多物源输入背景下页岩岩相发育类型及页岩油潜力OA

The shales developed in continental rifted lacustrine basins in the eastern part of China have shown promising potential of shale oil exploration.However,influenced by multi-provenance inputs,these shales exhibit complex lithofacies and significant heterogeneity in shale oil accumulation.Therefore,we investigated the 3rd lower sub-member of Shahejie Formation in the Gubei Sag,Bohai Bay Basin,to unravel the developmental pat-terns of shale lithofacies under multi-provenance condition,elucidate differential shale oil enrichment in different lithofacies,and thereby evaluate the resource potential.Key findings reveal that in the ternary discrimination of carbonate,felsic,and clayey terminals for shale lithofacies,the clay-rich hybrid lithofacies exhibits optimal oil content due to high organic matter abundance,dominance of Type I kerogen,well-developed micropore-fracture network formed by oriented arrangement of illite/smectite mixed layers,and high hydrocarbon retention effi-ciency.The carbonate-rich and felsic-rich hybrid lithofacies display moderate oil content.In contrast,the felsic-carbonate lithofacies,despite possessing the highest brittleness index,shows the lowest organic matter abundance and oil content.Reservoir spaces in different lithofacies are dominated by micron-scale dissolution pores,inter-crystalline pores,and clay interlayer fractures.Importantly,the predominant orientation of high-conductivity frac-tures aligns with the present maximum horizontal principal stress,which significantly enhanced the potential for generating complex fracture networks during hydraulic fracturing.Comprehensive analysis of crude oil properties(light-medium oil)and over-pressured zone distribution identified that the eastern subsag and northern central up-lift in the study area are the"sweet spots"of shale oil accumulation.This study provided a guidance to the ex-ploration deployment in the Gubei Sag with theoretical insights for shale oil exploration in similar continental rift lacustrine basins with strong multi-provenance inputs.