and clay. Texture density has the most significant influence on the texture-type shale oil reservoir, and fractures mainly affect the interlayer-type shale oil reservoir. The fracability evaluation model established in this paper allowed the classification and accurate evaluation of reservoir fracability through the microscopic analysis of rocks and the quantification of influencing factors, which largely determined the accurate and efficient development of shale oil and gas.

Tight sandstone reservoirs are affected by various factors such as pore structure, formation water salinity, and siliceous cementation, which lead to the abnormal phenomenon of high-resistivity water layers and increase the difficulty in identifying gas and water layers by conventional logging. In this study, the pore types and pore size distribution characteristics of tight sandstone reservoirs were firstly determined by NMR and high-pressure mercury injection experiments, and then the iterative least-square method was used to automatically optimize the inversion method of pseudo-capillary pressure curve and search for the optimal conversion coefficient. Finally, the apparent free water porosity was inversed and the fluid identification standard was obtained and applied. The results showed that the reservoirs mainly developed intergranular pores, cutting solution pores, and intergranular pores. The pore throats were poorly sorted, and the displacement pressure was high. The median radius ranged from 0.01 to 0.48μm, and the main peak range was from 0.02 to 0.06μm. Pores were of mainly small-hole fine throat type. In the inversion results of the optimal conversion coefficient, the correlation coefficient between the aperture parameters and the results of high-pressure mercury injection experiments was greater than 0.93. According to the fluid property identification standard based on nuclear magnetic apparent free water porosity, the high-resistivity water layers were effectively identified and its coincidence rate with the final field test was 10.7 higher than that of the conventional method. This identification method can be used to identify complex fluids in tight sandstone reservoirs.

Carbonate reservoirs characterized by fractures and caves exhibit a complex spatial distribution and significant heterogeneity. The establishment of precise and reliable three-dimensional geological models is imperative to elucidate the influence mechanism of fracture and cave parameters on macroscopic petrophysical properties from a micro scale. This is the foundation and prerequisite for the efficient development of such reservoirs. In this paper, dual-scale CT core scanning data is utilized to adjust the segmentation threshold of high-resolution (small-scale) cores to the segmentation of low-resolution (large-scale) cores. This approach enables the comprehensive characterization of multi-scale porosity in large-scale cores and the realization of multi-scale digital core fusion. A 3D fracture digital core model was generated using a Slice-GAN neural network model and SEM images. A well-developed cave was extracted from low-resolution CT data and used as a cave digital core. Through model superposition, a multi-scale digital core containing fractures and caves was constructed. The reliability of the constructed digital core was verified based on four parameters: aperture distribution, coordination number, porosity, and resistivity. The research outcomes establish a foundation for subsequent simulations, which aim to assess the resistivity response of the digital core under varied fracture size, angle, and cave size conditions. This provides a technical foundation for advancing the fundamental theoretical research of carbonate rocks.