journal article·2025-01-25Open access

Detection of Rock Mass Defects Using Seismic Tomography

Zheng Jian, Guoyan Zhao, Ju Ma, Leilei Liu, Weizhang Liang, Shuang Wu

Applied Sciences· Volume 15· Issue 3

Abstract

Elastic wave tomography is a non-destructive technique used to obtain velocity images of internal structures. Wave velocity tomography has been used to quantitatively describe abnormal structures and identify boundaries in different media and shapes. This research aims to quantitatively describe anomalous structures on a laboratory scale and identify boundaries in different media and shapes. Wave velocity tomography technology was applied to non-empty and empty anomalous areas, and the accuracy of the resulting velocity images was quantified. The reliability of boundary recognition was studied and analyzed. The accuracy of the results was found to relate to the size and shape of the anomalous structures estimated in the prior model, as well as the wave velocity difference between the anomalous and normal regions. In practical engineering, when the presence of abnormal areas cannot be determined, a completely homogeneous prior model is used. The results indicate that, although the inversion velocity may not be accurate, it is sufficient to identify boundaries. The larger the velocity difference, the clearer the boundary to be recognized. Furthermore, to assess the practical efficacy of this physical detection method, the wave velocity tomography technology was used to detect hidden goafs within a tantalum–niobium mine belonging to the Hunan Fuguihengtong Mining Company. Utilizing physical detection, 12 potential goafs and 100 confirmed goafs were identified within the mine, demonstrating the efficacy of the proposed empty anomalous area detection methodology in accurately identifying and delineating the boundaries of hidden goafs.
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Research context

OpenAlex topics: Seismic Imaging and Inversion Techniques · Seismic Waves and Analysis · Drilling and Well Engineering

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Resources and Safety Engineering, Central South University, Changsha 410083, China

Funding

National Natural Science Foundation of China

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