Volume 40 Issue 1
Jan.  2012
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Jiang Guancheng, Wang Xiaojun, Guan Jian, Li Jiancheng, Yang Peng, Guo Linhao. The Quantitative Prediction Method of Water Blocking Damage in Low and Extra-Low Permeability Reservoir[J]. Petroleum Drilling Techniques, 2012, 40(1): 69-73. DOI: 10.3969/j.issn.1001-0890.2012.01.014
Citation: Jiang Guancheng, Wang Xiaojun, Guan Jian, Li Jiancheng, Yang Peng, Guo Linhao. The Quantitative Prediction Method of Water Blocking Damage in Low and Extra-Low Permeability Reservoir[J]. Petroleum Drilling Techniques, 2012, 40(1): 69-73. DOI: 10.3969/j.issn.1001-0890.2012.01.014
shu

The Quantitative Prediction Method of Water Blocking Damage in Low and Extra-Low Permeability Reservoir

  • 1.

    MOE Key Laboratory of Petroleum Engineering(China University of Petroleum(Beijing)), Beijing, 102249, China;

  • 2.

    Engineering Technology Research Institute, PetroChina Great Wall Drilling Company, Panjin, Liaoning, 124010, China

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  • Received Date: July 23, 2010
  • Revised Date: December 07, 2011
    Graphical Abstract
    • Abstract
  • There are very serious damages during the exploitation of low permeability and extra-low permeability reservoirs,and water blocking is the most remarkable damage.So the mathematical model which can accurately and rapidly predict water blocking damage level will play an important role in the effective development of low permeability oilfield.Linear regression analysis was used to establish prediction model of water blocking damage in the past,but the model could not accurately reflect the real damage essence to the reservoir,especially the prediction accuracy was low.As we all know that the non-linear regression model can better reflect the relationship between damage factors and extent of damage than the conventional linear regression model.The stepwise regression method was adopted to select regression factors and the new water blocking damage prediction model was established.The test results for the new model indicated that,the new model had higher accuracy than the conventional one,for example,the prediction accuracy rate of 15 tested samples were greater than 80%,and the average prediction accuracy rate was 91.69%.It will provide evidence for reservoir protection and measures to optimize the design of reservoir unplugging.
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    • References (15)
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