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This invention establishes a method and system for three-dimensional facies-controlled sand body modeling and connectivity evaluation. The method is based on a dimensionality-reduction modeling architecture: a planar sedimentary facies distribution map is generated through probability-guided sequential indicator simulation; under the constraint of planar facies zones, a one-dimensional vertical sequence of interbedded sand and mud layers is independently generated point-by-point using probabilistic sampling; the planar facies map and the vertical sequence are stitched together in three-dimensional space; then, based on graph theory undirected graph algorithms, the connectivity of the three-dimensional sand body is identified using vertical depth interval overlap and non-interlayer occlusion as dual criteria; finally, connectivity uncertainty is quantified through Monte Carlo iteration. Compared with traditional full-3D grid sequential Gaussian simulation, this method is applicable to clastic reservoirs with gradual lateral variation and dominant vertical accretion (lateral variation coefficient of planar facies zones less than 0.3). It eliminates the computationally expensive three-dimensional spatial interpolation and complex structural modeling, forming a simplified engineering path of "trading computational power for uncertainty assessment," which can be used for reservoir connectivity evaluation and development scheme optimization.