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Volume 44 Issue 5
Sep.  2022
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Article Navigation >  PETROLEUM GEOLOGY & EXPERIMENT  > 2022  >  44(5): 755-760
NIU Huawei, LIU Miao, JIANG Cen, ZHU Lixin, CHEN Maogen. Identification of lithologic trap in coal-bearing stratum of Pingbei area, Xihu Sag, East China Sea Shelf Basin[J]. PETROLEUM GEOLOGY & EXPERIMENT, 2022, 44(5): 755-760. doi: 10.11781/sysydz202205755
Citation: NIU Huawei, LIU Miao, JIANG Cen, ZHU Lixin, CHEN Maogen. Identification of lithologic trap in coal-bearing stratum of Pingbei area, Xihu Sag, East China Sea Shelf Basin[J]. PETROLEUM GEOLOGY & EXPERIMENT, 2022, 44(5): 755-760. doi: 10.11781/sysydz202205755
shu

Identification of lithologic trap in coal-bearing stratum of Pingbei area, Xihu Sag, East China Sea Shelf Basin

doi: 10.11781/sysydz202205755

  • Shanghai Offshore Oil & Gas Company, SINOPEC, Shanghai 200120, China

  • Received Date: 2021-12-07
  • Rev Recd Date: 2022-07-25
  • Publish Date: 2022-09-28
    Abstract
  • In the Pingbei area of Xihu Sag, East China Sea Shelf Basin, the sedimentation of the main target Eocene Pinghu Formation, is significantly affected by tidal action. Thin sand bodies are stacked on top of each other, the lateral changes are fast, and coal seams are developed. The target layer has a depth of bury generally deeper than 3 500 m, and the physical properties of reservoir are relatively poor. The existing seismic data have low signal-to-noise ratio, weak energy, small impedance difference of sand and shale in the deep, and it is difficult for the reservoir prediction and description. Based on deep amplitude-preserved and broadband processing, this paper studied the type of lithologic trap development, characterization of sand reservoir, and implementation of lithologic trap targets. The paleogeomorphic background, sand development pattern and the type of litho-logic trap are defined. Under the constraints of this framework, accurate sandstone description is carried out. The sand reservoir is predicted by comprehensive analysis of seismic waveform, seismic reflection characteristics and the elastic properties of pre-stack inversion, the coal seam distribution is predicted by post-stack statistical inversion, and the accuracy and reliability of sand description are improved.

     

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