Method for determining favorable area of sandstone type rhenium ore

Abstract

The invention relates to the technical field of new energy, and provides a sandstone type rhenium ore favorable area determination method comprising the following steps: S1, obtaining distribution data and content data of uranium ore and rhenium ore, and establishing a rhenium ore distribution range model based on the distribution data and the content data; s2, dividing layers, and determining a main exploration target layer; s3, samples are collected in the target layer and tested and analyzed to determine the distribution range and content of uranium ore and the content of rhenium ore; and S4, delineating a rhenium ore favorable area based on the distribution range and content of the uranium ore, the content of the rhenium ore and the rhenium ore distribution range model. According to the method, the rhenium ore exploration cost can be effectively reduced, the success rate is increased, and the method has high application value.

Description

Technical Field

[0001] The present invention relates to the field of new energy technology, and more specifically to a method for determining a favorable area of ​​sandstone-type rhenium ore. Background Art

[0002] New energy (NE), also known as unconventional energy, refers to various forms of energy other than traditional energy. It refers to energy that has just begun to be developed or is being actively researched and is yet to be promoted, such as solar energy, geothermal energy, wind energy, ocean energy, biomass energy and nuclear fusion energy. Among them, key minerals are important materials that support the development of strategic emerging industries such as new energy, and are the source of power for high-quality development. Rhenium (Re), known as the "metal of the future", is widely used in high temperature, high stress and radioactive environments due to its high melting point, high strength, corrosion resistance and wear resistance. For example, it is used in the production and manufacturing of high-temperature alloy parts such as engine turbine blades and high-efficiency jet engine afterburner nozzles in the aerospace industry, high-octane gasoline catalysts in the petrochemical industry, thermocouples in chemical synthesis, and radiation nuclide imaging gamma cameras in medical equipment. At present, my country's rhenium mines are mainly distributed in Shaanxi, Heilongjiang, Liaoning and other places.

[0003] In recent years, my country has conducted research on the characteristics and mining of rhenium ore. Among them, Qin Mingkuan and other scholars studied the geochemical characteristics of rhenium in the 512 uranium deposit in the Ili Basin in the article "Geochemistry of Re in the 512 Uranium Deposit and Its Research Significance" published in "Uranium Geology" in 1997, and pointed out that Re in this uranium deposit has reached the index of comprehensive utilization of in-situ leaching mining, and suggested strengthening the research on its in-situ leaching process; Wang Zhengqi and other scholars published an article in "Geological Review" in 2006 entitled "Discussion on the Extraordinary Enrichment Mechanism of Dispersed Elements Rhenium and Selenium in the Interlayer Oxidation Zone - Taking the Zaghistan Interlayer Oxidation Zone Sandstone-type Uranium Deposit in the Ili Basin as an example" and explained the extraordinary enrichment law of dispersed elements Re and Se in it; Zeng Aihua and other scholars took the No. 7 mining area of ​​the 511 deposit as an example in the article "Distribution Characteristics of U-Se-Re-Mo and Other Elements in the No. 7 Mining Area of ​​the 511 Deposit in Xinjiang" published in "Mineral Deposits" in 2012, taking the No. 7 mining area of ​​the 511 deposit as an example, and conducted field geological surveys and indoor analysis A technical route combining testing and comprehensive research is adopted to explore the distribution characteristics of elements such as Re, Se, and Mo and their relationship with the enrichment of U. In the article "Geochemical Behavior of Rhenium in Interlayer Oxidation Zone Sandstone-type Uranium Deposits and Its Prospecting Significance" published in Uranium Geology in 2004, Tan Chenglong and other scholars made a discussion on the prospecting significance of rhenium in interlayer oxidation zone sandstone-type uranium deposits at present, based on the basic fact that rhenium and uranium increase and decrease together in interlayer oxidation zone sandstone-type uranium deposits verified in nature. The significance of the study was questioned; Wang Yanli conducted relevant research on the occurrence form, determination and leaching of trace rhenium in sandstone-type uranium deposits in her master's thesis in 2017; Chen Zhenyan and other scholars published an article entitled "Geochemical Characteristics and Mineralization of Rhenium in the Qianjiadian Uranium Mining Area, Kailu Basin" in the "Journal of Sedimentary Science" in 2022. Through the study of the geochemical characteristics of the dispersed element rhenium in the Qianjiadian uranium deposit in the Kailu Basin, and combined with the previous achievements, the mineralization of rhenium associated with uranium in the study area was discussed.

[0004] The above methods discussed the geochemical characteristics and significance of rhenium in sandstone-type uranium deposits, including the spatial distribution characteristics of rhenium ores, the occurrence forms of sandstone-type rhenium ores, the correlation and spatial position relationship between uranium and rhenium ores, and the enrichment mechanism of uranium and rhenium. It also introduced the controlling factors of rhenium mineralization, preliminarily studied the distribution law of rhenium in sandstone-type uranium deposits, and discussed its enrichment mechanism, but no specific exploration suggestions were put forward. The exploration of rhenium ores still requires the deployment of a large number of drill holes, the prospecting method is single, and the exploration cost is high.

[0005] Therefore, considering the close connection between sandstone-type rhenium ore and uranium mineralization mechanism, it is necessary to explore a set of effective prospecting methods based on the correlation between uranium and rhenium. Summary of the invention

[0006] The purpose of the present invention is to provide a method for determining favorable areas of sandstone-type rhenium ore by applying logging data analysis, sedimentary phase analysis and comprehensive geochemical research, so as to effectively reduce the cost of rhenium ore exploration, improve the success rate, and have high application value.

[0007] According to the present invention, a method for determining a favorable area of ​​sandstone-type rhenium ore is provided, comprising the following steps: S1, obtaining distribution data and content data of uranium ore and rhenium ore, and establishing a rhenium ore distribution range model based on the distribution data and the content data; S2, dividing the horizons to determine the target layer for main exploration; S3, collecting samples in the target layer and conducting tests and analyses to determine the distribution range and content of uranium ore and the content of rhenium ore; S4, delineating a favorable area of ​​rhenium ore based on the distribution range and content of uranium ore, the content of rhenium ore and the rhenium ore distribution range model.

[0008] According to one embodiment of the present invention, step S1 includes: S11, designing a well network density for a specific area and opening multiple mines; S12, acquiring distribution data and content data of uranium and rhenium ores in multiple different blocks; S13, establishing a rhenium ore distribution range model based on the distribution data and the content data.

[0009] According to an embodiment of the present invention, step S11 includes: using existing uranium mines in a uranium-rich area in a specific region as mines for obtaining distribution data and content data of uranium and rhenium ores.

[0010] According to one embodiment of the present invention, step S1 includes: defining the distribution range of uranium ore and rhenium ore in an elliptical shape, and the distribution range model of rhenium ore is:

[0011] W=a×w 2 +b×w+c

[0012] L=d×ln(l)+e

[0013] in,

[0014] w represents the distance in the minor axis direction of the uranium ore, m;

[0015] l represents the distance in the direction of the long axis of the uranium ore, m;

[0016] W represents the distance in the minor axis direction of rhenium ore, m;

[0017] L represents the distance in the long axis direction of rhenium ore, m;

[0018] a, b, c, d, e represent constants.

[0019] According to an embodiment of the present invention, step S1 includes: determining content correlation based on content data of uranium ore and rhenium ore, and establishing a distribution range model of the rhenium ore based on the content correlation and the distribution data.

[0020] According to one embodiment of the present invention, SPSS software is used to perform correlation analysis on the content data of uranium ore and rhenium ore to determine the content correlation.

[0021] According to one embodiment of the present invention, based on the distribution data and content data of uranium and rhenium ores in the Qianjiadian area of ​​the Kailu Basin, the rhenium ore distribution range model is established as follows:

[0022] When 0<r≤0.5,

[0023] W=24.6w 2 -102.12w+53.6

[0024] L = 35.6ln(l) + 411.6

[0025] When 0.5<r≤1,

[0026] W=38.2w 2 -153.4w+258

[0027] L = 68.5ln(l) + 115.64

[0028] in,

[0029] r represents the correlation coefficient;

[0030] w represents the distance in the minor axis direction of the uranium ore, m;

[0031] l represents the distance in the direction of the long axis of the uranium ore, m;

[0032] W represents the distance in the minor axis direction of rhenium ore, m;

[0033] L represents the distance in the long axis direction of the rhenium ore, m.

[0034] According to an embodiment of the present invention, step S2 includes: S21, determining a layer division standard; and S22, determining a top interface and a bottom interface of the target layer.

[0035] According to an embodiment of the present invention, in step S21, a stable waterproof layer is determined as a basic classification criterion.

[0036] According to an embodiment of the present invention, in step S22, the mudstone at the top of the sedimentary cycle is used as the top interface of the target layer when performing stratigraphic correlation.

[0037] According to an embodiment of the present invention, in step S22, the middle of the top mudstone of the early sedimentary cycle connecting with the bottom sandstone of the sedimentary cycle is used as the bottom interface of the target layer.

[0038] According to an embodiment of the present invention, in step S22, the thickness of the target layer does not exceed 30 mm.

[0039] According to one embodiment of the present invention, step S3 includes: S31, collecting samples; S32, testing the samples to determine the reducing agent information in the sandstone of the target layer; S33, determining the spatial configuration relationship between the external reducing medium of the uranium reservoir and the uranium ore based on the reducing agent information to determine the distribution range of the uranium ore.

[0040] According to one embodiment of the present invention, in step S31, based on the development of interlayer oxidation zones and the dual directions of exploration lines, sampling drill holes are arranged in the target layer.

[0041] According to one embodiment of the present invention, in step S31, samples are taken from both the mineralized section and the non-mineralized section of the same borehole.

[0042] According to an embodiment of the present invention, in step S31, key areas are determined based on the associated element information for supplementary sampling.

[0043] According to an embodiment of the present invention, in step S31, sampling is performed preferentially on boreholes constructed this year.

[0044] According to an embodiment of the present invention, in step S32, the reducing agent information includes at least one of TOC content, S total content, and ω(Fe2O3) / ω(FeO).

[0045] According to an embodiment of the present invention, in step S33, a contour map of uranium ore in the target layer is drawn for each type of reducing agent information; the mineralization conditions are evaluated with reference to the quantitative evaluation standard of uranium reservoir physical properties, the favorable mineralization position of a single well is determined, and the spatial distribution superposition map of each type of reducing agent information and sandstone-type uranium ore is determined; based on the superposition maps of multiple reducing agent information and sandstone-type uranium ore spatial distribution, a distribution range map of uranium ore in the target layer is obtained.

[0046] According to one embodiment of the present invention, step S4 includes: S41, determining the target layer content correlation based on the uranium ore and rhenium ore contents of the target layer; S42, delineating the rhenium ore favorable area based on the uranium ore distribution range, the target layer content correlation and the rhenium ore distribution range model.

[0047] Due to the adoption of the above technical scheme, the present invention, at least on the premise of dividing the horizon, samples and analyzes the uranium and rhenium contents of the uranium mine section, performs correlation analysis on the rhenium and uranium element contents, and then draws a map of favorable areas for superimposed mineralization of uranium, TOC, S and ω (Fe2O3) / ω (FeO), combines comprehensive research such as sedimentary phases and structural relationships, and on this basis determines the favorable area for rhenium, delineates the distribution range of favorable rhenium mineralization positions on the plane, realizes efficient rhenium exploration deployment, and saves drilling costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The accompanying drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. Together with the following specific embodiments, they are used to explain the present disclosure but do not constitute a limitation of the present disclosure. In the accompanying drawings:

[0049] Figure 1 is a flow chart of a method for determining a favorable area for sandstone-type rhenium ore according to the present invention;

[0050] Figure 2 It is a superimposed diagram of the TOC content and the spatial distribution of sandstone-type uranium deposits according to the present invention;

[0051] Figure 3 It is a superimposed diagram of the total S content and the spatial distribution of sandstone-type uranium deposits according to the present invention;

[0052] Figure 4 It is a superimposed diagram of the spatial distribution of ω(Fe2O3) / ω(FeO) content and sandstone-type uranium ore according to the present invention;

[0053] Figure 5 is a distribution range map of uranium ore in the target layer according to the present invention;

[0054] Figure 6 is a graph showing a correlation between Re and U content of a ore deposit according to an embodiment of the present invention;

[0055] Figure 7 is a distribution diagram of Re and U content of a first target layer according to an embodiment of the present invention;

[0056] Figure 8 is a distribution diagram of Re and U content of a second target layer according to an embodiment of the present invention;

[0057] Fig. 9 is a distribution map of favorable areas of rhenium ore according to an embodiment of the present invention. DETAILED DESCRIPTION

[0058] The specific implementation of the present disclosure is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the present disclosure, and is not used to limit the present disclosure.

[0059] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0060] Figure 1A flow chart showing a method for determining a favorable area for sandstone-type rhenium ore according to the present invention is shown, which generally comprises the following steps:

[0061] Step S1, obtaining distribution data and content data of uranium ore and rhenium ore, and establishing a rhenium ore distribution range model based on the distribution data and content data;

[0062] Step S2, dividing the layers and determining the target layers for main exploration;

[0063] Step S3, collecting samples from the target layer and conducting tests and analyses to determine the distribution range and content of uranium ore and the content of rhenium ore;

[0064] Step S4, based on the distribution range and content of uranium ore, the content of rhenium ore and the rhenium ore distribution range model, delineate the favorable area of ​​rhenium ore.

[0065] In an embodiment of the present invention, step S1 includes: S11, designing a well network density for a specific area and opening multiple mines; S12, obtaining distribution data and content data of uranium and rhenium ores in multiple different blocks; S13, establishing a rhenium distribution range model based on the distribution data and content data. In actual operation, it is preferred to use existing uranium mines in uranium-rich areas in a specific area as mines for obtaining distribution data and content data of uranium and rhenium ores.

[0066] The distribution range of uranium ore and rhenium ore are mostly elliptical. Therefore, it is preferred to define the distribution range of uranium ore and rhenium ore in an elliptical shape. In an embodiment of the present invention, the distribution range model of rhenium ore is:

[0067] W=a×w 2 +b×w+c

[0068] L=d×ln(l)+e

[0069] in,

[0070] w represents the distance in the minor axis direction of the uranium ore, m;

[0071] l represents the distance in the direction of the long axis of the uranium ore, m;

[0072] W represents the distance in the minor axis direction of rhenium ore, m;

[0073] L represents the distance in the long axis direction of rhenium ore, m;

[0074] a, b, c, d, e represent constants.

[0075] Based on the content data of uranium and rhenium, the content correlation can be determined. According to the uranium and rhenium content data of different blocks, scatter point analysis is performed to obtain the correlation, and it is found that the size value has a certain relationship with the distribution range of uranium and rhenium. In the embodiment of the present invention, it is preferred to establish a rhenium distribution range model based on the content correlation and distribution data. Correlation analysis is a commonly used method in statistics, which is mainly used to measure the degree of correlation between two or more categories of things. It calculates the distance between two related variables and converts them into a linear relationship to analyze the degree of correlation between two or more variables. In an embodiment of the present invention, SPSS software can be used to perform correlation analysis on rhenium and uranium, and the Pearson simple correlation coefficient is obtained to determine the correlation. SPSS is a general term for a series of software products and related services launched by IBM for statistical analysis operations, data mining, predictive analysis and decision support tasks. The software has the advantages of fast speed and accurate analysis in statistical analysis. The correlation can be described by the correlation coefficient r. In the correlation analysis, the present invention uses the Pearson simple correlation coefficient to represent the linear relationship between variables. Among them, the Pearson simple correlation coefficient formula is:

[0076]

[0077] The larger the absolute value of the correlation coefficient, the stronger the correlation: the closer the correlation coefficient is to 1, the stronger the correlation is; the closer the correlation coefficient is to 0, the weaker the correlation is. The correlation strength of the variables can be judged by observing the Pearson simple correlation coefficient in a certain range of values: a correlation coefficient of 0.8 to 1.0 indicates a very strong correlation; 0.6 to 0.8 indicates a strong correlation; 0.4 to 0.6 indicates a moderate correlation; 0.2 to 0.4 indicates a weak correlation; and 0.0 to 0.2 indicates a very weak correlation or no correlation.

[0078] The embodiment of the present invention defines the distribution range of uranium and rhenium ores in an elliptical shape. The distribution range of uranium ores in the known study area is combined with the fitting relationship between the major and minor axes of uranium and rhenium ores to delineate the distribution range of rhenium ores. Sandstone-type rhenium ores are mainly developed in braided river channels or braided river delta plain sand bodies, where Re and U have similar geochemical characteristics during the oxidation-reduction process, the output locations of Re ores and uranium ores basically overlap, Re mineralization and uranium mineralization are roughly synchronized, and the distribution of rhenium ore bodies and uranium ore bodies are both in the shape of long pancakes. Most of the rhenium ore bodies are coupled with the uranium ore bodies on the plane, and a small number of wells contain rhenium but not uranium, or contain uranium but not rhenium. In general, the distribution range of rhenium ore bodies is wider than that of uranium ore bodies. The distribution of rhenium enrichment areas is highly coupled with that of uranium enrichment areas. The uranium ore bodies are distributed in a north-south direction, and the rhenium enrichment areas also extend from south to north. However, the distribution areas of the enrichment centers of the two are slightly different. Compared with the uranium ore bodies, some enrichment centers of the rhenium ore bodies are slightly offset to the side of the reduction zone, suggesting that some rhenium was precipitated later than uranium. From the perspective of the entire mining area, statistics of existing drilling data show that uranium mineralization does overlap with most areas of rhenium mineralization, and in a few cases, rhenium mineralization slightly exceeds the range of uranium mineralization. This invention also established for the first time a rhenium ore distribution range model that reflects the corresponding relationship between the planar distribution ranges of uranium and rhenium in interlayer oxidation zone sandstone-type deposits.

[0079] In the embodiment of the present invention, for the five uranium-rich areas in Qianjiadian area, the well network density reached 100m*200m, the number of uranium wells totaled more than 700, and the Yaojia Formation target layer was sampled more than 1,000 times, 825 pieces of uranium analysis test data, and more than 430 pieces of rhenium analysis test data. According to the uranium and rhenium content data of different blocks, scatter point analysis was performed to obtain the correlation, and the correlation r was divided into two intervals of 0<r≤0.5 and 0.5<r≤1, and the relationship between the long axis and the short axis in the distribution range of uranium and rhenium was explored, and the mathematical curve was fitted to establish the following uranium-rhenium ore distribution range model:

[0080] When 0<r≤0.5,

[0081] W=24.6w 2 -102.12w+53.6

[0082] L = 35.6ln(l) + 411.6

[0083] When 0.5<r≤1,

[0084] W=38.2w 2 -153.4w+258

[0085] L = 68.5ln(l) + 115.64

[0086] in,

[0087] r represents the correlation coefficient;

[0088] w represents the distance in the minor axis direction of the uranium ore, m;

[0089] l represents the distance in the direction of the long axis of the uranium ore, m;

[0090] W represents the distance in the minor axis direction of rhenium ore, m;

[0091] L represents the distance in the long axis direction of the rhenium ore, m.

[0092] In an embodiment of the present invention, step S2 includes: S21, determining the stratigraphic division standard; and S22, determining the top interface and the bottom interface of the target layer. Specifically, sandstone-type rhenium ores are usually found in braided river or braided river delta sand bodies, with one or more sedimentary cycles as a mineralization unit (target layer). Among them, a sedimentary cycle refers to a sequence composed of sedimentation and sedimentary conditions that are repeatedly deposited in the same order. Therefore, when dividing the stratigraphic units, the basic division standard is to have a set of stable impermeable layers. When performing stratigraphic comparison, it is preferred to use the mudstone at the top of the sedimentary cycle as the top boundary; the middle of the mudstone at the top of the early sedimentary cycle that is connected to the sandstone at the bottom of the sedimentary cycle can be used as the bottom boundary of the target layer.

[0093] In an embodiment of the present invention, step S3 may include: S31, collecting samples; S32, testing the samples to determine the reducing agent information in the sandstone of the target layer; S33, determining the spatial configuration relationship between the external reducing medium of the uranium reservoir and the uranium ore based on the reducing agent information to determine the distribution range of the uranium ore; S34, determining the correlation based on the content of uranium ore and rhenium ore in the target layer.

[0094] Since the boreholes involved in the sampling work were completed in different years, the alternative exploration line profiles were checked one by one on site and in the core library to check whether the cores were well preserved and whether there were enough cores in the planned sampling section, etc., and finally determine the borehole profile that meets the research requirements. The collection of borehole core samples is based on the development of the interlayer oxidation zone and the dual direction of the exploration line. The samples collected systematically must also be in the same layer. Field sampling tries to take into account the representativeness of the samples. The basic principles of sampling are: for the same borehole, focus on sampling the mineralized section and also consider sampling the non-mineralized section; on the plane, select key areas for additional sampling based on the associated element data that have been mastered; in addition, the boreholes constructed this year are given priority.

[0095] The samples can be tested and analyzed using conventional methods in the field. Specifically, uranium is measured according to "Analysis Method of Uranium in Uranium Ore" EJ / T267.3-1984 and "Determination of Uranium in Soil, Rock and Other Samples by Laser Fluorescence Method" EJ / T550-2000. The samples are decomposed by nitric acid, hydrofluoric acid and perchloric acid and then measured on a MUA laser fluorescence instrument manufactured by Beijing Institute of Geology of Nuclear Industry. The high-content samples are screened out and melted with sodium oxide and then titrated with ammonium vanadate standard solution for analysis. Ferrous oxide is measured according to "Chemical Analysis Methods for Silicate Rocks Part 14: Measurement of Ferrous Oxide" According to GB / T14506.14-2010, the sample is decomposed by hydrofluoric acid and sulfuric acid, and then titrated with potassium dichromate standard solution using sodium dimethylbenzene sulfonate as an indicator; the total iron is determined according to DZG20.01-2011 (84.2.5) of Rock and Mineral Analysis by Inductively Coupled Plasma Spectrometry for Determination of 27 Major, Minor and Trace Elements; the sample is decomposed by hydrofluoric acid, nitric acid and perchloric acid, and the perchloric acid is driven out, the volume is fixed, and the mixture is shaken, and the total iron is determined by ICPS-7510 plasma emission spectrometry manufactured by Shimadzu, Japan; the result of trivalent iron is obtained by subtracting divalent iron from the total iron. The total sulfur is determined according to DZG20.01-2011 (21.22.3) of Rock and Mineral Analysis by Aqua Regia Decomposition-Inductively Coupled Plasma Emission Spectrometry for Determination of 11 Elements in Sulfide Ores; the sample is decomposed by aqua regia and then determined by ICPS-7510 plasma emission spectrometry manufactured by Shimadzu, Japan. Re was determined on an XSERIESⅡ ICP-MS manufactured by ThermoFisher in the United States after the samples were dissolved in hydrofluoric acid and nitric acid according to “Chemical Analysis Methods for Silicate Rocks Part 30: Determination of 44 Elements” GB / T14506.30-2010.

[0096] In the interlayer oxidation zone sandstone deposit, the reductant of the reservoir restricts the mineralization of uranium and rhenium. Therefore, the reductant information in the sandstone is first determined to study the spatial configuration relationship between the external reducing medium of the uranium reservoir and the uranium mineralization, and to explore in depth to achieve accurate prediction of uranium mineralization. Combined with the correlation between rhenium and uranium content, the favorable area of ​​rhenium is further delineated. In the embodiment of the present invention, step S33 may include: drawing a contour map of uranium ore in the target layer for each reductant information; referring to the quantitative evaluation standard of uranium reservoir physical properties, evaluating the mineralization conditions, determining the favorable mineralization position of a single well, and determining the spatial distribution superposition map of each reductant information and sandstone-type uranium ore; based on multiple reductant information and sandstone-type uranium ore spatial distribution superposition maps, obtain the distribution range map of uranium ore in the target layer. For example, taking the average organic carbon value of the same borehole sample as an indicator, the total organic carbon content (TOC content) of the work area is counted, and the contour map of the layer is drawn using software. With reference to the quantitative evaluation standards for uranium reservoir physical properties, the mineralization conditions are evaluated and the favorable mineralization locations of individual wells are determined.

[0097] The enrichment and precipitation of uranium in sandstone-type uranium deposits is closely related to reservoir heterogeneity. During the research process, the present invention statistically analyzed the correspondence between the target layer organic carbon index and mineralization, the S total index and mineralization, and the ω(Fe2O3) / ω(FeO) and mineralization of four typical uranium deposits with different mineralization levels. The results show that there is an obvious correspondence between a certain range of variation of each index and the mineralization in the transition zone. When the TOC index of the target layer is between 0.1% and 0.2%, the mineralization is the best; when the TOC index of the target layer is between 0.05% and 0.1% and 0.2% and 0.3%, the mineralization is good, but does not meet the industrial standard; when the TOC index of the target layer is lower than 0.05% and higher than 0.3%, the mineralization is poor; when the S total index of the target layer is greater than 0.2%, the mineralization is the best; when the S total index of the target layer is between 0.1% and 0.2%, The mineralization is good, but does not meet the industrial standard; when the S total index of the target layer is lower than 0.1%, the mineralization is poor; when the ω(Fe2O3) / ω(FeO) index of the target layer is lower than 3.0, the mineralization is the best; when the ω(Fe2O3) / ω(FeO) index of the target layer is between 3.0 and 4.0, the mineralization is good, but does not meet the industrial standard; when the ω(Fe2O3) / ω(FeO) index of the target layer is greater than 4.0, the mineralization is poor.

[0098] In an embodiment of the present invention, step S4 includes: S41, determining the content correlation of the target layer based on the contents of uranium and rhenium in the target layer; S42, delineating the favorable area of ​​rhenium based on the distribution range of uranium, the content correlation of the target layer and the distribution range model of rhenium. Specifically, the plane distribution range of uranium is regarded as an ellipse, the lengths of the major axis and minor axis of the distribution range of rhenium are calculated according to the distribution range model of rhenium, and an ellipse is delineated with the known well as the center as the approximate distribution range of rhenium.

[0099] The following is a description based on specific embodiments.

[0100] Example 1

[0101] This embodiment is aimed at the exploration of rhenium ore in a certain ore deposit in Qianjiadian.

[0102] Divide the layers

[0103] 1. Determine the scale of stratigraphic division: The rhenium ore bodies in this area are hosted in braided river delta sand bodies. The main exploration target layer is the Y1 cycle of the Yaojia Formation, with a thickness of no more than 30m;

[0104] 2. Determine the top and bottom interfaces of the target layer: In the application of the present invention, the middle part of the mudstone at the top of the sedimentary cycle is used as the top boundary of the mineralization unit, and the middle of the mudstone at the top of the early sedimentary cycle connected to the sandstone at the bottom of the sedimentary cycle is used as the bottom boundary of the mineralization unit.

[0105] Sample testing and analysis

[0106] Sampling: Samples were arranged in the dual directions of the interlayer oxidation zone development and exploration line. The systematically collected samples were guaranteed to be in the Y1 cycle of the Yaojia Formation. Drilling was given priority this year. The TOC content, total S content, ω(Fe2O3) / ω(FeO) content of the Y1 cycle and the spatial distribution superposition diagram of sandstone-type uranium deposits are shown in the figure below: Figure 2-4 shown. Figure 5 The distribution range of uranium ore in the target layer is shown.

[0107] The Y1 cycle uranium and rhenium contents were statistically analyzed, and the following linear relationship was obtained by fitting Re and U contents using SPSS software:

[0108] y=-835.36x 2 +2890.4x+595.31

[0109] in,

[0110] x represents the uranium content, 10 -6 ;

[0111] y represents the rhenium content, 10 -6 .

[0112] Based on the above formula, the correlation between Re and U content is determined. The correlation between rhenium and uranium in the Y1 cycle of the Yaojia Formation in the study area is 0.6.

[0113] Delineation of favorable rhenium mining areas

[0114] The correlation between rhenium and uranium in this area is 0.6. Combining the fitting relationship between the long axis and short axis of uranium and rhenium, the plane distribution range of rhenium is delineated.

[0115] When 0.5<r≤1,

[0116] W=38.2w 2 -153.4w+258

[0117] L = 68.5ln(l) + 115.64

[0118] Among them, w represents the distance in the direction of the short axis of the uranium ore, and l represents the distance in the direction of the long axis of the uranium ore; W represents the distance in the direction of the short axis of the rhenium ore, and L represents the distance in the direction of the long axis of the rhenium ore.

[0119] The length of the major axis of the rhenium ore plane distribution range is 1.35km, and the length of the minor axis is 0.9km.

[0120] Example 2

[0121] This example also explores rhenium ore in a certain deposit in Qianjiadian, and the main exploration target layer is the Y2 cycle of the Yaojia Formation, which is no more than 30m thick. The top and bottom interfaces of the target layer and the sample collection and analysis steps are similar to those in Example 1.

[0122] The uranium and rhenium contents of the Y2 cycle were statistically analyzed, and the following linear relationship was obtained by fitting the Re and U contents using SPSS software:

[0123] y=-0.058x 2 +0.271x+1.515

[0124] in,

[0125] x represents the uranium content, 10 -6 ;

[0126] y represents the rhenium content, 10 -6 .

[0127] Based on the above formula, the correlation between Re and U content is determined. The correlation between rhenium and uranium in the Y2 cycle of the Yaojia Formation in the study area is 0.3.

[0128] Delineation of favorable rhenium mining areas

[0129] The correlation between rhenium and uranium in this area is 0.3. Combining the fitting relationship between the long axis and short axis of uranium and rhenium, the plane distribution range of rhenium is delineated.

[0130] When 0.5<r≤1,

[0131] W=38.2w 2 -153.4w+258

[0132] L = 68.5ln(l) + 115.64

[0133] Among them, w represents the distance in the direction of the short axis of the uranium ore, and l represents the distance in the direction of the long axis of the uranium ore; W represents the distance in the direction of the short axis of the rhenium ore, and L represents the distance in the direction of the long axis of the rhenium ore.

[0134] The length of the major axis of the rhenium ore plane distribution range is 2.61km, and the length of the minor axis is 1.56km.

[0135] Fig. 9 The distribution of favorable areas of rhenium ore in a certain deposit in Qianjiadian is shown, which is obtained by integrating the test results of multiple target layers. The deposit deployed 8 exploration wells in the early stage of 2022, of which 6 wells obtained industrial rhenium ore display, with an industrial ore-seeking rate of 75%, which is much higher than the average level of the previous 5 years. It is estimated that the amount of rhenium ore resources has increased by more than 50t, and the application effect is very significant.

[0136] The preferred embodiments of the present disclosure are described in detail above in conjunction with the accompanying drawings; however, the present disclosure is not limited to the specific details in the above embodiments. Within the technical concept of the present disclosure, a variety of simple modifications can be made to the technical solution of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0137] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present disclosure will not further describe various possible combinations.

[0138] In addition, various embodiments of the present disclosure may be arbitrarily combined, and as long as they do not violate the concept of the present disclosure, they should also be regarded as the contents disclosed by the present disclosure.

Claims

1. A method for determining favorable areas of sandstone-type rhenium ore, characterized in that: The following steps are involved: S1, obtaining distribution data and content data of uranium ore and rhenium ore, and establishing a rhenium ore distribution range model based on the distribution data and the content data; S2, divide the layers and determine the target layers for main exploration; S3, collecting samples from the target layer and conducting tests and analyses to determine the distribution range and content of uranium ore and the content of rhenium ore; S4. Based on the distribution range and content of uranium ore, the content of rhenium ore and the rhenium ore distribution range model, the favorable area of ​​rhenium ore is delineated.

2. The method according to claim 1, characterized in that Step S1 comprises: S11, design the well network density for specific areas and open multiple mines; S12, obtaining the distribution and content data of uranium and rhenium ores in multiple different blocks; S13, establishing a rhenium ore distribution range model based on the distribution data and the content data.

3. The method according to claim 2, characterized in that Step S11 comprises: Existing uranium mines in uranium-rich areas in specific regions are used as mines for obtaining distribution and content data of uranium and rhenium.

4. The method according to claim 2, characterized in that: Step S1 comprises: The distribution range of uranium ore and rhenium ore is defined in an elliptical shape, and the distribution range model of rhenium ore is: W=a×w 2 +b×w+c L=d×ln(l)+e in, w represents the distance in the minor axis direction of the uranium ore, m; l represents the distance in the direction of the long axis of the uranium ore, m; W represents the distance in the minor axis direction of rhenium ore, m; L represents the distance in the long axis direction of rhenium ore, m; a, b, c, d, e represent constants.

5. The method according to claim 4, characterized in that Step S1 comprises: Based on the content data of uranium ore and rhenium ore, the content correlation is determined, and based on the content correlation and the distribution data, the rhenium ore distribution range model is established.

6. The method according to claim 5, characterized in that SPSS software was used to perform correlation analysis on the content data of uranium ore and rhenium ore to determine the content correlation.

7. The method according to claim 5, characterized in that Based on the distribution and content data of uranium and rhenium ores in the Qianjiadian area of ​​the Kailu Basin, the rhenium ore distribution range model is established as follows: When 0<r≤0.5, W=24.6w 2 -102.12w+53.6 L = 35.6ln(l) + 411.6 When 0.5<r≤1, W=38.2w 2 -153.4w+258 L = 68.5ln(l) + 115.64 in, r represents the correlation coefficient; w represents the distance in the minor axis direction of the uranium ore, m; l represents the distance in the direction of the long axis of the uranium ore, m; W represents the distance in the minor axis direction of rhenium ore, m; L represents the distance in the long axis direction of the rhenium ore, m.

8. The method according to claim 5, characterized in that Step S2 comprises: S21, determine the horizon division standard; and S22, determining the top interface and the bottom interface of the target layer.

9. The method according to claim 8, characterized in that In step S21, a stable waterproof layer is determined as a basic classification standard.

10. The method according to claim 9, characterized in that In step S22, when performing stratigraphic correlation, the mudstone at the top of the sedimentary cycle is used as the top interface of the target layer.

11. The method according to claim 10, characterized in that In step S22, the middle of the mudstone at the top of the early sedimentary cycle connecting with the sandstone at the bottom of the sedimentary cycle is taken as the bottom interface of the target layer.

12. The method according to claim 11, characterized in that In step S22, the thickness of the target layer does not exceed 30 mm.

13. The method according to claim 5, characterized in that Step S3 comprises: S31, collect samples; S32, testing the sample to determine the reducing agent information in the sandstone of the target layer; S33, determining the spatial configuration relationship between the reducing medium outside the uranium reservoir and the uranium ore based on the reducing agent information, so as to determine the distribution range of the uranium ore.

14. The method according to claim 13, characterized in that In step S31, Based on the development of interlayer oxidation zones and the dual directions of exploration lines, sampling drill holes are arranged in the target layer.

15. The method according to claim 13, characterized in that In step S31, The same drill hole was sampled from both the mineralized section and the non-mineralized section.

16. The method according to claim 13, characterized in that In step S31, Based on the information of associated elements, key areas are identified for additional sampling.

17. The method according to claim 13, characterized in that In step S31, Priority will be given to sampling from boreholes constructed this year.

18. The method according to claim 13, characterized in that In step S32, the reducing agent information includes at least one of TOC content, S total content, and ω(Fe2O3) / ω(FeO).

19. The method according to claim 13, characterized in that In step S33, Draw a contour map of uranium ore in the target layer for each type of reducing agent information; Refer to the quantitative evaluation standard of uranium reservoir physical properties to evaluate the mineralization conditions, determine the favorable mineralization location of a single well, and determine the superposition map of the spatial distribution of each reducing agent and sandstone-type uranium deposits; Based on the information of multiple reducing agents and the spatial distribution superposition map of sandstone-type uranium deposits, a distribution range map of the uranium deposits in the target layer is obtained.

20. The method according to claim 1, characterized in that Step S4 comprises: S41, determining the content correlation of the target layer based on the contents of uranium ore and rhenium ore in the target layer; S42, based on the distribution range of uranium ore, the content correlation of the target layer and the distribution range model of rhenium ore, the favorable area of ​​rhenium ore is delineated.

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