Journal of Jilin University(Earth Science Edition) ›› 2020, Vol. 50 ›› Issue (6): 1639-1647.doi: 10.13278/j.cnki.jjuese.20190160

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Reservoir Classification Method in Second Member of Liushagang Formation in Bailian Area, Fushan Sag

Wei Bo1, Zhao Jianbin1, Wei Yanwei2, Li Zhenlin1, Xiong Kui3   

  1. 1. Logging Co. LTD. Applied Research Institute, CNPC, Xi'an 710077, China;
    2. Daqing Geophysical Second Company, Bureau of Geophysical Prospecting INC., China National Petroleum Corporation, Songyuan 138000, Jilin, China;
    3. Logging Co. LTD. Huabei Branch, CNPC, Renqiu 062550, Hebei, China
  • Received:2019-08-16 Online:2020-11-26 Published:2020-12-11
  • Supported by:
    Supported by Major Scienceand Technology Projects of Petro China Company Limited (2017E-15)

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Abstract: The sandstone reservoir of the Second Member of Liushagang Formation in Bailian area in Fushan sag has the characteristics of deep buried,gravel developed and complex pore structures, which make it difficult to accurately evaluate the effectiveness of the reservoir. Aiming at this, the authors analyzed the core test data firstly to ensure that the main factor affecting the pore structure of the reservoir is the contact property of the skeleton particles, that is, the property of throat. Based on this research, the characterization of the reservoir effectiveness based on mercury intrusion experimental data was carried out, and the characterization of rock pore throat parameters (maximum radius, average radius, median radius, sorting coefficient) and rock porosity was constructed. The comprehensive indices of reservoir seepage and storage capacity were determined in combination with the oil test data to further establish regional reservoir classification criteria. Finally, by using the regression analysis to scale the conventional logging data, the evaluation of reservoir effectiveness using conventional logging data was realized, which is popularized and applied in actual production. The coincidence rate of logging interpretation is increased from 72% to 80%.

Key words: Fushan sag, sandstone, pore structure, reservoir effectiveness, mercury intrusion, reservoir classification

CLC Number: 

  • P618.13
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