A novel approach for evaluating the transport capacity of sandstone carriers and determining effective hydrocarbon migration channels: Application to the Pinghu Slope Belt of the Xihu Depression, East China Sea Basin

Preferential hydrocarbon migration pathways are of great significance to reveal and predict large-scale hydrocarbon accumulation. However, hydrocarbon migration within heterogeneous sandstone carriers is highly complex and involves geological and technical uncertainties. In this study, the hydrocarbon flow coefficient (Chf) considering the sandstone heterogeneity and fluid properties was first defined to quantify the seepage performance of sandstone carriers using experimental, geological and geophysical techniques. Through twodimensional numerical simulation, the hydrocarbon convergence coefficient (Chc) was proposed to characterize the differential hydrocarbon convergence controlled by structural morphology. These two parameters were then integrated into the hydrocarbon transport coefficient (Cht) to comprehensively evaluate the hydrocarbon transport capacity of sandstone carrier, and finally combined with the charging conditions to determine the effective migration channels. The Pinghu Formation in the Pinghu slope belt of Xihu Depression, East China Sea Basin, characterized by large-scale lateral migration of hydrocarbons, is selected as a case study. The results demonstrate that only sandstone carriers with Cht values greater than 10 cm2/s and extensive contact with mature source rocks can serve as effective migration channels. In the effective channels with insufficient hydrocarbon supply, the migration intensity decreases rapidly and only small-scale hydrocarbon migration occurs, while the effective channels with sufficient hydrocarbon supply are accompanied by large-scale hydrocarbon occurrence and the migration intensity weakens slowly. Consequently, three effective channels conducive to hydrocarbon migration were determined in the sandstone carrier units of Pinghu Formation. The quantitative method in this study can be used to predict preferential hydrocarbon migration pathways and reduce exploration risks.