Rockburst is defined as a phenomenon with immediate dynamic instability under excavation unloading conditions of deep or high geostress areas. Inadequate knowledge and lack of characterizing information prevent engineers and experts from achieving appropriate prediction results related to the rockburst behaviour. In this study, a data set including 220 rockburst instances was collected for rockburst classification via the geostatistical method. An update of the 2D graph, the tunnel rockburst classification (TRC) chart, was introduced based on analysing three indicators, namely, elastic energy index (W_et), tangential stress in rock mass (σ_θ), and uniaxial compressive strength (σ_c). Distribution and correlation of data were drawn on 2D plot, and the boundaries of rockburst were distinguished according to the achieved interpolate points by kriging method. Hierarchically, the validation phase was performed using an additional set of 28 case histories obtained from several projects around the world. The results showed that the TRC chart with an average error percentage of 3.6% in the prediction of rockburst had a significant and effective implementation in comparison to the exiting heuristic systems. Despite the initial character of the prediction, the described chart may be a helpful tool in the first steps of design and construction.

岩爆被定义为在深部或高地应力区域的开挖卸载条件下具有即时动态不稳定的现象。知识不足和特征信息的缺乏阻碍了工程师和专家获得与岩爆行为相关的适当预测结果。在这项研究中，通过地质统计学方法收集了包括 220 个岩爆实例的数据集用于岩爆分类。在分析弹性能量指数（W _et）、岩体切向应力（σ _θ）和单轴抗压强度（σ _C）。在二维图上绘制数据的分布和相关性，并通过克里金方法根据获得的插值点区分岩爆边界。从层次上讲，验证阶段是使用从世界各地的几个项目中获得的另外一组 28 个案例历史来执行的。结果表明，与现有启发式系统相比，TRC 图在岩爆预测中的平均误差百分比为 3.6%，具有显着且有效的实现。尽管预测的初始特征，所描述的图表可能是设计和构建的第一步中的有用工具。