## 1 Introduction  
Research on the microporous flow mechanism is crucial in optimizing extraction strategies and improving recovery rates. The accurate characterization of a pore-throat network is the basis of the study of the micro-seepage mechanism of reservoirs [1]. Direct imaging characterization methods of microscopic pore-throat networks include high-resolution focused ion beam scanning electron microscopy (FIB-SEM), transmission electron microscopy, atomic force microscopy (AFM), small-angle X-ray scattering, and nano-computed tomography (CT) [2, 3]. FIB-SEM is known for its high resolution and is used for imaging nanopores, primarily for two-dimensional (2D) observation [4, 5]. High-resolution CT can be used for non-destructive scanning and three-dimensional (3D) reconstruction of pores in samples. However, due to instrument limitations, the accuracy of wide-field CT scans is relatively low [6]. New techniques, such as small-angle neutron scattering (SANS) and ultra-SANS, use neutron beams to penetrate rock samples and obtain information about their pore structure by measuring the intensity of scattered radiation within a specific range [7]. AFMcan be used to image the 3D morphology of shale samples in their real state, showing a pore-throat network composed of micropores and nanopores connected by relatively small throats. However, the drawbacks of this technique are the very small scanning area and slow scanning rate [8; 9]. High-pressure mercury injection porosimetry (MIP) and nuclear magnetic resonance (NMR) are commonly used techniques for quantifying pore size distribution too [10]. However, the test samples of the above technologies are generally smaller, and the imaging scale is small, which cannot directly generate super-sized microscopic pore-throat networks [11]. Microsimulation, including physical simulation and numerical simulation, is an important field in which to study the characteristics of oil-water seepage in reservoirs [12; 13]. Its visualization offers advantages in understanding the laws of micro-scale seepage. At present, how to apply the results of micro-scale seepage to macro-scale is an important problem. One solution is to directly increase the size of the pore-throat network model. This can not only study the flow or phase transition in the pores but also observe the macroscopic distribution characteristics of the fluid. The combined application can systematically clarify the fluid flow mechanisms in reservoirs and effectively evaluate the potential for utilizing remaining oil [14]. The design of the pore-throat network model is the basis of microsimulation. Due to the limitation of image accuracy, the image size obtained by existing microscopic imaging techniques is relatively small. For example, traditionally, the microscopic pore-throat network model was typically based on images obtained from cast slices or CT scans, where the pores and throats were extracted, and the images were then spliced together to enlarge the model [15]. However, the microscopic pore-throat model produced by this method exhibits strong repeatability, but its size remains insufficient. Designing a larger pore-throat network model more efficiently is a fundamental challenge that continues to puzzle researchers studying microscopic seepage. Given the limitations of image-based modeling methods, researchers have explored direct generation techniques for microscopic pore-throat networks, focusing on two main approaches: equivalent modeling and random modeling [16; 17; 18]. The equivalent model is based on the simplified pore throat model, so it is difficult to truly reflect the seepage situation in the complex rock structure [19; 20]. Relatively speaking, the stochastic modeling approach is more effective in characterizing pores and throats, and its technical development is more advanced. In 1974, [PERSON] proposed the Gaussian field method for reconstructing porous media, which enabled the construction of a two-dimensional rock model [21].