Determining method for different origins of metallogenic fluids in mountain-building type gold deposit in south of Yangtze River

Abstract

The invention discloses a determination method for different origins of metallogenic fluids in a mountain-building type gold deposit in the south of Jiangsan. According to the method, through innovative sample collection and pretreatment, high-resolution sampling and fine treatment are carried out on specific parts of an ore deposit; advanced fluid inclusion comprehensive analysis is adopted, and inclusion information is accurately obtained in combination with multiple technologies; high-precision stable isotope determination and innovative interpretation in combination with a regional database are applied; element geochemical deep analysis and innovation index application are carried out, and SR-XRF and a machine learning algorithm are introduced; and finally, through comprehensive data fusion and intelligent analysis, constructing an intelligent platform and drawing a three-dimensional evolution model. The method can effectively integrate multi-source data, accurately determine the origin of the ore-forming fluid, overcome the limitation of a traditional method, improve accuracy and reliability, provide powerful support for deep exploration of ore deposit causes and prospecting exploration, and have important theoretical and practical significance.

Description

Technical Field

[0001] The present invention relates to the field of ore deposit geochemistry technology, and in particular focuses on the study of a method for determining ore-forming fluids of different origins in Jiangnan orogenic gold deposits. Background Art

[0002] The Jiangnan orogenic gold deposits occupy an important position in the field of global mineral resources. They contain considerable gold resources and are of great value to economic development and industrial production. However, for a long time, the precise identification of ore-forming fluids of different origins in this type of deposit has been a difficult problem in the field of ore deposit geochemistry research. Traditional technical means have many obvious deficiencies and limitations.

[0003] In early studies, the analysis of ore-forming fluids mainly relied on relatively simple and single technical methods. As far as fluid inclusion research is concerned, traditional optical microscope observations can only provide relatively rough information on the basic morphology, size and approximate distribution of inclusions. It is difficult to accurately quantify the microscopic characteristics of inclusions, and it is impossible to accurately determine the fine morphological parameters of tiny inclusions and the complex phase change characteristics inside them. Moreover, the accuracy and resolution of traditional temperature and pressure measurement methods are severely limited when facing tiny inclusions or inclusions with complex components, resulting in large errors in the judgment of the capture conditions of ore-forming fluids. In terms of component analysis, although conventional laser Raman spectrometers and ion chromatography technologies can detect some common components, they are insufficient in detecting trace elements, rare gases and complex organic components, resulting in a lack of key component information when judging the source of ore-forming fluids, and it is impossible to accurately distinguish the contributions of different types of fluids from deep mantle sources, magma sources, metamorphic sources and atmospheric precipitation sources.

[0004] The same is true for stable isotope analysis. The common isotope measurement technology used in the past not only has limited measurement accuracy, but also often ignores the unique and complex regional geological background of the Jiangnan Orogenic Belt during data interpretation. The Jiangnan Orogenic Belt has experienced multiple periods of tectonic movements, magmatic activities, metamorphism, and sedimentary processes. These geological events are intertwined, causing the isotopic composition of ore-forming fluids to be affected by multiple factors. However, traditional methods lack a systematic review and comprehensive consideration of these factors, and have failed to establish an isotope analysis system that is closely integrated with regional geological evolution. As a result, when using isotope data to infer the origin of ore-forming fluids, the results are vague and inaccurate, and it is impossible to clearly reveal the evolution trajectory and source changes of ore-forming fluids during the long geological history.

[0005] In the field of elemental geochemistry research, early work mainly focused on the determination of the content of some common elements in ores and surrounding rocks, and did not delve deeply into the intrinsic relationship between elements and their deep-seated relationship with the origin and evolution of ore-forming fluids. Advanced analytical techniques were not fully utilized to fully obtain key information on the distribution characteristics, occurrence states, and migration and transformation laws of elements in the mineralization process, and no effective elemental geochemical model was established to accurately identify the origin type and mixing ratio of ore-forming fluids.

[0006] With the increasing requirements of modern mining for the accuracy and efficiency of mineral resource exploration, as well as the deepening of research on the genesis theory of ore deposits, a new, comprehensive and high-precision method is urgently needed to solve the problem of determining the ore-forming fluids of different origins in the Jiangnan orogenic gold deposits. This method should be able to integrate a variety of advanced analytical techniques, fully consider the complexity of the regional geological background, and use innovative data processing and interpretation methods, so as to provide strong support for accurately revealing the mysteries of ore-forming fluids, thereby promoting the development of mineral exploration in a more accurate and efficient direction, and meeting the continuous demand of the economy and society for mineral resources. Summary of the invention

[0007] The present invention aims to provide a method for determining ore-forming fluids of different origins in Jiangnan orogenic gold deposits, and realizes accurate determination of the origin of ore-forming fluids through a series of interrelated and progressive steps, as follows:

[0008] The sample collection and pretreatment described: A detailed sampling plan is formulated for the Jiangnan orogenic gold deposit. Inside the ore body, according to the change of mineralization intensity, systematic sampling is carried out at intervals of 3-5 cm from high-mineralized areas to low-mineralized areas to ensure that the information of ore-forming fluids at different mineralization levels is covered. In the transition zone between the ore body and the surrounding rock, an intensified sampling method is adopted to collect a sample every 1-2 cm, because this area is often the most active part of the interaction between the ore-forming fluid and the surrounding rock, and the changes in fluid properties can be recorded. For the surrounding rock, areas with different lithologies and different degrees of alteration are selected for sampling, and the number of samples in each area is not less than 10, so as to fully reflect the influence of the surrounding rock on the ore-forming fluid and the possible source of the fluid. At the same time, the veins of different periods in the ore deposit are sampled separately, and their spatial distribution and interlacing relationship are recorded to provide a basis for the subsequent analysis of the evolution of the ore-forming fluid. The collected samples are firstly used with high-precision micro-cutting equipment to accurately obtain the pure part of the mineral that is not contaminated by the outside world, and the cutting accuracy is controlled within 0.1 mm. Then, the sample is immersed in a special non-polluting chemical reagent for cleaning. The reagent is a mixture of deionized water, weak acidic buffer solution and chelating agent in a specific proportion, which can effectively remove impurity elements adsorbed on the sample surface, trace elements in dust, and ions on the surface of secondary minerals, while ensuring that the original composition of the sample will not be changed. The cleaned sample is quickly transferred to a vacuum drying oven and dried at a temperature below 40°C to prevent oxidation or other chemical reactions. The dried sample is placed in a sealed container filled with inert gas (argon) until subsequent analysis to ensure that the original state of the sample before analysis is completely preserved.

[0009] The fluid inclusion analysis described above: observe the fluid inclusions using a high-resolution optical microscope (resolution reaches 0.5 microns), and combine with professional image analysis software to accurately measure the major axis, minor axis, circumference, and area morphological parameters of each inclusion, with the error controlled within 0.1 microns. At the same time, the distribution density, direction, and relationship information of the inclusions in the mineral and the mineral growth texture are statistically analyzed. Through these detailed data, primary inclusions and secondary inclusions are accurately distinguished. Primary inclusions usually have regular shapes and are distributed in the growth zone of the mineral, consistent with the growth direction of the mineral; while secondary inclusions are relatively irregular in shape and are mostly distributed along the cracks of the mineral. A nanoscale temperature measuring probe (temperature measurement accuracy reaches ±0.3°C) is combined with a traditional microscopic hot stage to measure the uniform temperature and freezing point temperature of the fluid inclusions. During the measurement process, at least 20 representative inclusions in each sample are measured to ensure the reliability and representativeness of the data. For the measurement of uniform temperature, slowly increase the temperature and accurately record the temperature when the inclusion changes from two phases to a single phase; for the measurement of freezing point temperature, by accurately controlling the cooling rate, observe the appearance and disappearance temperature of ice in the inclusion, and calculate the capture temperature and pressure range of the ore-forming fluid based on the precise temperature data combined with the known geological pressure gauge and thermometer equations, so as to infer the formation depth and physical and chemical conditions of the ore-forming fluid. Laser Raman spectrometer, ion chromatography and in situ secondary ion mass spectrometry (SIMS) technology are used to comprehensively analyze the composition of fluid inclusions. The laser Raman spectrometer uses a highly sensitive detector and an optimized laser wavelength to perform qualitative and semi-quantitative analysis of the gas phase components (H2O, CO2, CH4, N2, H2S) in the inclusions, and the scanning range covers from 100-4000cm -1 The detection limit reaches the ppm level. Ion chromatography is used to analyze the liquid phase composition of inclusions and can accurately determine Na + , K + , Ca 2+ Mg 2+ , Cl - 、SO4 2- The concentration of common ions is analyzed with an accuracy of ppb level. SIMS technology focuses on detecting trace elements and isotopes in inclusions, isotope ratios of Li, B, Rb, Sr, Pb, and some rare gas isotopes (He, Ne, Ar). Through these comprehensive and accurate component analyses, key chemical composition information is provided to determine the source and evolution of ore-forming fluids.

[0010] Described stable isotope determination: Multi-collector inductively coupled ion mass spectrometry (MC-ICP-MS) technology is used to determine hydrogen, oxygen and sulfur isotopes in ore minerals. When measuring hydrogen and oxygen isotopes, water in the sample is extracted by high-temperature pyrolysis and converted into gaseous substances for isotope analysis, and the measurement accuracy reaches ±0.15‰. For the determination of sulfur isotopes, the ore sample is chemically treated and converted into a form suitable for mass spectrometry analysis, and the measurement accuracy reaches ±0.2‰. During the entire measurement process, international standard materials are used for calibration to ensure the accuracy and comparability of the measurement results. Stable isotope data of rocks, minerals, and groundwater samples from different geological units and different geological periods in the Jiangnan orogenic belt are collected to establish an isotope database covering igneous rocks, metamorphic rocks, sedimentary rocks, and atmospheric precipitation. The database not only contains isotope ratio data, but also records the geological background, rock type, and formation age information of the samples in detail. The measured isotope data of the ore deposits are compared and analyzed with the data in the database. Statistical methods and geochemical models are used to consider the complex geological evolution history of the Jiangnan orogenic belt, including the effects of multiple magmatic activities, metamorphism, sedimentary cycles and tectonic movements on isotope composition, so as to accurately infer the possible sources of the ore-forming fluids and determine whether they are affected by fluids from different sources such as magmatic water, metamorphic water, seawater or atmospheric precipitation, as well as their respective contribution ratios.

[0011] The elemental geochemical analysis: the synchrotron radiation X-ray fluorescence spectroscopy (SR-XRF) technology is used to perform in-situ, non-destructive trace element analysis of ores and surrounding rocks. During the analysis process, the energy and spot size of the synchrotron radiation light source are adjusted so that it can be focused on a small area of ​​the sample (the spot diameter can be controlled at 10-50 microns), and at least 40 trace elements (including Au, Ag, As, Sb, Hg, W, Sn, Mo, Ba, Sr, Cu, Zn, Ni, Co, Cr, V, Ti, Zr, Hf, Nb, Ta, REE) are accurately measured to analyze their content distribution characteristics and occurrence states in minerals. By observing the changes in the X-ray fluorescence intensity and peak shape of the elements, it is determined whether the elements exist in independent mineral phases or in other minerals in the form of isomorphous substitution, providing detailed element information for a deep understanding of the interaction between ore-forming fluids and minerals. Based on a large amount of elemental geochemical data, a machine learning algorithm is used to construct an ore-forming fluid origin discrimination model. First, the elemental geochemical data of Jiangnan orogenic gold deposits and other known genetic types of deposits were collected as training data sets, and the data were preprocessed, including normalization, standardization and feature selection operations. Then, appropriate machine learning algorithms, support vector machine (SVM), random forest (RF), neural network (NN) were selected to train and optimize the model through the training data set. During the training process, the cross-validation method (5-10 fold cross-validation) was used to evaluate and adjust the performance of the model to ensure that the model has high accuracy and stability. The final model can accurately identify the characteristic patterns of ore-forming fluids of different origins based on the input elemental geochemical data, and distinguish between magmatic hydrothermal type, metamorphic hydrothermal type, and atmospheric precipitation hydrothermal type ore-forming fluids. The accuracy of the model is not less than 90%.

[0012] The data fusion and analysis: establish an intelligent analysis platform for multi-source data fusion, and integrate and input fluid inclusion analysis data, stable isotope data and element geochemical data. The platform adopts advanced database management system and data interface technology to ensure efficient data transmission and storage. The data are comprehensively analyzed using a deep learning neural network algorithm. The neural network structure is designed to include multiple hidden layers (4-6 layers), and the number of neurons in each layer is adjusted according to the complexity of the data (generally between 100-500). By training a large amount of Jiangnan orogenic gold deposit data of known origin, the model can automatically learn the characteristic patterns and relationships of ore-forming fluids of different origins in various data dimensions, thereby realizing accurate judgment of the origin of ore-forming fluids of unknown samples. According to the output results of the intelligent analysis platform, combined with the geological exploration data of the deposit, stratigraphic distribution, structural morphology, and ore body occurrence information, a three-dimensional evolution model of the ore-forming fluid is drawn using professional three-dimensional modeling software (such as GOCAD, Surpac). During the model construction process, the geometric shape of the geological body is accurately digitally represented, and the modeling accuracy of the strata and ore bodies is within 0.5 meters, and the modeling accuracy of the structural surface is within 1 square meter. At the same time, the temperature, pressure, and composition parameters of the ore-forming fluid are assigned to the corresponding spatial positions in the model as attribute information, and the evolution of the ore-forming fluid in time and space is displayed through visualization technology. The time resolution is set to 50,000-100,000 years, and the spatial resolution is set to 0.5-1 cubic meters, providing intuitive and clear visualization tools for in-depth research on the genesis of ore deposits and guiding prospecting and exploration. Through the above series of detailed and precise steps, the present invention can comprehensively and accurately determine the ore-forming fluids of different origins in the Jiangnan orogenic gold deposits, overcome the limitations of traditional methods, and provide an efficient and reliable technical means for ore deposit geochemical research and mineral resource exploration.

[0013] The above technical solution can bring the following significant technical effects:

[0014] High-precision determination of the origin of ore-forming fluids: Through innovative sample collection strategies and sophisticated pre-processing methods, we ensure that the analyzed samples can accurately reflect the true information of ore-forming fluids. Advanced comprehensive analysis technology of fluid inclusions, high-resolution microscopy observation and quantification, high-precision nanoscale temperature and pressure measurement, and the combination of multiple component analysis methods can accurately determine the various characteristics and components of fluid inclusions, providing high-precision data support for the judgment of the origin of ore-forming fluids. The precise determination of stable isotopes combined with comparative analysis of regional geological background databases, in-depth research on elemental geochemistry and the application of machine learning models cross-validate and accurately identify the origin of ore-forming fluids from multiple dimensions. This multi-technical fusion and multi-dimensional analysis method has greatly improved the accuracy of determining the origin of ore-forming fluids compared to traditional methods, and can more accurately distinguish ore-forming fluids from different sources (magma, metamorphic, and atmospheric precipitation) and their mixing ratios, providing a solid foundation for a deep understanding of the genesis of mineral deposits.

[0015] 2. Comprehensively reveal the evolution process of ore-forming fluids: This technical solution not only focuses on the origin of ore-forming fluids, but also constructs a three-dimensional evolution model of ore-forming fluids through data fusion and intelligent analysis. In the process of model construction, the stratigraphic, structural, and ore body information in the geological exploration data is fully considered, and the changes in fluid temperature, pressure, and composition parameters obtained by fluid inclusion analysis, stable isotope determination, and elemental geochemical analysis over time and space are incorporated into it. This enables researchers to intuitively observe the migration path of ore-forming fluids in three-dimensional space, the interaction process with surrounding rocks, and the evolutionary characteristics in different geological periods, and comprehensively reveal the entire evolution process of ore-forming fluids from the source area to the mineralization site. Compared with traditional methods that can only obtain limited and discrete fluid information, this solution can provide continuous and dynamic fluid evolution images, which is helpful for in-depth research on the formation mechanism of ore deposits and the coupling relationship between geological processes, and provide more forward-looking guidance for mineral exploration.

[0016] 3. Significantly improve the efficiency of prospecting and exploration: Since the origin of ore-forming fluids can be determined with high precision and their evolution process can be fully revealed, the geological locations and geological conditions closely related to mineralization can be more accurately locked in during mineral exploration. Through an in-depth understanding of the characteristics of ore-forming fluids, the possible location, scale and mineralization type of the ore body can be predicted, thereby optimizing the exploration plan and reducing blind drilling and exploration costs. According to the source and evolution path of the ore-forming fluids, favorable ore-forming structural locations and surrounding rock alteration areas can be inferred, and exploration projects can be arranged in a targeted manner to improve the success rate of prospecting. Compared with traditional exploration methods based on experience and limited geological information, this technical solution can greatly improve the efficiency and accuracy of prospecting and exploration, shorten the exploration cycle, and provide a strong technical guarantee for the rapid discovery and development and utilization of mineral resources, with significant economic and social benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 Flow chart of the method for determining ore-forming fluids of different origins in the Jiangnan orogenic gold deposit of the present invention DETAILED DESCRIPTION

[0018] The following will be combined with the attached embodiment of the present invention Figure 1 , the technical solutions in the embodiments of the present invention are clearly and completely described. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] Example 1: Accurate analysis of complex multi-source fluids:

[0020] In the study of an orogenic gold deposit in Jiangnan, the traditional method only collected 20 samples in the center of the ore body, with a large sampling interval and no attention to the transition zone. The pretreatment was just a simple cleaning, and the fluid inclusions were observed using an ordinary optical microscope. The size and shape of the inclusions could only be roughly distinguished, and their parameters could not be accurately quantified. The temperature was measured using a conventional hot stage with an accuracy of only ±5°C, and the composition analysis only used a laser Raman spectrometer, which detected a limited number of elements. Stable isotope determination used an ordinary mass spectrometer with an accuracy of about ±1‰, and was not combined with the regional geological background for in-depth analysis. Elemental geochemical analysis determined some common elements through conventional chemical analysis methods, without considering the potential relationship between elements. In the end, it can only be roughly judged that the ore-forming fluid may have two sources, but its specific proportion and interaction relationship cannot be determined, and the explanation of the genesis of the deposit is vague.

[0021] According to the method of the present invention, a study was conducted in the complex mineralization area of ​​the deposit. First, the sampling was carefully planned, and a total of 80 samples were collected at intervals of 2-3 cm in the contact zone between the ore body and the surrounding rock and in the different mineralization stages inside the ore body. These samples were micro-cut with a cutting accuracy of 0.05 mm and cleaned with a special pollution-free reagent. When conducting fluid inclusion analysis, a high-resolution microscope with a resolution of 0.5 μm was used for observation, and the parameters such as the long axis and short axis of the inclusions were accurately measured with an error within 0.1 μm. A nanoscale temperature measurement probe was used in combination with a traditional microscopic hot stage with a temperature measurement accuracy of ±0.3°C. The laser Raman spectrometer, ion chromatography and SIMS technology were combined to comprehensively analyze the composition of the inclusions, and more than 20 elements and compounds were detected, including rare gas isotopes. The stable isotope determination uses MC-ICP-MS technology with an accuracy of ±0.15‰, combined with a regional isotope database covering more than 50 different geological units and period samples. The elemental geochemical analysis uses SR-XRF technology to detect more than 40 trace elements, and is further verified by a model built on a machine learning algorithm trained on data from more than 500 known deposits. Finally, the intelligent analysis platform and 3D modeling software are used to clearly present the different origins of fluids in three-dimensional space at a speed of 0.5m 3 The high-resolution mixing and evolution process can accurately determine that the mixing ratios of magmatic water, metamorphic water and atmospheric precipitation are approximately 40%, 30% and 30%, respectively, providing precise fluid information basis for in-depth research on the genesis of mineral deposits.

[0022] Example 2: Effective prediction of concealed ore bodies:

[0023] In another Jiangnan orogenic gold deposit exploration area, conventional exploration methods were used in the early stage to collect samples at only a few limited points based on geological maps and simple geochemical data, with a total of 10 samples collected. The samples were only observed under a conventional microscope and subjected to basic chemical analysis, without in-depth research on the ore-forming fluids. Based on limited geological information and empirical judgment, several possible ore bodies were speculated, but no ore bodies were found in drilling verification, and the exploration work was in trouble, and the exact location and scale of the ore body could not be determined.

[0024] Using the method of the present invention, systematic sampling was carried out in the area, including intensive sampling of potential surrounding rock alteration areas and structural weak zones, and a total of 60 samples were collected at intervals of 1-2m. After rigorous preprocessing, various analyses were carried out in depth. Fluid inclusion analysis uses a high-resolution microscope combined with image analysis software to accurately count the number and distribution density of inclusions. The temperature is accurately measured by nanoscale temperature probes and traditional microscopic hot stages, and signs of deep high-temperature (uniform temperature up to 400°C) and high-salinity (salinity of about 25wt%) fluids are found. Stable isotope data show that the hydrogen and oxygen isotope compositions deviate from the atmospheric precipitation line and tend to be biased towards the magmatic water area, and the sulfur isotopes have specific deep magma source characteristics. Elemental geochemical analysis found abnormal distribution of some elements (such as W, Sn, etc.) indicating deep fluid migration through SR-XRF technology, and their content is 5-10 times higher than the background value. The data is integrated and a three-dimensional evolution model is constructed through an intelligent analysis platform with a time resolution of 50,000 years and a 1m 3 Based on the spatial resolution of the ore-forming fluid, the source, migration path and evolution trend, it is predicted that there may be hidden ore bodies at a certain depth of 800-1000m and at the intersection of structures. Subsequent drilling verification successfully discovered a hidden gold ore body of a certain scale, with an average grade of 5g / t and a reserve of about 50 tons.

[0025] Example 3: Fine differentiation of similar mineral deposits:

[0026] In two seemingly similar gold deposit areas in the Jiangnan orogenic belt, the traditional method collected 30 samples from each deposit, and the sampling locations were relatively random. Ordinary microscopes were used to observe fluid inclusions, conventional hot stage temperature measurements were performed, laser Raman spectrometers were used for component analysis, ordinary mass spectrometers were used for stable isotopes, and conventional chemical analysis methods were used for elemental geochemical analysis. Due to limited technical means, both deposits were judged to be magmatic hydrothermal in origin based only on partial mineralization characteristics and simple analytical data, and no essential differences were found. The same strategy was used in subsequent exploration and development, but the effect was poor and resource utilization was low.

[0027] In the first deposit, the fluid inclusions sampled and analyzed according to the method of the present invention have a relatively high CO2 / CH4 ratio (about 10:1), and the stable isotope data show that the hydrogen and oxygen isotope compositions are biased towards the magmatic water region (δD value is about -80‰, δ 18 O value is about +10‰) and the sulfur isotopes have specific magmatic source characteristics (δ 34S value is about +5‰), and elemental geochemical analysis shows abnormal enrichment of certain high-temperature elements (such as W and Sn) (W content is about 50ppm, Sn content is about 30ppm). Through the intelligent analysis platform, it is determined that its ore-forming fluid mainly comes from deep magmatic hydrothermal fluids and is affected by about 20% of atmospheric precipitation. The mineralization process is closely related to a specific magmatic activity in the region. In the second deposit, although there are similar mineralization phenomena, the various analysis results of the present invention show that the fluid inclusion composition contains more ion characteristics of sedimentary origin (such as Ba 2+ , Sr 2+ The stable isotope data are closer to the isotope composition range of seawater (δD value is about -40‰, δ 18 O value is about 0‰), and the content of some elements related to sedimentary rocks in elemental geochemical analysis (such as Ba content of about 1000ppm, Sr content of about 500ppm) is relatively high. Analysis has determined that the origin of its ore-forming fluid is related to the transformation of ancient sedimentary strata, and in the later period it was affected by the superposition of about 10% deep fluid. This fine distinction enables targeted exploration and development strategies to be adopted for the two deposits, improving resource recovery rate and economic benefits.

[0028] Example 4: Accurate definition of mineralization boundaries:

[0029] For an area around an already mined Jiangnan orogenic gold deposit, the traditional method is to collect a sample every 10-20m at the edge and outward extension area, for a total of 20 samples. Through simple microscopic observation of fluid inclusions and conventional chemical analysis to determine the content of some elements, a mineralization boundary range was roughly delineated based on limited data and experience, but the boundary was fuzzy and the uncertainty was large. Subsequent exploration in the demarcated boundary area only found a small number of scattered mineralized bodies, resulting in serious waste of resources and an inability to accurately assess the potential value of the deposit.

[0030] The method of the present invention is used to carry out detailed sampling at intervals of 2-3m at the edge of the ore deposit and the transition zone extending outward, and a total of 50 samples are collected. After sample pretreatment and the application of various analytical techniques, fluid inclusion analysis shows that from the inside of the ore body to the edge of the ore body, the temperature of the inclusions gradually decreases from 350°C to 200°C, the salinity decreases from 20wt% to 5wt%, and the composition gradually changes from rich in metal ions and volatiles to relatively depleted, and the stable isotope and elemental geochemical data also show corresponding regular changes. The three-dimensional evolution model constructed by the intelligent analysis platform intuitively shows the changes in the properties of the ore-forming fluid during the diffusion process to the edge of the ore body, so that the mineralization boundary range is accurately delineated according to these change characteristics, and the boundary accuracy reaches within 5m. Subsequent exploration work has discovered new mineralized bodies in the delineated boundary area, with an average grade of 3g / t and an additional reserve of about 30 tons, which confirms the accuracy of the boundary definition and provides a reliable basis for the rational development and utilization of mineral resources. Through the above four embodiments, compared with the traditional method, the present invention has shown significant advantages in the identification of ore-forming fluids of different origins in the Jiangnan orogenic gold deposits, whether in terms of data accuracy, the ability to analyze complex situations, or the prediction and guidance effects in practical applications. It can provide more powerful technical support for mineral exploration and development, and improve resource utilization and economic benefits.

[0031] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for determining ore-forming fluids of different origins in a Jiangnan orogenic gold deposit, characterized in that: The following steps are involved: S1 Sample collection: Systematic sampling of the ore bodies, surrounding rocks, different mineralization stages and structural parts of the Jiangnan orogenic gold deposits, with special emphasis on the sampling of the transition area between the ore bodies and surrounding rocks and veins of different stages. The sampling interval is no more than 5 cm to ensure that representative samples of ore-forming fluid information are fully obtained; s2 Sample pretreatment: Use micro-cutting technology to obtain the pure part inside the mineral to avoid surface contamination, and then use non-polluting and mild chemical reagents to clean the sample to remove impurity elements while ensuring that the original composition of the sample is not changed. After cleaning, the sample needs to be stored in a vacuum or inert gas environment for future use; s3 Fluid inclusion analysis: Use a high-resolution microscope to observe the morphology of fluid inclusions, measure their major axis, minor axis, and area parameters with an accuracy of 0.1 micron, and use image analysis software to count the number and distribution density of inclusions to distinguish between primary and secondary inclusions; use a high-precision nanoscale temperature measurement probe combined with a traditional microscopic hot stage to measure the uniform temperature and freezing point temperature of fluid inclusions with a temperature measurement accuracy of ±0.5°C, and determine the capture temperature range of the ore-forming fluid based on the temperature data; use laser Raman spectrometer, ion chromatography, and in-situ secondary ion mass spectrometry (SIMS) technology to comprehensively analyze the gas and liquid phase components of fluid inclusions, and detect at least 10 elements and compounds, including common H2O, CO2, CH4, Na + , K + , Ca 2+ Mg 2+ and noble gas isotopes to characterize the chemical composition of the fluid; s4. Stable isotope determination: Use multi-collector inductively coupled ion mass spectrometry (MC-ICP-MS) technology to accurately determine the hydrogen, oxygen and sulfur isotopes in ore minerals, with measurement accuracy of ±0.2‰ and ±0.3‰ respectively, to obtain isotope ratio data; establish a stable isotope database based on the regional geological evolution of the Jiangnan orogenic belt, compare and analyze the measured ore deposit isotope data with the database, consider the influence of regional magmatic activity, metamorphism, and sedimentation geological processes on isotope composition, and determine the possible source of ore-forming fluids; s5. Elemental geochemical analysis: Use synchrotron radiation X-ray fluorescence spectroscopy (SR-XRF) technology to conduct in-situ, non-destructive trace element analysis of ores and surrounding rocks, detect the content and distribution characteristics of at least 30 trace elements, including Au, Ag, As, Sb, Hg, W, Sn, Mo, Ba, Sr, and analyze the occurrence state of elements in minerals; Based on elemental geochemical data, a machine learning algorithm is used to construct an ore-forming fluid origin discrimination model. By training on a large number of elemental data of known genetic deposits, the model can accurately identify the element combination characteristics of ore-forming fluids of different origins, and the model accuracy rate is not less than 85%; s6. Data fusion and analysis: Establish an intelligent analysis platform for multi-source data fusion, integrate fluid inclusion analysis data, stable isotope data and elemental geochemical data, use deep learning neural network algorithm to conduct comprehensive analysis of the data, identify the characteristic patterns of ore-forming fluids of different origins through training models, and output the key information of the origin, mixing ratio and evolution process of the ore-forming fluids; according to the results of the intelligent analysis platform, use 3D modeling software to draw a 3D evolution model of the ore-forming fluid to intuitively display the changes of the ore-forming fluid in time and space. The spatial resolution of the model is not less than 1 cubic meter, and the temporal resolution is not less than 100,000 years, providing a visualization tool for ore deposit genesis research and prospecting prediction.

2. The determination method according to claim 1, characterized in that: In the sample collection step, for areas with obvious mineralization zoning, sampling is carried out according to the gradient of mineralization intensity, and the number of samples for each gradient is not less than 5, so as to accurately obtain information on ore-forming fluids at different mineralization stages.

3. The determination method according to claim 1, characterized in that: In the fluid inclusion analysis step, when performing laser Raman spectrometer analysis, a method of taking an average value by multiple scans is adopted, and the number of scans is not less than 5 times, so as to improve the accuracy and reliability of the component analysis.

4. The determination method according to claim 1, characterized in that: In the stable isotope determination step, when establishing a stable isotope database, the data in the database are quality evaluated and screened to ensure the accuracy and representativeness of the data, and the data sources cover samples from at least 10 different geological units and geological periods in the Jiangnan orogenic belt.

5. The determination method according to claim 1, characterized in that: In the elemental geochemical analysis step, when using the machine learning algorithm to construct the discriminant model, the model is optimized by a cross-validation method to ensure the stability and generalization ability of the model, and the number of cross-validation folds is not less than 50%.

6. The determination method according to claim 1, characterized in that: In the data fusion and analysis steps, the deep learning neural network algorithm of the intelligent analysis platform adopts a structure of at least 3 hidden layers, with no less than 100 neurons in each layer, and improves the model's ability to recognize the characteristic patterns of ore-forming fluids by continuously adjusting network parameters.

7. The determination method according to claim 1, characterized in that: In the step of drawing the three-dimensional evolution model, the stratigraphic and structural geological elements in the model are accurately restored based on geological information and actual measurement data, and the geometric accuracy error of the model does not exceed 5%, so that it can truly reflect the geological background of the ore deposit and the evolution environment of the ore-forming fluid.

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