Amir Bijan Yasrebi
University of Exeter
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Featured researches published by Amir Bijan Yasrebi.
Geologica Carpathica | 2013
Amir Bijan Yasrebi; Peyman Afzal; Andrew Wetherelt; Patrick Foster; Reza Esfahanipour
Abstract This study identifies the major mineralized zones including supergene enrichment and hypogene enrichment in the Kahang Cu-Mo porphyry deposit which is located in Central Iran based on subsurface data and utilization of the concentration-volume (C-V) fractal model. Additionally, a correlation between results achieved from a C-V fractal model and geological models consisting of zonation, mineralography and alteration have been conducted in order to have an accurate recognition and modification of the main mineralized zones. Log-log plots indicate five geochemical populations for Cu and Mo in the deposit which means that mineralization commences with 0.075 % and 13 ppm for Cu and Mo (as the first thresholds) respectively. The main mineralization began for Cu ≥ 0.42 % and Mo ≥ 100 ppm and also enriched mineralization containing Cu ≥1.8 % and Mo ≥ 645 ppm which is located in the central part of the deposit. According to the C-V model, the main Cu-Mo mineralized zones occur in the hypogene zone, especially in the central, NW and NE parts of the Kahang deposit. The supergene enrichment zone derived via the C-V model is smaller than that in the geological model and is located in the central and eastern parts of the deposit. Results analysed by the C-V fractal model certify that the interpreted zones based on the fractal model are accurate. To certify this, a logratio matrix has been employed to validate the C-V fractal model for the Cu and Mo main mineralized zones
Arabian Journal of Geosciences | 2014
Mojtaba Shamseddin Meigoony; Peyman Afzal; Mehran Gholinejad; Amir Bijan Yasrebi; Behnam Sadeghi
The aim of this study is to delineate the Cu, Au, and Pb anomalies in Sarajeh 1:100,000 sheet located in Urumieh-Dokhtar ore belt, central Iran. The analyzed elements of stream sediment samples taken in the area can be classified into six groups (factors) by factor analysis. The concentration–area and number–size multifractal inverse distance weighted models were applied for recognition of the elemental thresholds which are similar in both used multifractal models. According to the thresholds, the elemental concentration distribution for Cu, Au, and Pb were divided to three lithological classifications, namely mainly c alkaline porphyry with Cu–Au mineralization, mafic and sedimentary rocks. The results illustrate that the major anomalies of Cu, Au, Pb and related factors are mostly located around intrusions, volcanics, and along NW–SE faults.
Arabian Journal of Geosciences | 2015
Ramin Aramesh Asl; Peyman Afzal; Ahmad Adib; Amir Bijan Yasrebi
The aim of this study is to investigate the reconnaissance of alteration zones and faults in Hashtjin 1:100,000 sheet (NW Iran) using concentration-area (C-A) fractal model based on remote sensing data, which has been extracted from enhanced thematic mapper (ETM)+ multispectral images. There are Oligocene volcano-plutonic rocks and Tarom-Hashtjin metallogenic zone with Cu, Au, and Pb-Zn occurrences in the studied area. The concentration-area (C-A) fractal model proposed in this paper for the interpretation of pixel value distribution spatial patterns based on the extracted data from ETM+ multispectral images. The pixel values were calculated by the PCA (principal component analysis) method for iron oxides and argillic alteration. Furthermore, the sharpen-filtering has been applied to calculate the value pixels for the main fault zone in the Hashtjin area. The C-A model can be used to establish power-law relationships between the area and the pixel value. The log-log C-A plots show multifractal nature for iron oxides, argillic alteration zones, and faults. Results obtained by the fractal model reveal that alteration zones and major faults have a NNW-SSE trend. The alteration zones and major faults have a strong correlation with the geological map of the area.
Arabian Journal of Geosciences | 2015
Amir Bijan Yasrebi; Andrew Wetherelt; Patrick Foster; Gareth A. Kennedy; Dariush Kaveh Ahangaran; Peyman Afzal; Ahmad Asadi
One of the most fundamental problems in a mining operation is how to recognise an optimum cut-off grade, which defines the grade for discriminating between ore and waste in an ore body, including ore that is extracted at different periods over a mine life period. Therefore, the identification of an optimised cut-off grade (COG) is a crucial function which has to be monitored during the mine life. The main aim of this study is to propose a modified optimum COG model in order to maximise the profit value (PV) for mining projects. Maximising the PV of a mining operation, which is a non-linear programming, is subject to different constraints involving a general grade distribution within a deposit and three stages of production namely mining, concentrating and refining. The proposed computer-based model is more effective in long-term planning of the open pit mines. To provide a better understanding of the algorithm efficiency, a numerical example is given and subsequently solved based on the Lane algorithm. In order to achieve this, the LINGO software was employed.
Journal of Mining and Metallurgy A: Mining | 2015
Amir Bijan Yasrebi; Andrew Wetherelt; Patrick Foster; Peyman Afzal; D. Kaveh Ahangaran
The aim of this study is to determine an optimum voxel size in the Kahang Cu porphyry deposit (Central Iran) using statistical parameters and vector analysis based on the 26 drilled boreholes. The mean, median and Median Absolute Deviation (MAD) were calculated for total distances between 14 pairs of closest boreholes in terms of X and Y directions. Based on the results, three block models were determined with 3 x 3 x 10 m3, 4 x 4 x 10 m3 and 5 x 5 x 10 m3 of voxel volumes for Cu distribution utilising inverse distance weighted (IDW) method. According to calculation of Non-Zero voxel numbers and decreasing of standard deviations and Cu average values, the block model with 4 x 4 x 10 m3 voxel sizes determined as an optimum block model.
Archive | 2014
Amir Bijan Yasrebi; Andrew Wetherelt; Patrick Foster; Peyman Afzal; Daryoush Kaveh Ahangaran; Reza Esfahanipour
In the past, many studies relating to staff motivation within the workplace have been conducted for the mining sector. Of course, motivated employees are the main key to achieving success of any organisation. However, the goal of this paper is to identify factors and behaviours which principally motivate staff within the mining sector. In order to determine these elements, this research was carried out at different copper mines located within Iran with differing climates and working conditions by the collection of a set of questionnaires distributed amongst the mining workforce. The results of this research indicate that the highest rates of demotivation occur often among old and experienced personnel in comparison to the younger employees although older staff definitely has the talent and initiative of younger personnel. As a result, older employees continue to work with cynicism, negativism and defiance. To successfully control and correspondingly overcome the problem of employees’ demotivation that appears to prevent the mining sector from achieving their planned targets, a set of proposals based on this study have been recommended.
Journal of Geochemical Exploration | 2012
Behnam Sadeghi; Parviz Moarefvand; Peyman Afzal; Amir Bijan Yasrebi; Lili Daneshvar Saein
Chemie Der Erde-geochemistry | 2013
Peyman Afzal; Hamid Harati; Younes Fadakar Alghalandis; Amir Bijan Yasrebi
Journal of African Earth Sciences | 2013
Behnam Sadeghi; Masoumeh Khalajmasoumi; Peyman Afzal; Parviz Moarefvand; Amir Bijan Yasrebi; Andrew Wetherelt; Patrick Foster; Afshar Ziazarifi
Journal of African Earth Sciences | 2016
Peyman Afzal; Misagh Mirzaei; Mahyar Yousefi; Ahmad Adib; Masoumeh Khalajmasoumi; Afshar Zia Zarifi; Patrick Foster; Amir Bijan Yasrebi