NL2033632A - Method for evaluating ore-bearing potential of porphyry system based on mineral geochemistry - Google Patents
Method for evaluating ore-bearing potential of porphyry system based on mineral geochemistry Download PDFInfo
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- 229910052500 inorganic mineral Inorganic materials 0.000 title claims abstract description 41
- 239000011707 mineral Substances 0.000 title claims abstract description 41
- 238000000034 method Methods 0.000 title claims abstract description 30
- 239000011435 rock Substances 0.000 claims abstract description 130
- 239000000126 substance Substances 0.000 claims abstract description 15
- 239000011573 trace mineral Substances 0.000 claims description 44
- 235000013619 trace mineral Nutrition 0.000 claims description 44
- 235000010755 mineral Nutrition 0.000 claims description 35
- 229910052892 hornblende Inorganic materials 0.000 claims description 31
- VYPSYNLAJGMNEJ-UHFFFAOYSA-N Silicium dioxide Chemical compound O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 claims description 29
- 238000011109 contamination Methods 0.000 claims description 25
- 229910052845 zircon Inorganic materials 0.000 claims description 25
- GFQYVLUOOAAOGM-UHFFFAOYSA-N zirconium(iv) silicate Chemical compound [Zr+4].[O-][Si]([O-])([O-])[O-] GFQYVLUOOAAOGM-UHFFFAOYSA-N 0.000 claims description 25
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 24
- 229910052760 oxygen Inorganic materials 0.000 claims description 24
- 239000001301 oxygen Substances 0.000 claims description 24
- 229910052681 coesite Inorganic materials 0.000 claims description 19
- 229910052906 cristobalite Inorganic materials 0.000 claims description 19
- 229910052682 stishovite Inorganic materials 0.000 claims description 19
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- 239000010936 titanium Substances 0.000 claims description 16
- 230000000155 isotopic effect Effects 0.000 claims description 15
- 238000004458 analytical method Methods 0.000 claims description 14
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- 238000011065 in-situ storage Methods 0.000 claims description 12
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- LIVNPJMFVYWSIS-UHFFFAOYSA-N silicon monoxide Inorganic materials [Si-]#[O+] LIVNPJMFVYWSIS-UHFFFAOYSA-N 0.000 claims description 11
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 claims description 10
- 238000005065 mining Methods 0.000 claims description 9
- 229910052712 strontium Inorganic materials 0.000 claims description 9
- 229910052684 Cerium Inorganic materials 0.000 claims description 8
- 229910052693 Europium Inorganic materials 0.000 claims description 8
- 229910052688 Gadolinium Inorganic materials 0.000 claims description 8
- 229910052779 Neodymium Inorganic materials 0.000 claims description 8
- 229910052772 Samarium Inorganic materials 0.000 claims description 8
- 229910052706 scandium Inorganic materials 0.000 claims description 8
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- 239000012530 fluid Substances 0.000 claims description 6
- 238000000095 laser ablation inductively coupled plasma mass spectrometry Methods 0.000 claims description 6
- 230000005856 abnormality Effects 0.000 claims description 5
- 229910052586 apatite Inorganic materials 0.000 claims description 5
- VSIIXMUUUJUKCM-UHFFFAOYSA-D pentacalcium;fluoride;triphosphate Chemical compound [F-].[Ca+2].[Ca+2].[Ca+2].[Ca+2].[Ca+2].[O-]P([O-])([O-])=O.[O-]P([O-])([O-])=O.[O-]P([O-])([O-])=O VSIIXMUUUJUKCM-UHFFFAOYSA-D 0.000 claims description 5
- 239000000377 silicon dioxide Substances 0.000 claims description 5
- 238000004452 microanalysis Methods 0.000 claims description 4
- 239000000203 mixture Substances 0.000 claims description 4
- 229910052719 titanium Inorganic materials 0.000 claims description 4
- RTAQQCXQSZGOHL-UHFFFAOYSA-N Titanium Chemical compound [Ti] RTAQQCXQSZGOHL-UHFFFAOYSA-N 0.000 claims description 3
- 229910052788 barium Inorganic materials 0.000 claims description 3
- DSAJWYNOEDNPEQ-UHFFFAOYSA-N barium atom Chemical compound [Ba] DSAJWYNOEDNPEQ-UHFFFAOYSA-N 0.000 claims description 3
- 238000004453 electron probe microanalysis Methods 0.000 claims description 3
- 229910052746 lanthanum Inorganic materials 0.000 claims description 3
- FZLIPJUXYLNCLC-UHFFFAOYSA-N lanthanum atom Chemical compound [La] FZLIPJUXYLNCLC-UHFFFAOYSA-N 0.000 claims description 3
- GWXLDORMOJMVQZ-UHFFFAOYSA-N cerium Chemical compound [Ce] GWXLDORMOJMVQZ-UHFFFAOYSA-N 0.000 claims description 2
- OGPBJKLSAFTDLK-UHFFFAOYSA-N europium atom Chemical compound [Eu] OGPBJKLSAFTDLK-UHFFFAOYSA-N 0.000 claims description 2
- UIWYJDYFSGRHKR-UHFFFAOYSA-N gadolinium atom Chemical compound [Gd] UIWYJDYFSGRHKR-UHFFFAOYSA-N 0.000 claims description 2
- 230000008676 import Effects 0.000 claims description 2
- QEFYFXOXNSNQGX-UHFFFAOYSA-N neodymium atom Chemical compound [Nd] QEFYFXOXNSNQGX-UHFFFAOYSA-N 0.000 claims description 2
- KZUNJOHGWZRPMI-UHFFFAOYSA-N samarium atom Chemical compound [Sm] KZUNJOHGWZRPMI-UHFFFAOYSA-N 0.000 claims description 2
- SIXSYDAISGFNSX-UHFFFAOYSA-N scandium atom Chemical compound [Sc] SIXSYDAISGFNSX-UHFFFAOYSA-N 0.000 claims description 2
- 229910052814 silicon oxide Inorganic materials 0.000 claims description 2
- CIOAGBVUUVVLOB-UHFFFAOYSA-N strontium atom Chemical compound [Sr] CIOAGBVUUVVLOB-UHFFFAOYSA-N 0.000 claims description 2
- LEONUFNNVUYDNQ-UHFFFAOYSA-N vanadium atom Chemical compound [V] LEONUFNNVUYDNQ-UHFFFAOYSA-N 0.000 claims description 2
- VWQVUPCCIRVNHF-UHFFFAOYSA-N yttrium atom Chemical compound [Y] VWQVUPCCIRVNHF-UHFFFAOYSA-N 0.000 claims description 2
- UQSXHKLRYXJYBZ-UHFFFAOYSA-N Iron oxide Chemical compound [Fe]=O UQSXHKLRYXJYBZ-UHFFFAOYSA-N 0.000 claims 4
- 235000012239 silicon dioxide Nutrition 0.000 claims 4
- GWEVSGVZZGPLCZ-UHFFFAOYSA-N Titan oxide Chemical compound O=[Ti]=O GWEVSGVZZGPLCZ-UHFFFAOYSA-N 0.000 claims 2
- OGIDPMRJRNCKJF-UHFFFAOYSA-N titanium oxide Inorganic materials [Ti]=O OGIDPMRJRNCKJF-UHFFFAOYSA-N 0.000 claims 2
- 230000002378 acidificating effect Effects 0.000 claims 1
- 238000003801 milling Methods 0.000 claims 1
- 238000012360 testing method Methods 0.000 abstract description 4
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- 238000012863 analytical testing Methods 0.000 description 3
- 230000033558 biomineral tissue development Effects 0.000 description 3
- 208000010642 Porphyrias Diseases 0.000 description 2
- 229910052782 aluminium Inorganic materials 0.000 description 2
- 230000015572 biosynthetic process Effects 0.000 description 2
- 239000011575 calcium Substances 0.000 description 2
- 239000000460 chlorine Substances 0.000 description 2
- 239000010949 copper Substances 0.000 description 2
- 238000012937 correction Methods 0.000 description 2
- 239000010438 granite Substances 0.000 description 2
- SZVJSHCCFOBDDC-UHFFFAOYSA-N iron(II,III) oxide Inorganic materials O=[Fe]O[Fe]O[Fe]=O SZVJSHCCFOBDDC-UHFFFAOYSA-N 0.000 description 2
- 239000000155 melt Substances 0.000 description 2
- 229910052751 metal Inorganic materials 0.000 description 2
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- 238000011160 research Methods 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- OYPRJOBELJOOCE-UHFFFAOYSA-N Calcium Chemical compound [Ca] OYPRJOBELJOOCE-UHFFFAOYSA-N 0.000 description 1
- ZAMOUSCENKQFHK-UHFFFAOYSA-N Chlorine atom Chemical compound [Cl] ZAMOUSCENKQFHK-UHFFFAOYSA-N 0.000 description 1
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 description 1
- 208000035126 Facies Diseases 0.000 description 1
- DGAQECJNVWCQMB-PUAWFVPOSA-M Ilexoside XXIX Chemical compound C[C@@H]1CC[C@@]2(CC[C@@]3(C(=CC[C@H]4[C@]3(CC[C@@H]5[C@@]4(CC[C@@H](C5(C)C)OS(=O)(=O)[O-])C)C)[C@@H]2[C@]1(C)O)C)C(=O)O[C@H]6[C@@H]([C@H]([C@@H]([C@H](O6)CO)O)O)O.[Na+] DGAQECJNVWCQMB-PUAWFVPOSA-M 0.000 description 1
- 229910003251 Na K Inorganic materials 0.000 description 1
- ZLMJMSJWJFRBEC-UHFFFAOYSA-N Potassium Chemical group [K] ZLMJMSJWJFRBEC-UHFFFAOYSA-N 0.000 description 1
- NINIDFKCEFEMDL-UHFFFAOYSA-N Sulfur Chemical compound [S] NINIDFKCEFEMDL-UHFFFAOYSA-N 0.000 description 1
- UCKMPCXJQFINFW-UHFFFAOYSA-N Sulphide Chemical compound [S-2] UCKMPCXJQFINFW-UHFFFAOYSA-N 0.000 description 1
- 239000004411 aluminium Substances 0.000 description 1
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 229910052791 calcium Inorganic materials 0.000 description 1
- 229910052951 chalcopyrite Inorganic materials 0.000 description 1
- DVRDHUBQLOKMHZ-UHFFFAOYSA-N chalcopyrite Chemical compound [S-2].[S-2].[Fe+2].[Cu+2] DVRDHUBQLOKMHZ-UHFFFAOYSA-N 0.000 description 1
- 229910052801 chlorine Inorganic materials 0.000 description 1
- 229910052802 copper Inorganic materials 0.000 description 1
- 238000002425 crystallisation Methods 0.000 description 1
- 230000008025 crystallization Effects 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 238000001640 fractional crystallisation Methods 0.000 description 1
- 238000000227 grinding Methods 0.000 description 1
- 230000005764 inhibitory process Effects 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 229910052976 metal sulfide Inorganic materials 0.000 description 1
- 150000002739 metals Chemical class 0.000 description 1
- 238000013508 migration Methods 0.000 description 1
- 230000005012 migration Effects 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 239000011591 potassium Substances 0.000 description 1
- 229910052700 potassium Inorganic materials 0.000 description 1
- 238000001556 precipitation Methods 0.000 description 1
- 229910052708 sodium Inorganic materials 0.000 description 1
- 239000011593 sulfur Substances 0.000 description 1
- 229910052717 sulfur Inorganic materials 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/24—Earth materials
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
- G01N27/62—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating the ionisation of gases, e.g. aerosols; by investigating electric discharges, e.g. emission of cathode
- G01N27/64—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating the ionisation of gases, e.g. aerosols; by investigating electric discharges, e.g. emission of cathode using wave or particle radiation to ionise a gas, e.g. in an ionisation chamber
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Abstract
Method For Evaluating Ore-Bearing Potential Of Porphyry System Based On Mineral Geochemistry 5 The present disclosure provides a method for evaluating ore-bearing potential of a porphyry system based on mineral geochemistry, which uses whole rock geochemical and mineral chemical parameters to indicate the ore-bearing potential of rock masses. Specifically, according to metallogenic characteristics of porphyry deposits, whole rock geochemical and mineral chemical data are used to quantitatively identify discrimination factors of 10 metallogenetic rocks in the porphyry systems that are used in the field of porphyry systems exploration. With the advantages of short testing time, low cost, convenience and efficiency, the method can effectively discriminate between metallogenetic and barren rocks in the porphyry system and shorten a mineral exploration cycle. The method is a new and indispensable means and method, which is worthy of promotion and popularization.
Description
METHOD FOR EVALUATING ORE-BEARING POTENTIAL OF PORPHYRY
SYSTEM BASED ON MINERAL GEOCHEMISTRY
[0001] The present disclosure belongs to the field of mineral resources exploration and evaluation, and particularly relates to a method for evaluating ore-bearing potential of a porphyry system based on mineral geochemistry. The present disclosure aims to discriminate between metallogenetic and barren rocks in the porphyry system by designing and using whole rock geochemistry and mineral (zircon and hornblende) chemistry.
[0002] Porphyry deposits are typically characterized by large tonnage, low grade, large-scale hydrothermal alteration, and metal sulfide enrichment. The formation of large porphyry deposits requires magma with high oxygen fugacity, water content, and volatile elements such as sulfur (S) and chlorine (Cl). Herein, magmatic water has important control effects on metal element migration and ore-bearing hydrothermal fluid precipitation, and high oxygen fugacity enables deep metals to be released from the sulfide facies and thus brought to shallow metallogenic system. Therefore, finding out characteristics of magmatic water in rock masses and oxygen fugacity is a key to the determination of metallogenetic rocks. During the formation of porphyry deposits, high magmatic water content and oxygen fugacity are recorded in magma generation and fractional crystallization. Thus, metallogenetic and barren rocks can be effectively discriminated by using whole rock geochemistry and chemical composition of minerals (zircon and hornblende).
[0003] Conventionally, to look for areas with metallogenic potential of porphyries, a wide range of geochemical surveys, geophysical surveys, regional geological surveys, systematic testing and comprehensive research should be carried out, but there are certain disadvantages: long pre-cycle of exploration and evaluation, high cost, low accuracy, and failure to meet the urgent demand for rapid exploration and evaluation.
[0004] In view of the above problems, the present disclosure, through substantial experimental research and prospecting practice, sets forth quantitative indexes for the rapid identification of metallogenetic rocks in the porphyry metallogenic system, solves technical problems of prospecting porphyry deposits, and realizes the organic combination of mineral geochemistry and ore-bearing potential evaluation.
[0005] An objective of the present disclosure is to provide a method for evaluating ore- bearing potential of a porphyry system based on mineral geochemistry, with short testing time, low cost, convenience and efficiency. The method can rapidly evaluate the ore-bearing potential of porphyry on a large scale, effectively discriminate between metallogenetic and barren rocks in the porphyry systems, and shorten a mineral exploration cycle.
[0006] To solve the above-mentioned technical problem, the present disclosure adopts the following technical solution:
[0007] A method for evaluating ore-bearing potential of a porphyry system based on mineral geochemistry is provided, including the following steps:
[0008] step 1, systematically collecting pre-existing regional geological, geophysical exploration, geochemical exploration and remote sensing data, and defining a prospecting target area;
[0009] step 2, systematically collecting all intermediate-acidic rock masses in a targeted area, and describing lithological, alteration and mineralization characteristics of each type of sample;
[0010] step 3, selecting non-altered or weakly altered samples from the target area for chemical analysis to obtain: content of whole rock major and trace elements silica (S102), strontium (Sr), yttrium (Y), vanadium (V), and scandium (Sc), denoted as c(S102), c(Sr), c(Y), c(V), and c(Sc), respectively; content of zircon trace elements cerium (Ce), neodymium (Nd), Y, europium (Eu), samarium (Sm), and gadolinium (Gd), denoted as c(Ce), c¢(Nd), c(Y'), c(Eu), ¢(Sm), and c(Gd), respectively; and temperature of hornblende (T) and oxygen fugacity (AFMQ); and
[0011] step 4, conducting discrimination on the samples by using discrimination factors F1 to
F4 to determine whether the samples are metallogenetic rocks or barren rocks:
[0012] discrimination factor F1: F1 =-0.925%¢(S10;) + 113.75 (formula 1);
[0013] discrimination factor F2: F2 = -0.355*c(S102) + 34.15 (formula 2);
[0014] discrimination factor F3: F3 = -41.7*(c(Ce)/c(Nd))/c(Y") + 4.707 (formula 3);
[0015] discrimination factor F4: F4 = -0.0025*c(T) + 3.8 (formula 4),
[0016] substituting the content of whole rock major and trace elements SiO; obtained in step 3 into the formula 1 to calculate the discrimination factor F1, where if ¢(Sr)/c(Y) > F1, the samples are determined as the metallogenetic rocks, and otherwise, the samples are determined as the barren rocks;
[0017] substituting the content of whole rock major and trace elements SiO; obtained in step
3 into the formula 2 to calculate the discrimination factor F2, where if ¢(V)/c(Sc) > F2, the samples are determined as the metallogenetic rocks, and otherwise, the samples are determined as the barren rocks;
[0018] substituting a zircon (c(Ce)/c(Nd))/c(Y') ratio calculated according to the content of zircon trace elements obtained in step 3 into the formula 3 to calculate the discrimination factor F3, where if 10000*(c(Eu)/c(Eu*))/c(Y') > F3, the samples are determined as the metallogenetic rocks, and otherwise, the samples are determined as the barren rocks, where c(Eu*) = Je(Sm)/c(Gd); and
[0019] substituting the temperature of hornblende (T) obtained in step 3 into the formula 4 to calculate the discrimination factor F4, where if AFMQ > F4, the samples are determined as the metallogenetic rocks, and otherwise, the samples are determined as the barren rocks;
[0020] if all of the four discrimination factors are calculated to indicate that the samples are the metallogenetic rocks, the samples are determined as the metallogenetic rocks; if at least one of these discrimination factors is discriminated to obtain a barren rock, the samples are determined as the barren rocks.
[0021] If an individual sample is equivalent to a discrimination factor, comprehensive judgment and error correction may be conducted with reference to results of the other three discrimination factors. On the condition that sufficient sample size is guaranteed, discrimination between the metallogenetic and barren rocks obtained based on statistics may be authentic and accurate.
[0022] According to the above solution, in step 3, a specific step of selecting the non-altered or weakly altered samples for the chemical analysis includes: grinding the samples to prepare a powder, microprobe slices and laser in situ targets, where the powder is used to determine whole rock major and trace elements, the microprobe slices and the laser in situ targets are used to determine major and trace elements in monominerals.
[0023] Preferably, the monominerals may be zircon and hornblende.
[0024] More preferably, the samples are ground to prepare the powder, the microprobe slices and the laser in situ targets, the powder is used for whole rock major and trace element analysis to obtain the content of whole rock major and trace elements SiO, Sr, Y, V, and Sc; magmatic hornblende is sorted out from the microprobe slices, and electron microprobe analysis is conducted to further determine a chemical composition and a type of the hornblende and to obtain the temperature of hornblende and the oxygen fugacity; the temperature of hornblende is obtained by T(°C) = (-151.487 x Si*) + 2041, and herein, Si* =
Si + (AIY/15) — (2 x Ti) — (A1Y1/2) — (TiVV1.8) + (Fe**/9) + (Fe?*/3.3) + (Mg/26) + (BCa/5) + (BNa/1.3) — (*Na/15) + ((1 — ANa — #K)/2.3), where AIV and Ti!" are numbers of aluminium (Al) and Ti atoms in a tetrahedron, AI! and Ti"! are numbers of Al and Ti atoms in an octahedron, “Na is sodium (Na) content at position A, AK is potassium (K) content at position A, BNa is Na content at position B, and BCa is calcium (Ca) content at position B; the oxygen fugacity is obtained by log fO; = -24441.9/T (K) + 8.290 (+0. 167); representative minerals (zircon) are selected from the laser iz sifu targets to conduct laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) for in situ microanalysis of elements to obtain the content of zircon trace elements Ce, Nd, Y, Eu, Sm, and Gd.
[0025] According to the above solution, in step 3, for a monomineral, granulated mineral inclusions or inherited minerals are generally met in the process of analysis. To acquire more accurate data, data are necessary to be pre-processed and interpreted, including the following three steps: step (i), importing acquired raw data in a csv format into ICPMSDataCal software, and deleting data of stricken inclusions or punched minerals according to abnormalities of integral curves of elements at each analytical testing point; step (i1), in view of the above undeleted data, using the following criteria to further eliminate contamination data: if a concentration of lanthanum (La) > 1.5 ppm, the monomineral is construed as apatite contamination, if a concentration of iron (Fe) > 5500 ppm, the monomineral is construed as
Fe oxide contamination, if a concentration of titanium (Ti) > 60 ppm, the monomineral is construed as Ti oxide contamination, and if a concentration of barium (Ba) > 10 ppm, the monomineral is construed as fluid inclusion contamination; and step (iii), using *°Pb/2**U isotopic ages to eliminate interference of inherited minerals, wherein an acquired data point is construed as invalid data on conditions that a 2°°Pb/2*8U isotopic age at the data point is less than or greater than a weighted mean 2"*Pb/***U isotopic age of a sample; after the data are processed using the above three steps, the remaining data may be used for subsequent ore- bearing potential evaluation.
[0026] According to the above solution, the obtaining the discrimination factors F1 to F4 in step 4 specifically includes:
[0027] step I, separately selecting at least 60 non-altered or weakly altered metallogenetic rock samples and at least 60 barren rock samples;
[0028] step II, conducting chemical analysis on the samples selected in step I to obtain: the content of whole rock major and trace elements SiO», Sr, Y, V, and Sc, denoted as c(S102), c(Sr), c(Y), c(V), and c(Sc), respectively; the content of zircon trace elements Ce, Nd, Y, Eu,
Sm, and Gd, denoted as c(Ce), c(Nd), c(Y"), c{Eu), c(Sm), and c(Gd), respectively; and the temperature of hornblende (T) and the oxygen fugacity (AFMQ);
[0029] step HI, plotting a scatter plot based on substantial data of metallogenetic and barren rocks developed in mining areas obtained in step 11, and fitting a plurality of data points near a dividing point between the metallogenetic and barren rocks into a straight line to obtain an equation of the straight line, namely the discrimination factor, specifically:
[0030] obtaining the discrimination factors F1 to F4 by fitting and calculation, specifically:
[0031] step a, calculating the discrimination factor F1 5 [0032] for the whole rock major and trace elements obtained in step II, plotting with ¢(Si0;) as an abscissa and c(Sr)/c(Y) as an ordinate, obtaining and fitting a dividing line between the metallogenetic and barren rocks according to a plotting range, and using the following formula to calculate the discrimination factor FI: F1 =-0.925%¢(S10;) + 113.75 (formula 1);
[0033] step b, calculating the discrimination factor F2
[0034] for the whole rock major and trace elements obtained in step II, plotting with c(S102) as an abscissa and ¢(V)/c(Sc) as an ordinate, obtaining and fitting a dividing line between the metallogenetic and barren rocks according to a plotting range, and using the following formula to calculate the discrimination factor F2: F2 = -0.355*¢(S10;) + 34.15 (formula 2);
[0035] step c, calculating the discrimination factor F3
[0036] for the zircon trace elements obtained in step II, plotting with (c(Ce)/c{Nd))/c(Y") as an abscissa and 10000*(c(Eu)/c(Eu*))/c(Y") as an ordinate, where Eu* = Je(Sm)/c(Gd); obtaining and fitting a dividing line between the metallogenetic and barren rocks according to a plotting range, and using the following formula to calculate the discrimination factor F3: F3 = -41.7*(c(Ce)/c(Nd))/c(Y") + 4.707 (formula 3); and
[0037] step (4), calculating the discrimination factor F4
[0038] for components of the hornblende obtained in step II, calculating a forming temperature thereof and the oxygen fugacity, plotting with temperature (T) as an abscissa and the oxygen fugacity (AFMQ) as an ordinate, obtaining and fitting a dividing line between the metallogenetic and barren rocks according to a plotting range, and using the following formula to calculate the discrimination factor F4: F4 = -0.0025* T + 3.8 (formula 4).
[0039] Preferably, in step II, for a monomineral, the granulated mineral inclusions or the inherited minerals are generally met in the process of analysis. To acquire more accurate data, data are necessary to be pre-processed and interpreted, including the following three steps: step (2.1), importing the acquired raw data in a csv format into ICPMSDataCal software, and deleting the data of the stricken inclusions or the punched minerals according to the abnormalities of the integral curves of the elements at each analytical testing point; step (2.2), in view of the above undeleted data, using the following criteria to further eliminate the contamination data: if a concentration of La > 1.5 ppm, the monomineral is construed as the apatite contamination, if a concentration of Fe > 5500 ppm, the monomineral is construed as
Fe oxide contamination, if a concentration of Ti > 60 ppm, the monomineral is construed as the Ti oxide contamination, and if a concentration of Ba > 10 ppm, the monomineral is construed as the fluid inclusion contamination; and step (2.3), using the 29Pb/233U isotopic ages to eliminate the interference of the inherited minerals, wherein the acquired data point is construed as the invalid data on conditions that the 29Pb2338U isotopic age at the data point is less than or greater than the weighted mean 2°5Pb/233U isotopic age of the sample; after the data are processed using the above three steps, the remaining data may be used for subsequent ore-bearing potential evaluation.
[0040] The present disclosure provides a new method for rapidly evaluating ore-bearing potential of regional porphyries on a large scale, which uses whole rock geochemical and mineral chemical parameters to indicate the ore-bearing potential of rock masses. Herein, the principle of obtaining the discrimination factors F1 to F4 is as follows: in view of porphyry deposits, a key to mineralization is high magmatic oxygen fugacity and water content, for example, in H:O-rich magmatic system (>6% HzO), hornblende, plagioclase, and magnetite crystallize successively, and inhibition of early crystallization of the plagioclase and the magnetite leads to increases in Sr and V in residual melts and near-normalization of EwEu* value in evolving aqueous melts; the hornblende crystallizes out to cause decreases in Sc and
Y, and finally causes rock masses with metallogenic potential to have the characteristics of high whole rock ¢(Sr)/c(Y) and c(V)/c(Sc) ratios, high zircon 10000*(c(Eu)/c(Eu*))/c(Y') and (c(Ce)/c(Nd))/c(Y') ratios, and high oxygen fugacity of hornblende. A scatter plot is plotted based on these characteristics and substantial data of metallogenetic and barren rocks developed in mining areas, and a straight line is fitted according to a plurality of data points near a dividing point between the metallogenetic and barren rocks, an equation of the straight line, namely the discrimination factor, is obtained, and thus four discrimination factors, F1 to
F4, are obtained.
[0041] Relevant parameters of discrimination factors may have some errors, but on the premise of taking metallogenic characteristics of porphyry deposits into account (there are no significant changes in chemical properties of metallogenetic and barren rocks in different porphyry deposits) and in the case of a large number of data points (>10) of prediction samples, the discrimination factors provided by the present disclosure based on statistics can define the scopes of the metallogenetic and barren rocks and satisfy rapid evaluation of the ore-bearing potential of rock masses developed on a regional scale.
[0042] The present disclosure has the following beneficial effects:
[0043] The present disclosure provides a method for evaluating ore-bearing potential of a porphyry system based on mineral geochemistry. According to metallogenic characteristics of porphyry deposits, whole rock geochemical and mineral chemical data are used to quantitatively identify discrimination factors of metallogenetic rocks in the porphyry systems that are used in the field of the exploration of porphyry systems. Due to advantages of short testing time, low cost, convenience and efficiency, the method can effectively discriminate between metallogenetic and barren rocks in the porphyry systems and shorten a mineral exploration cycle. The method is a new and indispensable means and method and has important value in promotion and popularization.
[0044] FIG. 1 shows scatter plots and fitting straight lines plotted based on the data of metallogenetic and barren rocks according to an embodiment of the present disclosure, wherein panels (a) and (b) illustrate whole rock major and trace elements; panel (c) illustrates zircon trace elements; panel (d) illustrates temperature of hornblende and oxygen fugacity, and curve equations of panels (a) to (d) correspond to discrimination factors F1 to F4.
[0045] FIG. 2 shows a flowchart for discriminating metallogenetic rocks in a porphyry metallogenic system according to an embodiment of the present disclosure.
[0046] The present disclosure will be further described below in conjunction with specific examples.
[0047] Example 1
[0048] Discrimination factors F1 to F4 were obtained. Specific steps were as follows:
[0049] Step 1, 61 non-altered or weakly altered metallogenetic rock samples and 66 barren rock samples were selected, respectively.
[0050] Step 2, samples selected in step 1 were ground to prepare powders, microprobe slices and laser in situ targets. Rock powders were used for whole rock major and trace element analysis. For the microprobe slice, magmatic hornblende was sorted out microscopically to carry out electron microprobe analysis to further determine a chemical composition and a type of the hornblende. For the laser in sifu targets, representative minerals (zircon) were selected to conduct LA-ICP-MS for in situ microanalysis of elements.
[0051] Step 3, for a monomineral, granulated mineral inclusions or inherited minerals were generally met in the process of LA-ICP-MS for in situ microanalysis. To acquire more accurate data, data were necessary to be pre-processed and interpreted, including the following three steps: step (2.1), acquired raw data in a csv format were imported into
ICPMSDataCal software, and data of stricken inclusions or punched minerals were deleted according to abnormalities of integral curves of elements at each analytical testing point; step
(2.2), in view of the above undeleted data, the following criteria were used to further eliminate contamination data: if a concentration of La > 1.5 ppm, the monomineral is construed as apatite contamination, if a concentration of Fe > 5500 ppm, the monomineral is construed as Fe oxide contamination, if a concentration of Ti > 60 ppm, the monomineral is construed as Ti oxide contamination, and if a concentration of Ba > 10 ppm, the monomineral is construed as fluid inclusion contamination; and step (2.3), 295Pb/233U isotopic ages were used to eliminate the interference of inherited minerals, wherein an acquired data point is construed as invalid data on conditions that a 2°°Pb/2*8U isotopic age at the data point was less than or greater than a weighted mean 2“*Pb/***U isotopic age of a sample. After the data were processed using the above three steps, the remaining data could be used for subsequent ore- bearing potential evaluation.
[0052] Step 4, Excel was used to process the data obtained in step 3 to obtain discrimination factors F1 to F4. Herein, the temperature of hornblende was obtained by T(°C) = (-151.487 x
Si*) + 2041, and the oxygen fugacity was obtained by log 02 = -24441.9/T (K) + 8.290 (+0.167). The content of whole rock major and trace elements SiO, Sr, Y, V, and Sc was defined as c(Si02), c(Sr), c(Y), c(V), and c(Sc), respectively; the content of zircon trace elements Ce, Nd, Y, Eu, Sm, and Gd was defined as c(Ce), c(Nd), ¢(Y"), c(Eu), c(Sm), and c(Gd), respectively. The content of S10: is a weight percentage content of S10; (wt%), while the contents of the rest elements are in unit of ug/g. Specifically:
[0053] A scatter plot shown in FIG. 1 was plotted on the premise that substantial data of metallogenetic and barren rocks developed in mining areas were collected, and a plurality of data points near a dividing point between the metallogenetic and barren rocks were fitted into a straight line to obtain an equation of the straight line, namely the discrimination factor, where:
[0054] step I, calculating the discrimination factor F1
[0055] for the whole rock major and trace elements obtained in step 2, plotting with c(S102) as an abscissa and ¢(Sr)/c(Y) as an ordinate, obtaining and fitting a dividing line between the metallogenetic and barren rocks according to a plotting range, and using the following formula to calculate the discrimination factor F1: F1 = -0.925*¢(S102) + 113.75 (formula 1);
[0056] step II, calculating the discrimination factor F2
[0057] for the whole rock major and trace elements obtained in step 2, plotting with c(S102) as an abscissa and ¢(V)/c(Sc) as an ordinate, obtaining and fitting a dividing line between the metallogenetic and barren rocks according to a plotting range, and using the following formula to calculate the discrimination factor F2: F2 = -0.355*c(S102) + 34.15 (formula 2);
[0058] step III, calculating the discrimination factor F3
[0059] for the zircon trace elements obtained in step 2, plotting was conducted with (c(Ce)/c(Nd))/c(Y") as an abscissa and 10000*(c(Eu)/c(Eu*))/c(Y") as an ordinate; a dividing line between the metallogenetic and barren rocks was obtained and fitted according to a plotting range, and the following formula was used to calculate the discrimination factor F3:
F3 =-41.7*(c(Ce)/c(Nd))/c(Y') + 4.707 (formula 3); and
[0060] step IV, calculating the discrimination factor F4
[0061] for components of the hornblende obtained in step 2, a forming temperature and the oxygen fugacity were calculated, plotting was conducted with temperature (T) as an abscissa and the oxygen fugacity (AFMQ) as an ordinate, a dividing line between the metallogenetic and barren rocks was obtained and fitted according to a plotting range, and the following formula was used to calculate the discrimination factor F4: F4 = -0.0025* T + 3.8 (formula 4).
[0062] Step 5, a method for discriminating between the metallogenetic and barren rocks
[0063] The content of whole rock major and trace elements SiO; obtained was substituted into the formula 1 to calculate the discrimination factor F1. If ¢(Sr)/c(Y) > F1, the samples are determined as the metallogenetic rocks, otherwise, the samples are determined as the barren rocks.
[0064] The content of whole rock major and trace elements SiO; obtained was substituted into the formula 2 to calculate the discrimination factor F2. If c(V)/c(Sc) > F2, the samples are determined as the metallogenetic rocks, otherwise, the samples are determined as the barren rocks.
[0065] A zircon (c(Ce)/c(Nd))/c(Y') ratio obtained was substituted into the formula 3 to calculate the discrimination factor F3. If 10000*(c(Eu)/c(Eu*))/c(Y') > F3, the samples are determined as the metallogenetic rocks, otherwise, the samples are determined as the barren rocks, where c(Eu*) = Je(Sm)/c(Gd)
[0066] The temperature of homblende (T) was substituted into the formula 4 to calculate the discrimination factor F4. If AFMQ > F4, the samples are determined as the metallogenetic rocks, otherwise, the samples are determined as the barren rocks.
[0067] If all of the four discrimination factors are calculated to indicate that the samples are the metallogenetic rocks, the samples are determined as the metallogenetic rocks; if at least one of these discrimination factors is discriminated to obtain a barren rock, the samples are determined as the barren rocks.
[0068] If an individual sample is equivalent to a discrimination factor, comprehensive judgment and error correction may be conducted with reference to results of the other three discrimination factors. On the condition that sufficient sample size is guaranteed, discrimination between the metallogenetic and barren rocks obtained based on statistics may be authentic and accurate.
[0069] Example 2
[0070] A method for evaluating ore-bearing potential of a porphyry system based on whole rock geochemistry and mineral chemistry was provided: for example, Zhunuo porphyry copper (Cu) deposit in Tibet, as shown in FIG. 2, specifically including the following steps:
[0071] Step a. Intermediate-acidic rock masses in Zhunuo mining area, including quartz porphyry, monzogranite porphyry, monzogranite and granite porphyry, were identified through geological mapping and logging.
[0072] Step b. Field sample collection: Weakly altered or non-altered intermediate-acidic rock masses were collected from the ground surface and drill-core of Zhunuo deposit. In the sampling process, the following information was recorded faithfully in detail, as shown in
Table 1:
Table 1 Sampling record sheet of Zhunuo mining area
Sample
No. X Y Lithology Hand specimen alteration ~~ Mineralization Location
ZN1501 527394 3268370 Quartz Weak sericitization None Zhunuo porphyiy
ZN1502 527359 3267072 monzogranite No alteration None Zhunuo
ZN1503 526129 3266961 Granite Weak potassic alteration Minor chalcopyrite Zhunuo porphyry
[0073] Step c. Sample analysis: Samples were ground into powders or microprobe slices and laser in situ targets, the powders were used to determine whole rock major and trace elements, and the microprobe slices and laser in situ targets were used to determine major and trace elements in monominerals. For specific steps, refer to step 2 in Example 1.
[0074] Step d. Data processing: ICPMSDataCal software was used for data processing, including three steps: 1) data import; 2) data interpretation (same as step 3 in Example 1); and 3) data filtering. Finally, the content of whole rock major and trace elements SiOz, Sr, Y, V, and Sc was obtained and denoted as c(S102), c(Sr), e(Y), c(V), and (Sc), respectively; the content of zircon trace elements Ce, Nd, Y, Eu, Sm, and Gd was obtained and denoted as c(Ce), c(Nd), c(Y"), c(Eu), c(Sm), and c(Gd), respectively; the temperature of hornblende and the oxygen fugacity were obtained, where the temperature of hornblende was obtained by
T(°C)=(-151.487 x Si*) + 2041, and the oxygen fugacity was obtained by log fO: = -
24441 9/T (K) + 8.290 (£0.167).
[0075] Step e. Ore-bearing potential evaluation: Using the final data processed in Excel (Tables 2, 3, and 4), the monzogranite (porphyry) sampled in Zhunuo were discriminated as metallogenetic rocks according to calculated results of discrimination factors F1, F2, F3, and
F4, which were consistent with actual metallogenetic rocks in the Zhunuo deposit. This further demonstrated the effectiveness of the new method for evaluating ore-bearing potential of a porphyry system based on mineral geochemistry (FIG. 1).
Table 2 Results of the partial data of whole rock elements in Zhunuo mining area,
Tibet
Lithology Sample No. SiO: (wt%) Sr (ug/g) Y (ng/g) V (ng/g) Se (ug/g) monzogranite 14-D01 70.12 604.01 8.75993 43.4805 4.78 monzogranite 14-D06 69.22 695.495 6.84855 67.4415 6.78 monzogranite ZX2-8 67.29 598.31 6.59775 72.3975 6.84 monzogranite 802-105.8 68.48 6482 9.065 68.38 6.44 monzogranite 802-106.3 68.55 644.5 10.46 78.1 7.19 monzogranite 802-249 4 67.42 631.9 10.09 70.8 6.48
Monzogranite (porphyry) 702-276.2 71.05 37343 4.863 44.6 3.64
Monzograniteporphyty 702-278.5 72.17 3514 4.733 44.39 3.75
Monzograniteporphy ty 702-336.5 71.21 420.9 6.314 46.41 3.73
Monzograniteporphy ry 005-330.1 69.83 424.27 8.3304 46.08 475
Monzogranite porphyry 005-4447 70.00 446.16 7.7058 45.25 3.77
Monzograniteporphy ty 806-202.9 67.92 547.47 10.341 57.62 5.36 monzogranite 1-13 69.11 729.6 6.3483 48.95 3.92 monzogranite 11-14 69.62 748.03 6.19185 53.775 419 monzogranite {1-15 69.44 818.33 6.96465 58.375 4.96 monzogranite 11-16 69.29 743.755 6.05323 51.3875 4.24
Table 3 Results of the partial data of zircon in Zhunuo mining area, Tibet
Lithology Sample No. Y (ug/g) Ce(ng/g) Nd (ug/g) Sm (ug/l) Fu (ug/g) Gd ugg)
Monzogranite ZN11-17-5 285 20.27 0.79 0.67 0.36 3.26
Monzogranite ZN11-17-7 478 31.18 0.33 1.15 0.62 6.24
Monzogranite ZN11-17-11 664 20.72 1.14 2.67 1.03 11.25
Monzogranite ZN11-17-12 898 36.84 1.73 3.55 1.11 17.37
Monzogranite ZN11-17-13 558 28.60 1.18 1.48 0.59 6.98
Monzogranite ZN11-17-16 507 5501 2.14 2.74 1.02 11.88
Monzogranite ZN11-17-17 508 20.11 1.21 1.27 0.61 7.72
Monzogranite ZN11-17-18 1187 52.95 2.66 5.83 2.45 23.69
Monzogranite ZN11-17-20 323 22.85 0.55 1.06 0.34 4.36
Monzogranite ZN11-17-21 319 23.28 0.57 0.95 0.34 3.87
Monzogranite ZN11-17-22 711 31.36 1.16 2.25 0.78 10.34
Monzogranite ZN11-17-23 1454 90.32 3.77 7.82 1.86 32.01
Monzogranite ZN11-17-24 665 34.89 1.23 1.30 0.46 7.04
Monzograniie porphyry ZN005-189-2 980 54.65 2.76 4.79 1.46 23.17
Monzogranite porphyry ZN005-189-3 630 37.66 3.24 3.05 0.71 13.16
Monzogranite porphyry ZN005-189-4 836 56.37 3.51 3.83 0.86 18.42
Monzograniieporphyry ZN005-189-7 828 44.16 5.03 3.19 0.83 16.86
Monzogranite porphyry ZN005-189-8 595 33.30 202 2.67 0.53 12.26
Monzogranite porphyry ZN005-189-13 641 35.84 2.08 3.25 0.81 14.27
Monzograniie porphyry ZN005-189-14 576 49.25 4.40 3.38 1.04 14.01
Monzogranite porphyry ZN005-189-16 1024 38.11 3.57 5.81 1.55 27.70
Monzogranite porphyry ZN005-189-17 1116 62.09 2.59 447 1.48 24.28
Monzograniie porphyry ZN005-189-20 849 49.83 5.95 4.90 1.15 19.66
Monzogranite porphyry ZN005-189-21 611 28.52 1.01 2.11 0.61 12.03
Monzopranite porphyry ZN005-189-22 466 27.04 1.63 1.57 0.64 7.57
Monzogranite porphyry ZN005-189-23 943 33.92 3.45 5.75 1.98 25.58
Monzogranite porphyry ZN005-189-25 710 40.95 6.35 3.95 0.78 14.11
Monzogranite porphyry ZN005-189-26 531 2741 0.97 1.80 0.54 10.14
Monzogranite porphyry ZN005-189-29 833 60.43 5.03 4.99 1.72 21.38
Monzogramte porphyry ZN005-189- 35 544 25.30 0.87 2.28 0.55 9.90
Table 4 Results of the compositional data of hornblende in Zhunuo mining area, Tibet (wt%)
Sampl SiO TiO ALO Cr0 Fe Mn Mg Ca Na K PO Ni
Litholegy ce No. 2 2 3 3 0 0 0 0 0 0 5 0 802-
Monzograniteporph 50. 11. 208-8- 07 49 0.0 04 163 122 11 05 00 00 yry 9 3 1 802-
Monzograniteporph 52. 10. 208-9- 04 33 0.0 04 178 124 07 03 00 00 yry 5 1 1 802-
Monzograniteporph 52. 208- 0.4 3.2 00 98 04 176 124 08 03 00 00
YIy , 8 10-1 802-
Monzograniteporph 52. 10. 208-7- 0.5 3.5 0.0 05 175 124 08 03 00 00 yTy 5 0 1 802-
Monzogtanite 53. 10. 208(50 0.1 3.3 0.0 0.5 175 127 07 02 00 00 porphyry 5 4 )-7 802- 54 54.
Monzogranite 233-6- 4 0.2 24 0.0 96 05 18.2 126 06 02 00 00 1 802- 51. 10.
Monzogranite 233-6- 4 0.7 42 0.1 0 0.5 169 122 10 04 00 00 2
/ 802- 49. 12. )
Monzogranite 0.9 54 0.0 05 162 125 10 05 00 01 324-1 5 1 802- 51. 10.
Monzogranite 0.6 41 0.0 05 170 122 10 04 01 00 324-2 0 8 . 802- 52. 10.
Monzogranite 0.5 3.4 0.0 04 178 123 07 03 00 00 324-6 7 2 802- 53. 10.
Monzogranite 0.3 28 0.0 65 179 124 08 02 00 00 300b-3 1 2
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