The Karamay Formation in the Mahu 446 well district is an important oil-producing layer in the Karamay oilfield.However,the unclear characterization of favorable sandstone bodies in the Upper Karamay Formation has constrained further exploration and development in this area.This paper provides sedimentary fa-cies distribution characteristics and seismic inversion methods to characterize the favorable sandbodies in the T2k22 section of the Upper Karamay Formation in the 446 well area,based on a re-understanding of the sedimen-tary reservoir and geophysical response characteristics of favorable sandstone bodies in the Upper Karamay For-mation.The research suggests that this area belongs to a braided river delta front subfacies sedimentation,which can be mainly divided into four sedimentary microfacies:underwater distributary channels,inter-distributary bays,mouth bars,and sheet sands.The T2k22 section of underwater distributary channels is the most developed and is the primary favorable reservoir development section in this area.The overall provenance of the T2k22 sec-tion comes from the northwest,with the central channels being the most developed and having the most favor-able sedimentary background.The pseudo-acoustic impedance seismic inversion method has a good effect on identifying T2k22 sandbodies,with the impedance boundary at 8 900 g/cm3·m/s,which can identify two sets of fa-vorable channel sandbodies with strong amplitude and high pseudo-acoustic impedance characteristics.Combin-ing sedimentary facies distribution,seismic inversion,and structural features,this study predicts one lithological trap and its range beyond the oil-containing area controlled by the T2k22 section.The trap exhibits a U-shaped distribution,develops approximately 6 m of oil layer,which thins from high to low,covers an area of 8.4 km2,and has a closure of approximately 300 m.
关键词
有利砂体预测/玛湖斜坡/拟声波阻抗/岩性圈闭/克上组
Key words
prediction of favorable sandstone bodies/Mahu slope/pseudo-acoustic impedance/lithological trap/Upper Karamay Formation
维普
万方数据