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Heterogeneity assessment for grade engineering in complex ore bodies

机译:复杂矿石级工程的异质性评估

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Traditional methods of resource modelling and mine planning rely upon geostatistical methods applied to exploration drill core data to derive a three dimensional model of the distribution of metal grades, quantised into rectangular prisms or blocks. The resulting block model is a primary input into short, medium and long term mine planning. However, block attributes are averaged or interpolated over a complete block, meaning that information at smaller scales is lost to the mine planning process. Grade engineering for new mining methods, such as the development of more accurately controlled blast designs, continuous miners for hard rock and sensors for rock properties that can be distributed along the operations process and value chain, allows excavation to be much more selective than traditional blasting, and provides data for driving earlier separation of waste from ore. This selectivity can be optimised if the resolution of resource models can match or exceed the spatial resolution of selective mining technologies. Opportunities for selective mining increase as a deposit becomes more heterogeneous. This leads to an interest in methods for estimating the distribution and characteristics of mineral heterogeneity within the ore-body. The objective of this work is to present some definitions of mineral heterogeneity, and to explore how heterogeneity as defined can be measured and inferred within ore-bodies.
机译:资源建模和矿山规划的传统方法依赖于地统计学方法应用于探索钻探核心数据,从而导出金属等级分布的三维模型,量化为矩形棱镜或块。结果块模型是进入短,中和长期矿山规划的主要输入。但是,块属性在完整的块上取平均或插值,这意味着较小尺寸的信息丢失到矿山规划过程。新型采矿方法等级工程,如开发更精确控制的爆破设计,连续矿工用于沿着运营过程和价值链分布的岩石属性的硬岩和传感器,允许挖掘比传统爆破更具选择性,并提供用于从矿石中提前分离浪费的数据。如果资源模型的分辨率可以匹配或超过选择性挖掘技术的空间分辨率,则可以优化这种选择性。选择性采矿的机会随着沉积物而增加变得更加异质。这导致对估算矿体内矿物异质性分布和特征的方法的兴趣。这项工作的目的是呈现矿物异质性的一些定义,并探讨如何在矿体内测量和推断定义的异质性。

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