煤层厚度与煤质特征(包括发热量、挥发分、灰分与硫分)的变异性决定了煤炭价格的空间分布，准确表征煤层经济价值对于煤炭资源的合理开发利用有着重要作用。首先明确煤厚煤质等地质属性为区域化变量，使用块体模型的方法对研究区域地质实体进行离散化；其次利用地质统计学方法获取实测钻孔煤厚煤质的实验半变异函数，当变异性较小、实测数据丰度较大、能建立变程内实验半变异函数的数学模型时，使用普通克里金进行空间估值，反之则考虑使用距离幂次反比法进行空间估值，并使用交叉验证获取均方误差最小的幂次；然后使用动力煤计价方法计算每个块体单元上的煤炭价格，建立煤层价值块体模型；最后以准格尔煤田麻地梁煤矿5号煤层为例，考虑煤层价值模型对工作面开采接替顺序进行优化。结果表明：煤炭价格呈现出明显的空间异质性，变化范围从574元/t至1192元/t，平均834元/t，符合正态分布；工作面开采接替顺序优化后煤炭销售额净现值NPV (Net Present Value)增加4.16亿元，提升1.64%，显著提高了采矿收益。使用地质统计学方法可充分挖掘实测数据的空间相关性，建立的块体模型不仅获得煤厚、煤质与煤炭价格在宏观上的统计信息，还可以给出其精细化的空间分布，在后续的选煤、配煤及销售环节具有广泛的应用前景；使用地质统计学方法建立的块体模型精度受控于实测数据规模，可根据开采过程中的新生数据进行动态修正与预测。

The variations in coal seam thickness and coal quality parameters (i.e., calorific value, volatile matter, ash content, and sulfur content) determine the spatial distribution of coal prices. The accurate characterization of coal seams’ economic value plays an important role in the rational mining and utilization of coal resources. This study first determined that the geological attributes of coal seams including their thickness and coal quality are regional variables. Based on this, this study discretized geological bodies in the study area using a block model. Then, using a geostatistical method, this study obtained the experimental semivariograms of coal seam thickness and coal quality measured from geological boreholes. The spatial evaluation was performed using the Ordinary Kriging method when coal seams featured small variations and abundant measured data and it was possible to construct a mathematical model of the experimental semivariograms within the variation ranges. Otherwise, the spatial estimation was conducted using the inverse distance weighted (IDW) method, and the optimized power with the smallest root mean square error was obtained using the cross-validation method. Subsequently, the coal price of each block was calculated using the steam coal pricing method, and the block model for coal seam economic value was established. Finally, taking the No. 5 coal seam of the Madiliang coal mine in the Jungar coalfield as an example, this study optimized the mining sequence of several mining faces considering the heterogenous block model of coal seam economic value. The results indicated that the spatial distribution of coal prices exhibited significant heterogeneity. Specifically, the coal prices ranged from 574 yuan/t to 1192 yuan/t (average: 934 yuan/t), showing a normal distribution. The net present value (NPV) of shales increased by 416 million yuan, i.e., 1.64%, after the mining sequence was optimized, indicating a significant increase in the mining benefit. The geostatistical method can fully explore the spatial correlations of measured data. The block models of coal seam thickness, coal quality, and coal prices established using this method yielded macroscopic statistics. Moreover, the geostatistical method allows for fine-scale spatial mapping of those coal seam properties. Therefore, this method can be widely applied in the subsequent coal dressing, coal blending, and coal sales. The block models of coal seams established using the geostatistical method, whose accuracy is influenced by the measured data amount, can be further dynamically corrected and predicted using newly generated data in the process of mining.