In the deep mining areas of western China, there exist ultrathick and weak cementation strata in the overburdens above the Jurassic coal seams, and the overburden lithology is generally moderately a little weaker than the medium-hard strata. Yet, the practical measurement indicates that the surface movement rule in this area displays the specialty that is apparently inconsistent with its lithology, which increases the uncertainty of safe production in coal mines. In this study, the similar material and numerical simulations were conducted to investigate the movement rule and failure pattern of the ultrathick and weak cementation overburden. In addition, the photographing scale transformation-time baseline parallax (PST-TBP) method was used to monitor the similar material model to makeup for the lacks of Xi'an Jiaotong University Digital Close-range Industrial Photogrammetry System (XJTUDP) software. The findings of this study can be summarized as follows. (1) To some extent, the PST-TBP method can makeup for the deficiency of the XJTUDP software because the measurement accuracy of the PST-TBP method is 0.47 mm. (2) The height of the caving zone is approximately 66 m, and the height of the water suture zone is about 112 m, which is obviously larger than that of the medium-hard and soft overburden in eastern-central China. (3) The first breaking span of the immediate roof reaches 120 m, the cyclic fracturing length is about 60 m, and the separation occurred at 43 m and 66 m above the coal seam. (4) The failure pattern of the ultrathick and weak cementation overburden is “beam-arch shell,” and the failure boundary is arch. (5) The Zhidan group sandstone and Jurassic sandstone formations have strong control effects. The Zhidan group sandstone is the main control stratum and the Jurassic sandstone formation is the secondary-control stratum. The research results provide an insight into guiding the safe mining of deep coal in the ultrathick and weak cementation overburden.

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Although big data are widely used in various fields, its application is still rare in the study of mining subsidence prediction (MSP) caused by underground mining. Traditional research in MSP has the problem of oversimplifying geological mining conditions, ignoring the fluctuation of rock layers with space. In the context of geospatial big data, a data-intensive FLAC 3D (Fast Lagrangian Analysis of a Continua in 3 Dimensions) model is proposed in this paper based on borehole logs. In the modeling process, we developed a method to handle geospatial big data and were able to make full use of borehole logs. The effectiveness of the proposed method was verified by comparing the results of the traditional method, proposed method, and field observation. The findings show that the proposed method has obvious advantages over the traditional prediction results. The relative error of the maximum surface subsidence predicted by the proposed method decreased by 93.7% and the standard deviation of the prediction results (which was 70 points) decreased by 39.4%, on average. The data-intensive modeling method is of great significance for improving the accuracy of mining subsidence predictions.

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