# A New Method of Geological Modeling for the Hydrocarbon Secondary Migration Research
## 1 Introduction  
Since the 1970s, the field of computer science has undergone rapid development, leading to an increased use of numerical modeling for various purposes related to underground oil and gas resources. These include the quantitative assessment of resources, the prediction of exploration targets, and the design of recovery schemes [1; 2; 3; 4; 5; 6; 7]. A comprehensive geological model encompasses important elements such as tectonic structures, sedimentary facies distribution, and petrophysical properties like porosity and permeability. The accuracy of geological modeling, particularly in three dimensions, forms the foundation for the subsequent numerical modeling used in decision-making processes within the field of oil and gas exploration and production. An unreliable geological model can result in unfeasible simulations of reservoir/hydrocarbon migration and hinder effective decision making [8; 9; 10; 11; 12]. Geological modeling work is based on various data sources, including well logs, seismic interpretations, net-to-gross data, and property measurements, among others. The primary objective is to interpolate missing data, and interpolation methods can generally be categorized as deterministic or stochastic [8; 13]. The deterministic method widely known for interpolation in geological modeling is the Kriging method, initially employed in ore body modeling [14]. However, it tends to produce smooth results due to its reliance on the variogram. Since geological bodies are typically heterogeneous and possess non-smooth properties, the predictions made by the Kriging method are often considered unreliable [15]. On the other hand, stochastic methods such as Sequential Gaussian Simulation and Sequential Indicator Simulation generate multiple results that follow the same probability distribution, thereby accommodating uncertainties by producing realizations that align better with the available data [16]. These methods discretize the model space into hexahedral cells or pixels in three dimensions. Nonetheless, pixel-based methods may fail to capture the geometries and internal structures of sand bodies and sedimentary facies. To address this limitation, object-based methods were introduced [2], which involve creating geological objects with defined geometries and generating them statistically using stochastic methods within the geological model space [17]. In 1978, [PERSON] introduced the term \"architecture\" to the field of river sedimentation, establishing the concept of \"fluvial architecture\" [18]. Expanding on [PERSON]'s work, [PERSON] [19] presented analytical methods for studying the architectural elements of fluvial facies within reservoirs. The notion of architecture elements and interfaces was introduced, with reservoir architecture being defined as \"the geometry, size, orientation, and relationships of the reservoir and its internal components\". When diagenesis and fracture formation exert minimal influence, the sedimentary architecture becomes the dominant factor in determining the hierarchical structure of the reservoir, primarily guided by the architecture interface [19; 20]. During the development phase of an oil field, fluid movement within the reservoir encounters various flow barriers that significantly influence the formation and distribution of residual oil. Therefore, comprehending the architecture of underground reservoirs is crucial for enhancing hydrocarbon recovery and maximizing the development of oil and gas resources [21]. With the advancement of oil and gas exploration research, there is an increasing emphasis on understanding the heterogeneity of carrier beds and their impact on hydrocarbon accumulation [22]. The distribution, internal structure, and geometry of sand bodies have a significant influence on the migration pathway of hydrocarbons and the amount accumulated in traps [23; 24]. Hence, it is imperative for geological models to accurately capture sedimentary and tectonic heterogeneity.