Multiscale Fractal Characterization of Pore Structure and Reservoir Quality Based on Deep-Learning-Assisted Pore Extraction in the Majiagou Tight Dolomite Gas Reservoir, Central Ordos Basin, China

Tight dolomite gas reservoirs are promising exploration targets, yet their evaluation is complicated by multiscale pore-throat heterogeneity and poor seepage connectivity. Here, high-pressure mercury intrusion (HPMI), nuclear magnetic resonance (NMR), scanning electron microscopy (SEM), and deep-learning-assisted pore extraction were integrated to characterize the pore-throat structure and fractal features of the Middle Ordovician Majiagou Formation in the Ordos Basin. The reservoir is dominated by diagenetic-origin pores, mainly intercrystalline and intragranular dissolution pores, together with microfractures, and can be classified into three types with progressively poorer connectivity and flow capacity. Type I reservoirs contain more regular pores, larger pore-throat systems, and better storage and seepage capacity; Type II reservoirs are intermediate, whereas Type III reservoirs exhibit complex pore morphology, isolated pore networks, poor petrophysical properties, and limited gas-flow potential. The corresponding fractal dimensions are weakly correlated but complementary: DSEM captures pore-boundary complexity, DHPMI reflects pore-throat architecture and capillary-pressure-controlled seepage pathways, and DNMR reflects multiscale movable-fluid distribution. Clay minerals, especially illite-rich mixed layers, further intensify pore-throat heterogeneity. Increasing fractal dimension is generally associated with higher displacement and median pressures, but poorer connectivity, porosity, permeability, movable-fluid content, and gas deliverability. These results provide a basis for the quantitative evaluation of multiscale pore systems and reservoir quality in tight dolomite gas reservoirs.