煤矿智能开采工艺与装备对于地质条件适应性不足，急需在各种复杂地质条件下构建高精度透明化的煤层地质模型。以山西某地质条件复杂的矿井为例，选择陷落柱、断层、褶曲等较为发育的XY-S工作面，通过利用不同勘查、生产阶段获取的地质数据，递进式构建了设计阶段的黑箱模型、掘进阶段的灰箱模型、回采前的白箱模型和开采中的透明模型；以XY-S工作面7 400 m掘进巷道、1 470 m推采范围的实测数据作为统计依据，对不同模型的地质建模精度进行实证分析。试验结果表明：①煤层底板的建模误差：黑箱模型10~20 m（仅有钻探数据时）、5~10 m（钻探+三维地震），灰箱模型和白箱模型0~5 m，透明模型0~1.0 m；②断层、陷落柱的控制程度：槽波解释的3条落差1.5 m以上断层验证可靠，直径20 m以上陷落柱的解释准确率平均75%，但是槽波探测的陷落柱范围明显偏大、推断的异常区偏多；③煤厚预测误差：主采煤层平均厚度2.70 m，黑箱、灰箱、白箱模型煤厚预测最大误差1.5 m、均方误差0.5 m左右，透明模型的煤厚预测误差小于0.30 m，但是可统计的实证点偏少。按照智能开采工作面地质模型梯级构建的思路，智能开采前白箱模型的建模精度只能满足自适应截割模拟开采的需求，急需研发随采智能探测、孔中地质雷达、视频煤岩识别等新技术新装备，实现工作面高精度三维地质建模，为煤矿智能开采提供可靠的地质保障。

Coal mine intelligent mining technology and equipment are not adaptable to geological conditions, and it is urgent to build a high-precision and transparent coal seam geological model under various complex geological conditions.Taking a mine with complicated geological conditions in Shanxi as an example, the more conditions in Working Faces XY-S such as collapse columns, faults, folds, etc.were selected to discuss cascade modelling and optimizing, and the black box model at the design stage was constructed progressively by using the geological data obtained at different exploration and production stages.The accuracy of above four models has been verified according to the measured data which consisted of 7 400 m excavated roadways and 1 470 m mined area.The compared indicators includes the prediction accuracy of coal seam floor and thickness, and the explored geological structures.The test results show that: ① modeling error of coal seam floor: black box model 10～20 m(only drilling data is available), 5～10 m(drilling + 3D seismic), the error ranges of gray box model and white box model are 0～5 m, and the range for transparent model is 0～1.0 m; ②The degree of control of faults and subsidence columns: three faults with a gap difference more than 1.5 m explained by in-seam seismic(ISS)are verified reliably.The interpretation accuracy of the subsidence column with a diameter no more than 20 m is 75% on average, but the ranges of subsidence column detected by ISS tend to be larger than the actual ranges.③coal thickness prediction error:the average thickness of the main coal seam is 2.70 m.The maximum error of the coal thickness prediction of the black box, gray box and white box model is 1.5 m and the mean square error is about 0.5 m.The transparent model’s coal thickness prediction error is less than 0.30 m, but there are few empirical statistical points.According to the idea of cascade geological modeling,the accuracy of white box model can basically satisty the demands of adaptive cutting of intelligent coal mining.In order to improve the accuracy of longwall panel model, it is urgent to develop intelligent detection with, geological radar in hole, and video coal and rock identification with new technologies and new equipment, which can realize high-precision three-dimensional geological modeling of the working face and provide reliable geological guarantee for coal mine intelligent mining.