The Tarim basin is rich in oil and gas resources, where fault-controlled fracture-cavity systems represent crucial reservoir types in Ordovician carbonate formations. However, the ultra-deep burial depth of these reservoirs (exceeding 7, 000 meters), coupled with complex fracture-cavity interactions and low-resolution seismic data, poses significant challenges in precisely characterizing strike-slip faults, thereby constraining exploration and development efforts. This study presents an integrated approach: First, texture attribute volumes are extracted, utilizing texture entropy to delineate fracture-cavity systems with high signal-to-noise ratio characteristics, effectively identifying their contour features. During extraction, parameters including time window size and gray level are optimized to enhance the overall continuity and clarity of fault-controlled fracture-cavity systems. Subsequently, leveraging the anisotropic tracking advantages of ant colony algorithm, a cascade methodology combining texture entropy with directional tracking enables precise identification of main strike-slip faults. The optimization process systematically considers key parameters such as ant movement direction, search step length, and termination criteria to ensure comprehensive path traversal and rational fracture information extraction. Finally, data volume fusion technology integrates original texture entropy attributes with main faults extracted through ant colony algorithm, significantly enhancing the spatial distribution characteristics of fault-controlled fracture-cavity systems. This methodological framework demonstrates practical value for the exploration and development of ultra-deep fault-controlled fracture-cavity reservoirs.