The Paleogene low-permeability reservoirs in the Bohai Bay Basin harbor substantial oil and gas resources, where the spatial distribution of micro-fracture development zones serves as a critical geological determinant for post-stimulation productivity. Current methodologies for predicting micro-fracture development zones predominantly rely on single seismic attribute analysis techniques. Nevertheless, constrained by seismic resolution (vertical resolution of 20–30 m) and interpretational non-uniqueness, traditional approaches (e.g., conventional coherence cube analysis) exhibit planar prediction accuracy below 60% for millimeter-scale fractures. In response to these challenges, this study presents a multi-scale predictive framework integrating cast thin-section analysis, well logging, and seismic data: Micro-scale (10–3–10–1 m): Through qualitative characterization of 136 cast thin sections, the occurrence and filling attributes of structural fractures (68%), diagenetic fractures (22%), and composite fractures (10%) were systematically analyzed. A vertical classification criterion was established to distinguish “extremely intense development” (4200–4400 m) from “weak development” (3400–4000 m) intervals, facilitating the rapid identification of preferential fracture distribution intervals. Mesoscopic-scale (10–1–101 m): Leveraging imaging log-calibrated conventional logging curves, a fracture response model was constructed using the triple-porosity ratio method (X = (neutron porosity + density porosity − acoustic porosity)/acoustic porosity). This approach transformed discrete well-point data into continuous wellbore trajectory datasets, enabling quantitative assessment of fracture density. Macro-scale (101–103 m): Seismic coherence analysis was employed to extract coherence slices. By integrating cast thin-section observations and fracture characteristic curves, micro-fracture development zones were delineated on planar seismic sections. This research establishes a novel cross-scale data fusion paradigm of “micro-scale qualitative analysis—mesoscopic-scale quantitative evaluation—macro-scale spatial localization” for optimizing target zones in low-permeability reservoir stimulation campaigns.