回采工作面煤层动态标定预测技术应用研究

智能开采对于地质条件的不适应问题非常突出，特别是对煤层起伏和厚度的绝对精度提出了更高的要求。三维地震勘探横向分辨率高，能够对煤层起伏进行控制，但在地震解释时，煤层底板高程受时深转换计算影响，存在一定的误差。针对这一问题，以工作面三维地震数据和采掘过程中探煤厚数据为基础，通过不断更新速度场提高煤层底板时深转换绝对精度；同时利用迭代插值算法，不断更新工作面煤层厚度；通过对计算得到的数据进行误差统计和分析。在TJH304回采工作面进行试验，利用工作面巷道和切眼探煤厚数据并结合三维地震资料动态解释后，工作面推采前方煤层底板高程值和厚度值绝对误差变小；特别是距离当前采煤面30 m以内的4个验证点煤层底板高程值误差范围为0.37~0.58 m，煤层厚度值误差为0.32~0.44 m。结果表明，三维地震动态解释技术可最大化将三维地震和井下生产数据有效结合，不断提高煤层空间精度，为智能开采提供预想煤层模型。 

Application research on dynamic calibration and prediction technology of coal seam in coalmine working face

One of the prominent problems of intelligent mining is its inadaptability to geological conditions, especially for the absolute accuracy of coal seam floor and thickness. 3D seismic has a high horizontal resolution and it can control the ups and downs of the coal seam. However, due to the time domain data, the calculation of the coal seam floor elevation is negatively affected by the time-depth conversion point. On the basis of the 3D seismic data of the working face and the coal thickness data during the mining process, the absolute accuracy of the time-depth conversion of the coal seam floor is improved by continuously refreshing the velocity field. At the same time, the iterative interpolation algorithm is used to continuously update the coal seam thickness of the working face, then error statistics and analysis are conducted based on the calculated data. The experiment was carried out at TJH304 working face after using coal seam floor height and thickness of working face tunnel and mining face combined with the dynamic interpretation of the 3D seismic data. The absolute error of the coal seam floor elevation and thickness values in front of the working face is reduced. In particular, the four verification points within thirty meters from the current mining face and the coal seam floor elevation error is between 0.37-0.58 m; the coal seam thickness error is between 0.32-0.44 m. The results show that the 3D seismic dynamic interpretation technology can maximize the effective combination of 3D seismic and downhole production data, continuously improve the spatial accuracy of coal seam, and provide a prospective coal seam model for intelligent mining.