TECTONICS OF MANTLE PLUME AND POSTMAGMATIC PROCESSES OF ORE SUBSTANCE CRYSTALLIZATION, BLOCK STRUCTURE FORMATION IN ROCK MASS AND THEIR INCLUSION IN THE SURFACE AND UNDERGROUND MINE PLANNING AND DESIGN

2017 ◽  
Vol 11 ◽  
pp. 5-12
Author(s):  
Keyword(s):  
Rock Mass ◽  
Structure Formation ◽  
Mantle Plume ◽  
Block Structure ◽  
Underground Mine ◽  
Mine Planning ◽  
Planning And Design

scholarly journals APPLICATION OF RQD-NUMBER AND RQD-VOLUME MULTIFRACTAL MODELLING TO DELINEATE ROCK MASS CHARACTERISATION IN KAHANG Cu-Mo PORPHYRY DEPOSIT, CENTRAL IRAN / ZASTOSOWANIE METOD MODELOWANIA NUMERYCZNEGO ORAZ MODELOWANIA FRAKTALNEGO DO ANALIZY JAKOŚCI SKAŁ W CELU OKREŚLENIA CHARAKTERYSTYKI GÓROTWORU W OBSZARZE ZŁOŻA Cu-Mo W KAHANG, ŚRODKOWY IRAN

2013 ◽  
Vol 58 (4) ◽  
pp. 1023-1035 ◽  
Author(s):  
Amir Bijan Yasrebi ◽  
Andrew Wetherelt ◽  
Patrick J. Foster ◽  
Peyman Afzal ◽  
John Coggan ◽  
...  
Keyword(s):  
Rock Mass ◽  
Fractal Model ◽  
Mine Planning ◽  
Central Iran ◽  
Rock Classification ◽  
Porphyry Deposit ◽  
Planning And Design ◽  
Fractal Models ◽  
Rock Quality ◽  
Rock Mass Characterisation

Abstract Identification of rock mass properties in terms of Rock Quality Designation (RQD) plays a significant role in mine planning and design. This study aims to separate the rock mass characterisation based on RQD data analysed from 48 boreholes in Kahang Cu-Mo porphyry deposit situated in the central Iran utilising RQD-Volume (RQD-V) and RQD-Number (RQD-N) fractal models. The log-log plots for RQD-V and RQD-N models show four rock mass populations defined by RQD thresholds of 3.55, 25.12 and 89.12% and 10.47, 41.68 and 83.17% respectively which represent very poor, poor, good and excellent rocks based on Deere and Miller rock classification. The RQD-V and RQD-N models indicate that the excellent rocks are situated in the NW and central parts of this deposit however, the good rocks are located in the most parts of the deposit. The results of validation of the fractal models with the RQD block model show that the RQD-N fractal model of excellent rock quality is better than the RQD-V fractal model of the same rock quality. Correlation between results of the fractal and the geological models illustrates that the excellent rocks are associated with porphyric quartz diorite (PQD) units. The results reveal that there is a multifractal nature in rock characterisation with respect to RQD for the Kahang deposit. The proposed fractal model can be intended for the better understanding of the rock quality for purpose of determination of the final pit slope.

Underground mine planning with regard to preparedness of mineral reserves

2019 ◽  
Vol 5 ◽  
pp. 34-43 ◽  
Author(s):  
T. Kalybekov ◽  
◽  
K.B. Rysbekov ◽  
A.A. Toktarov ◽  
O.M. Otarbaev ◽  
...  
Keyword(s):  
Underground Mine ◽  
Mine Planning ◽  
Mineral Reserves

Incorporation of mineralisation risk into underground mine planning

2019 ◽  
pp. 286-291
Author(s):  
Rafael Campos Rosado ◽  
João Felipe C.L. Costa ◽  
Artur Almgren Saldanha
Keyword(s):  
Underground Mine ◽  
Mine Planning

Application of Concentration-Number and Concentration-Volume Fractal Models to Recognize Mineralized Zones in North Anomaly Iron Ore Deposit, Central Iran / Zastosowanie Modeli Fraktalnych Typu K-L (Koncentracja-Liczba), Oraz K-O (Koncentracja Objętość) Do Rozpoznawania Stref Występowania Surowców Mineralnych W Regionie Złóż Rud Żelaza North Anomaly, W Środkowym Iranie

2015 ◽  
Vol 60 (3) ◽  
pp. 777-789 ◽  
Author(s):  
Peyman Afzal ◽  
Reza Ghasempour ◽  
Ahmad Reza Mokhtari ◽  
Hooshang Asadi Haroni
Keyword(s):  
Iron Ore ◽  
Wall Rock ◽  
Fractal Model ◽  
Mine Planning ◽  
Central Iran ◽  
Ore Deposit ◽  
Planning And Design ◽  
Fractal Models ◽  
Mineralized Zone ◽  
Iron Ore Deposit

Abstract Identification of various mineralized zones in an ore deposit is essential for mine planning and design. This study aims to distinguish the different mineralized zones and the wall rock in the Central block of North Anomaly iron ore deposit situated in Bafq (Central Iran) utilizing the concentration-number (C-N) and concentration-volume (C-V) fractal models. The C-N model indicates four mineralized zones described by Fe thresholds of 8%, 21%, and 50%, with zones <8% and >50% Fe representing wall rocks and highly mineralized zone, respectively. The C-V model reveals geochemical zones defined by Fe thresholds of 12%, 21%, 43% and 57%, with zones <12% Fe demonstrating wall rocks. Both the C-N and C-V models show that highly mineralized zones are situated in the central and western parts of the ore deposit. The results of validation of the fractal models with the geological model show that the C-N fractal model of highly mineralized zones is better than the C-V fractal model of highly mineralized zones based on logratio matrix.

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