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Quantitative evaluation of low-permeability gas reservoirs based on an improved fuzzy-gray method

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Abstract

Accurate and quantitative evaluation of low-permeability reservoirs and other more complex reservoirs not only depends on various control factors related to the reservoir but is also affected by our incomplete understanding of reservoirs and the imperfections inherent in evaluation methods. The evaluation of reservoirs may be improved by determining the integrity and uncertainty of the reservoir evaluation process and effectively examining the differences between evaluation results. Taking membership as the linking factor, utilizing the idea of information superposition, and combining the fuzzy comprehensive and gray relational evaluation methodologies in the uncertainty evaluation, this study presents a differentiated and improved internal algorithm and establishes a more effective fuzzy-gray comprehensive evaluation method. The example of E32 interval evaluation in the southern Nanbaxian gas field of the Qaidam Basin shows that this method not only considers the fuzziness and grayness related to reservoir evaluation but also provides improved discrimination of low-permeability reservoirs and increased accuracy in the reservoir description. According to the improved reservoir classification results, the E32 intervals are divided into four types of reservoirs, of which types I and II are favorable reservoirs. The lateral distribution of the reservoir is described in more detail than previously, with near-continuous knowledge, and there is a good distinction between the reservoir type. The obtained results are in line with the development rules of geological deposition and the geological knowledge base, approximately matching existing practical results and geological knowledge. This method can be used to quickly and effectively guide exploration and development strategies related to gas fields, and provides a new approach for low permeability and tight reservoir evaluation.

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Authors and Affiliations

  1. College of Energy Resources, Chengdu University of Technology, Chengdu, 610059, People’s Republic of China

    Peng Zhu

  2. School of Earth Science and Engineering, Hebei University of Engineering, Handan, 056038, Hebei, People’s Republic of China

    Zhaoqun Zhu

  3. Exploration and Development Research Institute of PetroChina Changqing Oilfield Company, Xi’an, 710018, People’s Republic of China

    Yuanyuan Zhang

  4. Sino Getech Science and Technology Co., Ltd., Beijing, 100015, People’s Republic of China

    Lianpu Sun

  5. Institute of Sedimentary Geology, Chengdu University of Technology, Chengdu, 610059, People’s Republic of China

    Yixin Dong

  6. China Radio Wave Research Institute, Xinxiang, 453003, Henan, People’s Republic of China

    Zhiqiang Li

  7. CNOOC (China) Co., Ltd. Zhanjiang Branch, Zhanjiang, 524000, Guangdong, People’s Republic of China

    Ming Chen

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  1. Peng Zhu
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  2. Zhaoqun Zhu
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  3. Yuanyuan Zhang
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  4. Lianpu Sun
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  5. Yixin Dong
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  7. Ming Chen
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Correspondence to Peng Zhu.

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Zhu, P., Zhu, Z., Zhang, Y. et al. Quantitative evaluation of low-permeability gas reservoirs based on an improved fuzzy-gray method. Arab J Geosci 12, 80 (2019). https://doi.org/10.1007/s12517-019-4231-5

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  • DOI: https://doi.org/10.1007/s12517-019-4231-5

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