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RETRACTED ARTICLE: Research on shale gas productivity prediction method based on optimization algorithm

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This article was retracted on 01 April 2024

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Abstract

Shale gas, as one of the new natural gas deposits, has been widely concerned. Due to the multi-stage fracturing technology of horizontal wells used in shale gas development, frequent opening and closing of gas wells, and complicated characteristics of gas reservoirs, the problem of productivity prediction has not been well solved. At home and abroad, the empirical formula methods, analytical methods based on seepage theory, and reservoir numerical simulation methods are mainly used for shale gas productivity prediction. The common problem of these methods is that the productivity prediction accuracy is not high and it can not effectively guide shale gas development. In this paper, the traditional productivity prediction method is improved by using machine learning, the characteristics that represent the productivity change of gas wells are selected, and the optimization algorithm with strong classification ability for small sample data is introduced to establish an effective productivity prediction model. The model has been applied to the gas reservoir production prediction of a platform in Chinese Southwest Region and achieved high productivity evaluation accuracy, which proved to be a useful supplement to the traditional productivity prediction methods.

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Acknowledgements

The authors sincerely thank the reviewers for their valuable comments that helped us to improve the quality of the paper. This work was supported in part by Anhui Provincial Scientific research projects (KJ2021A1194), Anhui Provincial Academic program for top professional talents (gxbjZD2022090), Anhui Wenda Information Engineering College scientific research project (XZR2021A18) and University Natural Sciences Research Project of Anhui Province (Project Number: 2022AH051797).

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Authors and Affiliations

  1. School of Computer Engineering, AnHui WenDa University of Information Engineering, Hefei, 231201, People’s Republic of China

    Shaowei Zhang, Mengzi Zhang & Zhen Wang

  2. School of Artificial Intelligence and Big Data, Hefei University, Hefei, 230601, People’s Republic of China

    Rongwang Yin

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  1. Shaowei Zhang
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  2. Mengzi Zhang
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  3. Zhen Wang
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Correspondence to Rongwang Yin.

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This article has been retracted. Please see the retraction notice for more detail:https://doi.org/10.1007/s10878-024-01137-7

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Zhang, S., Zhang, M., Wang, Z. et al. RETRACTED ARTICLE: Research on shale gas productivity prediction method based on optimization algorithm. J Comb Optim 45, 123 (2023). https://doi.org/10.1007/s10878-023-01049-y

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  • DOI: https://doi.org/10.1007/s10878-023-01049-y

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