Abstract

Reliable prediction of reservoir properties and internal reservoir architecture is critical for the exploration and appraisal of hydrocarbon accumulations characterized by complex geological structure and high uncertainty in the spatial distribution of reservoir rocks. This study presents a hybrid event-process algorithm for sedimentary-process modeling of deep-water turbidite systems and demonstrates its applicability to the Achimov Formation in Western Siberia. The proposed methodology combines a regular-grid representation of reconstructed paleotopography with a Lagrangian description of sediment particles and Eulerian reconstruction of flow fields. The terrigenous material is represented by four grain-size fractions: coarse-grained sand, medium-grained sand, silt, and clay. Application of the algorithm made it possible to reproduce the internal architecture of deep-water submarine fans. The modeling results reflect the main principles of lithological differentiation in turbidite bodies: sandy fractions are deposited predominantly in the proximal part of the system, whereas the pelitic component is transported toward more distal areas. The resulting distributions of total thickness and net-to-gross ratio make it possible to delineate areas characterized by increased reservoir development. Comparison of the modeled results with well data showed reliable agreement: for total thickness, the coefficient of determination was R2 = 0.83 with an RMSE of 4.5 m, while for the net-to-gross ratio, it was R2 = 0.81 with an RMSE of 0.08. The model shows that the internal architecture is controlled by morphodynamic feedback between paleorelief inheritance, depocenter filling, and subsequent flow diversion, which leads to compensational lobe stacking. These results indicate that the developed algorithm can be applied to the modeling of deep-water submarine fans. The proposed approach contributes to reducing geological uncertainty and can be used to provide a more reliable basis for identifying prospective zones when planning exploration programs.

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