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Natural fractures are widely developed and distributed in tight sandstone reservoirs in the western Sichuan Basin, China, influenced by complex tectonic movements and diagenetic processes. These natural fractures serve as the main flow channels and important storage spaces in such reservoirs. Understanding their development characteristics and controlling factors determines the positioning and production efficiency of tight gas wells. This paper first explores the types and characteristics of natural fractures in the second member of the Upper Triassic Xujiahe Formation (T3x2) in the western Sichuan Basin through outcrop investigations, core observations, image log interpretations, and thin section analyses. We study the main influencing factors controlling the development and distribution of tectonic shear fractures by combining the characterization of fracture attributes. The results show that the tight sandstone reservoirs in the T3x2 mainly contain tectonic fractures, diagenetic fractures, and overpressure fractures, among which shear fractures in tectonic fractures are the main types. There are four sets of tectonic shear fractures in the study area, oriented in the E-W, N-S, NE-SW, and NW-SE directions. The dip angles of fractures range from 20° to 80°, with an average dip angle of 53°, predominantly consisting of high-angle fractures. The lengths of fractures are mainly within 100 cm, with a mean value of 47.53 cm, and 76.2% of fractures have lengths less than 50 cm. Fracture apertures range from 2.51 to 163.19 μM, with an average of 30.54 μM. The proportion of effective fractures in tectonic shear fractures reaches 85.7%. The development of tectonic shear fractures is primarily influenced by lithology, rock mechanics stratigraphy, diagenetic processes and facies, and faults. Lithology stands as the fundamental factor influencing the degree of fracture development in tight reservoirs. In rocks with the same composition, as the grain size decreases, the degree of fracture development increases. Simultaneously, with the rise in muddy content, fracture development diminishes in siltstone, argillaceous siltstone, silty mudstone, and mudstone. The formation and distribution of fractures are governed by rock mechanics stratigraphy, primarily manifested as a decrease in fracture density with an increase in rock mechanics layer thickness within a certain range. Diagenetic processes affect the abundance of tectonic shear fractures by influencing the mechanical properties of rocks. The stronger the compaction and cementation, the poorer the physical properties, and the higher the brittleness of the rocks, resulting in a greater abundance of tectonic shear fractures. Rocks with strong compaction and robust cementation facies exhibit high brittleness, rendering them more susceptible to fracturing under identical stress conditions. Fractures are highly prevalent in both the hanging wall and footwall of faults. As the distance from the fault increases, the linear density of fractures significantly decreases, owing to the uneven distribution of stress perturbation caused by fault activity. [ABSTRACT FROM AUTHOR]

With the continuous improvement of shale oil and gas recovery technologies and achievements, a large amount of geological information and data have been accumulated for the description of shale reservoirs, and it has become possible to use machine learning methods for "sweet spots" prediction in shale oil and gas areas. Taking the Duvernay shale oil and gas field in Canada as an example, this paper attempts to build recoverable shale oil and gas reserve prediction models using machine learning methods and geological and development big data, to predict the distribution of recoverable shale oil and gas reserves and provide a basis for well location deployment and engineering modifications. The research results of the machine learning model in this study are as follows: ① Three machine learning methods were applied to build a prediction model and random forest showed the best performance. The R2 values of the built recoverable shale oil and gas reserves prediction models are 0.7894 and 0.8210, respectively, with an accuracy that meets the requirements of production applications; ② The geological main controlling factors for recoverable shale oil and gas reserves in this area are organic matter maturity and total organic carbon (TOC), followed by porosity and effective thickness; the main controlling factor for engineering modifications is the total proppant volume, followed by total stages and horizontal lateral length; ③ The abundance of recoverable shale oil and gas reserves in the central part of the study area is predicted to be relatively high, which makes it a favorable area for future well location deployment. [ABSTRACT FROM AUTHOR]