The distribution of methane content in the coalbed is complex in the Qinshan Syncline of western Guizhou Province. Analyses of factors controlling on the distribution of gas content are made in this paper. Coal ranks and geo-structure in the region showed strong controls on the gas distribution. Coals with higher degree of metamorphism or located in syncline most likely have higher gas content. With the concept of coalbed methane content unite thickness (CBMCUT), those factors such as coal seam buried depth and coal structure present positive relations with gas content. Results indicated that the variation of CBMCUT is not fixed in different research areas or in different coal structures. Namely, the variation follows "v-shaped" correlation with the increasing coal buried depth in the region of Qinshan Syncline. However, the trend is smooth for the coals in the Panzhuang mining area. Usually, the critical value for primary-texture coal and mylonitized is different based on the analysis of the relationship between coal structure and CBMCUT in those two areas described above. The value is commonly higher in mylonitized coal and lower in those mainly primary-texture and fragmented coals.
The waste mine water is produced in the process of coal mining, which is the main cause of mine flood and environmental pollution. Therefore, economic treatment and efficient reuse of mine water is one of the main research directions in the mining area at present. It is an urgent problem to use an intelligent algorithm to realize optimal allocation and economic reuse of mine water. In order to solve this problem, this paper first designs a reuse mathematical model according to the mine water treatment system, which includes the mine water reuse rate, the reuse cost at different stages and the operational efficiency of the whole mine water treatment system. Then, a hybrid optimization algorithm, GAPSO, was proposed by combining genetic algorithm (GA) and particle swarm optimization (PSO), and adaptive improvement (TSA-GAPSO) was carried out for the two optimization stages. Finally, simulation analysis and actual data detection of the mine water reuse model are carried out by using four algorithms, respectively. The results show that the hybrid improved algorithm has better convergence speed and precision in solving the mine water scheduling problem. TSA-GAPSO algorithm has the best effect and is superior to the other three algorithms. The cost of mine water reuse is reduced by 9.09%, and the treatment efficiency of the whole system is improved by 5.81%, which proves the practicability and superiority of the algorithm.
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