Mineral Resource Classification Using Geostatistical and Fractal Simulation in the Masjed Daghi Cu–Mo Porphyry Deposit, NW Iran
Mineral resource classification is an important step in mineral exploration and mining engineering. In this study, copper and molybdenum resources were classified using a combination of the Turning Bands Simulation (TBSIM) and the Concentration–Volume (C–V) fractal model based on the Conditional Coe...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Minerals |
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| Online Access: | https://www.mdpi.com/2075-163X/13/3/370 |
| _version_ | 1797609997549436928 |
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| author | Peyman Afzal Hamid Gholami Nasser Madani Amir Bijan Yasrebi Behnam Sadeghi |
| author_facet | Peyman Afzal Hamid Gholami Nasser Madani Amir Bijan Yasrebi Behnam Sadeghi |
| author_sort | Peyman Afzal |
| collection | DOAJ |
| description | Mineral resource classification is an important step in mineral exploration and mining engineering. In this study, copper and molybdenum resources were classified using a combination of the Turning Bands Simulation (TBSIM) and the Concentration–Volume (C–V) fractal model based on the Conditional Coefficient of Variation (CCV) for Cu realizations in the Masjed Daghi porphyry deposit, NW Iran. In this research, 100 scenarios for the local variability of copper were correspondingly simulated using the TBSIM and the CCVs were calculated for each realization. Furthermore, various populations for these CCVs were distinguished using C–V fractal modeling. The C–V log–log plots indicate a multifractal nature that shows a ring structure for the “Measured”, “Indicated”, and “Inferred” classes in this deposit. Then, the results obtained using this hybrid method were compared with the CCV–Tonnage graphs. Finally, the results obtained using the geostatistical and fractal simulation showed that the marginal parts of this deposit constitute inferred resources and need more information from exploration boreholes. |
| first_indexed | 2024-03-11T06:08:17Z |
| format | Article |
| id | doaj.art-63b96aca249f4d14aaedbfc241585ff1 |
| institution | Directory Open Access Journal |
| issn | 2075-163X |
| language | English |
| last_indexed | 2024-03-11T06:08:17Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Minerals |
| spelling | doaj.art-63b96aca249f4d14aaedbfc241585ff12023-11-17T12:47:39ZengMDPI AGMinerals2075-163X2023-03-0113337010.3390/min13030370Mineral Resource Classification Using Geostatistical and Fractal Simulation in the Masjed Daghi Cu–Mo Porphyry Deposit, NW IranPeyman Afzal0Hamid Gholami1Nasser Madani2Amir Bijan Yasrebi3Behnam Sadeghi4Department of Petroleum and Mining Engineering, South Tehran Branch, Islamic Azad University, Tehran 1418653411, IranDepartment of Petroleum and Mining Engineering, South Tehran Branch, Islamic Azad University, Tehran 1418653411, IranSchool of Mining and Geosciences, Nazarbayev University, Astana 010000, KazakhstanSharif Ideator Metals and Mining Industrial Co., Tehran 1418653411, IranEarthByte Group, School of Geosciences, University of Sydney, Camperdown, NSW 2006, AustraliaMineral resource classification is an important step in mineral exploration and mining engineering. In this study, copper and molybdenum resources were classified using a combination of the Turning Bands Simulation (TBSIM) and the Concentration–Volume (C–V) fractal model based on the Conditional Coefficient of Variation (CCV) for Cu realizations in the Masjed Daghi porphyry deposit, NW Iran. In this research, 100 scenarios for the local variability of copper were correspondingly simulated using the TBSIM and the CCVs were calculated for each realization. Furthermore, various populations for these CCVs were distinguished using C–V fractal modeling. The C–V log–log plots indicate a multifractal nature that shows a ring structure for the “Measured”, “Indicated”, and “Inferred” classes in this deposit. Then, the results obtained using this hybrid method were compared with the CCV–Tonnage graphs. Finally, the results obtained using the geostatistical and fractal simulation showed that the marginal parts of this deposit constitute inferred resources and need more information from exploration boreholes.https://www.mdpi.com/2075-163X/13/3/370mineral resource classificationturning bands simulation (TBSIM)concentration–volume (C–V) fractal modelconditional coefficient of variation (CCV) |
| spellingShingle | Peyman Afzal Hamid Gholami Nasser Madani Amir Bijan Yasrebi Behnam Sadeghi Mineral Resource Classification Using Geostatistical and Fractal Simulation in the Masjed Daghi Cu–Mo Porphyry Deposit, NW Iran Minerals mineral resource classification turning bands simulation (TBSIM) concentration–volume (C–V) fractal model conditional coefficient of variation (CCV) |
| title | Mineral Resource Classification Using Geostatistical and Fractal Simulation in the Masjed Daghi Cu–Mo Porphyry Deposit, NW Iran |
| title_full | Mineral Resource Classification Using Geostatistical and Fractal Simulation in the Masjed Daghi Cu–Mo Porphyry Deposit, NW Iran |
| title_fullStr | Mineral Resource Classification Using Geostatistical and Fractal Simulation in the Masjed Daghi Cu–Mo Porphyry Deposit, NW Iran |
| title_full_unstemmed | Mineral Resource Classification Using Geostatistical and Fractal Simulation in the Masjed Daghi Cu–Mo Porphyry Deposit, NW Iran |
| title_short | Mineral Resource Classification Using Geostatistical and Fractal Simulation in the Masjed Daghi Cu–Mo Porphyry Deposit, NW Iran |
| title_sort | mineral resource classification using geostatistical and fractal simulation in the masjed daghi cu mo porphyry deposit nw iran |
| topic | mineral resource classification turning bands simulation (TBSIM) concentration–volume (C–V) fractal model conditional coefficient of variation (CCV) |
| url | https://www.mdpi.com/2075-163X/13/3/370 |
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