Inter-well connectivity in deep fractured reservoirs is critical for the efficient extraction of hydrocarbon and geothermal resources. Conventional approaches, such as chemical tracers and geophysical techniques, have generally been inadequate for delineating complex fracture networks and tracing fluid migration pathways. This study proposes a novel high-throughput biogeochemical method based on core-derived microbial similarity as a proxy to infer inter-well connectivity. This method is founded on the hypothesis that hydraulic connectivity promotes community homogenization through environmental selection and dispersal. Core samples were collected from 16 wells in the buried-hill reservoir, Jiyang Depression, China, and analyzed via 16S rRNA gene sequencing to assess microbial community similarity. The results demonstrated that the studied wells could be classified into four distinct ecotypes (Types A–D) according to community diversity, phylogenetic distance, and predicted metabolic functions. Types A and B exhibited distinct community similarity patterns, which were hypothesized to reflect contrasting intra-group hydraulic connectivity: “highly heterogeneous” (Type A) and “stable homogeneous” (Type B). These patterns were consistent with fluid dynamics inferred from seismic calibration, which were influenced by structural discontinuities. In contrast, Type C showed physical isolation and poor connectivity due to the pinch-out of reservoir sandbodies. Type D, characterized by a higher abundance of rare taxa, suggested a distinct sedimentary-diagenetic environment. Microbial data specifically responded to and integrated multiple geochemical signals, thereby translating limited geochemical variables into high-throughput “biological fingerprints” that allowed refined micro-zonation within connectivity units. This study introduced core-based microbial analysis as a reservoir assessment tool, offering a new biogeochemical perspective for characterizing connectivity in fractured reservoirs and optimizing developmental stratigraphic units.