Reservoir Engineering

A Classification Method of Tight Sandstone Gas Reservoirs Based on Improved Cloud Model

  • Li Xiaogang ,
  • Liu Xing ,
  • Du Jia ,
  • Yi Liangping ,
  • Wu Luofei ,
  • Xie Binghong
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  • 1. State Key Laboratory of Oil and Gas Reservoir Geology and Exploration, Southwest Petroleum University, Chengdu, Sichuan 610500, China;
    2. China United Coalbed Methane Corporation Ltd., Beijing 100016, China

Received date: 2021-07-20

  Revised date: 2022-03-21

  Online published: 2023-01-09

Abstract

A method of classifying dense sandstone gas reservoirs based on improved cloud model was proposed to address the difficulties in accurate classification of oil and gas reservoirs due to ambiguity and randomness. Five evaluation parameters were preferentially selected according to the characteristics of dense sandstone reservoirs, the classification and grading thresholds of each parameter were determined, the cloud numerical characteristics were calculated with an improved cloud model to generate a cloud map, the certainty of each parameter belonging to different reservoirs was analyzed, and a comprehensive model for reservoir evaluation and classification was established in combination with the weighting coefficients of the parameters. The method was applied to the evaluation of sample wells in Linxing Block, Sulige, and the classification results showed that the high-quality reservoirs of Type I and II were of open-flow capacity, while the open-flow capacity of Type III and Ⅳ reservoirs was relatively low, verifying the feasibility and effectiveness of the established reservoir classification method. The study results are both fuzzy and stochastic, improving the accuracy of reservoir classification and grading, with important guiding significance for field exploration and development.

Cite this article

Li Xiaogang , Liu Xing , Du Jia , Yi Liangping , Wu Luofei , Xie Binghong . A Classification Method of Tight Sandstone Gas Reservoirs Based on Improved Cloud Model[J]. Special Oil & Gas Reservoirs, 2022 , 29(3) : 84 -91 . DOI: 10.3969/j.issn.1006-6535.2022.03.012

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