Method for predicting lead-zinc deposit based on minimum prediction area delineation method

Abstract

A method for predicting a lead-zinc deposit based on a minimum prediction area delineation method comprises the following steps: step 1, determination of prediction elements: on the basis of collecting existing geological mineral data, performing comparatively rough positioning prediction in combination with ore control conditions and metallogenic laws of typical deposits in an area, and during metallogenic law research, performing repeated research and comparison on the prediction elements to obtain a prediction result; the method comprises the following steps: screening metallogenic structures, ore-bearing construction, known lead-zinc ore deposits, ore deposit density and found resource quantity, geochemical exploration anomaly Pb and Zn, and heavy sand anomaly Pb; assigning the weight of each prediction element according to the determination of the prediction elements, so as to perform positioning prediction, select a prediction area, predict the resource quantity, calculate a formula of the resource quantity by using a geological volume method, and finally achieve the purpose of quantitative prediction, thereby solving the problem of the possibility of local mineralization, and analyzing the possibility of local mineralization; and the ore control condition research of each typical ore deposit has no corresponding data and formula for speculation, and is lack of scientificity, quantificaiton and specific purposiveness.

Description

Technical Field

[0001] The present invention relates to a prospecting prediction method for mineral deposits, and specifically to a method for predicting lead-zinc deposits based on the method of delineating the minimum prediction area. Background Art

[0002] 1. Research status of the same type of deposits in Southeast Guizhou, China:

[0003] a Longjingjie lead-zinc deposit (Yang Zongwen and Huang Yuancheng, 2003): It is located on the Yuping-Kaili-Sandu regional major fault zone in the transitional zone. The Mandong deep fault passes through the southeast side of the mining area, and ultrabasic rocks are exposed on both sides. Moreover, obvious lithofacies changes occur in the sedimentary cover rocks on both sides of the fault, showing typical characteristics of major deep faults. The strata exposed in the southeast plate of the Longjingjie fault are mainly the shallower metamorphic rock series of the Fanzhao Formation and the second member of the Qingshuijiang Formation of the Xiajiang Group in the Qingbaikou System, which is the basement rock combination in the South China fold belt; the northwest plate mainly exposes the Cambrian and Ordovician strata. The rock combination is carbonate rock intercalated with clastic rock, which is the cover rock combination of the non-Yangtze paraplatform. Among them, the third member of the Qingxudong Formation and the first member of the Shilengshui Formation in the Lower Cambrian are the main ore-bearing strata for lead-zinc ores. The rocks of the third member of the Qingxudong Formation and the first member of the Shilengshui Formation are oolitic, pisolitic dolomite, fine-crystalline dolomite, powder-crystalline dolomite, gravel-bearing dolomite, etc. The large amount of ooids, pisoids and a small amount of intraclastic particles contained indicate oolitic beach deposits at the platform margin. The ooids formed in this facies belt can be diagenetically accumulated in situ or transported to the basin for accumulation and diagenesis. The ore bodies are stratiform, lenticular intermittently along the layer, and occur along the interlayer faults. The occurrence of each ore (mineralized) body is basically the same as that of the ore-hosting wall rock, and there is a small-angle cross-stratification phenomenon in the local lenticular ore bodies. The mineralized zone is 2000 m long, and the maximum length of the ore body preliminarily controlled by surface engineering is 1000 m, the maximum thickness is 12.8 m, and generally (4 - 6) m. The grade is Zn (5.96 - 7.15)%, Pb (6.03 - 6.70)%. The ore composition is simple. The ore minerals are mainly sphalerite and galena, followed by smithsonite, limonite and hematite, and a small amount of pyrite; the gangue minerals are mainly dolomite, and a small amount of calcite, quartz and bituminous matter. The beneficial components are mainly zinc, followed by lead, and others: Cd (0.04 - 0.09)%, Ga < 0.001%, Ge (0.001 - 0.003)%, Ag (2.39 - 4.78)×10 -6 。

[0004] The ore shows euhedral granular structure, unequal-grained mosaic structure, fragmental structure, spherulitic structure, replacement residue structure, etc.; the ore structures are disseminated, spotted, brecciated, massive, veinlet, honeycomb, etc.

[0005] Sandu Niuchang Lead-Zinc Mine: It is located in the southern section of the Sandu-Dan Lead-Zinc-Mercury-Antimony-Gold Ore Belt, distributed outside mercury, antimony, and gold deposits, and occurs in the fault block held by the north-south Yaji-Dixiang Fault and Yangyongguan-Lantu Fault, and is controlled by the secondary north-south Niuchang Fault; the ore-bearing wall rock is the thick massive breccia limestone in the middle and upper parts of the Sandu Formation, intercalated with banded argillaceous limestone, laminated marl, and calcareous shale intercalated with medium-thick limestone; the ore body occurs in the nearly north-south F2 and the secondary fault fracture zones on its side, and is strictly controlled by the fault, with the occurrence consistent with that of the fault. The ore body is 155 - 253 m long and extends obliquely for (75 - 100) m; it contains Zn (1.70 - 9.44)%, Pb (0.56 - 6.65)%, and associated with Cd, Ga, Ge, Ag, etc.; the ore minerals mainly include sphalerite, galena, and pyrite, and the gangue minerals are calcite, dolomite, barite, and a small amount of quartz. The ore is brown to black, with fine to coarse grain structure, euhedral to subhedral granular structure, and dissolution replacement structure, and disseminated, veinlet, and massive structures.

[0006] c Qiandong Zhenyuan Jinbao Lead-Zinc Mine: The Jinbao Lead-Zinc Deposit is located in the middle section of the Qiandong Lead-Zinc Metallogenic Belt. Through field investigation, sampling, and testing analysis, the carbon, oxygen, and sulfur isotope geochemical characteristics of the Zhenyuan Jinbao Lead-Zinc Deposit in Guizhou, Qiandong are studied. The carbon isotopes of calcite and dolomite are between (-5.7‰ and -6.9‰), falling within the typical igneous carbonate rock region (-5‰ to -7‰); the oxygen isotopes are between (11.2‰ and 12.2‰), slightly higher than that of igneous carbonate rocks, indicating that the igneous carbonate rock materials have undergone low-temperature alteration, resulting in higher oxygen isotopes. The sulfur isotopes of sphalerite are relatively concentrated, between (11.5‰ and 14.2‰). Combining with the carbon isotopes in this region, it is suggested that the ore-forming materials come from the deep mantle or magmatic action. Through carbon-oxygen stable isotope tracer analysis, combined with regional geological conditions and ore deposit geological characteristics research, it is considered that the ore-forming hydrothermal fluid of the Jinbao Lead-Zinc Mine is related to magmatic action.

[0007] 2. Research Foundation and Current Situation of the Laodongzhai Lead-Zinc Deposit in Danzhai County, Guizhou Province:

[0008] This study was carried out on the basis of fully collecting and understanding domestic typical ore deposits and typical ore deposits in Southeast Guizhou. Through comparison, it is found that both domestic typical ore deposits and typical ore deposits in Southeast Guizhou are significantly controlled by faults, strata, and lithology, and are hydrothermal ore deposits formed after the normal deposition of strata and being transformed by later tectonic, magmatic, and regional metamorphic actions. The discovered Laodongzhai Lead-Zinc Mine is a medium to large-sized ore deposit, which is also significantly controlled by faults, strata, and lithology, showing similarity, and has great prospecting potential, worthy of further research to find out the regularity.

[0009] The geotectonic position of the Laodongzhai Lead-Zinc Deposit is located in the transitional zone between the Yangtze Block and the South China Fold Belt, belonging to the northern section of the Sandu - Danzhai Polymetallic Metallogenic Belt, where the interlayer fracture zone F 21It is closely related to mineralization. The first member of the Doushantuo Formation is the main occurrence horizon of lead-zinc ore in the area. The lithology is silt-bearing carbonaceous argillaceous slate intercalated with dolomitic carbonaceous calcareous slate and lenticular dolomitic limestone. The ore bodies are controlled by both interlayer fracture zones and strata. The ore bodies generally occur in fault breccia (dolomite, dolomitic limestone) in the form of stratoid, lenticular and vein-like, belonging to nearly concealed ore bodies. The ore body is about 800 m long and extends up to about 440 m along the dip. The thickness of the ore body changes relatively stably (0.92 - 25.76) m, with an average of 5.91 m. The average grade of the ore is 5.95% for Zn and 2.03% for Pb. The ore structures mainly include disseminated, brecciated, massive and vein-like structures. The ore textures mainly include subhedral crystal, anhedral grain, interstitial, replacement and cataclastic (powder) textures. The wall rock alteration is mainly silicification, followed by pyritization, dolomitization / calcitization and baritization. Mineralization is particularly closely related to silicification. The stronger the silicification, the better the mineralization. Silicification is an important direct prospecting indicator. Through the analysis of the characteristics of trace elements, rare earth elements and sulfur isotopes in the area, it is considered that the material source of its ore is relatively complex, and the material source is the ore-bearing layer itself or the wall rock strata. It basically excludes a large amount of deep magma as the material source, and is a medium-low temperature mineralization. It is speculated to be a sedimentary reformation hydrothermal deposit.

[0010] Difficulties in prospecting work: Typical lead-zinc deposits are significantly controlled by regional major faults and carbonate strata. The ore-forming strata are variable; the ore-forming positions are variable, with stratigraphic ore control types, fault ore control types, and even types controlled by both strata and faults; the ore structures and wall rock alterations are generally the same with minor differences, and the material sources are relatively complex. It has become a difficult problem to accurately predict the ore-forming target area in the area.

[0011] The previous studies on typical deposits only generally introduced their genetic and ore control conditions, and did not analyze where there is a possibility of mineralization; the research on the ore control conditions of each typical deposit lacked corresponding data and formulas for speculation, lacking scientificity, quantification and specific purpose. Summary of the Invention

[0012] (1) Technical problems to be solved

[0013] In view of the above deficiencies of the prior art, the present invention provides a method for predicting lead-zinc deposits based on the method of delineating the minimum prediction area. The technical problems to be solved are: The previous studies on typical deposits only generally introduced their genetic and ore control conditions, and did not analyze where there is a possibility of mineralization; the research on the ore control conditions of each typical deposit lacked corresponding data and formulas for speculation, lacking scientificity, quantification and specific purpose.

[0014] (2) Technical solutions

[0015] To achieve the above object, the present invention provides the following technical solutions: A method for predicting lead-zinc deposits based on the method of delineating the minimum prediction area, and the specific method is as follows:

[0016] The first step, determination of prediction elements: In this prediction, on the basis of collecting existing geological and mineral resources data, a relatively rough location prediction is carried out by combining the ore-controlling conditions and metallogenic laws of typical deposits in the area. When studying the metallogenic laws, the prediction elements are repeatedly studied and compared, and five types of prediction elements are selected: metallogenic structures (including regional ore-controlling faults, ore-bearing faults, and ore-hosting faults), ore-bearing formations (gray-grayish black silt-bearing carbonaceous argillaceous slate intercalated with dolomitic carbonaceous calcareous slate and lenticular dolomitic limestone, dolomite <the first section of the Doushantuo Formation>, metabasite sandstone, silt-bearing slate, sericite slate, tuffaceous slate <Qingbaikou System>), known lead-zinc deposits (points) (including ore point density and proven resource reserves), geochemical anomalies (Pb, Zn), and heavy sand anomalies (Pb).

[0017] The second step: Delineate the boundaries of the prediction areas. The boundaries of the prediction areas in this area are delineated by the superposition method of location prediction elements. That is, all necessary location prediction elements are superimposed, and the boundaries of the overlapping parts are the approximate boundaries of the prediction areas. According to the above principles, a total of 7 minimum prediction areas are delineated in the area, which are, from north to south, Nangao minimum prediction area, Jiaogao small prediction area, Xinhua minimum prediction area, Wuzuo minimum prediction area, Fanyang minimum prediction area, Laodongzhai minimum prediction area, and Wutan minimum prediction area.

[0018] The third step, classification of the minimum prediction areas and calculation of the metallogenic probability:

[0019] I. Calculation of the metallogenic probability of the minimum prediction areas

[0020] 1. Prediction element assignment method

[0021] According to the metallogenic laws in the area and the importance of the influence on metallogenesis, finally, the prediction elements of metallogenic structures (including regional ore-controlling faults, scale of ore-bearing faults, and ore-hosting structures), ore-bearing formations (gray-grayish black silt-bearing carbonaceous argillaceous slate intercalated with dolomitic carbonaceous calcareous slate and lenticular dolomitic limestone, dolomite <the first section of the Doushantuo Formation>, metabasite sandstone, silt-bearing slate, sericite slate, tuffaceous slate <Qingbaikou System>), known lead-zinc deposits (points) (including ore point density and proven resource reserves), geochemical anomalies (Pb, Zn, Cd), and heavy sand anomalies (Pb) are assigned values according to the weights. The situation from high to low in terms of importance is shown in (Table 8-2)

[0022] 2. Calculation of the metallogenic probability of the minimum prediction areas

[0023] The mineralization probability of each minimum prediction area is scored according to the assignment of each prediction factor. Those with a total score of ≥ 0.8 are "Class A minimum prediction areas"; those with a total score of 0.7 ≤ n < 0.8 are "Class B minimum prediction areas"; those with a total score of 0.6 ≤ n < 0.7 are "Class C minimum prediction areas" (Table 8-3).

[0024] II. Classification of minimum prediction areas. According to the classification requirements of minimum prediction areas and combined with the overall mineralization probability of the prediction areas, 7 prediction areas are classified, including 1 Class A, 2 Class B, and 4 Class C;

[0025] Step 4: Quantitative prediction of resources. In this case, geological volume parameters are selected for quantitative estimation of resources. The lead-zinc ore in this prediction area belongs to the non-magmatic hydrothermal type, and the ore bodies occur in a stratoid, vein-like, and lenticular shape. The formula for calculating resources by the geological volume method is as follows:

[0026] Zpre = ((Spre × Hpre × K × α) / COS(β)) - Zcha

[0027] Explanation of prediction parameters: Zpre: Predicted resources in the prediction area; Zcha: Proven reserves; Spre: Planar area of the minimum prediction area; Hpre: True thickness of the ore-bearing formation (geological body); K: Ore-bearing coefficient in the model area; α: Similarity coefficient; β: Dip angle of the ore-bearing geological body.

[0028] (III) Beneficial effects

[0029] The present invention provides a method for predicting lead-zinc deposits based on the method of delineating minimum prediction areas, with the following beneficial effects:

[0030] According to the determination of prediction factors, the boundaries of the prediction areas are delineated, the minimum prediction areas are classified, the mineralization probability is calculated, and weights are assigned to each prediction factor, so as to conduct positioning prediction, select the prediction areas, and predict the resources. The formula for calculating resources by the geological volume method is used to finally achieve the purpose of quantitative prediction, solving the problems of analyzing the possibility of local mineralization; there are no corresponding data and formulas for inferring the ore-controlling conditions of each typical ore deposit, lacking scientificity, quantification, and specific purpose, etc. Specific implementation manners

[0031] Next, in combination with the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention. The specific method is as follows:

[0032] Step 1: Determination of prediction elements: Although some geological and mineral exploration work has been carried out in the prediction area in the past, due to insufficient funding, most of it remains at the level of ore point investigation and evaluation, scattered market project exploration work, and regional research work. Generally speaking, the research degree in the area is relatively low, and there are few elements available for metallogenic prediction. Based on the collection of existing geological and mineral data, this prediction conducts a relatively rough location prediction by combining the ore-controlling conditions and metallogenic laws of typical ore deposits in the area. When studying the metallogenic laws, the prediction elements are repeatedly studied and compared, and five types of prediction elements are selected, namely metallogenic structures (including regional ore-controlling faults, ore-bearing faults, and ore-hosting faults), ore-bearing formations (gray to grayish-black silt-bearing carbonaceous argillaceous slate intercalated with dolomitic carbonaceous calcareous slate and lenticular dolomitic limestone, dolomite <the first member of the Doushantuo Formation>, metabasite sandstone, silt-bearing slate, sericite slate, and tuffaceous slate <Qingbaikou System>), known lead-zinc ore deposits (points) (including ore point density and identified resource reserves), geochemical anomalies (Pb, Zn), and heavy sand anomalies (Pb).

[0033] 1. Ore-bearing formation

[0034] The non-magmatic hydrothermal lead-zinc ores in the area occur in the Qingshuijiang Formation, Pinglue Formation, and Longli Formation of the Qingbaikou System; the first member of the Doushantuo Formation of the Sinian System.

[0035] The ore-bearing formation is gray to grayish-black silt-bearing carbonaceous argillaceous slate intercalated with dolomitic carbonaceous calcareous slate and lenticular dolomitic limestone, dolomite (the first member of the Doushantuo Formation of the Sinian System), metabasite sandstone, silt-bearing slate, sericite slate, and tuffaceous slate (Qingbaikou System). The above two ore-bearing formations are one of the essential elements in the prediction area.

[0036] According to the outcrop situation of the ore-bearing formation, stratigraphic attitude, etc., the horizontal projections of the hidden parts of each set of ore-bearing formations at a buried depth of 1000 m are inferred by several short profiles; finally, the outcropping part of the ore-bearing formation and the horizontal projection of its hidden part at the buried depth are used as one of the bases for delineating the prediction area.

[0037] 2. Metallogenic structure

[0038] The lead-zinc ores in the area are controlled by ore-forming structures such as NE-trending and nearly NS-trending faults and secondary folds. All lead-zinc ore (point) deposits are distributed near the regional ore-controlling structures. Therefore, the existence or non-existence of NE-trending and nearly NS-trending faults and secondary folds is one of the necessary conditions for the existence of this type of ore deposit. Ore-bearing faults and fault intersections are one of the important elements for ore formation.

[0039] NE-trending and nearly NS-trending regional ore-controlling faults: Through comprehensive analysis of the existing mine area data, the distance of 0 - 5.0 km from the fault is favorable for ore formation, and 5.0 - 7.25 km is sub-favorable for ore formation.

[0040] Ore-bearing faults: Statistics are carried out according to the influence range of ore-bearing faults. A distance of 0.5 km from the fault is favorable for mineralization.

[0041] Ore-hosting faults: Secondary faults on the side of regional faults are often ore-hosting faults. The interlayer sliding fault at the bottom of the first member of the Doushantuo Formation provides a good ore-hosting space.

[0042] The above elements are all used as the basis for delineating the prediction area.

[0043] 3. Known lead-zinc deposits (points) and proven resource reserves

[0044] Except for the proven resource reserves, most of the known lead-zinc deposits (points) have further prospecting potential in their surrounding areas and deep parts. The distribution, quantity, and proven resource reserves of known lead-zinc deposits (points) are the basis for prediction work. Therefore, known lead-zinc deposits (points) and proven resource reserves are important prediction elements and are used as the basis for delineating the prediction area.

[0045] 4. Geochemical anomalies

[0046] By analyzing the anomalies of two elements, Pb and Zn, the geochemical anomalies of Pb and Zn coincide well with the known lead-zinc deposits (points). Therefore, the geochemical anomalies of Pb and Zn are an important prediction element.

[0047] 5. Natural heavy mineral anomalies

[0048] Through the analysis of natural heavy mineral anomalies of Pb and Zn, the known deposits coincide well with the natural heavy mineral anomalies of Pb, and are mainly distributed in the I and II grade anomaly zones. Therefore, the natural heavy mineral anomalies of Pb are an important prediction element.

[0049] The second step: Delineate the boundary of the prediction area

[0050] The boundary of the prediction area in this area is delineated by the superposition method of positioning prediction elements. That is, all necessary positioning prediction elements are superimposed, and the boundary of the overlapping part is the approximate boundary of the prediction area.

[0051] There are two categories of necessary positioning prediction elements considered here:

[0052] (1) The basic boundary of the prediction area is the distribution range of the ore-bearing formation (including the surface outcropping area and the covered area by the caprock). Areas outside the boundary of this type of element are not considered.

[0053] (2) The influence range of regional ore-controlling faults. Areas outside are not considered.

[0054] The boundary of the overlapping part of the above two types of necessary positioning prediction element ranges is the approximate boundary of the prediction area; then the boundary determined by the comprehensive analysis and correction of geological experts based on relevant information such as geophysical, geochemical, and remote sensing anomalies, ore (deposit) points, etc. is the boundary of the prediction area; finally, the delineated area is the minimum prediction area.

[0055] According to the above principles, a total of 7 minimum prediction areas have been delineated in the area, which are, from north to south, Nangao Minimum Prediction Area, Jiaogao Small Prediction Area, Xinhua Minimum Prediction Area, Wuzuo Minimum Prediction Area, Fanyang Minimum Prediction Area, Laodongzhai Minimum Prediction Area, and Wutan Minimum Prediction Area.

[0056]

[0057]

[0058]

[0059]

[0060]

[0061] II. Classification of Minimum Prediction Areas

[0062] According to the classification requirements of the minimum prediction areas and combined with the overall ore-forming probability of the prediction areas, the 7 prediction areas are classified, including 1 Class A, 2 Class B, and 4 Class C. The classification of each specific prediction area is shown in Table 6-4.

[0063] Table 6-4 List of Ore-forming Elements of Laodongzhai Lead-Zinc Deposit

[0064]

[0065]

[0066] Fourth step: Quantitative prediction of resource reserves. In this prediction, geological volume parameters are selected for quantitative estimation of resource reserves. The lead-zinc ore in this prediction area belongs to the non-magmatic hydrothermal type, and the ore bodies occur in a stratoid, vein-like, and lenticular shape.

[0067] The formula for calculating resource reserves by the geological volume method is as follows:

[0068] Zpre = ((Spre × Hpre × K × α) / COS(β)) - Zchk

[0069] Zpre: Predicted resource reserves in the prediction area

[0070] Zchk: Identified resource reserves

[0071] Spre: Planar area of the minimum prediction area

[0072] Hpre: True thickness of the ore-bearing formation (geological body)

[0073] K: Ore-bearing coefficient of the model area

[0074] α: Similarity coefficient

[0075] β: Dip angle of ore-bearing geological body

[0076] There are two main types of lead-zinc ore production in the area. One is the lead-zinc ore that is obviously controlled by layers and mainly produced in the first section of the Doushantuo Formation. The other is the lead-zinc ore that is obviously controlled by faults and mainly produced in shallow metamorphic rocks. Therefore, different methods are used to determine different types of ore-bearing geological bodies. The ore-bearing geological body refers to the ore-bearing lithology section (the first section of the Doushantuo Formation is gray-gray-black silty carbonaceous argillaceous slate intercalated with dolomite carbonaceous calcareous slate and lenticular dolomite limestone and dolomite); the fault-type ore-bearing geological body refers to the thickness of the ore-bearing lithology section, but the thickness of the ore-bearing lithology section is replaced by the true thickness of the ore body passing through the rock layer, rather than the thickness of the entire rock layer.

[0077] 1. Determination of resource prediction parameters:

[0078] 1. Typical (representative) ore deposit prediction model and parameter determination

[0079] (1) Identified resources / reserves and their estimated parameters

[0080] Through the research and analysis of the data, two lead-zinc deposits in the prediction area, Laodongzhai in Danzhai County and Wuzuo in Danzhai County, were selected as model areas to estimate the resources in the prediction area. The proven resources / reserves of the deposits and their estimated parameters are shown in Table 8-4.

[0081] The parameters of the identified resource reserves, area, extension, and dip of the ore-bearing structure in Table 8-4 are respectively derived from the Exploration Report of the Laodongzhai-Wuzuo Lead-Zinc Mine in Danzhai County, Guizhou Province and the Detailed Exploration Report of the Laodongzhai-Wuzuo Lead-Zinc Mine in Danzhai County, Guizhou Province. Among them: the identified resource reserves are 333 and above level resources, the area is the sum of the estimated resource range of the mining area and the flat area of ​​the controlled but unseen area, the extension is the maximum true thickness of the controlled ore-bearing structure, and the dip of the ore-bearing structure is the average dip of the ore-bearing structure in the mining area. The volume mineralization rate is the identified resource reserves / ((area×extension) / cosine value of dip).

[0082] (2) Predicted resources and estimated parameters in the deep and peripheral areas of typical (representative) deposits

[0083] According to the metallogenic regularity and the distribution characteristics of lead-zinc deposits, the predicted resources and their estimation parameters in the deep and peripheral parts of typical (representative) deposits are selected, and the parameters are shown in Table 8-5. The parameters in the table are from the following sources: the area is the horizontal area, and the peripheral area of the deposit is the minimum predicted area minus the area where the deposit is distributed; the depth extension is the true thickness of the ore-bearing geological body, which is determined according to the average thickness of the ore-bearing formation in the mining area. The depth extension of the Laodongzhai predicted area is 135 m, and that of the Wuzuo predicted area is 350 m; the volume ore-bearing rate is selected from Table 8-4 according to the deposits selected above; the dip angle is the average dip angle of the ore-bearing geological body in the predicted area; the predicted resources = ((the predicted area of the ore-bearing formation × the formation depth extension) / COS(dip angle)) × the volume ore-bearing rate.

[0084] (3) Determination of the total predicted resources and ore-bearing coefficient in the model area

[0085] Through the above methods, the resources in the deep and peripheral parts of typical (representative) deposits in the area are calculated. The summary of the resources in the predicted areas where each typical (representative) deposit is distributed is shown in Table 8-7. The sources of the parameters in the table are as follows: the identified resources are the resources of grade 333 and above of the typical (representative) deposits participating in the prediction; the predicted resources are the sum of the predicted resources in the deep and peripheral parts of the typical (representative) deposits; the total resources are the identified resources + the predicted resources; the total area is the minimum predicted area where the typical deposit is located; the total depth extension is the average true thickness of the ore-bearing geological body; the dip angle is the average dip angle of the ore-bearing geological body within the predicted range; the ore-bearing coefficient = total resources / ((total area × total depth extension) / COS(dip angle))

[0086]

[0087]

[0088] 2. Estimation methods and parameters of the predicted resources in the model area

[0089] (1) Predicted resources and their estimation parameters in the model area

[0090] The model mining area refers to the minimum predicted area where the typical (representative) deposit or the known identified resources are located.

[0091] Two model areas are selected for prediction, namely the Laodongzhai model area and the Wuzuo model area. The predicted resources and their estimation parameters in the model mining area are shown in Table 8-8. The sources of the parameters in the table are as follows: the predicted resources in the model mining area are the sum of the predicted resources in the deep and peripheral parts of the typical deposit and the identified resources; the area of the model area is the horizontal area of the minimum predicted area; the depth extension is the average true thickness of the ore-bearing geological body. Through comprehensive analysis of the exploration geological reports in the area, the depth extension of the Laodongzhai model area is 135 m, and that of the Wuzuo model area is 350 m; the area of the ore-bearing geological body is the horizontal area actually surrounded by the ore-bearing geological body.

[0092] (2) Determination of Ore-bearing Coefficient in the Model Area

[0093] Table 8-7 Predicted Resources and Estimation Parameters in the Model Area

[0094]

[0095] After determining the parameters of the above model area, the ore-bearing coefficients of the two model areas of Laodongzhai and Wuzuoshan are obtained as shown in Table 8-8. In the table: the total resources are the model area resources in Table 8-6; the total volume of ore-bearing geological bodies is (area × depth extension) / COS(dip angle) in the model area of Table 8-6; the ore-bearing coefficient of the model area

[0096] = total resources / total volume of ore-bearing geological bodies.

[0097] Table 8-8 Ore-bearing Coefficient Table of Ore-bearing Geological Bodies in the Model Area of the Predicted Working Area

[0098]

[0099] 3. Estimation Method and Parameters of Predicted Resources in the Minimum Prediction Area

[0100] (1) Resource Estimation Method

[0101] The geological volume method is adopted for estimating the resources in the prediction area.

[0102] (2) Determination of Estimation Parameters

[0103] ① Method and Results for Defining the Minimum Prediction Area

[0104] In the area, the minimum prediction area is initially defined by the superposition method of necessary elements; then, some areas with lower ore-forming probabilities are removed by the characteristic analysis method of prediction elements; finally, experts use comprehensive information such as geology, geophysics, geochemistry, remote sensing, gravity, and ore occurrences to correct the minimum prediction area. According to the above principles, 7 minimum prediction areas are defined in the Laodongzhai Lead-Zinc Mine and its peripheral areas in Danzhai County, and the definition results are shown in Table 8-9.

[0105] Table 8-9 Area and Method Basis for Defining the Minimum Prediction Area in the Prediction Area

[0106]

[0107]

[0108] ② Determination and Results of Depth Extension Parameters

[0109] The depth extension parameter in the area is the average true thickness of the ore-bearing formation (geological body). Through comprehensive analysis of the exploration geological reports in the area, different values are taken for different ore-bearing geological bodies for the depth extension, and generally, the maximum value of the extension in the exploration geological reports in the prediction area is taken. Pt 33 The average true thickness of the ore-bearing geological body in d is 135 m, and that of the Qingbaikou System ore-bearing geological body is 160 - 433 m. The depth extension of the ore-bearing geological body in each prediction area is shown in Table 8 - 10.

[0110] Table 8 - 10 Minimum Prediction Area Depth Extension, Enclosed Size and Method Basis

[0111]

[0112]

[0113] ③ Method and Results for Determining Ore-bearing Geological Body Surface Parameters and Dip Angle Parameters

[0114] Due to the influence of structures and ore-bearing formations, the area of the minimum prediction area is often larger than that of the ore-bearing geological body. The area of the ore-bearing geological body is the horizontal area where the ore-bearing formation is distributed in the prediction area; the dip angle of the ore-bearing geological body is the average dip angle where the ore-bearing formation is distributed in the area. The area and dip angle parameters of the ore-bearing geological body in each minimum prediction area are shown in Table 8 - 11.

[0115] Table 8 - 11 List of Ore-bearing Geological Body Surface Parameters and Dip Angle Parameters in Each Minimum Prediction Area

[0116]

[0117] ④ Determination of Similarity Coefficient

[0118] Principles for determining the similarity coefficient of each minimum prediction area in the prediction area: one is the overall similarity coefficient of all prediction elements in the model mining area and the prediction area; the other is the similarity coefficients of various quantitative estimation parameters for comparison.

[0119] In this area, by using the characteristic analysis method for each prediction element, the ore-forming probability of each minimum prediction area is obtained (Table 8 - 3). The similarity coefficient of the minimum prediction area is equal to the ore-forming probability of the minimum prediction area / the ore-forming probability of the model area. According to the ore-forming law research and the principle of estimating the resource quantity in the model area nearby, the resource quantity of the three minimum prediction areas of Wutan, Fanyang, and Nangao is estimated using the parameters of the Laodongzhai model area; the resource quantity of the minimum prediction areas of Xinhua and Jiaogao is estimated using the parameters of the Wuzuo model area. The similarity coefficients of each minimum prediction area are shown in Table 8 - 12.

[0120] Table 8 - 12 Similarity Coefficient Table of Minimum Prediction Areas

[0121]

[0122] III. Estimation Results of Resource Quantity in Prediction Area

[0123] 1. Estimation Results of Resource Quantity in Minimum Prediction Area

[0124] Using the ore-bearing geological body volume method, the estimation results of resource quantity in each minimum prediction area are shown in Table 8 - 13.

[0125]

[0126]

[0127] 2. Statistical Results of Predicted Resource Quantities in the Prediction Work Area

[0128] Using the ore-bearing geological volume method, the total amount of resources in the prediction work area is estimated as follows: Pb: 714,000 tons, Zn: 2,111,900 tons. Among them, the identified resources (inferred resources and above) are Pb: 106,700 tons, Zn: 389,800 tons. The predicted resources are Pb: 607,300 tons, Zn: 1,722,100 tons. (Note: The total amount of resources in this section = identified resources + predicted resources)

[0129] (1) Statistics by the smallest prediction area

[0130] The estimated total amount of resources in the Laodongzhai smallest prediction area is Pb: 266,500 tons, Zn: 760,700 tons. Among them, the identified resources (inferred resources and above) are Pb: 96,700 tons, Zn: 276,000 tons. The predicted resources are Pb: 169,800 tons, Zn: 484,700 tons.

[0131] The estimated total amount of resources in the Wuzuo smallest prediction area is Pb: 12,400 tons, Zn: 69,500 tons. Among them, the identified resources (inferred resources and above) are Pb: 1,600 tons, Zn: 8,800 tons. The predicted resources are Pb: 10,800 tons, Zn: 60,700 tons.

[0132] The estimated total amount of resources in the Xinhua smallest prediction area is Pb: 5,600 tons, Zn: 31,600 tons. Among them, the identified resources (inferred resources and above) are Zn: 17,500 tons. The predicted resources are Pb: 5,600 tons, Zn: 14,100 tons.

[0133] The estimated total amount of resources in the Jiaogaopo smallest prediction area is Pb: 8,800 tons, Zn: 49,100 tons. Among them, the identified resources (inferred resources and above) are Pb: 2,800 tons, Zn: 27,000 tons. The predicted resources are Pb: 6,000 tons, Zn: 22,100 tons.

[0134] The estimated total amount of resources in the Wutan smallest prediction area is Pb: 212,800 tons, Zn: 607,500 tons. Among them, the identified resources (inferred resources and above) are Pb: 5,600 tons, Zn: 60,500 tons. The predicted resources are Pb: 207,200 tons, Zn: 547,000 tons.

[0135] The estimated total resources in the minimum predicted area of ​​the inversion are Pb: 122,800 tons, Zn: 350,600 tons. Among them, the identified resources (inferred resources and above) are Pb: 0 tons, Zn: 0 tons. The predicted resources are Pb: 122,800 tons, Zn: 350,600 tons.

[0136] The estimated total resources in the minimum prediction area of ​​Nangao are Pb: 85,100 tons, Zn: 242,900 tons. Among them, the identified resources (inferred resources and above) are Pb: 0 tons, Zn: 0 tons. The predicted resources are Pb: 85,100 tons, Zn: 242,900 tons.

[0137] (2) Statistics by minimum prediction area level

[0138] According to whether the prediction basis is sufficient, the matching degree with the prediction elements of the model area, the size of the predicted resources, the burial depth of the ore body, etc., the minimum prediction area is divided into three categories: A, B, and C. The resource amounts of each category are as follows:

[0139] There is one minimum prediction area of ​​Class A, which is the minimum prediction area of ​​Laodongzhai. The total estimated resources are Pb: 266,500 tons, Zn: 760,700 tons. Among them, the identified resources (inferred resources and above) are Pb: 96,700 tons, Zn: 276,000 tons. The predicted resources are Pb: 169,800 tons, Zn: 484,700 tons.

[0140] There are two Class B minimum prediction areas, Wutan minimum prediction area and Wuzuo minimum prediction area. The estimated total resources are Pb: 225,200 tons, Zn: 677,000 tons. Among them, the identified resources (inferred resources and above) are Pb: 7,200 tons, Zn: 69,300 tons. The predicted resources are Pb: 218,000 tons, Zn: 607,700 tons.

[0141] There are 4 Class C minimum prediction areas, namely Nangao minimum prediction area, Fanyang minimum prediction area, Jiaogao minimum prediction area, and Xinhua minimum prediction area. The estimated total resources are Pb: 222,300 tons, Zn: 674,200 tons. Among them, the identified resources (inferred resources and above) are Pb: 2,800 tons, Zn: 44,500 tons. The predicted resources are Pb: 219,500 tons, Zn: 629,700 tons.

[0142] IV. Summary of evaluation results

[0143] A comprehensive geological evaluation is conducted on each minimum prediction area based on the overall geological information of the area, especially the geological characteristics, mineralization conditions, physical, chemical, and remote gravity information, and prospecting potential. The minimum prediction areas are now classified and evaluated according to A, B, and C levels.

[0144] 1. Class A minimum prediction area

[0145] Laodongzhai Minimum Prediction Area: Located in the southeast of the prediction work area, approximately at the southern plunging end of the Fang Anticline, on the northwest side of the Laodongzhai ore-controlling fault. In this area, there is the Laodongzhai lead-zinc deposit. The ore bodies are distributed in a stratiform shape in the strata at the bottom of the Doushantuo Formation, strictly controlled by the strata and faults. There are geochemical anomalies in the outer zones of lead, zinc, and cadmium, and a secondary placer anomaly of lead. The area of the prediction area is 16.16 km 2 , with a mineralization probability of 0.86. The predicted resource volume (confidence level ≥ 0.75) is Pb: 169,800 tons, Zn: 484,700 tons. The identified Pb is 96,700 tons, and Zn is 276,000 tons.

[0146] The mineralization conditions in this minimum prediction area are relatively favorable, with great resource potential and good prospecting potential, and it is expected to obtain a large-scale lead-zinc deposit.

[0147] 2. Class B Minimum Prediction Areas

[0148] (1) Wuzuo Minimum Prediction Area: Located in the central-northern part of the prediction work area, between the Mandong Fault and the Laodongzhai Fault. There are a series of ore-bearing faults trending nearly north-south and northwest-southeast. In this area, there are the Wuzuo lead-zinc deposit, Sifangshan lead-zinc mine, Wuzhong lead-zinc mine, and Wulixiazhai lead-zinc mine. The ore bodies are distributed in a vein shape in the slightly metamorphosed rocks, controlled by the faults. There is a secondary placer anomaly of lead. The area of the prediction area is 8.95 km 2 , with a mineralization probability of 0.760382. The predicted resource volume (confidence level ≥ 0.75) is Pb: 10,800 tons, Zn: 60,700 tons. The identified resource volume of Pb is 1,600 tons, and Zn is 8,800 tons.

[0149] The mineralization conditions in this minimum prediction area are relatively favorable, with general resource potential and certain prospecting potential.

[0150] (2) Wutan Minimum Prediction Area: Located in the Wutan area in the south of the prediction work area. There are nearly north-south ore-bearing faults. In this area, there is the Wutan lead-zinc deposit. The ore bodies are distributed in a stratiform shape in the strata at the bottom of the Doushantuo Formation, strictly controlled by the strata and faults. There is a secondary placer anomaly of lead. The area of the prediction area is 14.82 km 2 , with a mineralization probability of 0.683615. The predicted resource volume (confidence level ≥ 0.75) is Pb: 207,200 tons, Zn: 547,000 tons. The identified Pb is 5,600 tons, and Zn is 60,500 tons.

[0151] The mineralization conditions in this minimum prediction area are relatively favorable, with great resource potential and good prospecting potential, and it is expected to obtain a large-scale lead-zinc deposit.

[0152] 2. Class C Minimum Prediction Areas

[0153] (1) Fanyang Minimum Prediction Area: Located in the Fanyang area in the central and western part of the prediction work area, between the Mandong Fault and the Laodongzhai Fault, there are a series of ore-bearing faults trending nearly north-south and northwest-southeast. There is the Fanyang lead-zinc ore deposit in the area, and the ore bodies are distributed in a stratiform shape in the bottom strata of the Doushantuo Formation, strictly controlled by the strata and faults; the predicted area is 12.51 km 2 , with a mineralization probability of 0.497399, and the predicted resources (confidence level 0.5 - 0.75) are Pb: 122,800 tons and Zn: 350,600 tons.

[0154] The mineralization conditions in this minimum prediction area are relatively favorable, with great resource potential and certain prospecting prospects, and it is expected to obtain a large lead-zinc deposit.

[0155] (2) Nangao Minimum Prediction Area: Located in the Nangao area in the northern part of the prediction work area, on the east side of the Mandong Fault, the ore bodies are distributed in a stratiform shape in the bottom strata of the Doushantuo Formation, strictly controlled by the strata and faults; the predicted area is 9.02 km 2 , with a mineralization probability of 0.483614, and the predicted resources (confidence level 0.5 - 0.75) are Pb: 85,100 tons and Zn: 242,900 tons, and it is expected to obtain a large lead-zinc deposit.

[0156] The mineralization conditions in this minimum prediction area are relatively favorable, with great resource potential and certain prospecting prospects.

[0157] (3) Xinhua Minimum Prediction Area: Located in the north-central part of the prediction work area, between the Mandong Fault and the Laodongzhai Fault, there are a series of ore-bearing faults trending nearly north-south and northwest-southeast. There are the Xinhua lead-zinc deposit, the Kongtiao phosphorite lead-zinc deposit in Danzhai County, and the Yangpai lead-zinc deposit in the area. The ore bodies are distributed in a vein shape in the slightly metamorphosed rocks and are controlled by faults; there is a secondary placer anomaly of lead; the predicted area is 10.13 km 2 , with a mineralization probability of 0.658139, and the predicted resources (confidence level ≥ 0.75) are Pb: 10,800 tons and Zn: 60,700 tons, and the identified resources of Zn are 17,500 tons.

[0158] The mineralization conditions in this minimum prediction area are relatively favorable, with general resource potential and good prospecting prospects.

[0159] (4) Jiaogao Minimum Prediction Area: Located in the Jiaogao area in the northern part of the prediction work area, between the Mandong Fault and the Laodongzhai Fault, there are NE-trending ore-bearing faults. There are the Jiaogaopo lead-zinc deposit, the Jiaogaopozhaijiao lead-zinc deposit, and the Paizhai lead-zinc deposit in the area. The ore bodies are distributed in a vein shape in the slightly metamorphosed rocks and are controlled by the fault fracture zone; there are geochemical anomalies in the outer zones of lead and zinc, a primary placer anomaly of lead, and the northwest side of the inferred NNE-trending fault by the Bouguer gravity anomaly; the predicted area is 6.06 km 2, metallogenic probability is 0.710114, predicted resource amount (confidence level ≥ 0.75): Pb: 0.60 ten thousand tons, Zn: 2.21 ten thousand tons; identified resource amount: Pb: 0.28 ten thousand tons, Zn: 2.70 ten thousand tons.

[0160] The metallogenic conditions of this minimum prediction area are relatively favorable, with general resource potential and certain prospecting prospects.

[0161] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for predicting lead-zinc deposits based on the method of delineating the minimum prediction area. The first step is to determine the prediction elements: based on the collection of existing geological and mineral data, this prediction is combined with the ore-controlling conditions and metallogenic laws of typical deposits in the area to make a relatively rough positioning prediction. When studying the metallogenic laws, the prediction elements are repeatedly studied and compared, and the metallogenic structures include regional ore-controlling faults, ore-bearing faults, ore-bearing faults, ore-bearing structures including gray-gray-black silty carbonaceous argillaceous slate intercalated with dolomite carbonaceous calcareous slate and lenticular dolomite limestone, dolomite <the first section of Doushantuo Formation>, metamorphic residual sandstone, silty slate, sericite slate, tuffaceous slate <Qingbaikou System>, known lead-zinc deposits, points including ore point density and proven resources, geochemical anomalies Pb, Zn, and heavy sand anomalies Pb. Five types of prediction elements are selected; Step 2: Delineate the boundary of the prediction area. The boundary of the prediction area in this area is delineated by the positioning prediction element superposition method, that is, all necessary positioning prediction elements are superimposed, and the boundary of the overlapping part is the approximate boundary of the prediction area. According to the above principles, a total of 7 minimum prediction areas are delineated in the area, from north to south, they are Nangao Minimum Prediction Area, Jiaogao Minimum Prediction Area, Xinhua Minimum Prediction Area, Wuzuo Minimum Prediction Area, Fanyang Minimum Prediction Area, Laodongzhai Minimum Prediction Area, and Wutan Minimum Prediction Area; The third step is the classification of the minimum prediction area and calculation of the mineralization probability: Ⅰ. Calculation of mineralization probability in the minimum prediction area a. Method of assigning values ​​to prediction factors According to the metallogenic law in the area and the importance of its influence on the mineralization, the metallogenic structures including regional ore-controlling faults, the scale of ore-bearing faults, ore-bearing structures, ore-bearing structures including gray-gray-black silty carbonaceous argillaceous slate intercalated with dolomite carbonaceous calcareous slate and lenticular dolomite limestone, dolomite <the first section of Doushantuo Formation>, metamorphic residual sandstone, silty slate, sericite slate, tuffaceous slate <Qingbaikou System>, known lead-zinc deposits, points including ore point density and proven resources, geochemical anomalies Pb, Zn, and heavy sand anomaly Pb prediction elements are assigned values ​​according to weights; b. Calculation of the minimum prediction area mineralization probability According to the value assignment of each prediction factor, the metallogenic probability of each minimum prediction area is scored. The total score ≥ 0.8 points is "Class A minimum prediction area"; the total score 0.7 ≤ n < 0.8 points is "Class B minimum prediction area"; the total score 0.6 ≤ n < 0.7 points is "Class C minimum prediction area"; 2. Classification of minimum prediction areas. According to the classification requirements of the minimum prediction area and combined with the overall metallogenic probability of the prediction area, 7 prediction areas are classified, including 1 Class A, 2 Class B, and 4 Class C; Step 4: Quantitative prediction of resources. This time, geological volume parameters are used for quantitative estimation of resources. The lead-zinc ore in this prediction area is non-magmatic hydrothermal type, and the ore body is layered, vein-like, and lens-like. The formula for calculating resources by geological volume method is as follows: Zpred = ((Spred × Hpred × K × α) / COS (β)) - Zcheck Prediction parameter description: Z prediction: predicted resource volume in the prediction area; Z investigation: confirmed resource reserves; S prediction: Minimum predicted area; Hpred: true thickness of ore-bearing structure (geological body); K: ore-bearing coefficient of model area; α: similarity coefficient; β: inclination of ore-bearing geological body.

2. The method for predicting lead-zinc deposits based on the minimum prediction area delineation method according to claim 1, characterized in that: The lead-zinc mineralization structure in the area is controlled by the northeast, nearly north-south faults and secondary folds and other mineralization structures. All lead-zinc mineral points and beds are distributed near the regional mineralization-controlling structures. The existence or non-existence of northeast, nearly north-south faults and secondary wrinkles is one of the necessary conditions for the existence of this type of deposits. Ore-bearing faults and fault intersections are one of the important elements of mineralization. Northeast and nearly north-south regional mineralization-controlling faults: Through comprehensive analysis of the existing mining area data, 0-5.0km from the fault is favorable for mineralization, and 5.0-7.25km is less favorable for mineralization.

3. The method for predicting lead-zinc deposits based on the minimum prediction area delineation method according to claim 1, characterized in that: The ore-bearing structure, the non-magmatic hydrothermal lead-zinc ore in the area is produced in the Qingshuijiang Formation, Pinglue Formation and Longli Formation of the Qingbaikou System; the first section of the Doushantuo Formation of the Sinian System, the ore-bearing structure is gray-gray-black silty carbonaceous mudstone interbedded with dolomite carbonaceous calcareous slate and lenticular dolomite limestone, dolomite the first section of the Doushantuo Formation of the Sinian System, residual sandstone, silty slate, sericite slate, tuffaceous slate Qingbaikou System, the above two kinds of ore-bearing structures are one of the indispensable elements of the prediction area, according to the exposure of the ore-bearing structures, the occurrence of the strata, etc., several short sections are used to infer the horizontal projection of the concealed part of each set of ore-bearing structures at a burial depth of 1000m; finally, the horizontal projection of the exposed part of the ore-bearing structure and the concealed part at its burial depth is used as one of the bases for delineating the prediction area.

4. The method for predicting lead-zinc deposits based on the minimum prediction area delineation method according to claim 1, characterized in that: The mineralized fault: According to statistics based on the impact range of the mineralized fault, a distance of 0.5 km from the fault is favorable for mineralization.

5. The method for predicting lead-zinc deposits based on the method of delineating the minimum prediction area according to claim 1 is characterized in that: The ore-bearing fault: The secondary faults beside the regional fault are often ore-bearing faults, and the interlayer sliding fault at the bottom of the first section of the Doushantuo Formation provides a better ore-bearing space.

6. The method for predicting lead-zinc deposits based on the minimum prediction area delineation method according to claim 1, characterized in that: In addition to the proven resource reserves, most of the known lead-zinc deposits have further prospecting potential in their surroundings and deep areas. The distribution, quantity and proven resource reserves of known lead-zinc deposits and points are the basis of prediction work. The known lead-zinc deposits, points and proven resource reserves are important prediction elements and serve as the basis for delineating the prediction area.

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