Journal of Jilin University(Earth Science Edition) ›› 2016, Vol. 46 ›› Issue (3): 930-937.doi: 10.13278/j.cnki.jjuese.201603307

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Gas-Bearing Logging Features and Quantitative Evaluation for Tight Sandstone Reservoirs

Pan Baozhi1, Jiang Bici1,2, Liu Wenbin1, Fang Chunhui1, Zhang Rui1   

  1. 1. College of GeoExploration Science and Technology, Jilin University, Changchun 130026, China;
    2. Xi'an Research Institute of China Coal Technology and Engineering Group Corp, Xi'an 710077, China
  • Received:2015-09-09 Online:2016-05-26 Published:2016-05-26
  • Supported by:

    Supported by the National Nature Science Foundation (41174096) and the 12th Five-Year Major Projects(2011ZX05040-002)

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Abstract:

Tight sandstone reservoirs always show the characteristics, such as, low porosity, low permeability, and strong heterogeneity.The logging response characteristics corresponding to gas-bearing reservoir is very complex, so that the identification and evaluation of gas are difficult and it always shows multiple solution. Conventional well log is used for qualitative evaluating the gas-bearing characteristics.However, the classification model in intelligent recognition method still belongs to qualitative evaluation, which makes the traditional well log difficult to quantitatively evaluate gas.We use the core, geology, gas testing and conventional logging data to analyze the gas characteristics by cross-plot method and build two indexes, which can be used for qualitatively evaluating the gas containing. The workflow includes the generalized regression neural network (GRNN)that reconstructs gas and water indication curve to quantitatively evaluate the gas containing. Finally, we used the index method and GRNN curve reconstruction method to evaluate the tight sandstone gas in the Sulige area.The results show the good application effects.

Key words: tight sandstone, gas-bearing quantitativeevaluation, curve reconstruction, GRNN, index method, Sulige area

CLC Number: 

  • P631.8

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