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多矿化元素地质冶金学模型动态模拟OA

Dynamic Simulation of Geometallurgical Model for Multi-Mineralization Elements:A Case Study of the Bayan Obo Deposit

中文摘要英文摘要

地质冶金学模型可为矿产资源开发与生产优化提供重要技术支撑.然而,复杂共伴生矿床元素种类繁多、空间非均质性强,传统模型对有害元素的约束作用表征不足,导致矿域划分精度偏低、配矿决策缺乏量化依据,难以满足探、采、选一体化精准生产需求.为此,本文以白云鄂博矿床为实例,提出一种融合有害元素评价的多矿化元素地质冶金学动态模拟方法,在探矿者软件平台统一框架下融合地质模型、储量估算模型及采场实时生产数据,采用普通克里格方法对TFe、mFe、F和S四种矿化元素进行空间插值,并基于高斯混合模型与马尔可夫随机场构建贝叶斯推理框架实现矿域迭代优化划分.本研究基于61,748个三维网格单元(2 m×2 m×14 m),其中约75%为待估未知单元,依据TFe含量梯度(以15%、20%、30%、45%为界)与S含量阈值(14%)将矿体划分为7类矿域,采用18-邻域系统与最优平滑参数β=0.3进行迭代优化.迭代过程中,首次矿域变化率达0.8,经6次迭代后收敛至阈值0.38以下;最终各矿域TFe均值介于12.24%~45.48%,S均值介于0.882%~2.082%,其中矿域2(高硫高铁)维持全矿区最高硫含量梯度.以566个典型样本为验证集的交叉验证进一步表明,迭代后矿域划分精度显著提升.该模型已成功应用于智能生产设计、精准配矿及无人设备协同调度等实际生产环节,实现了从静态初步划分到动态精细建模的有效衔接,可为复杂共伴生矿床在有害元素约束条件下的精细化开发与智能矿山建设提供技术参考.

Geometallurgical models underpin the optimization of mineral resource exploitation and production.However,for complex paragenetic deposits with multi-element assemblages and strong spatial heterogeneity,conventional models poorly characterize harmful element constraints,leading to inaccurate ore domain delineation and insufficient quantitative support for ore blending,which fails to meet the integrated precise production demands of exploration,mining and beneficiation.Taking the Bayan Obo deposit as a case study,this work develops a multi-element dynamic geometallurgical simulation method incorporating harmful element evaluation.Within the unified Surpac platform framework,geological models,reserve estimation models and real-time stope production data are integrated.Ordinary Kriging is used for the spatial interpolation of TFe,mFe,F and S,and a Bayesian inference framework based on Gaussian Mixture Model and Markov Random Field is established to achieve iterative optimization of ore domain delineation.A total of 61,748 three-dimensional grid blocks(2 m×2 m×14 m,75%unknown)are adopted,and the orebody is classified into seven ore domains using TFe cut-off gradients(15%,20%,30%,45%)and a 14%sulfur threshold.Iterative optimization is implemented via an 18-neighborhood system with an optimal smoothing parameter β of 0.3.The initial ore domain variation rate of 0.8 converges to below 0.38 after six iterations.The average TFe and S contents of optimized domains range from 12.24%~45.48%and 0.882%~2.082%,respectively,with high-sulfur and high-iron ore domain 2 possessing the highest sulfur gradient in the mining area.Cross-validation on 566 typical samples confirms that iterative optimization significantly improves ore delineation accuracy.Successfully applied to intelligent production design,precise ore blending and unmanned equipment collaborative scheduling,the proposed model realizes the transition from static delineation to dynamic refined modeling.It provides a technical reference for the refined exploitation and intelligent construction of mines for complex paragenetic deposits subject to harmful element constraints.

杨楠;张丽;田琦;刘峰;王国栋;尹世滔;刘小玲;陈进;李以科

包头钢铁(集团)有限责任公司白云鄂博铁矿,内蒙古 包头 014080包头钢铁(集团)有限责任公司白云鄂博铁矿,内蒙古 包头 014080包头钢铁(集团)有限责任公司白云鄂博铁矿,内蒙古 包头 014080包头钢铁(集团)有限责任公司白云鄂博铁矿,内蒙古 包头 014080包头钢铁(集团)有限责任公司白云鄂博铁矿,内蒙古 包头 014080中国地质科学院矿产资源研究所,北京 100037包头钢铁(集团)有限责任公司白云鄂博铁矿,内蒙古 包头 014080中南大学,湖南 长沙 410083中国地质科学院矿产资源研究所,北京 100037

天文与地球科学

地质冶金学多矿化元素有害元素评价矿域划分动态模拟白云鄂博矿床

geometallurgymultiple mineralization elementsdeleterious element evaluationore domain delineationdynamic simulationBayan Obo deposit

《地质与勘探》 2026 (4)

797-808,12

中国地质科学院矿产资源研究所科技成果转化项目"白云鄂博铁矿精细三维地质动态模型构建及其智能化采矿综合研究"(编号:HE2547)资助.

10.12134/j.dzykt.2026.04.010

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