谷歌浏览器插件
订阅小程序
在清言上使用

Mineralogical Approach-A Tool for Geo-Metallurgical Prediction of Tizert Copper Deposit (Ighrem Inlier, Anti-Atlas, Morocco)

JOURNAL OF MINING AND ENVIRONMENT(2022)

引用 0|浏览12
暂无评分
摘要
This work aims to define an efficient and innovative tool in order to make early metallurgical predictions of the Tizert deposit in western Anti-Atlas-Morocco. To do this, the mineralogical approach is used as a tool of geometallurgical prediction using a combination of the lithological field observations on representative drill cores, microscopic characterization performed on 54 thin sections, and automated quantitative mineralogy (AQM) conducted on five composite samples. The metallurgical prediction of the Tizert ore is based on the liberation data, notably on the copper content locked in the gangue and on unrecoverable copper buried as a solid matrix in the gangue minerals (refractory copper). In order to ensure the validity of the proposed method, the results of mineralogical prediction are compared with the flotation test work performance. As a result, the predicted copper recovery results from the mineralogical data are practically the same as those obtained through the flotation tests, showing a maximum difference of 2.02%, an R2 value of 0.96, and a Root Mean Square Error of 1.64%. These results indicate that using the AQM data, the copper recovery could be predicted accurately for the Tizert ore. Furthermore, an early prediction of the flotation performance is very useful in the geo-metallurgical model conception. In addition, such an approach ensures visibility throughout the life of the mine, and provides quick and cost-effective data for processing the performance. On an industrial scale, the applicability of this method can be expanded further by integrating the mineralogical approach into all steady-state processes in order to cover the possible mineralogical variety during the operations, and ensure an industrial process control.
更多
查看译文
关键词
Automated quantitative mineralogy,Tizert,Copper,Geometallurgy,Morocco
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要