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Coal Geology & Exploration

Abstract

Background Reflected in-seam wave detection represents a major method for exploring geological anomalies in underground coal mines. This method is well suited to detecting concealed structures (e.g., faults and collapse columns) within coal seams in the tunneling direction of roadways or along their side walls. In recent years, to meet the safety requirements of green mine construction, explosive sources have been substituted with mechanical hammer impacts in increasing reflected in-seam wave detection. However, compared to conventional explosive sources, hammer impacts exhibit significantly lower instantaneous energy intensity and consistency. These limitations lead to reduced quality of reflected in-seam wave imaging, thus compromising the accuracy and reliability of the detection results. Objective and Method To achieve effective reflected in-seam wave imaging under mechanical hammer impacts as seismic sources, local-consistency-based weighted stacking, instead of conventional direct stacking, was applied to images of multiple gathers. Specifically, each common-shot or common-receiver gather is first subjected to diffraction migration imaging. Then, at each image point, the local similarity between the image of the current gather and images of its adjacent gathers is determined using the structural similarity index (SSIM). The SSIM values are then used to set weighting factors for various points in the current gather image. Lastly, the weighted stacking of all gather images yields the final reflected in-seam wave image. This SSIM-based weighting strategy ensures that regions with high similarity in the gather images exert a more significant influence on the final image, thus suppressing the impacts of mine vibration noise and source-receiver inconsistency and further enhancing imaging quality. Results and Conclusions A fault-bearing numerical model was designed and established based on the geological conditions of a typical mining face and roadway tunneling. Three-dimensional (3D) elastic wave forward modeling was then performed to generate in-seam wave data. Subsequently, fault imaging was conducted using conventional direct stacking and the improved SSIM-weighted stacking for reflected in-seam waves. While direct stacking concentrated fault anomalies in the central part of the image, the SSIM-weighted stacking derived more significantly extended fault anomaly zones, reflecting the fault morphology more accurately. In practical engineering, field trials were conducted to detect faults encountered by roadway tunneling using explosive sources and concealed faults using mechanical hammer impacts. The results indicate that in all images derived using local SSIM-weighted stacking, fault anomalies with improved lateral extension were presented. Notably, in the case where mechanical hammer impacts were employed as seismic sources to detect three faults within the side walls of the roadway, the conventional direct stacking produced a disordered image where small edge faults were indistinguishable, making it difficult to pinpoint these faults through interpretation. In contrast, the image derived using SSIM-weighted stacking exhibited continuous anomaly bands, clearly reflecting the major fault morphology and presenting distinct minor faults. The faults determined through interpretation were subsequently verified through borehole drilling by the mining company, confirming that SSIM-weighted stacking is more applicable to non-explosive sources such as mechanical hammer impacts. With continuous innovations in intelligent coal mining modes, this novel method will enable the flexible application of reflected in-seam wave detection.

Keywords

in-seam wave detection, reflected in-seam wave, migration imaging, advance detection, structural similarity index (SSIM), mechanical hammer-impact as a seismic source

DOI

10.12363/issn.1001-1986.26.02.0091

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