Study on Overlying Rock Deformation and Surface Subsidence Prediction under Layered Grouting Filling Conditions
DOI:
https://doi.org/10.54097/92622v37Keywords:
Layered filling, surface movement patterns, SBAS-InSAR monitoring, probability integral method, parameter inversionAbstract
To investigate the movement mechanism of overlying rock and surface under layered filling extraction conditions, scientifically evaluate the applicability of traditional prediction models under layered filling conditions, and improve the accuracy of surface subsidence prediction parameters, this paper takes the 1605 layered filling working face of Guhanshan Coal Mine as the engineering background. A comprehensive approach combining long-term field precise levelling measurements, non-contact microwave remote sensing (SBAS-InSAR) monitoring, and parameter optimisation inversion using the probability integral method was employed to conduct an in-depth study of overlying rock and surface movement patterns under layered filling. The study shows that under the disturbance of filling excavation, surface deformation exhibits distinct staged evolution characteristics of "grouting disturbance," "dynamic pressure balance," and finally "rheological stability." The high-pressure grouting filling area shows significant local atypical settlement different from the traditional caving method. SBAS-InSAR technology was used to obtain multi-dimensional surface deformation monitoring results for the entire field, achieving a leap from "point-line" unidirectional control to full "area" coverage in mining area settlement monitoring. On this basis, the limitations of the probability integral method in layered filling mining were explored, and an equivalent mining thickness correction model and optimisation fitting inversion algorithm were established. Engineering verification shows that the corrected probability integral model after parameter inversion can highly fit the measured scatter points, successfully achieving refined prediction of the atypical surface subsidence under layered filling, providing scientific data support for disaster prevention, loss reduction, and optimisation of filling parameters in mining areas.
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