突出煤层区域预测指标W-P模型优化及应用

    Optimization and application of W-P model for regional prediction index of outburst coal seam

    • 摘要: 为了获取适合贵州不同矿区瓦斯含量和瓦斯压力内在关联,并能准确计算出符合煤层特征的两者指标测值,通过统计8个矿区57对矿井107组煤层瓦斯基础参数数据,基于Langmuir方程,引入破坏系数X和瓦斯放散初速度△p,建立了W-P优化模型,并对W-P经典模型与W-P优化模型在贵州矿区的适用性进行了对比研究。结果表明:W-P优化模型计算得到的瓦斯含量及压力数据与实测值拟合度较高,且随着实测值样本量的增加,拟合度逐渐增高;反演瓦斯含量及反演瓦斯压力的平均相对误差分别为6.44%和14.27%;相对于经典模型,优化模型的平均相对误差分别降低了17.54%和83.59%;应用W-P优化模型确定了矿井M16煤层瓦斯含量和瓦斯压力临界值分别为8.0 m3/t和0.74 MPa,与M16煤层实际发生瓦斯动力现象处的瓦斯含量和瓦斯压力值相吻合。

       

      Abstract: In order to obtain the internal correlation of gas content and gas pressure suitable for different mining areas in Guizhou Province, and accurately calculate the measured values of the two indexes in line with the characteristics of coal seams, the W-P optimization model was established by statistical analysis of 107 groups of coal seam gas basic parameter data of 57 pairs of mines in 8 mining areas, based on the Langmuir equation, introducing the failure coefficient X and the initial velocity of gas emission △p, and the W-P classical model and W-P optimization model were compared. This paper makes a comparative study on the applicability in Guizhou mining area. The results show that: the gas content and pressure data calculated by W-P optimization model have high fitting degree with the measured value, and the fitting degree gradually increases with the increase of the sample size of the measured value, and the average relative error is 6.44% and 14.27% respectively. Compared with the classical model, the average relative error of the optimization model is reduced by 17.54% and 83.59% respectively; the critical values of gas content and gas pressure in M16 coal seam are determined to be 8.0 m3/t and 0.74 MPa respectively by using W-P optimization model, which is consistent with the gas content and gas pressure at the actual gas dynamic phenomenon in M16 coal seam.

       

    /

    返回文章
    返回