The grains composing the skeleton of conglomerate typically exhibit multiple particle size gradations, poor sorting, and strong heterogeneity, leading to complex pore structure characteristics and petrophysical relationships, which make it difficult to establish an effective logging method for water saturation calculation. Despite its poor sorting, conglomerate often displays distinct fractal characteristics. The fractal theory of porous media was combined with conductivity efficiency theory to derive a fractal conductivity efficiency model for conglomerate. Based on this model, a water saturation calculation method was established using fractal conductivity efficiency. Practical well application results demonstrate that, based on obtaining the fractal characteristics of conglomerate formations through nuclear magnetic resonance(NMR) logging, the fractal conductivity efficiency model can significantly improve the accuracy of water saturation calculations in conglomerate formations. The results indicate that fractal parameters, due to their statistical self-similarity and scale invariance, can effectively characterize the pore structure features of conglomerate. This enables accurate calculation of water saturation in conglomerate without the need for logging classification of pore structure types. Thus, it overcomes the challenges posed by strongly heterogeneous formations where logging identification of pore structure types is difficult, which can lead to misclassification of pore structure types and affect calculation accuracy. The established fractal conductivity model is not only applicable to conglomerate formations but can also serve as a reference for water saturation logging calculations in other formations with poor sorting and strong heterogeneity.