Method of Predicting Surface Subsidence Caused by Underground Mining: A Review

Authors

  • Huy Dinh NGUYEN Author
  • Trong Dinh TRAN Author
  • Canh Van LE Author
  • Stanisław PIETRZYK Author

DOI:

https://doi.org/10.29227/IM-2024-01-91

Keywords:

subsidence prediction, underground mining, artificial neural networks

Abstract

In recent years, there has been a global increase in energy demand, with the extraction of underground mineral energy sources such as coal playing a significant role in the energy supply. However, the extraction of these natural resources always faces many challenges and risks. This process has created large voids, causing an imbalance in the original stress state within the earth and resulting in surface terrain deformations. Therefore, ensuring efficient extraction must be accompanied by safety measures. Among these, predicting surface subsidence due to underground mining is a crucial task. This paper presents an overview of the current method of predicting mining subsidence and their application scope. The result synthesizes various methodologies applied to different regions worldwide. Finally, the findings of this research can provide guidelines for establishing essential requirements for the application of surface displacement forecasting technologies due to underground mining.

Author Biographies

  • Huy Dinh NGUYEN

    1) Faculty of Bridges and Roads, 55 Giai Phong Street, Hanoi University of Civil Engineering, Hanoi, Vietnam; ORCID https://orcid.org/0000-0002-2049-3338

  • Trong Dinh TRAN

    3) Faculty of Bridges and Roads, 55 Giai Phong Street, Hanoi University of Civil Engineering, Hanoi, Vietnam; ORCID https://orcid.org/0000-0002-8113-9949

  • Canh Van LE

    2) Faculty of Geomatics and Land Administration, 18 Vien street, Hanoi University of Mining and Geology, Hanoi, Vietnam; ORCID https://orcid.org/0000-0002-3838-9950

  • Stanisław PIETRZYK

    4) AGH; ORCID https://orcid.org/0000-0002-2240-3332

Published

2024-08-01

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