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Volume 20 Issue 6
Dec 2009
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Article Contents
Liqun Chen, Changchun Zou, Zhonghao Wang, Haijun Liu, Shuang Yao, Dong Chen. Logging Evaluation Method of Low Resistivity Reservoir—A Case Study of Well Block DX12 in Junggar Basin. Journal of Earth Science, 2009, 20(6): 1003-1011. doi: 10.1007/s12583-009-0086-0
Citation: Liqun Chen, Changchun Zou, Zhonghao Wang, Haijun Liu, Shuang Yao, Dong Chen. Logging Evaluation Method of Low Resistivity Reservoir—A Case Study of Well Block DX12 in Junggar Basin. Journal of Earth Science, 2009, 20(6): 1003-1011. doi: 10.1007/s12583-009-0086-0

Logging Evaluation Method of Low Resistivity Reservoir—A Case Study of Well Block DX12 in Junggar Basin

doi: 10.1007/s12583-009-0086-0
Funds:

the PetroChina Xinjiang Oilfield Exploration & Production Research Institute 

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  • Corresponding author: Chen Liqun, taitan_winter@163.com
  • Received Date: 13 May 2009
  • Accepted Date: 30 Aug 2009
  • The Hutubi (呼图壁) River reservoir of well block DX12 is a lithologic hydrocarbon reservoir that is under tectonic settings. The main oil-bearing sand body in this area is thin and has a poor transverse connectivity. Because of the complexity of the oil-water relationship, the oil reservoir presents a low resistivity feature, which brings great difficulties to hydrocarbon reservoir identification. This article develops an effective method of well log interpretation that can meet the requirement of low resistivity reservoir well logging evaluation. The authors combine the oil reservoir geology feature, the oil well logging curve characteristics and chemical analytical data to analyze the reasons for low resistivity, then establish the appropriate reservoir parameter explanation model, which uses different saturation computational methods according to different generations. When the clay content is more than 5%, we select W-S dual water model; when the shale content is more than 13%, we use the Schlumberger formula; when the shale content is less then 13%, we use Archie's formula. The well logging evaluation method of low resistivity reservoir has been improved by the irreducible water saturation formula which is established by the permeability, the porosity, the coefficient of pore structure and the shale content, hydrocarbon reservoir recognition charts, and the non-resistivity logging methods (repeat formation test (RFT); modular dynamic test (MDT), etc.). The coincidence rate for this arrangement of the well logging integrated interpretation is 82.6% in the well block DX12. It is a powerful direction for low resistivity well log interpretation.

     

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  • Archie, G. E., 1942. The Electrical Resistivity Log as an Aid in Determining Some Reservoir Characteristics. Trabsactions AIME, 146: 54–62 doi: 10.2118/942054-G
    Clavier, C., Coates, G., Dumanoir, J., 1984. The Theoretical and Experimental Bases for the "Dual Water" Model for Interpretation of Shaly Sands. Society of Petroleum Engineers Journal, 24(2): 153–168 doi: 10.2118/6859-PA
    Givens, W. W., 1987. A Conductive Rock Matrix Model (CRMM) for the Analysis of Low-Contrast Resistivity Formation. The Log Analyst, 28(2): 138–151
    Hill, H. J., Milburn, J. D., 1956. Effect of Clay and Water Salinity on Electrochemical Behavior of Reservoir Rocks. SPE Reprint Series, 55: 31–38
    Jing, J. E., Wei, W. B., Jin, S., et al., 2007. A Study on the Classification and Well-Logging Identification of Eclogite in the Main Hole of Chinese Continental Scientific Drilling Project. Journal of China University of Geosciences, 18(4): 357–365 doi: 10.1016/S1002-0705(08)60017-5
    Silva, P. L., Bassiouni, D., 1986. Statistical Evalution of the S-B Conductivity Model for Water-Bearing Shaly Formations. The Log Analyst, 27(3): 9–19
    Song, Y. J., Wang, Q., Yin, C. H., 1995. A New S-B Conductivity Model for Determining Water Saturation of Shaly Sands. Well Logging Technology, 19(4): 244–249 (in Chinese with English Abstract)
    Tan, J. D., 1997. Typical Example of Hydrocarbon Reservoir Discovery by Logging Data Interpretation. Oil Geophysical Prospecting, 32(1): 16–25 (in Chinese with English Abstract)
    Tobola, D. P., Holditch, S. A., 1991. Determination of Reservoir Permeability from Repeated Induction Logging. SPE Formation Evaluation, l6(1): 20–26
    Wang, Z. H., Zhang, C. G., Chai, C. Y., et al., 2004. Log Identification Model of Low Permeability Reservoir Type. Natural Gas Industry, 24(9): 36–38 (in Chinese with English Abstract)
    Waxman, M. S., Thomas, E. C., 1974. Electrical Conductivities in Oil-Bearing Shaly Sands; I. The Relation between Hydrocarbon Saturation and Resistivity Index; II. The Temperature Coefficient of Electrical Conductivity. SPE Journal, 26(2): 213–225
    Zhao, J., Song, F., 2004. Genesis and Evaluation of Low Resistivity Oil Formation in Tarim Basin. Earth Science-Journal of China University of Geosciences, 29(3): 317–322 (in Chinese with English Abstract)
    Zou, C. C., 2003. Logging Tool Response Characteristic Analysis of Natural Gas Hydrate Reservoir. World Well Logging Technology, 16(6): 32–35 (in Chinese with English Abstract)
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