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[Super-low-frequency spectrum analysis for buried faults in coalfield]
Li Chen1, Qi-Ming Qin, Guang-Wei Zhen
1Institute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, China. chenlixyz@163.com
Guang Pu Xue Yu Guang Pu Fen Xi = Guang Pu
|October 29, 2013
Summary
Super-low-frequency (SLF) electromagnetic detection effectively identifies buried coalfield faults. This advanced technology offers a practical solution for coal mine safety and design.
Area of Science:
- Geophysics
- Electromagnetism
Context:
- Buried fault detection in coalfields is crucial for mine safety and design.
- Current detection methods are limited, necessitating advanced techniques.
- Super-low-frequency (SLF) electromagnetic detection shows promise for addressing these limitations.
Purpose:
- To evaluate the effectiveness of SLF electromagnetic detection for identifying buried faults in coalfields.
- To analyze SLF signal characteristics using wavelet transform for noise reduction.
- To correlate SLF data with geological and seismic information for fault verification.
Summary:
- SLF electromagnetic signals were collected and analyzed using wavelet transform to filter noise.
- Geological interpretation of measurement profiles identified SLF spectrum characteristics of buried faults.
- Integration with seismic data confirmed fault structure distribution in the mining area.
Impact:
- SLF electromagnetic detection provides a rapid and effective method for identifying buried faults.
- This technology has significant practical implications for coal mine production and operational safety.
- The study validates SLF electromagnetic detection as a viable tool for subsurface exploration in mining environments.
