As one of the most common disasters in deep mine roadway, floor heave has caused serious obstacles to mine transportation and normal production activities. The third section winch roadway in the third mining area of Qitaihe Longhu coal mine has a serious floor heave due to the large buried depths of the roadway and the semicoal rock roadway, and the maximum floor heave is 750 mm. For the problem of floor stability, this paper establishes a mechanical model to analyze the stability of roadway floor heave by analogy with the basement heave of deep foundation pit. It provides a model reference for analyzing the problem of roadway floor heave. Aiming at the problem of roadway floor heave in Longhu coal mine, the roadway model is established by using FLAC3D, and the roadway model after support is established according to the on-site support measures. Through the analysis of the distribution of roadway plastic area, stress nephogram, and displacement field simulation results, the results show that the maximum displacement of roadway roof and floor after support is reduced by 15% and 23%, but the maximum floor heave is still 770 mm, which is close to the measured floor heave of roadway. In order to solve the problem of roadway floor heave and integrate economic factors, this paper puts forward three support optimization schemes, simulates the support effect of each scheme, and finally determines that scheme 3 is the best support optimization scheme. Compared with that under the original support, the amount of floor heave is reduced by 81%, and the final amount of floor heave is 150 mm, which can meet the requirements of roadway floor deformation. The results provide a scheme and guidance for roadway support optimization.
One of the primary factors affecting safe and effective mining in fully mechanized mining faces with large mining heights is coal wall sloughing. This paper establishes the mechanical model of the coal wall and uses the deflection theory for the mechanics of materials to find the maximum point of the deflection of the coal wall, which is the most easily deformed and damaged during the mining process, based on the mining production conditions of the 12-2up108 working face in the Jinjitan Coal Mine. In order to simulate the characteristics of the coal wall in the large mining height working face at various mining heights, the FLAC-3D numerical method was used. The stability of the mining area was assessed in conjunction with the multi-factor fuzzy comprehensive evaluation mathematical model, and the corresponding control of the coal wall was suggested. The study demonstrates that: (1) The working surface at Jinjitan Coal Mine 112-2up108 is a typical drum-out sloughing. The coal wall is most likely to sustain damage at the point where it contacts the roof when the frictional resistance between the coal seam and the roof and floor is less than the uniform load, and at 0.578 times the mining height when the frictional resistance between the coal seam and the roof and floor is greater than the uniform load. (2) In the working face with a large mining height, mining height of the coal wall is one of the significant influencing factors. With increasing mining height, the coal wall’s height also rises nonlinearly, as does the depth of the coal wall in the working face with the large mining height. The growth is linear. The coal wall’s maximum deflection value point moves up and the slab’s height significantly increases when the mining height exceeds 7.5 m. (3) The Jinjitan Coal Mine should be supported by a pressurized and enhanced composite support bracket with a support force greater than 0.245 MPa and a support plate of 3500 mm because it belongs to a Class I stable coal wall, according to a thorough evaluation of a multi-factor fuzzy mathematical model. The working face’s mining pressure is continuously and dynamically monitored, and the stress is released in a timely manner to prevent the occurrence of dynamic disasters.
The pore structure and its complexity and heterogeneity control the occurrence states and fluidity of shale oil. The multifractal theory effectively characterizes the complexity and heterogeneity of the shale pore structure. In this study, serial technologies were applied to detect the pore systems of shale obtained from Dongying Sag, Bohai Bay Basin in China. The multifractal characteristics of the pore structure of the shale were analyzed based on its nuclear magnetic resonance (NMR) T 2 spectrum. The analysis results show that shale oil reservoirs can be classified into four types based on their T 2 spectra. Type I shales T 2 spectra show large p2 (1−20 ms), moderate p3 (>20 ms), but little p1 (<1 ms), characterized by large NMR and connected porosity, the lowest BET specific surface area (SSA), and the largest average pore throat diameter and S 1 contents. Large p2, moderate p1, and tiny p3 are the main distinctions of type II shales with the largest NMR porosity, large connected porosity, and BET SSA. The T 2 spectra of type III shales have large p1, moderate p2, and little p3, corresponding to large NMR porosity and BET SSA and the largest total organic content (TOC) and S 1 contents but lower connected porosity. Type IV shales have the most significant contents of micropores with the relatively largest p1 in the T 2 spectra characterized by the lowest NMR and connected porosity, the largest BET SSA, the lowest TOC, and S 1 contents but the largest clay mineral contents. Both types III and IV shales are unfavorable shale oil reservoirs. D q decreases monotonically as q increases, indicating the multifractal nature of shale pore structures. D 0 varies from 0.88 to 1.00 (mean: 0.95), and Δα ranges from 1.24 to 2.82 (mean: 1.79), suggesting complex and heterogeneous pore structures. Types I and II shales have lower D 0 values than types III and IV shales. Thus, type I organic-bearing massive felsic and type II organic-rich layered calcareous shales are favorable for shale oil reservoirs with large pores and large porosity. They have the least complex pore structures among the four shale types considered.
Abstract. With the launch of altimetry satellites with different observation frequencies and different survey missions, it is necessary to integrate multi-satellites altimeter data to establish a new global marine gravity anomaly model. Based on Ka-band SSHs from SARAL/AltiKA and Ku-band SSHs from other satellites (including HY-2A) in geodetic missions and exact repeat missions, the global marine gravity anomaly model of SDUST2021GRA on a 1′×1′ grid is derived. Gridded deflections of vertical (DOVs) are determined from along-track geoid gradients by the least-squares collocation method, in which the noise variances of along-track geoid gradients are obtained by the iteration method for Ka-band geodetic mission and by the SSH crossover discrepancies for other altimetry missions. SDUST2021GRA is recovered from the gridded DOVs by the inverse Vening-Meinesz formula, and analyzed by comparing with the recognized marine gravity anomaly models of DTU17 and SIO V30.1. Final, the accuracy of SDUST2021GRA, DTU17 and SIO V30.1 is assessed by preprocessed shipborne gravity anomalies. In conclusion, the differences between SDUST2021GRA and recognized models are small, indicating the reliability of SDUST2021GRA. The differences are mainly concentrated between -5 mGal and 5 mGal, which accounts for more than 95 % of the total number. Assessed by shipborne gravity, the accuracy of SDUST2021GRA is 2.37 mGal in the global, which is higher than that of DTU17 (2.74 mGal) and SIO V30.1(2.69 mGal). The precision advantage of SDUST2021GRA is mainly concentrated in offshore areas. SDUST2021GRA is concluded to reach an international advanced level for the altimeter-derived marine gravity model, especially in the offshore area. The SDUST2021GRA model are freely available at the site of https://doi.org/10.5281/zenodo.6668159 (Zhu et al., 2022).
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