Quantitative prediction and spatial analysis of structural fractures in deep shale gas reservoirs within complex structural zones: A case study of the Longmaxi Formation in the Luzhou area, southern Sichuan Basin, China

The characteristics of structural fractures (faults) have a significant impact on the preservation, enrichment, and hydraulic fracturing of deep shale gas in complex structural zones. In this study, the development characteristics and controlling factors of structural fractures are analyzed using collected data, such as field outcrops, cores, thin sections, imaging logs, seismic interpretations, and production test data, etc. The distribution pattern of fractures is quantitatively predicted using geophysical properties. Shear fractures of structural origin predominate in the study area, displaying consistent and inheritable multiscale development characteristics. The presence of fractures is prominent in the Wufeng Formation and the 1st, 2nd, and 3rd layers of the 1st Submember of the Longmaxi Formation, with the 4th layer exhibiting the lowest fracture density. The development of fractures is primarily influenced by faults, folds, brittle minerals, total organic content (TOC), and other geological variables. The degree of fracture development displays an exponential relationship with the distance from faults. Variations in fracture development are observed in different structural positions, with the closed anticline area displaying the highest fracture development. High TOC and brittle mineral content are conducive to fracture development, with respective critical values of 2 % and 44 %. Employing the average density of typical drilling-induced fractures as a constraint, we have developed a quantitative multi -parameter regression-based fracture prediction model based on geological (core and imaging logging) and geophysical methods. The prediction results indicate that fracture density ranges from 0 to 3.5 m-1, and the distribution of fractures is jointly governed by structural positions and faults. Compared with the actual fracture density of the wells, the quantitative fracture prediction accuracy reaches approximately 90 %.