Pyrite-based carbonate ore-containing lead-zinc deposit prospecting prediction method

Abstract

The invention discloses a carbonatite ore-containing type lead-zinc deposit prospecting prediction method based on pyrite, and relates to the technical field of resource exploration. The method specifically comprises the following steps: drawing a macroscopic feature map according to the pyrite occurrence of different parts of the lead-zinc ore body; pyrite samples of different occurrence states are collected to prepare laser denudation sheet samples, then structural characteristic analysis is conducted, a structural characteristic graph is obtained, in-situ element and isotope analysis is conducted on the samples, original data are obtained and processed to obtain the content of main trace elements, then Pearson correlation coefficients of the main elements and the trace elements are calculated, and the content of the trace elements is calculated. Screening to obtain trace elements significantly related to the major elements; carrying out isotope analysis on the obtained delta 34S value; and finally, realizing prospecting prediction of the carbonate ore-containing lead-zinc deposit by integrating the structural characteristics of the pyrite, the content of trace elements, the occurrence state and the variation trend of the delta 34S value along with the distance from the ore body. According to the invention, a theoretical basis and a technical method system for prospecting prediction of the carbonate ore-containing lead-zinc deposit based on pyrite are established.

Description

Technical Field

[0001] This invention relates to a prospecting and prediction method for lead-zinc deposits hosted in carbonate rocks based on pyrite, belonging to the field of resource exploration technology. Background Technology

[0002] The Sichuan-Yunnan-Guizhou lead-zinc ore cluster is a key component of the low-temperature metallogenic domain in South China, containing various associated and co-existing metals. It is an important area for finding lead-zinc sulfide deposits and associated mineral resources (such as germanium and silver). Pyrite is the earliest precipitated metallic sulfide in carbonate-hosted lead-zinc deposits, providing valuable information on early-stage mineralization and serving as a marker mineral for prospecting this type of deposit. Pyrite plays a crucial role in the entire mineralization process of carbonate host lead-zinc deposits: in the early mineralization stage, various metallic elements (Mn, Co, Ni, Cu, Zn, As, Mo, Ag, Sb, Tl, Pb, Bi) are pre-enriched in pyrite through adsorption or combination with organic matter, providing important material carriers and enrichment foundations for later hydrothermal mineralization; in the main mineralization stage, the precipitation process of pyrite is affected by fluid composition, reducing sulfur concentration, temperature and pressure conditions, and mineral assemblages, and its trace element distribution characteristics can effectively reflect the formation environment of other sulfides at this stage; in the later mineralization stage, the limonite alteration zone formed by the surface oxidation of pyrite becomes an important surface prospecting indicator in field exploration. However, the analysis of the pyrite mineralization process in carbonate host lead-zinc deposits is mostly at the qualitative description stage, lacking quantitative constraints on key processes such as fluid composition, environment, and fluid mixing. The identification of multi-stage mineralization superposition mechanisms mainly relies on macroscopic geological observations, while research on mineral co-occurrence sequences and element migration patterns at the microscopic scale is relatively weak. In particular, effective models for the dynamic changes in trace element occurrence states and sulfur isotope fractionation have not yet been established, making it difficult to identify pyrite associated with lead-zinc mineralization. This makes it extremely difficult to use pyrite for prospecting and prediction of carbonate rock-hosted deposits. Furthermore, the current lack of clarity regarding the fluid-structure-mineralization coupling mechanism prevents the effective quantification of the intrinsic correlation between tectonic mineralization and fluid mineralization, thus limiting the universality of prospecting models. This invention utilizes microscopic features (mineral assemblage characteristics and crystal forms) of pyrite with different occurrences from the far-end to the near-end, trace element content, occurrence state, and δ¹⁸O of pyrite with different microstructures. 34 The S-value can predict the location of lead-zinc ore bodies in carbonate rock-hosted lead-zinc deposits. Summary of the Invention

[0003] To address the shortcomings of related technologies, this invention provides a prospecting and prediction method for carbonate rock-hosted lead-zinc deposits based on pyrite. This method incorporates the macroscopic, microscopic, and trace element characteristics of pyrite with different microstructures (ring-core structure, homogeneous structure) and their respective δ-values. 34By combining S-characteristics with the mineralization of carbonate-hosted lead-zinc deposits, we established the field macroscopic development characteristics, microscopic characteristics (mineral assemblage and crystal form), trace element characteristics, and δ-characteristics of pyrite with different microstructures in carbonate-hosted lead-zinc deposits. 34 The quantitative relationship between the differences in S-value characteristics and the mineralization of lead-zinc deposits was established, enabling mineral exploration location prediction and solving the problem of poor universality of mineral exploration models.

[0004] The purpose of this invention is to provide a method for prospecting and predicting lead-zinc deposits hosted in carbonate rocks based on pyrite, specifically including the following steps: (1) Based on the occurrence of pyrite in different parts of the lead-zinc ore body (preferably based on the observation of the pyrite development characteristics of carbonate rock host type lead-zinc ore body), draw a macroscopic feature map of pyrite in carbonate rock host type lead-zinc ore body.

[0005] (2) Based on the macroscopic feature map of pyrite in carbonate rock host lead-zinc deposits, pyrite samples with different occurrences were collected and laser ablation (LA) samples were prepared from the pyrite samples with different occurrences.

[0006] (3) Perform structural analysis (preferably microstructural analysis) on pyrite LA slices with different occurrences to obtain structural feature maps of pyrite with different occurrences; perform in-situ elemental and isotopic analysis on pyrite particles with different structural features in pyrite LA slices with different occurrences (preferably using an Agilent 7900 as a plasma mass spectrometer) to obtain raw data of pyrite elements and isotopes with different structural features in different occurrences.

[0007] (4) Analyze and process the raw data of pyrite elements and isotopes with different structural characteristics in different occurrences (preferably using ICPMSDATACAL11.8 / ICPMSDATACAL10.8 software to process and analyze the raw data of pyrite elements and isotopes), obtain the content of major and trace elements of pyrite with different structural characteristics, then calculate the Pearson correlation coefficient between major and trace elements, and combine the element correlation heatmap to screen out trace elements that are significantly correlated with major elements.

[0008] (5) By analyzing the raw isotopic data of pyrite with different structural characteristics in different occurrences, the δ¹⁸O values ​​of pyrite with different structural characteristics in different occurrences were obtained. 34 S-value.

[0009] (6) Based on the raw data of pyrite elements and isotopes with different structural characteristics obtained in step (3) and the element correlation law obtained in step (4), determine the occurrence state of trace elements in pyrite. Then, by analyzing the structural feature diagrams of pyrite with different occurrences, the content of trace elements in pyrite with different structural characteristics, the occurrence state, and δ¹⁸O, determine the occurrence state of trace elements in pyrite. 34 The S-value enables prospecting and prediction of carbonate rock-hosted lead-zinc deposits of pyrite.

[0010] Preferably, in step (3), a laser ablation-inductively coupled plasma mass spectrometer is used to perform elemental and isotopic analysis on pyrite particles with different structural characteristics in pyrite LA sheet samples with different occurrences. The specific conditions are: laser energy 80mJ, frequency 5Hz, and laser beam diameter 32μm.

[0011] Preferably, the trace elements and major elements screened in step (4) are significantly correlated if the correlation coefficient passes the significance test within the 95% confidence interval.

[0012] More preferably, in step (4), the major element is Fe, and the trace elements are one or more of Mn, Co, Ni, Cu, Zn, As, Mo, Ag, Sb, Tl, Pb, and Bi.

[0013] Preferably, in step (5), laser ablation-inductively coupled plasma mass spectrometry is used for in-situ sulfur isotope analysis of pyrite. The laser ablation conditions are: using a Resonetics-S155 system, laser beam diameter 23 μm, ablation frequency 5 Hz, ablation time 40 s, and helium (such as high-purity helium) as the carrier gas of the ablation cell. The mass spectrometer detection conditions are: using argon as the plasma working gas and introducing nitrogen.

[0014] More preferably, step (5) uses Nu Plasma II as a multi-receiver inductively coupled plasma mass spectrometer.

[0015] More preferably, the method for prospecting and predicting carbonate-hosted lead-zinc deposits of pyrite in step (6) is as follows: When a pyrite sample from an unknown area simultaneously meets the following conditions, its location is determined to be a favorable area for mineral exploration, especially if it is closer to a lead-zinc ore body: (1) Occurrence characteristics: It changes from star-shaped to vein-shaped or dense mass-shaped.

[0016] (2) Structural proportion characteristics: The proportion of homogeneous pyrite exceeds that of ring-core pyrite.

[0017] (3) Crystal evolution characteristics: Pyrite crystals change from anhedral to subhedral, specifically manifested as fine-grained subhedral veins or coarse / fine-grained subhedral veins.

[0018] (4) Characteristics of elemental changes: The content of trace elements in pyrite decreases, and the number of trace elements entering the pyrite lattice in the form of isomorphism increases.

[0019] (5) Sulfur isotope characteristics: δ 34 The S value is positive.

[0020] Mechanism of the invention: (1) Sulfur isotope fractionation mechanism: There are systematic differences in the sulfur isotope composition of pyrite of different origins; bacterial sulfate reduction (BSR) produces large sulfur isotope fractionation, which is mainly negative or extremely negative; thermochemical sulfate reduction (TSR) has a relatively small fractionation degree, which is mainly positive or extremely positive.

[0021] (2) Advantages of in-situ micro-area analysis technology: Using laser ablation-inductively coupled plasma mass spectrometry (LA-ICP-MS) technology, high-precision in-situ analysis of trace elements and sulfur isotopes in pyrite can be achieved, providing accurate data support for the study of mineralization mechanism and mineral exploration prediction.

[0022] (3) The mechanism of constructing a multi-parameter mineral exploration prediction model is based on the occurrence characteristics, mineral assemblage characteristics and geochemical characteristics of pyrite, and a comprehensive mineral exploration prediction model is constructed.

[0023] Through the systematic exposition of the above mechanisms, this invention establishes the theoretical basis and technical methodology system for prospecting and prediction of carbonate-hosted lead-zinc deposits based on pyrite, providing scientific basis and technical support for prospecting and exploration of this type of deposit.

[0024] The beneficial effects of this invention are: (1) This invention utilizes the macroscopic development characteristics of pyrite in the field, the microscopic characteristics (mineral assemblage characteristics and crystal form), trace elements and δ-type microstructures. 34 The trend of S-value variation with distance from the ore body is combined with the mineralization of carbonate-hosted lead-zinc deposits, based on pyrite occurrence, mineral assemblage, pyrite crystal form, trace elements, and δ-values. 34 The response of S-value to ore-forming fluids was used to collaboratively establish the macroscopic development characteristics, microscopic characteristics (mineral assemblage and crystal form), trace elements, and δ-values ​​of carbonate-hosted lead-zinc deposits. 34 The trend of S-value variation with distance from the ore body and the quantitative relationship between lead and zinc mineralization can be used to predict mineral exploration location through the above differences in variability.

[0025] (2) This invention utilizes the field macroscopic development characteristics, microscopic characteristics (mineral assemblage and crystal form), trace elements and δ-type pyrite in carbonate rock host lead-zinc deposits to analyze these characteristics. 34 Rapid and accurate identification of S-values ​​clearly defines the macroscopic and microscopic characteristics (mineral assemblage and crystal form), trace elements, and δ-values ​​of pyrite from the far end to the near end of the ore deposit.34 The changing trend of S value reflects the mineralization process. This is achieved through the analysis of macroscopic, microscopic, and trace element characteristics of pyrite, as well as δ... 34 Mineral exploration prediction is based on the differences in S-values. Attached Figure Description

[0026] Figure 1 This is a macroscopic feature diagram of pyrite in ore body I of the Maoping lead-zinc deposit (group) according to Embodiment 1 of the present invention.

[0027] Figure 2 Figure 1 shows the microstructural features of pyrite in different microstructures of the No. 1 ore body (group) of the Maoping lead-zinc deposit in Example 1 of this invention. Figure a shows the sulfur isotope differentiation characteristics of pyrite in the early stage at the far end (Py0 in the core of medium- to fine-grained ring-core pyrite, Py1a in the edge of medium- to fine-grained ring-core pyrite) and the coexistence with dolomite; Figure b shows the structural features of euhedral pyrite (Py0, Py1a) in the early mineralization stage at the far end; Figure c shows the superposition of multi-generation pyrite (Py0, Py1a, Py3) and sphalerite in the late mineralization stage near the ore end; Figure d shows the composition of multi-generation pyrite (Py0, Py1a, fine-grained homogeneous pyrite Py2, coarse- to fine-grained homogeneous pyrite Py3) in the tectonic-hydrothermal modified type near the ore end.

[0028] Figure 3 This is a diagram showing the trace element content of pyrite in different microstructures of the No. 1 ore body (group) of the Maoping lead-zinc deposit in Example 1 of the present invention.

[0029] Figure 4 The following are heat maps showing the correlation between elements in pyrite with different microstructures in the No. 1 ore body (group) of the Maoping lead-zinc deposit according to Example 1 of the present invention. Figure a shows the correlation between Fe and Mn, Co, Ni, Cu, Zn, As, Mo, Ag, Sb, Tl, Pb, and Bi in Py0; Figure b shows the correlation between Fe and Mn, Co, Ni, Cu, Zn, As, Mo, Ag, Sb, Tl, Pb, and Bi in Py1a; and Figure c shows the correlation between Fe and Mn, Co, Ni, Cu, Zn, As, Mo, Ag, Sb, Tl, Pb, and Bi in Py2 and Py3.

[0030] Figure 5Figure 1 shows the correlation characteristics of trace elements and Fe in pyrite with different microstructures in the No. 1 ore body (group) of the Maoping lead-zinc deposit according to Example 1 of the present invention. Figure a is a line graph showing the correlation coefficients of Fe with Mn, Co, Ni, Cu, Zn, As, Mo, Ag, Sb, Tl, Pb, and Bi in Py0; Figure b is a line graph showing the correlation coefficients of Fe with Mn, Co, Ni, Cu, Zn, As, Mo, Ag, Sb, Tl, Pb, and Bi in Py1a; and Figure c is a line graph showing the correlation coefficients of Fe with Mn, Co, Ni, Cu, Zn, As, Mo, Ag, Sb, Tl, Pb, and Bi in Py2 and Py3.

[0031] Figure 6 These are LA-ICP-MS time-resolution profiles of pyrite with different microstructures in the No. 1 ore body (group) of the Maoping lead-zinc deposit according to Example 1 of the present invention. Figure a is a multi-element time-resolution count profile of Py0 pyrite at the far end; Figure b is a multi-element time-resolution count profile of Py1a pyrite at the far end; Figure c is a multi-element time-resolution count profile of Py2 pyrite at the near end; and Figure d is a multi-element time-resolution count profile of Py3 pyrite at the near end.

[0032] Figure 7 Example 1 of the present invention: Different microstructures of sulfide δ-type deposits in the Maoping lead-zinc deposit No. I ore body (group) in northeastern Yunnan. 34 S-composition feature map. Detailed Implementation

[0033] To better illustrate the purpose, technical solution, and advantages of this invention, the following will further describe the invention in conjunction with specific embodiments. In the embodiments of this invention, unless otherwise specified, all chemical reagents used in the experiments were commercially available analytical grade. The trace element calibration standard sample for the plasma mass spectrometer in these embodiments was NIST 610, and the trace element monitoring standard sample was MASS-1. Both samples are international standard materials, and the recommended values ​​are derived from GeoRem. The method described in this invention ultimately aims to establish a set of mineral exploration prediction and discrimination rules based on the microscopic characteristics of pyrite. These rules, through a systematic study of known deposits (such as the Maoping deposit shown in Example 1) from the distant to the near ore-bearing end, extract key feature combinations closely related to the mineralization center and standardize them into discrimination criteria applicable to unknown areas.

[0034] Example 1 A prospecting and prediction method for lead-zinc deposits hosted in carbonate rocks based on pyrite is presented in this embodiment, taking the pyrite 439 section of a lead-zinc deposit in northeastern Yunnan as an example (this lead-zinc deposit in northeastern Yunnan is located in the north-central part of the depression zone on the southwestern margin of the Yangtze Platform, with dolomite as the bedrock of the Upper Devonian Zaige Formation, and most of the lead-zinc ore bodies hosted in dolomite). The method specifically includes the following steps: (1) Observe the pyrite in a lead-zinc deposit in northeastern Yunnan. Based on the occurrence of pyrite in different parts of the lead-zinc ore body, draw a macroscopic characteristic map of pyrite in a carbonate rock-hosted lead-zinc deposit (e.g. Figure 1 (As shown in the figure). The occurrence of pyrite from the far end to the near end is successively star-shaped, vein-shaped, and massive. Among them, the vein-shaped and massive pyrite are associated with galena and sphalerite.

[0035] (2) Collect pyrite samples in the form of star-shaped spots, veins, and dense blocks, and grind the pyrite samples in the form of star-shaped spots, veins, and dense blocks into LA slides. Collect fresh pyrite samples to avoid weathering and pollution affecting the accuracy of observation of LA slides.

[0036] (3) LA slides prepared from pyrite samples in the form of star-shaped, vein-shaped, and dense massive shapes were observed under a microscope to identify pyrite with a ring-nuclear structure (the core of medium- to fine-grained ring-nuclear pyrite (Py0), the edge of medium- to fine-grained ring-nuclear pyrite (Py1a)) and pyrite with a homogeneous structure (fine-grained homogeneous pyrite (Py2), coarse- to fine-grained homogeneous pyrite (Py3)). Microstructural feature diagrams of star-shaped, vein-shaped, and dense massive pyrite were obtained (e.g., Figure 2 As shown in the figures, Figure a illustrates the sulfur isotope differentiation characteristics (Py0, Py1a) of early-stage pyrite at the far-mineralized end and the coexistence with dolomite; Figure b illustrates the structural characteristics of anhedral pyrite (Py0, Py1a) in the early-stage mineralization at the far-mineralized end; Figure c illustrates the superimposed structure of multi-generational pyrite (Py0, Py1a, Py3) and sphalerite in the late-stage mineralization near the ore-mineralized end; Figure d illustrates the fragmented structure of multi-generational pyrite (Py0, Py1a, Py2, Py3) in the tectonic-hydrothermal altered type near the ore-mineralized end, consisting of… Figure 2 As can be seen from the perspective of the ore-end, pyrite exhibits a trend of changing from speckled, vein-like, to massive and compact forms from the ore-end to the near-ore-end. From the ore-end to the near-ore-end, the dominant microstructure of pyrite in different macroscopic occurrences (specimen, vein, massive and compact) shows a regular change: the ore-end is dominated by ring-core pyrite (Py0, Py1a), while the near-ore-end is dominated by homogeneous pyrite (Py2, Py3). A LA-ICP-MS system, consisting of a laser ablation system and an Agilent 7900 mass spectrometer, was used to perform LA-ICP-MS tests on LA slides prepared from speckled, vein-like, and massive pyrite samples. The elements (using in-situ elemental analysis) and isotopes in the LA slides were analyzed under the following conditions: laser energy 80 mJ, frequency 5 Hz, and laser beam diameter 32 μm. The tests yielded raw data on the elements and isotopes of pyrite with different microstructural characteristics in different occurrences.

[0037] (4) The raw data of elements and isotopes of pyrite with different microstructural characteristics obtained from LA-ICP-MS testing in different occurrences were processed and analyzed using ICPMSDATACAL11.8 / ICPMSDATACAL10.8 software to obtain the content of major and trace elements (i.e., Fe). Then, trace elements significantly related to Fe were screened by element correlation heatmap. After comparison, the trace elements whose correlation coefficient with Fe passed the significance test within the 95% confidence interval were Mn, Co, Ni, Cu, Zn, As, Mo, Ag, Sb, Tl, Pb, and Bi. The relationship diagram of Mn, Co, Ni, Cu, Zn, As, Mo, Ag, Sb, Tl, Pb, and Bi of the ring-core structure pyrite Py0 and Py1a and the homogeneous structure pyrite Py2 and Py3 of the No. I ore body (group) of a certain lead-zinc deposit in this embodiment is shown in the figure. Figure 3 ,from Figure 3 It can be seen that the pyrite at the far end mainly develops Py0 and Py1a, among which the Mn content of Py0 is 0.4094 × 10⁻⁶. -6 ~55.8769×10 -6 (The average value is 20.0926 × 10) -6 The Co content is 0.2530×10⁻⁶. -6 ~45.6620×10 -6 (The average value is 11.7162 × 10) -6 The Ni content is 6.2215 × 10⁻⁶. -6 ~333.8048×10 -6 (The average value is 115.3445 × 10) -6 The Cu content is 2.6925 × 10⁻⁶. -6 ~59.6973×10 -6 (The average value is 23.3442 × 10) -6 The Zn content is 1.2543 × 10⁻⁶. -6 ~12.8579×10 -6 (The average value is 7.9623 × 10) -6 The As content is 998.2699 × 10⁻⁶. -6 ~2319.6835×10 -6 (The average value is 1603.2417 × 10) -6 The Mo content is 0.0432 × 10⁻⁶. -6 ~177.5587×10 -6 (The average value is 101.7321 × 10) -6 The Ag content was 1.0606 × 10⁻⁶. -6 ~13.6621×10 -6 (The average value is 5.7903×10) -6The Sb content was 1.4797 × 10⁻⁶. -6 ~77.8218×10 -6 (The average value is 25.9293 × 10) -6 The Tl content is 0.2292×10 -6 ~84.1440×10 -6 (The average value is 41.4450 × 10) -6 The Pb content was 18.1952 × 10⁻⁶. -6 ~399.3577×10 -6 (The average value is 128.3563 × 10) -6 The Bi content is 0.0060×10⁻⁶. -6 ~0.0253×10 -6 (The average value is 0.0136×10) -6 The Mn content of Py1a is 0.1012 × 10⁻⁶. -6 ~0.5717×10 -6 (The average value is 0.3101×10) -6 The Co content is 0.0429×10⁻⁶. -6 ~1.5217×10 -6 (The average value is 0.2731×10) -6 The Ni content is 0.1962 × 10⁻⁶. -6 ~10.8175×10 -6 (The average value is 2.1830×10) -6 The Cu content is 0.4536 × 10⁻⁶. -6 ~4.6287×10 -6 (The average value is 1.5619 × 10) -6 The Zn content is 1.0882 × 10⁻⁶. -6 ~2.3885×10 -6 (The average value is 1.6053 × 10) -6 The As content is 404.2861 × 10⁻⁶. -6 ~1131.8726×10 -6 (The average value is 889.9829 × 10) -6 The Mo content is 0.0636 × 10⁻⁶. -6 ~2.7820×10 -6 (The average value is 0.7683×10) -6 The Ag content was 0.0114 × 10⁻⁶. -6 ~2.2774×10 -6 (The average value is 0.5747×10) -6 The Sb content was 1.2708 × 10⁻⁶. -6~23.6237×10 -6 (The average value is 7.1883 × 10) -6 The Tl content is 0.0027×10 -6 ~0.1666×10 -6 (The average value is 0.0334×10) -6 The Pb content is 4.5516 × 10⁻⁶. -6 ~120.8371×10 -6 (The average value is 27.7646 × 10) -6 The Bi content is 0.0040 × 10⁻⁶. -6 ~0.0147×10 -6 (The average value is 0.0092×10) -6 The near-ore end mainly develops Py2 and Py3, with a Mn content of 0.0478 × 10⁻⁶. -6 ~2.6528×10 -6 (The average value is 0.5166×10) -6 The Co content is 0.0071×10⁻⁶. -6 ~2.7550×10 -6 (The average value is 0.2541×10) -6 The Ni content is 0.0495×10⁻⁶. -6 ~23.3605×10 -6 (The average value is 3.0236×10) -6 The Cu content is 0.0766 × 10⁻⁶. -6 ~10.1791×10 -6 (The average value is 1.8806×10) -6 The Zn content is 0.7189 × 10⁻⁶. -6 ~53.8774×10 -6 (The average value is 4.2045×10) -6 The As content is 0.1480×10⁻⁶. -6 ~3285.9200×10 -6 (The average value is 552.8185 × 10) -6 The Mo content is 0.0043 × 10⁻⁶. -6 ~0.4506×10 -6 (The average value is 0.1346×10) -6 The Ag content was 0.0108 × 10⁻⁶. -6 ~107.5305×10 -6 (The average value is 7.1286×10) -6 The Sb content is 0.0277×10⁻⁶. -6 ~133.6314×10-6 (The average value is 18.3789 × 10) -6 The Tl content is 0.0005×10 -6 ~0.9137×10 -6 (The average value is 0.0853×10) -6 The Pb content is 0.9004×10⁻⁶. -6 ~80948.9805×10 -6 (The average value is 3650.1529 × 10) -6 The Bi content is 0.0006×10⁻⁶. -6 ~0.0286×10 -6 (The average value is 0.0087×10) -6 In this embodiment, the heatmap of elemental correlations in pyrite with different microstructures in ore body (group) I of a certain lead-zinc deposit, the line graph of the correlation between each element and Fe, and the time-resolution profile are shown in the figure. Figure 4 , Figure 5 as well as Figure 6 (where a and b are the distant ore ends, and c and d are the near ore ends). Figure 4 (Figure a shows the correlation heatmap of Fe with Mn, Co, Ni, Cu, Zn, As, Mo, Ag, Sb, Tl, Pb, and Bi in Py0; Figure b shows the correlation heatmap of Fe with Mn, Co, Ni, Cu, Zn, As, Mo, Ag, Sb, Tl, Pb, and Bi in Py1a; Figure c shows the correlation heatmap of Fe with Mn, Co, Ni, Cu, Zn, As, Mo, Ag, Sb, Tl, Pb, and Bi in Py2 and Py3.) Figure 5 (Figure a shows the correlation coefficients between Fe and Mn, Co, Ni, Cu, Zn, As, Mo, Ag, Sb, Tl, Pb, and Bi in Py0; Figure b shows the correlation coefficients between Fe and Mn, Co, Ni, Cu, Zn, As, Mo, Ag, Sb, Tl, Pb, and Bi in Py1a; Figure c shows the correlation coefficients between Fe and Mn, Co, Ni, Cu, Zn, As, Mo, Ag, Sb, Tl, Pb, and Bi in Py2 and Py3.) Figure 6 (Figure a is a multi-element time-resolution counting profile of Py0 pyrite at the far end; Figure b is a multi-element time-resolution counting profile of Py1a pyrite at the far end; Figure c is a multi-element time-resolution counting profile of Py2 pyrite at the near end; Figure d is a multi-element time-resolution counting profile of Py3 pyrite at the near end.) It can be seen that trace elements in pyrite at the far end mainly exist in the form of adsorption, combination with organic matter, or mechanical mixing; trace elements in pyrite at the near end mainly exist in the form of isomorphous inclusions.

[0038] (5) In-situ sulfur isotope analysis was performed using laser ablation-inductively coupled plasma mass spectrometry. The laser ablation conditions were as follows: a Resonetics-S155 system was used, with a laser beam diameter of 23 μm, an ablation frequency of 5 Hz, and an ablation time of 40 s. High-purity helium was used as the carrier gas in the ablation cell. The mass spectrometer detection conditions were as follows: a Nu Plasma II was used as a multi-receiver inductively coupled plasma mass spectrometer, with argon as the plasma working gas, and nitrogen was added to eliminate polyatomic ion interference. During the analysis, an ArF excimer laser generator produced a 193 nm deep ultraviolet beam, which was focused onto the sulfide surface through a homogenization optical path. Standard and sample points were obtained by direct testing. 34 S / 32 The S ratio was calculated using the external standard correction (SSB method) to obtain the δ ratio of pyrite with different occurrences and structural characteristics. 34 S-value; Analysis revealed that the δ-values ​​of different microstructures of pyrite in ore body (group) I of a certain lead-zinc deposit in this embodiment were obtained. 34 S-feature map see Figure 7 ,from Figure 7 It can be seen that the δ of Py0 at the far end of the ore is... 34 The S value ranges from -19.60‰ to -4.90‰ (with an average of -15.45‰), and the δ of Py1a... 34 S values ​​range from 19.8‰ to 22.70‰ (average 21.66‰); the near-ore ends of Py2 and Py3 exhibit similar and homogeneous sulfur isotopic compositions, δ... 34 S values ​​range from 20.1‰ to 22.90‰ (average 21.95‰), with δ near the ore end. 34 The S value is positive and higher than that at the far ore end, indicating that the Py0 sulfur at the far ore end is biogenic (usually generated by bacterial reduction of sulfate), while the Py1a at the far ore end and the Py2-Py3 sulfur near the ore end are hydrothermal sulfates (such as magmatic hydrothermal fluids or formation sulfates modified by hydrothermal processes); the δ¹⁴S value of pyrite near the ore end... 34 The consistent and high positive value of S indicates that the source of sulfur in the ore-forming fluid is relatively stable (mainly hydrothermal sulfate); the simultaneous presence of biogenic sulfur and hydrothermal sulfur at the far end reflects that the ore-forming fluid has mixed or reacted with the strata (including biogenic sulfur).

[0039] (6) Microscopic analysis of pyrite with different occurrences revealed that pyrite at the far end mainly developed a ring-core structure (Py0 and Py1a); pyrite near the ore end mainly developed a homogeneous structure (Py2 and Py3). The core of the ring-core structure pyrite (Py0) was mainly medium to fine-grained with a porous structure, while the edge of the ring-core structure pyrite (Py1a) was mainly developed at the edge of Py0 or as medium to fine-grained anhedral granules. The fine-grained homogeneous structure pyrite (Py2) was mainly fine-grained subhedral veins, and the coarse-fine-grained homogeneous structure pyrite (Py3) was mainly coarse-grained or fine-grained subhedral veins. Trace element analysis of pyrite with different microstructures revealed the presence of trace elements in the far end Py0 and Py1a and the near end Py2 and Py3. Crystal morphology and the content and occurrence states of Mn, Co, Ni, Cu, Zn, As, Mo, Ag, Sb, Tl, Pb, and Bi were studied. At the far end of the ore deposit, Py0 and Py1a crystals were mainly anhedral, with trace elements primarily occurring through adsorption or combination with organic matter. Near the ore end, Py2 and Py3 crystals were mainly subhedral, with Mn, Mo, Ag, Sb, and Bi occurring primarily in isomorphous forms, while Pb mainly occurred through mechanical inclusion. The contents of Mn, Co, Ni, Cu, Zn, As, Mo, Ag, Sb, Tl, and Bi gradually decreased from the far end to the near end, while Pb significantly accumulated near the ore end due to mechanical inclusion, resulting in an increasing content from the far end to the near end. The δ¹⁸O values ​​of pyrite with different microstructures were analyzed. 34 S-value analysis yielded the δ values ​​of Py0 and Py1a at the far ore end and Py2 and Py3 at the near ore end. 34 S-value characteristics; δ of Py0 at the far end of the ore deposit 34 S is negative, and Py1a's δ 34 The S value is positive, indicating that bacterial sulfate reduction (BSR) is predominant overall; the δ values ​​of Py2 and Py3 near the ore end are positive. 34 The S value is mainly positive, indicating that thermochemical sulfate reduction (TSR) is dominant. From the far end to the near end of the ore, the medium- to fine-grained cyclic nuclei (Py0 and Py1a) gradually decrease, while the coarse- to fine-grained homogeneous structures (Py2 and Py3) gradually increase. The more subhedral pyrite crystals there are, the lower the content of Mn, Co, Ni, Cu, Zn, As, Mo, Ag, Sb, Tl, Pb, and Bi, and the more elements are present in pyrite in isomorphous form. 34 A positive or higher S value indicates that the deposit is closer to the location of the ore body in a carbonate-hosted lead-zinc deposit.

[0040] The various embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or improvement of the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for prospecting and predicting lead-zinc deposits hosted in carbonate rocks based on pyrite, characterized in that, Specifically, the following steps are included: (1) Based on the occurrence of pyrite in different parts of the lead-zinc ore body, draw a macroscopic characteristic map of pyrite in carbonate rock-hosted lead-zinc deposits; (2) Based on the macroscopic feature map of pyrite in carbonate rock host lead-zinc deposits, pyrite samples with different occurrences were collected and laser ablation plates were made from the pyrite samples with different occurrences. (3) Structural analysis was performed on pyrite laser ablation specimens with different occurrences to obtain structural feature diagrams of pyrite with different occurrences; in-situ elemental and isotopic analysis was performed on pyrite particles with different structural features in pyrite laser ablation specimens with different occurrences to obtain raw data of pyrite elements and isotopes with different structural features in different occurrences. (4) Analyze and process the raw data of elements and isotopes of pyrite with different structural characteristics in different occurrences to obtain the content of major and trace elements of pyrite with different structural characteristics. Then calculate the Pearson correlation coefficient between major and trace elements. Combined with the element correlation heatmap, screen out trace elements that are significantly related to major elements. (5) By analyzing the raw isotopic data of pyrite with different structural characteristics in different occurrences, the δ¹⁸O values ​​of pyrite with different structural characteristics in different occurrences were obtained. 34 S-value; (6) Based on the raw data of pyrite elements and isotopes with different structural characteristics obtained in step (3) and the element correlation law obtained in step (4), determine the occurrence state of trace elements in pyrite. Then, by analyzing the structural feature diagrams of pyrite with different occurrences, the content of trace elements in pyrite with different structural characteristics, the occurrence state, and δ¹⁸O, determine the occurrence state of trace elements in pyrite. 34 The S-value enables prospecting and prediction of carbonate rock-hosted lead-zinc deposits of pyrite.

2. The prospecting and prediction method for carbonate rock-hosted lead-zinc deposits based on pyrite according to claim 1, characterized in that, In step (3), the laser ablation-inductively coupled plasma mass spectrometer was used to perform elemental and isotopic analysis on pyrite particles with different structural characteristics in laser ablation samples of pyrite with different occurrences. The specific conditions were: laser energy 80mJ, frequency 5Hz, and laser beam diameter 32μm.

3. The method for prospecting and predicting carbonate rock-hosted lead-zinc deposits based on pyrite according to claim 1, characterized in that, The trace elements and major elements screened in step (4) are significantly correlated if the correlation coefficient passes the significance test within the 95% confidence interval.

4. The method for prospecting and predicting carbonate rock-hosted lead-zinc deposits based on pyrite according to claim 1, characterized in that, In step (5), in-situ sulfur isotope analysis of pyrite is performed using a laser ablation-inductively coupled plasma mass spectrometer. The laser ablation conditions are as follows: a Resonetics-S155 system is used, the laser beam diameter is 23 μm, the ablation frequency is 5 Hz, the ablation time is 40 s, and helium is used as the carrier gas in the ablation cell. The mass spectrometer detection conditions are as follows: argon is used as the plasma working gas, and nitrogen is introduced.

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