6 research outputs found

    MODELING OF THE ILOVICA-SHTUKA COPPER-GOLD DEPOSIT, MINERAL RESOURCE ESTIMATION AND CLASSIFICATION

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    The Ilovica – Shtuka project's mineral resource estimation has been defined in accordance with the reporting requirements outlined in the 2012 edition of the 2012 edition of the β€œAustralasian Code for Reporting of Exploration Results, Mineral Resources and Ore Reserves” (the JORC Code). Statistical and grade continuity analyses were completed to characterise the mineralisation and subsequently used to develop grade interpolation parameters for the deposit. Exploratory data analysis highlighted a number of statistically differentiated grade populations, which were interpreted to be controlled by the following: stockwork intensity, oxidation state, supergene leaching and enrichment. Wireframe models were used to isolate grade populations into domains for the purpose of sample selection and to constrain the grade interpolation. Grade estimation was completed using ordinary kriging. The search ellipsoid dimen-sions and orientations were chosen to reflect the continuity revealed by geostatistical studies and optimised using quan-titative kriging neighbourhood analysis. The wireframe models were used within the sample selection and compositing routine and subsequently as a constraint to the grade estimation. In calculating dollar equivalent block values metal prices used are provided by Euromax management and are generated based on industry capacity analysis, global com-modity consumption and economic growth trends. A Mineral Resource classification scheme consistent with the JORC guidelines (2012) was applied. The estimates are categorised in the Measured, Indicated and Inferred mineral Resource categories, reported above a cut-off grade that defines the Resource as potentially mineable by open pit mining methods. Resource grade/ tonnage sensitivity graph were created based upon a range of dollar equivalent cut- offs for blocks within the Resource pit shell

    Modeling of the Ilovica-Ε tuka copper-gold deposit, mineral resource estimation and classification

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    The Ilovica-Ε tuka project's mineral resource estimation has been defined in accordance with the reporting requirements outlined in the 2012 edition of the β€œAustralasian Code for Reporting of Exploration Results, Mineral Resources and Ore Reserves” (the JORC Code). Statistical and grade continuity analyses were completed to characterize the mineralization and subsequently used to develop grade interpolation parameters for the deposit. Exploratory data analysis highlighted a number of statistically differentiated grade populations, which were interpreted to be controlled by the following: stockwork intensity, oxidation state, supergene leaching and enrichment. Wireframe models were used to isolate grade populations into domains for the purpose of sample selection and to constrain the grade interpolation. Grade estimation was completed using ordinary kriging. The search ellipsoid dimensions and orientations were chosen to reflect the continuity revealed by geostatistical studies and optimized using quantitative kriging neighbourhood analysis. The wireframe models were used within the sample selection and compositing routine and subsequently as a constraint to the grade estimation. In calculating dollar equivalent block values metal prices used are provided by Euromax management and are generated based on industry capacity analysis, global commodity consumption and economic growth trends. A Mineral Resource classification scheme consistent with the JORC guidelines (2012) was applied. The estimates are categorized in the Measured, Indicated and Inferred Mineral Resource categories, reported above a cut-off grade that defines the resource as potentially mineable by open pit mining methods. Resource grade/tonnage sensitivity graph were created based upon a range of dollar equivalent cut-offs for blocks within the resource pit shell

    GIS ΠΌΠΎΠ΄Π΅Π» Π½Π° Ρ€Π΅Π·ΡƒΠ»Ρ‚Π°Ρ‚ΠΈΡ‚Π΅ ΠΎΠ΄ ΠΈΡΡ‚Ρ€Π°ΠΆΡƒΠ²Π°ΡšΠ°Ρ‚Π° Π½Π° Π±Π°ΠΊΠ°Ρ€Π½Π°Ρ‚Π° ΠΌΠΈΠ½Π΅Ρ€Π°Π»ΠΈΠ·Π°Ρ†ΠΈΡ˜Π° Π½Π° Казандол

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    БвСтската ΠΏΠΎΠΏΡƒΠ»Π°Ρ†ΠΈΡ˜Π° растС сС ΠΏΠΎΠ±Ρ€Π·ΠΎ ΠΈ ΠΏΠΎΠ±Ρ€Π·ΠΎ, ΠΎΡ‚ΠΊΠΎΠ»ΠΊΡƒ Π²ΠΎ Π±ΠΈΠ»ΠΎ ΠΊΠΎΠ΅ Π²Ρ€Π΅ΠΌΠ΅ Π²ΠΎ ΠΈΡΡ‚ΠΎΡ€ΠΈΡ˜Π°Ρ‚Π° ΠΈ ΠΏΠΎΡ‚Ρ€ΠΎΡˆΡƒΠ²Π°Ρ‡ΠΊΠ°Ρ‚Π° Π½Π° ΠΌΠΈΠ½Π΅Ρ€Π°Π»Π½ΠΈΡ‚Π΅ рСсурси растС сС ΠΏΠΎΠ±Ρ€Π·ΠΎ ΠΎΠ΄ насСлСниСто ΠΊΠΎΠ³Π° повСќС корисници Π²Π»Π΅Π³ΡƒΠ²Π°Π°Ρ‚ Π²ΠΎ ΠΏΠ°Π·Π°Ρ€ΠΎΡ‚ Π·Π° ΠΌΠΈΠ½Π΅Ρ€Π°Π»ΠΈ рСсурси ΠΈ Π³Π»ΠΎΠ±Π°Π»Π½ΠΈΠΎΡ‚ стандард Π½Π° ТивССњС сС Π·Π³ΠΎΠ»Π΅ΠΌΡƒΠ²Π°. БвСтската ΠΏΠΎΠ±Π°Ρ€ΡƒΠ²Π°Ρ‡ΠΊΠ° Π½Π° ΠΌΠΈΠ½Π΅Ρ€Π°Π»Π½ΠΈ суровини Π΅ ΠΏΠΎΠ΄ влијаниС Π½Π° Ρ‚Ρ€ΠΈ ΠΎΠΏΡˆΡ‚ΠΈ Ρ„Π°ΠΊΡ‚ΠΎΡ€ΠΈ: Π·Π³ΠΎΠ»Π΅ΠΌΡƒΠ²Π°ΡšΠ΅ Π½Π° Π±Ρ€ΠΎΡ˜ΠΎΡ‚ Π½Π° корисници Π½Π° ΠΌΠΈΠ½Π΅Ρ€Π°Π»Π½ΠΈ рСсурси, пораст Π½Π° насСлСниСто ΠΈ Π½Π° ΠΆΠΈΠ²ΠΎΡ‚Π½ΠΈΠΎΡ‚ стандард. На ΠΏΡ€ΠΈΠΌΠ΅Ρ€, Кина ΠΈ Индија ΠΈΠΌΠ°Π°Ρ‚ ΠΏΠΎΡ‚Ρ€ΠΎΡˆΡƒΠ²Π°Ρ‡ΠΊΠ° Π½Π° Π±Π°ΠΊΠ°Ρ€ ΠΏΠΎ Π³Π»Π°Π²Π° Π½Π° ΠΆΠΈΡ‚Π΅Π» ΠΎΠ΄ 0,6 ΠΈ 2,7 ΠΊΠΈΠ»ΠΎΠ³Ρ€Π°ΠΌΠΈ ΠΏΠΎ Π»ΠΈΡ†Π΅ соодвСтно, Π΄ΠΎΠ΄Π΅ΠΊΠ° ΠˆΡƒΠΆΠ½Π° ΠšΠΎΡ€Π΅Ρ˜Π° ΠΈ Вајван, со Π·Π½Π°Ρ‡ΠΈΡ‚Π΅Π»Π½ΠΎ ΠΏΠΎΠΌΠ°Π»Π° ΠΏΠΎΠΏΡƒΠ»Π°Ρ†ΠΈΡ˜Π° ΠΈΠΌΠ°Π°Ρ‚ ΠΏΠΎΡ‚Ρ€ΠΎΡˆΡƒΠ²Π°Ρ‡ΠΊΠ° Π½Π° Π±Π°ΠΊΠ°Ρ€ ΠΏΠΎ Π³Π»Π°Π²Π° Π½Π° ΠΆΠΈΡ‚Π΅Π» Π½Π° 29,2 ΠΈ 66,7 ΠΊΠΈΠ»ΠΎΠ³Ρ€Π°ΠΌΠΈ. Π’Π°Ρ€ΠΈΡ˜Π°Ρ†ΠΈΠΈΡ‚Π΅ Π²ΠΎ стандардот Π½Π° ТивССњС Π±ΠΈ ΠΌΠΎΠΆΠ΅Π»ΠΎ Π΄Π° Π²Π»ΠΈΡ˜Π°Π°Ρ‚ Π²Ρ€Π· ΠΈΠ΄Π½Π°Ρ‚Π° ΠΏΠΎΠ±Π°Ρ€ΡƒΠ²Π°Ρ‡ΠΊΠ° Π½Π° ΠΌΠΈΠ½Π΅Ρ€Π°Π»Π½ΠΈ рСсурси повСќС ΠΎΠ΄ насСлСниСто. По Π³Π»Π°Π²Π° Π½Π° ΠΆΠΈΡ‚Π΅Π» ΠΏΠΎΡ‚Ρ€ΠΎΡˆΡƒΠ²Π°Ρ‡ΠΊΠ°Ρ‚Π° Π½Π° ΠΌΠΈΠ½Π΅Ρ€Π°Π»ΠΈ сС Π·Π³ΠΎΠ»Π΅ΠΌΡƒΠ²Π° Π²ΠΎ рСчиси ситС области Π²ΠΎ Ρ‚Π΅ΠΊΠΎΡ‚ Π½Π° ΠΌΠΈΠ½Π°Ρ‚ΠΈΠΎΡ‚ Π²Π΅ΠΊ, Π΄ΠΎΠ΄Π΅ΠΊΠ° азискитС зСмји сС Π²ΠΎ Ρ€Π°Π·Π²ΠΎΡ˜ ΠΈ ΠΈΠΌΠ°Π°Ρ‚ ΠΏΠΎΠΊΠ°ΠΆΠ°Π½ΠΎ особСно импрСсивСн раст Π²ΠΎ Ρ‚Π΅ΠΊΠΎΡ‚ Π½Π° послСднитС Π½Π΅ΠΊΠΎΠ»ΠΊΡƒ Π΄Π΅Ρ†Π΅Π½ΠΈΠΈ. Растот Π½Π° ΠΏΠΎΡ‚Ρ€ΠΎΡˆΡƒΠ²Π°Ρ‡ΠΊΠ°Ρ‚Π° Π½Π° Π±Π°ΠΊΠ°Ρ€ ΠΏΠΎ Π³Π»Π°Π²Π° Π½Π° ΠΆΠΈΡ‚Π΅Π» Π²ΠΎ ΠΎΠ²Π°Π° област сС Π΄Π²ΠΈΠΆΠΈ ΠΎΠ΄ ниско Π½ΠΈΠ²ΠΎ ΠΎΠ΄ ΠΎΠΊΠΎΠ»Ρƒ 40% Π²ΠΎ Индија Π½Π° висина ΠΎΠ΄ ΠΎΠΊΠΎΠ»Ρƒ 82 %, Π²ΠΎ Вајван ΠΏΠΎΠΌΠ΅Ρ“Ρƒ 1985 ΠΈ само Π²ΠΎ 1998 Π³ΠΎΠ΄ΠΈΠ½Π°. Π’ΠΎ Ρ†Π΅Π»ΠΈΠΎΡ‚ свСт, ΠΈΠΌΠ° Π²ΠΊΡƒΠΏΠ΅Π½ пораст Π½Π° ΠΏΠΎΡ‚Ρ€ΠΎΡˆΡƒΠ²Π°Ρ‡ΠΊΠ°Ρ‚Π° Π½Π° Π±Π°ΠΊΠ°Ρ€ ΠΏΠΎ Π³Π»Π°Π²Π° Π½Π° ΠΆΠΈΡ‚Π΅Π» ΠΎΠ΄ ΠΎΠΊΠΎΠ»Ρƒ 11 % Π²ΠΎ ΠΏΠ΅Ρ€ΠΈΠΎΠ΄ΠΎΡ‚ ΠΌΠ΅Ρ“Ρƒ 1985 ΠΈ 1998 Π³ΠΎΠ΄ΠΈΠ½Π°, Π° 13 % Π²ΠΎ ΠΏΠ΅Ρ€ΠΈΠΎΠ΄ΠΎΡ‚ 1971-1998, ΠΈΠ»ΠΈ ΠΎΠΊΠΎΠ»Ρƒ 0,5 % годишно. Ако ΠΌΠΈΠ½Π΅Ρ€Π°Π»Π½Π°Ρ‚Π° ΠΏΠΎΠ±Π°Ρ€ΡƒΠ²Π°Ρ‡ΠΊΠ° сС Π·Π³ΠΎΠ»Π΅ΠΌΡƒΠ²Π° Π½Π° годишно Π½ΠΈΠ²ΠΎ ΠΎΠ΄ 1,5%, Ρ‚Π°Π° ќС Π±ΠΈΠ΄Π΅ ΠΎΠΊΠΎΠ»Ρƒ 60 % повисока ΠΎΡ‚ΠΊΠΎΠ»ΠΊΡƒ дСнСс, сС Π΄ΠΎ 2050-Ρ‚Π° Π³ΠΎΠ΄ΠΈΠ½Π°. ΠŸΡ€ΠΈΠ΄ΠΎΠ½Π΅ΡΠΎΡ‚ Π½Π° ΠΈΡΡ‚Ρ€Π°ΠΆΡƒΠ²Π°ΡšΠ΅Ρ‚ΠΎ Π½Π° ΠΌΠΈΠ½Π΅Ρ€Π°Π»Π½ΠΈΡ‚Π΅ суровини ΠΈ рударството Π·Π° ΠΎΠ΄Ρ€ΠΆΠ»ΠΈΠ² Ρ€Π°Π·Π²ΠΎΡ˜ Ρ‚Ρ€Π΅Π±Π° Π΄Π° сС Π³Π»Π΅Π΄Π° Π²ΠΎ однос Π½Π° Скономската ΠΈ Ρ‚Π΅Ρ…Π½ΠΈΡ‡ΠΊΠ°Ρ‚Π° оправданост, Π΅ΠΊΠΎΠ»ΠΎΡˆΠΊΠ°Ρ‚Π° одрТливост ΠΈ ΡΠΎΡ†ΠΈΡ˜Π°Π»Π½Π° ΠΏΡ€Π°Π²Π΄Π°. ΠžΠ΄Ρ€ΠΆΠ»ΠΈΠ²ΠΎΡ‚ΠΎ ΠΊΠΎΡ€ΠΈΡΡ‚Π΅ΡšΠ΅ Π½Π° ΠΏΡ€ΠΈΡ€ΠΎΠ΄Π½ΠΈΡ‚Π΅ рСсурси ΠΈ Π±Π°Ρ€Π°ΡšΠ΅ Π½Π° ΠΏΠΎΡ‚Π΅Π½Ρ†ΠΈΡ˜Π°Π»Π½ΠΈ области Π·Π° ΠΈΡΡ‚Ρ€Π°ΠΆΡƒΠ²Π°ΡšΠ΅ сС ΠΎΡ†Π΅Π½ΡƒΠ²Π°Π°Ρ‚ Π²ΠΎ контСкст Π½Π° ΠΏΠΎΡΡ‚ΠΎΡ˜Π½ΠΈΡ‚Π΅ ΠΈ Π°Π»Ρ‚Π΅Ρ€Π½Π°Ρ‚ΠΈΠ²Π½ΠΈΡ‚Π΅ Π½Π°Ρ‡ΠΈΠ½ΠΈ Π½Π° ΠΊΠΎΡ€ΠΈΡΡ‚Π΅ΡšΠ΅ Π½Π° Π·Π΅ΠΌΡ˜ΠΈΡˆΡ‚Π΅Ρ‚ΠΎ, ΠΈΠ½Ρ‚Π΅Π³Ρ€ΠΈΡ€Π°ΡšΠ΅ Π½Π° ΡΠΎΡ†ΠΈΡ˜Π°Π»Π½ΠΈΡ‚Π΅, Π΅ΠΊΠΎΠ»ΠΎΡˆΠΊΠΈΡ‚Π΅, ΠΊΡƒΠ»Ρ‚ΡƒΡ€Π½ΠΈΡ‚Π΅ ΠΈ СкономскитС Ρ„Π°ΠΊΡ‚ΠΎΡ€ΠΈ. Π˜Π½Ρ‚Π΅Π³Ρ€ΠΈΡ€Π°Π½ΠΈΠΎΡ‚ пристап, кој ΠΏΠΎΠ²ΠΈΠΊΡƒΠ²Π° Π½Π° ΡΡ‚Ρ€Π°Ρ‚Π΅ΡˆΠΊΠΈ ΠΈ ΠΏΠ°Ρ€Ρ‚ΠΈΡ†ΠΈΠΏΠ°Ρ‚ΠΈΠ²Π΅Π½ процСс Π½Π° Π°Π½Π°Π»ΠΈΠ·Π°, Π΄Π΅Π±Π°Ρ‚Π°, Π·Π°Ρ˜Π°ΠΊΠ½ΡƒΠ²Π°ΡšΠ΅ Π½Π° ΠΊΠ°ΠΏΠ°Ρ†ΠΈΡ‚Π΅Ρ‚ΠΈΡ‚Π΅, ΠΏΠ»Π°Π½ΠΈΡ€Π°ΡšΠ΅ ΠΈ Π°ΠΊΡ†ΠΈΡ˜Π°, со Π²ΠΊΠ»ΡƒΡ‡ΡƒΠ²Π°ΡšΠ΅ Π½Π° ситС засСгнати страни - Π²ΠΊΠ»ΡƒΡ‡ΡƒΠ²Π°Ρ˜ΡœΠΈ Π³ΠΈ ΠΈ Π»ΠΎΠΊΠ°Π»Π½ΠΈΡ‚Π΅ Π·Π°Π΅Π΄Π½ΠΈΡ†ΠΈ, Π΅ СдинствСниот Π½Π°Ρ‡ΠΈΠ½ Π΄Π° сС ΠΎΠΏΡ‚ΠΈΠΌΠΈΠ·ΠΈΡ€Π° Π΅ΠΊΡΠΏΠ»ΠΎΠ°Ρ‚Π°Ρ†ΠΈΡ˜Π°Ρ‚Π° Π½Π° ΠΌΠΈΠ½Π΅Ρ€Π°Π»Π½ΠΈ суровини ΠΈ ΠΎΠ΄Ρ€ΠΆΠ»ΠΈΠ²ΠΈΠΎΡ‚ Ρ€Π°Π·Π²ΠΎΡ˜, ΠΈ Π΄Π° сС ΠΈΠ΄Π΅Π½Ρ‚ΠΈΡ„ΠΈΠΊΡƒΠ²Π°Π°Ρ‚ ΠΈ ΠΈΠ·Π±Π΅Π³Π½Π°Ρ‚ ΠΏΠΎΡ‚Π΅Π½Ρ†ΠΈΡ˜Π°Π»Π½ΠΈΡ‚Π΅ ΠΊΠΎΠ½Ρ„Π»ΠΈΠΊΡ‚ΠΈ Π²ΠΎ ΠΊΠΎΡ€ΠΈΡΡ‚Π΅ΡšΠ΅Ρ‚ΠΎ Π½Π° Π·Π΅ΠΌΡ˜ΠΈΡˆΡ‚Π΅Ρ‚ΠΎ. Π”Π° сС Ρ€Π°Π·Π²ΠΈΠ΅ Ρ‚Π°ΠΊΠΎΠ² процСс Π½Π° Ρ€Π°Ρ†ΠΈΠΎΠ½Π°Π»Π΅Π½ ΠΈ ΠΏΡ€Π°Π²Π΅Π΄Π΅Π½ Π½Π°Ρ‡ΠΈΠ½ ΠΊΠΎΠ΅ Π½Π΅ΠΈΠ·Π±Π΅ΠΆΠ½ΠΎ Π±Π°Ρ€Π° Ρ‚ΠΎΡ‡Π½ΠΈ Π±Π°Π·ΠΈ Π½Π° ΠΏΠΎΠ΄Π°Ρ‚ΠΎΡ†ΠΈ Π·Π° Ρ€Π°ΡΠΏΠΎΠ»Π°Π³Π°ΡšΠ΅ со ΠΌΠΈΠ½Π΅Ρ€Π°Π»Π½ΠΈΡ‚Π΅ рСсурси, 2 ΠΊΠ°ΠΊΠΎ ΠΈ транспарСнтСн ΠΈ ΠΎΡ‚Π²ΠΎΡ€Π΅Π½ Π½Π°Ρ‡ΠΈΠ½ Π·Π° ΡΠΏΠΎΠ΄Π΅Π»ΡƒΠ²Π°ΡšΠ΅ ΠΈ ΠΊΠΎΠΎΡ€Π΄ΠΈΠ½Π°Ρ†ΠΈΡ˜Π° Π½Π° ΠΌΡƒΠ»Ρ‚ΠΈ-кориснички ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ. Од ΠΏΠΎΡ‡Π΅Ρ‚ΠΎΠΊΠΎΡ‚ Π½Π° осумдСсСттитС Π³ΠΎΠ΄ΠΈΠ½ΠΈ, ΠΌΠ½ΠΎΠ³Ρƒ ΠΊΠΎΠΌΠΏΠ°Π½ΠΈΠΈ ΠΊΠΎΠΈ сС Π·Π°Π½ΠΈΠΌΠ°Π²Π°Π°Ρ‚ со гСолошки ΠΈΡΡ‚Ρ€Π°ΠΆΡƒΠ²Π°ΡšΠ° ΠΏΠΎΡ‡Π½Π°Π° Π΄Π° Ρ€Π°Π·Π²ΠΈΠ²Π°Π°Ρ‚ Π±Π°Π·ΠΈ Π½Π° ΠΏΠΎΠ΄Π°Ρ‚ΠΎΡ†ΠΈ Π½Π° Π½Π°ΠΎΡ“Π°Π»ΠΈΡˆΡ‚Π°Ρ‚Π°, ΠΈ дСнСс Π“Π˜Π‘ ΠΈ Π΄ΠΈΠ³ΠΈΡ‚Π°Π»Π½Π°Ρ‚Π° ΠΏΠΎΠ΄Π³ΠΎΡ‚ΠΎΠ²ΠΊΠ° Π½Π° ΠΊΠ°Ρ€Ρ‚ΠΈ ΠΊΠ°ΠΊΠΎ ΠΈ Π½ΠΈΠ²Π½ΠΎΡ‚ΠΎ ΠΌΠΎΠ΄Π΅Π»ΠΈΡ€Π°ΡšΠ΅ сС Π½Π° ΠΏΡ€Π²ΠΎ мСсто. Π£ΡˆΡ‚Π΅ ΠΏΠΎΠ²Π°ΠΆΠ½ΠΎ, сСпак Π΅ способноста Π΄Π° сС Ρ€Π°Π·ΠΌΠ΅Π½ΡƒΠ²Π°Π°Ρ‚ ΠΏΠΎΠ΄Π°Ρ‚ΠΎΡ†ΠΈ ΠΈ Π΄Π° сС ΠΈΠ½Ρ‚Π΅Π³Ρ€ΠΈΡ€Π° повСќС ΠΈΠ»ΠΈ ΠΏΠΎΠΌΠ°Π»ΠΊΡƒ со Π΄Ρ€ΡƒΠ³ΠΈ Π±Π°Π·ΠΈ Π½Π° ΠΏΠΎΠ΄Π°Ρ‚ΠΎΡ†ΠΈ, способноста Π΄Π° сС ΠΏΡ€Π΅Π±Π°Ρ€ΡƒΠ²Π° ΠΈ ΠΌΠ°Π½ΠΈΠΏΡƒΠ»ΠΈΡ€Π° со Π±Π°Π·Π°Ρ‚Π° Π½Π° ΠΏΠΎΠ΄Π°Ρ‚ΠΎΡ†ΠΈ ΠΈ Π΄Π° сС Π½Π°ΠΏΡ€Π°Π²Π°Ρ‚ ΠΊΠ°Ρ€Ρ‚ΠΈ ΠΈ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΊΠΎΠΈ сС основа Π½Π° ΠΌΠ½ΠΎΠ³Ρƒ истраТни ΠΏΡ€ΠΎΠ΅ΠΊΡ‚ΠΈ. Π¦Π΅Π»Ρ‚Π° Π½Π° овој магистарски Ρ‚Ρ€ΡƒΠ΄ Π΅ Π΄Π° сС Π½Π°ΠΏΡ€Π°Π²ΠΈ синтСза Π½Π° Ρ€Π΅Π·Π»ΡƒΡ‚Π°Ρ‚ΠΈΡ‚Π΅ ΠΎΠ΄ ΠΈΡΡ‚Ρ€Π°ΠΆΡƒΠ²Π°ΡšΠ΅Ρ‚ΠΎ Π½Π° Π½Π°ΠΎΡ“Π°Π»ΠΈΡˆΡ‚Π΅Ρ‚ΠΎ Π·Π° Π±Π°ΠΊΠ°Ρ€ Казандол, со посСбСн осврт Π½Π° Ρ„ΠΎΡ€ΠΌΠΈΡ€Π°ΡšΠ΅Ρ‚ΠΎ Π½Π° Π±Π°Π·Π° Π½Π° ΠΏΠΎΠ΄Π°Ρ‚ΠΎΡ†ΠΈ ΠΈ ΠΈΠ½Ρ‚Π΅Ρ€ΠΏΡ€Π΅Ρ‚Π°Ρ†ΠΈΡ˜Π° Π½Π° иститС ΠΊΠΎΠΈ ќС Π΄Π°Π΄Π°Ρ‚ придонСс Π²ΠΎ ΠΏΠΎΠ½Π°Ρ‚Π°ΠΌΠΎΡˆΠ½ΠΈΠΎΡ‚ Ρ‚Π΅ΠΊ Π½Π° ΠΈΡΡ‚Ρ€Π°ΠΆΡƒΠ²Π°ΡšΠ΅Ρ‚ΠΎ. Π‘ΠΎ овој магистарски Ρ‚Ρ€ΡƒΠ΄ ќС Π±ΠΈΠ΄Π΅ ΠΎΠΏΡ„Π°Ρ‚Π΅Π½Π° Π΅Π΄Π½Π° доста комплСксна Ρ‚Π΅ΠΌΠ° Π½Π° синтСза Π½Π° ΠΏΠΎΠ΄Π°Ρ‚ΠΎΡ†ΠΈΡ‚Π΅ ΠΎΠ΄ Ρ€Π°Π·Π»ΠΈΡ‡Π½ΠΈΡ‚Π΅ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈ Π½Π° ΠΈΡΡ‚Ρ€Π°ΠΆΡƒΠ²Π°ΡšΠ΅ ΠΊΠΎΠΈ Π±Π΅Π° ΠΏΡ€ΠΈΠΌΠ΅Π½Π΅Ρ‚ΠΈ Π½Π° Ρ‚Π΅Ρ€Π΅Π½ΠΎΡ‚ Π·Π° Ρ€Π΅ΡˆΠ°Π²Π°ΡšΠ΅ Π½Π° Π½ΠΈΠ·Π° ΠΏΡ€Π°ΡˆΠ°ΡšΠ° ΠΊΠΎΠΈ Π±Π΅Π° поставСни ΠΏΡ€Π΅Π΄ ΠΏΠΎΡ‡Π΅Ρ‚ΠΎΠΊΠΎΡ‚ Π½Π° ΠΈΡΡ‚Ρ€Π°ΠΆΡƒΠ²Π°ΡšΠ΅Ρ‚ΠΎ

    Geochemical study and 3D modelling of the Kazan Dol copper deposit, Republic of Macedonia

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    The latest explorations and study of the Kazan Dol locality displayed interesting lithogeochemistry and soil geochemistry results. Very indicative were copper contents of up to 9942 ppm Cu, zinc up to 1235 ppm Zn, lead up to 5501 ppm Pb, molybdenum up to 24 ppm Mo, etc. These anomalous zones were direct product of copper vein mineralizations in oxidation zones, which have been confirmed with later exploration drill holes. In some individual samples, from trenches and drill holes, copper content reached up to 4% Cu while the more common content is around 0.4% Cu. More than 27 drill holes were chosen for the construction of the 3D model of the Kazan Dol mineralized area, Republic of Macedonia. With use of the professional software ArcGIS was prepared 3D model of the deposit, which reflects the mineralization between level 340 and 180. This particular model should improve our understanding of the copper bearing mineralizations in this area

    RESOURCE MODELLING AT THE ILOVICA-Ε TUKA PORPHYRY COPPER-GOLD DEPOSIT, EASTERN MACEDONIA

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    The Ilovica-Ε tuka porphyry system is located in southeast Macedonia, within the Tertiary belt associated with tectonic accretion along the western Tethyan belt. The intrusive is about 1.5 km in diameter and comprises a dacite-granodiorite plug, emplaced along the northeastern border of the Strumica graben. Mineralization is typical porphyry style veining, most intense within the potassic zone. The mineralization shows good continuity and homogeneity that lends itself well to bulk-mining methods. Modelling and estimation has been completed using Geovia Surpac. Exploratory data analysis highlighted a number of statistically differentiated grade populations, which were interpreted to be controlled by the following: alteration style, lithology, oxidation state elevation and stockwork intensity. Statistical and grade continuity analyses were completed to characterize the mineralization and subsequently used to develop grade interpolation parameters. Grade estimation was completed using ordinary kriging. The search ellipsoid dimensions and orientations were chosen to reflect the continuity revealed by geostatistical studies and optimized using quantitative kriging neighbourhood analysis. The mineral resource was classified according to CIM Definition Standards on Mineral Resources and Mineral Reserves (CIM 2010). Key words: Canadian Institute of Mining; Metallurgy and Petroleum (CIM) Definition Standards; EDA (exploratory data analysis); domaining; block model; ordinary kriging; kriging neighbourhood analysi

    3D Modeling of some copper deposits in the Republic of Macedonia

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    This paper aims at presenting the 3D models of respective geological settings, deformation structures and geochemical distributions, in terms of better understanding of the related ore-genetic processes and exploration potential. Since the beginnings of mining industry the challenge of mineral exploration is to approach new exploration targets. In that direction, 3D and 4D modelling are the new exploration tools that can help the mineral explorers to visualise, interpolate and interpret geological data, which are critical timeand money-saving methods. In this study 3D-models had been constructed for several Macedonian CuAu polymetallic deposits Kadiica, Plavica, Kazan Dol and Borov Dol. Our 3D models were built by mapping geochemical variations in the Move software by Midland Valley for Kadiica Cu-porphyry deposit and Borov Dol Cu-Au porphyry deposit (gives the opportunity to the user to create slices of the 3D grid and take a closer look to the spatial variation of an assay) as well as in Target 3D for ArcGIS system for Cu-Au high sulphidation epithermal Plavica deposit and Cu vein type deposit Kazan Dol
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