Research on Anti-Scour Effect of Coal Seam Water Injection Based on Electromagnetic and Microseismic Signal Monitoring

ABSTRACT

The aim of this study was to examine the accuracy of electromagnetic radiation and microseismic signals in determining the anti-scour effect resulting from coal seam water injection. We established a simultaneous acquisition system of electromagnetic and microseismic full waveforms for coal rock damages under load, and an image acquisition system that captured the entire coal damage process was used. Uniaxial compression experiments of coal samples with different moisture contents were conducted, and the influence of water on the physical and mechanical properties of the coal samples and the generation of electromagnetic and microseismic signals were theoretically analyzed. The results showed that water reduced the adhesion and friction coefficient of particles in the coal body, promoted coal and rock fracture development, and weakened the generation of electromagnetic and microseismic signals. A significant positive correlation was found among stress drop, electromagnetic radiation signals, and microseismic signals, and the temporal distribution of the three variables was synchronous. As moisture content increased, the electromagnetic radiation and microseismic signal amplitude of the coal samples decreased, and the average signal of both signals exhibited an exponential downward trend. The relationship between the mean value of the signal and moisture content was obtained. To evaluate the water-injection effect of the coal samples, we also determined the theoretical percentage of the signal amplitude reduction corresponding to the increment in moisture content required by the on-site coal seam water injection and anti-erosion.

KEYWORDS:

• Uniaxial compression
• electromagnetic radiation
• microseismic monitoring
• moisture content
• coal seam water injection

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

All data, models, and code generated or used during the study appear in the submitted article.

Additional information

Funding

This work was financially supported by the Research and Demonstration of Cloud Warning Technology for Gas Disasters Driven by Multidimensional Data (Qiankehe Support [2021] General 514) and Key research and development and achievement transformation project in the Social Welfare field of the 14th Five-year plan of Inner Mongolia Autonomous Region (2022YFSH0019).