Method and system for rapidly delineating tin ore prospecting target area

Abstract

The invention provides a method and system for rapidly delineating a tin ore prospecting target area, and relates to the technical field of earth information scientificity, and the method comprises the steps: firstly setting the existing tin ore as a target area, uniformly sampling in each target area, recording the physical characteristics of a sample, and generating a comprehensive index of the sample; then geochemical data of a target area is obtained, relative abundance values of elements in samples are calculated, the relative abundance values of the elements and comprehensive indexes are input into the trained spatial distribution model, spatial autocorrelation indexes of each sample are generated, sorting is conducted according to the spatial autocorrelation indexes of the samples, and therefore the target area with the high tin ore potential is screened out. According to the method, the identification efficiency of the tin ore potential area is remarkably improved, and a reliable basis is provided for sustainable development of mineral resources.

Description

Technical Field

[0001] The invention relates to the field of geoinformation science and technology, and in particular to a method and system for rapidly delineating a tin ore prospecting target area. Background Art

[0002] In the field of mineral exploration, tin ore, as an important metal resource, has always been the focus of geological research in terms of its detection and evaluation. Traditional tin ore exploration methods mostly rely on geological surveys and empirical judgments, usually through the analysis of known deposits and the evaluation of the geological characteristics of the surrounding areas. Although these methods have achieved certain results in history, due to their subjectivity and limitations, they often cannot fully reveal the true situation of potential mining areas.

[0003] Traditional exploration methods, such as empirical identification and limited geological surveys, may lead to an incomplete assessment of potential mining areas. At the same time, many methods lack in-depth analysis of spatial distribution characteristics and cannot effectively utilize geographic information systems and data mining technologies, thus limiting the accurate identification of tin ore potential. In addition, traditional methods are inefficient in data collection and analysis, making it difficult to obtain high-quality exploration results in a short period of time. Therefore, it is particularly important to develop a systematic, fast and efficient method for tin ore target area delineation, which can provide strong technical support for the sustainable development of mineral resources.

[0004] The prior art has the following deficiencies:

[0005] With the development of science and technology, modern exploration technology has gradually introduced advanced methods such as geochemical analysis and geographic information systems. Through detailed analysis of soil and rock samples, researchers can obtain more accurate element distribution and rich geological information. However, existing technologies still face some challenges, such as low data processing efficiency, uneven sample collection, unilateral analysis of the physical properties of soil and rock samples, and insufficient analysis of spatial distribution characteristics, which limit the rapid identification and evaluation of potential tin mine targets.

[0006] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0007] The purpose of the present invention is to provide a method and system for quickly delineating a tin ore prospecting target area to solve the problems raised in the above background technology.

[0008] A method for quickly delineating a tin ore prospecting target area, the specific steps comprising:

[0009] Step 1: Set the existing tin mine as the target area, evenly calibrate N sampling points in each target area, dig the surface soil and rocks of the sampling points as samples, and record the geographical location, rock type, ore deposit type and geomorphic data of the samples;

[0010] Step 2: Analyze the topographic data of the sample, generate the terrain complexity index, and combine the rock type and deposit type of the sample to obtain the comprehensive index of the sample;

[0011] Step 3: Obtaining geochemical data of samples in the target area by laser ablation-inductively coupled plasma mass spectrometry technology, wherein the geochemical data of samples in the target area include the concentrations of tin, copper, lead, and zinc elements, and calculating the relative abundance of each element;

[0012] Step 4: Calculate the relative abundance mean and standard deviation of all samples, standardize the relative abundance of each element, integrate the standardized data into a data set, and divide it into a training set and a validation set;

[0013] Step 5: Analyze the spatial distribution based on the geographic information system, build a spatial distribution model, input the relative abundance of each element in the training set, combine the comprehensive indicators of the sample, obtain the spatial autocorrelation index of each element as a label, and verify the spatial distribution model;

[0014] Step 6: Select the area to be tested based on the geomorphic and topographic data of the target area, obtain samples from the area to be tested and collect relevant data to input into the spatial distribution model, sort the predicted spatial autocorrelation indicators, and screen the target area with high tin mining potential.

[0015] Furthermore, an area with known tin ore distribution is selected, and the boundary of the target area is drawn using geographic information system software. Systematic sampling is carried out using the grid sampling method, and the surface soil and rocks at a depth of 0-10 cm at each sampling point are excavated as samples. 50 grams of samples are collected, and the position of the Nth sample is calibrated as N(x, y), where x is the latitude of the position, and y is the longitude of the position. A rock type index is determined based on the rock type, and a deposit type index is determined based on the mineral type. The rock types include granite, metamorphic rock, volcanic rock, quartzite and sedimentary rock. The deposit types include hydrothermal deposits, magmatic deposits, metamorphic deposits, sedimentary deposits, volcanic rock deposits and placer deposits. The geomorphological and topographic data include contour lines and topographic line data of the area. The specific data of the contour lines are the density of the contour lines, the height of the highest point and the height of the lowest point corresponding to the contour lines, and the specific data of the topographic lines are the density of the topographic lines, the height of the highest point and the height of the lowest point corresponding to the topographic lines.

[0016] Furthermore, the logic for obtaining the comprehensive indicators of the samples is as follows:

[0017] The formula for obtaining the contour density is:

[0018]

[0019] Among them, D i is the contour density of the area where the i-th sample is located, M i is the number of contour lines in the area where the i-th sample is located, L i is the perimeter of the area where the i-th sample is located;

[0020] The formula for obtaining terrain line density is:

[0021]

[0022] Among them, F i represents the topographic line density of the area where the i-th sample is located, LF i is the total length of the terrain line in the area where the i-th sample is located, A i is the area of ​​the region where the i-th sample is located;

[0023] The formula for obtaining the terrain complexity index is:

[0024]

[0025] Among them, S i is the terrain complexity index of the area where the i-th sample is located, is the height of the highest point of the terrain line in the area where the i-th sample is located, is the lowest point height of the terrain line in the area where the i-th sample is located, is the height of the highest point of the contour line in the area where the i-th sample is located, is the height of the lowest point of the contour line in the area where the i-th sample is located;

[0026] The formula for obtaining the comprehensive index of the sample is:

[0027] Q i =ω1*R q i +ω2*O q i +ω3*S i

[0028] Among them, Q i is the comprehensive index of the i-th sample, R q i is the rock type index of the ith sample, O q i is the deposit type index of the i-th sample, S iis the terrain complexity index of the i-th sample, ω1, ω2, ω3 are weight coefficients, ω2>ω1>ω3 and ω1+ω2+ω3=1.

[0029] Furthermore, the logic for calculating the relative abundance of each element is:

[0030] Using a laser ablation instrument, the sample surface is ablated by a laser beam to generate an aerosol, which is introduced into the inductively coupled plasma through a catheter and ionized at high temperature. The mass-to-charge ratio of different ions is measured and the concentration of the element is calculated based on the specific peak intensity. The standard curve method is used for quantitative analysis of the element concentration. By measuring standard samples of known concentration, the relationship between the concentration and the corresponding mass spectrometry signal intensity is established. The specific formula based on the standard curve is:

[0031] Y=δX+b

[0032] Where Y is the mass spectrometry signal intensity, X is the known concentration, δ is the slope, which represents the signal change caused by each unit concentration change, and b is the intercept, which represents the signal when the concentration is 0;

[0033] The specific formula for obtaining the relative abundance of each element is:

[0034]

[0035] The tin, copper, lead and zinc elements in the samples are labeled 1, 2, 3 and 4 respectively, and the concentration of the ath element in the i-th sample is labeled a∈[1,4], is the relative abundance of the ath element in the ith sample.

[0036] Furthermore, the specific logic for standardizing the relative abundance of each element is as follows:

[0037] The formula for obtaining the mean relative abundance of each element is:

[0038]

[0039] in, is the mean relative abundance of the element in the i-th sample, n is the number of elements, which is 4 here;

[0040] The formula used to obtain the standard deviation of relative abundance is:

[0041]

[0042] Among them, σ i is the standard deviation of the relative abundance of the ith sample, n is the number of elements, which is 4 here;

[0043] The formula for normalizing the relative abundance of each element is:

[0044]

[0045] in, is the standardized value of the relative abundance of element a in the i-th sample.

[0046] Furthermore, the formula for obtaining the spatial autocorrelation index of each element is:

[0047]

[0048] Among them, I i is the spatial autocorrelation index of the ith sample, N is the number of samples, W is the sum of weights, η1 is the spatial weight of relative abundance, η2 is the spatial weight of the comprehensive index, η1>η2>0.

[0049] Furthermore, the logic for screening target areas with high tin potential is as follows:

[0050] By comparing with the contour line density, contour line height difference, terrain line density and terrain line height difference of the target area, if the total difference is lower than the preset similarity threshold, the area is set as the area to be tested; if the total difference is higher than the preset similarity threshold, the area is judged as a non-area to be tested;

[0051] Collect samples from the area to be tested and divide them into N parts. Calculate the comprehensive indicators and relative abundance values ​​of the elements of the samples to be tested and input them into the spatial distribution model. Then sort the predicted spatial autocorrelation indicators and calibrate the sample areas corresponding to the top three spatial autocorrelation indicators as target areas with high tin ore potential.

[0052] The present invention further provides a system for quickly delineating a tin ore prospecting target area, wherein the system for quickly delineating a tin ore prospecting target area is used to implement the above-mentioned method for quickly delineating a tin ore prospecting target area, and comprises:

[0053] The sample collection module is used to set the existing tin mine as the target area, evenly calibrate N sampling points in each target area, dig the surface soil and rocks of the sampling points as samples, and record the geographical location, rock type, ore deposit type and geomorphic data of the samples;

[0054] Geomorphic feature analysis module, used to analyze the geomorphic data of samples, generate the terrain complexity index, and combine the rock type and deposit type of the samples to obtain the comprehensive index of the samples;

[0055] A geochemical data acquisition module is used to acquire geochemical data of samples in the target area by laser ablation-inductively coupled plasma mass spectrometry technology, wherein the geochemical data of samples in the target area include the concentrations of tin, copper, lead and zinc elements, and calculate the relative abundance of each element;

[0056] The data preprocessing module is used to calculate the relative abundance mean and standard deviation of all samples, standardize the relative abundance of each element, integrate the standardized data into a data set, and divide it into a training set and a validation set;

[0057] The spatial distribution model building module is used to analyze spatial distribution based on the geographic information system, build a spatial distribution model, input the relative abundance of each element in the training set, combine the comprehensive indicators of the sample, obtain the spatial autocorrelation index of each element as a label, and verify the spatial distribution model;

[0058] The potential target area screening module is used to screen out the area to be tested based on the geomorphic and topographic data of the target area, obtain samples from the area to be tested and collect relevant data to input into the spatial distribution model, sort the predicted spatial autocorrelation indicators, and screen the target area with high tin ore potential.

[0059] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0060] This method significantly improves the efficiency and accuracy of tin ore target area delineation through a systematic sample collection and analysis process. Geochemical data, structural geomorphology and topographic index, rock type and other comprehensive indicators obtained by laser ablation-inductively coupled plasma mass spectrometry can more comprehensively reflect the mineral potential of the target area. Through the establishment and verification of the spatial distribution model, scientific identification of high-potential target areas is achieved, avoiding excessive reliance on experience in traditional methods. In addition, the spatial analysis capabilities of the geographic information system can be used to deeply explore the spatial autocorrelation between samples and improve the accuracy of prediction. This not only provides data support for rapid decision-making, but also lays a solid foundation for subsequent exploration work, and has good application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a schematic diagram of the overall method flow of the present invention;

[0062] Figure 2 It is a schematic diagram of the system structure of the present invention. DETAILED DESCRIPTION

[0063] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0064] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0065] Example:

[0066] See also Figure 1 The present invention provides a method for quickly delineating a tin ore prospecting target area, and the specific steps include:

[0067] Step 1: Set the existing tin mine as the target area, evenly calibrate N sampling points in each target area, dig the surface soil and rocks of the sampling points as samples, and record the geographical location, rock type, ore deposit type and geomorphic data of the samples;

[0068] In this embodiment, an area with known tin ore distribution is selected, and the boundary of the target area is drawn using geographic information system software. A grid sampling method is used for systematic sampling. The surface soil and rock at a depth of 0-10 cm at each sampling point are excavated as samples. 50 grams of samples are collected, and the position of the Nth sample is calibrated as N(x, y), where x is the latitude of the position and y is the longitude of the position. A rock type index is determined based on the rock type, and a ore deposit type index is determined based on the mineral type. The value range of the rock type index is [1, 5]. The rock types specifically include granite, metamorphic rock, volcanic rock, quartzite and sedimentary rock. According to the sorting, the rock type index is from high to low, and the corresponding flower type is The granite rock type index is calibrated as 4. Since granite is highly associated with many mineral deposits, especially tin mines, it is assigned a higher index value. The metamorphic rock type index is calibrated as 3. Metamorphic rocks also have a certain correlation with mineral deposits, but may not be as good as granite. The volcanic rock type index is calibrated as 3. Volcanic rocks are associated with mineral deposits in some cases, especially those associated with igneous rocks. The quartzite rock type index is calibrated as 3. Quartzite itself may not be directly associated with mineral deposits, but it is important in specific geological environments. The sedimentary rock type index is calibrated as 1. Sedimentary rocks have a lower correlation with mineral deposits, but may also contain mineral deposits in certain specific environments, so they are assigned the lowest index value. The value range of the deposit type index is [1,5]. The deposit types include hydrothermal deposits, magmatic deposits, metamorphic deposits, sedimentary deposits, volcanic rock deposits, and placer deposits. According to this ranking, the deposit type index is from high to low. The corresponding hydrothermal deposit has a deposit type index of 5. Hydrothermal deposits are one of the important mineralization environments of tin ores, so the deposit type index is the highest. The deposit type index of magmatic deposits is calibrated as 4. Although tin ores are mainly formed by hydrothermal action, magmatic deposits may also contain tin ores, especially in magmatic activities related to granite. The deposit type index of metamorphic deposits is calibrated as 3. Metamorphism can re-concentrate and enrich Minerals: Although metamorphic deposits are not the main genetic environment of tin ores, there is a certain possibility. The deposit type index of sedimentary deposits is calibrated to 3. Although tin ores are rarely formed directly in sedimentary environments, the sedimentation can redistribute tin minerals in hydrothermal deposits, so there is still a certain correlation. The deposit type index of volcanic rocks is calibrated to 2. Although there may be some metal minerals in volcanic rock-related deposits, the possibility of tin ores existing in such environments is low. The deposit type index of placer deposits is calibrated to 1. Placer deposits are mainly formed by mineral enrichment under mechanical action. Although there may be tin minerals in some places, the overall correlation is the lowest. Geomorphic terrain data includes contour lines and terrain line data of the area. The specific data of contour lines are contour line density, the height of the highest point and the height of the lowest point corresponding to the contour lines, and the specific data of terrain lines are the density of terrain lines, the height of the highest point and the height of the lowest point corresponding to the terrain lines.

[0069] Tin ores are often associated with specific rock types, such as granite, metamorphic rocks, and certain types of volcanic rocks. These rocks are often rich in tin minerals, such as cassiterite, and have undergone special geological processes during their formation, such as hydrothermal or metamorphic processes. These processes can promote the enrichment of tin and form economically viable tin deposits. Rock type not only affects the distribution and concentration of minerals, but can also reveal the underlying mechanism of deposit formation. By understanding the characteristics of different rock types, researchers can better determine the occurrence conditions and possible mineralization processes of tin ores.

[0070] In the area where tin mines are located, they are often associated with granite, especially deposits formed by hydrothermal action in granite and its intrusive bodies, and usually have higher content, followed by metamorphic rocks, quartzites, sedimentary rocks and volcanic rocks.

[0071] The type of mineral deposit helps identify the characteristics and distribution patterns of mineral resources in a specific area. Different types of mineral deposits have significant differences in mineralization processes, mineral assemblages and their economic value. By analyzing the type of mineral deposits, we can effectively guide exploration strategies and focus on the most promising areas, thereby improving the success rate and efficiency of prospecting. Therefore, the collection of rock types and mineral deposit types provides an important basis for subsequent exploration decisions and resource assessments.

[0072] Hydrothermal deposits are the most common type of tin deposits, which are closely related to intrusive rock bodies such as granite. The formation of tin ore mainly depends on hydrothermal action. Due to the action of water flow, tin minerals (such as cassiterite) are easily migrated and deposited from their origin, so placer deposits are also an important source of tin ore. The second is metamorphic deposits, sedimentary deposits, volcanic rock deposits and magmatic deposits.

[0073] Tin mining areas are often located in mountainous or hilly areas, so the contour lines may appear relatively dense, indicating that the terrain is undulating. Due to the geological structure (such as folds and faults), the highest point in the tin mining area may be higher and the lowest point may be lower, forming an obvious height difference. In some plains or sedimentary basins in non-tin mining areas, the contour lines are relatively sparse, indicating that the terrain is relatively flat, and the height difference between the highest point and the lowest point may be relatively small. Therefore, it is chosen to record the topographic lines and contour line data of the target area to provide a basis for the subsequent screening of high-potential mineral targets.

[0074] Step 2: Analyze the topographic data of the sample, generate the terrain complexity index, and combine the rock type and deposit type of the sample to obtain the comprehensive index of the sample;

[0075] In this embodiment, the logic for obtaining the comprehensive index of the sample is:

[0076] The formula for obtaining the contour density is:

[0077]

[0078] Among them, D i is the contour density of the area where the i-th sample is located, M i is the number of contour lines in the area where the i-th sample is located, L i is the perimeter of the area where the i-th sample is located;

[0079] The formula for obtaining terrain line density is:

[0080]

[0081] Among them, F i represents the topographic line density of the area where the i-th sample is located, LF i is the total length of the terrain line in the area where the i-th sample is located, A i is the area of ​​the region where the i-th sample is located;

[0082] The formula for obtaining the terrain complexity index is:

[0083]

[0084] Among them, S i is the terrain complexity index of the area where the i-th sample is located, is the height of the highest point of the terrain line in the area where the i-th sample is located, is the lowest point height of the terrain line in the area where the i-th sample is located, is the height of the highest point of the contour line in the area where the i-th sample is located, is the height of the lowest point of the contour line in the area where the i-th sample is located;

[0085] The formula for obtaining the comprehensive index of the sample is:

[0086] Q i =ω1*R q i +ω2*O q i +ω3*S i

[0087] Among them, Q i is the comprehensive index of the i-th sample, R q i is the rock type index of the ith sample, O q i is the deposit type index of the i-th sample, S i is the terrain complexity index of the i-th sample, ω1, ω2, ω3 are weight coefficients, ω2>ω1>ω3 and ω1+ω2+ω3=1.

[0088] Dependent variable Q iIt reflects the comprehensive mineral potential of the i-th sample. Through the comprehensive consideration of rock type, deposit type and terrain complexity factors, a comprehensive score is obtained to guide the prospecting decision. The rock type index reflects the geological background of the sample and directly affects the richness and type of minerals. Different rock types may mean different mineralization environments. The rock type index is positively correlated with the comprehensive index. The higher the rock type index, the larger the comprehensive index will be, which means that the target area has greater potential for tin ore target area. The deposit type index characterizes the deposit type of the area where the sample is located, determines the characteristics of the mineral resources in the area, and is positively correlated with the comprehensive index. The higher the deposit type index, the larger the comprehensive index will be, which means that the target area is more likely to be a tin ore target area. The terrain complexity index is also positively correlated with the comprehensive index. Relatively speaking, the terrain complexity of the tin ore area is more complex than that of the non-tin ore area. The higher the terrain complexity index, the larger the comprehensive index value. The deposit type directly affects the formation and distribution of minerals. The mineralization of tin ore is closely related to the deposit type, so the deposit type has the largest weight. Rock type also has an important influence on the formation of tin ore, especially tin ore is often associated with certain specific rock types (such as granite). However, compared with the type of ore deposit, rock type may have a relatively small impact on the prospecting target area. Although terrain complexity may affect the exposure and mining of ore bodies, in the mineralization environment of tin ore, topographic factors are usually not the most important influencing factors, so their weight should be relatively small. ω1+ω2+ω3=1. This constraint ensures that the comprehensive index is a normalized index, ensuring that the total contribution of the weighted combination of the three factors is 100%.

[0089] Step 3: Obtaining geochemical data of samples in the target area by laser ablation-inductively coupled plasma mass spectrometry technology, wherein the geochemical data of samples in the target area include the concentrations of tin, copper, lead, and zinc elements, and calculating the relative abundance of each element;

[0090] In this embodiment, the logic for calculating the relative abundance of each element is:

[0091] Using a laser ablation instrument, the sample surface is ablated by a laser beam to generate an aerosol, which is introduced into the inductively coupled plasma through a catheter and ionized at high temperature. The mass-to-charge ratio of different ions is measured and the concentration of the element is calculated based on the specific peak intensity. The standard curve method is used for quantitative analysis of the element concentration. By measuring standard samples of known concentration, the relationship between the concentration and the corresponding mass spectrometry signal intensity is established. The specific formula based on the standard curve is:

[0092] Y=δX+b

[0093] Where Y is the mass spectrometry signal intensity, X is the known concentration, δ is the slope, which represents the signal change caused by each unit concentration change, and b is the intercept, which represents the signal when the concentration is 0;

[0094] The specific formula for obtaining the relative abundance of each element is:

[0095]

[0096] The tin, copper, lead and zinc elements in the samples are labeled 1, 2, 3 and 4 respectively, and the concentration of the ath element in the i-th sample is labeled a∈[1,4], is the relative abundance of the ath element in the ith sample.

[0097] Laser ablation-inductively coupled plasma mass spectrometry technology can detect very low concentrations of elements with high sensitivity, which can improve the accuracy of element abundance data and is suitable for the analysis of geological, mineral and environmental samples. In addition, this technology can simultaneously analyze multiple elements in the sample and obtain relative concentrations and abundances in the same experiment, saving time and resources and avoiding interference from human factors.

[0098] The abundance and relative concentration of different elements can provide important information about the mineralization environment. Tin ores are usually associated with specific rock types, deposit types, and mineralization processes. By analyzing the distribution of elements in samples, possible mineralization environments can be inferred. Analysis of relative concentrations and abundances can reveal the characteristics of mineral assemblages and help identify potential mineralized areas. By detecting the relative abundance of elements that may be associated with tin deposits or related to the mineralization process of tin, target areas can be more effectively located.

[0099] Step 4: Calculate the relative abundance mean and standard deviation of all samples, standardize the relative abundance of each element, integrate the standardized data into a data set, and divide it into a training set and a validation set;

[0100] In this embodiment, the specific logic for normalizing the relative abundance of each element is as follows:

[0101] The formula for obtaining the mean relative abundance of each element is:

[0102]

[0103] in, is the mean relative abundance of the element in the i-th sample, n is the number of elements, which is 4 here;

[0104] The formula used to obtain the standard deviation of relative abundance is:

[0105]

[0106] Among them, σ iis the standard deviation of the relative abundance of the ith sample, n is the number of elements, which is 4 here;

[0107] The formula for normalizing the relative abundance of each element is:

[0108]

[0109] in, is the standardized value of the relative abundance of element a in the i-th sample.

[0110] The abundance values ​​of different elements in a sample may differ greatly by orders of magnitude. Standardization can convert these data to the same scale, making the comparison between different elements more reasonable and effective. In addition, standardization can help remove the influence of background noise and make the signal clearer, thereby improving the reliability of the data and the effectiveness of the analysis.

[0111] Step 5: Analyze the spatial distribution based on the geographic information system, build a spatial distribution model, input the relative abundance of each element in the training set, combine the comprehensive indicators of the sample, obtain the spatial autocorrelation index of each element as a label, and verify the spatial distribution model;

[0112] In this embodiment, the formula for obtaining the spatial autocorrelation index of each element is:

[0113]

[0114] Among them, I i is the spatial autocorrelation index of the ith sample, N is the number of samples, W is the sum of weights, η1 is the spatial weight of relative abundance, η2 is the spatial weight of the comprehensive index, η1>η2>0, the size of W depends on the number of samples N and the specific value of the weight of each sample. In the spatial aggregation effect, the relative abundance of the sample has a greater weight and can better reflect the content of tin ore in the sample.

[0115] The spatial autocorrelation index can help identify the spatial distribution model of each element. By analyzing the spatial autocorrelation of elements, the degree of aggregation in the geological body can be determined, which helps to understand the formation mechanism and distribution characteristics of the ore body. High autocorrelation values ​​usually indicate the aggregation of elements in space, which may indicate the existence of mineralized areas. By identifying these areas, potential prospecting targets can be more effectively determined and exploration efficiency can be improved. In addition, the spatial autocorrelation index can help identify outliers in the abundance of elements in the sample, which may indicate the existence of ore bodies or important information in the mineralization process.

[0116] Step 6: Select the area to be tested based on the geomorphic and topographic data of the target area, obtain samples from the area to be tested and collect relevant data to input into the spatial distribution model, sort the predicted spatial autocorrelation indicators, and screen the target area with high tin mining potential.

[0117] In this embodiment, the logic for screening target areas with high tin ore potential is:

[0118] By comparing with the contour line density, contour line height difference, terrain line density and terrain line height difference of the target area, if the total difference is lower than the preset similarity threshold, the area is set as the area to be tested; if the total difference is higher than the preset similarity threshold, the area is judged as a non-area to be tested;

[0119] Collect samples from the area to be tested and divide them into N parts. Calculate the comprehensive indicators and relative abundance values ​​of the elements of the samples to be tested and input them into the spatial distribution model. Then sort the predicted spatial autocorrelation indicators and calibrate the sample areas corresponding to the top three spatial autocorrelation indicators as target areas with high tin ore potential.

[0120] The calculated element abundance values ​​are input into the spatial distribution model to generate a spatial distribution map of the area. These models can effectively predict potential mineralized areas based on the geological background and the spatial characteristics of element abundance. By sorting the predicted spatial autocorrelation indicators, areas with highly spatially concentrated element abundance can be identified. High autocorrelation values ​​usually mean that the element abundance in the area is higher than the surrounding areas, indicating the potential for tin ore.

[0121] See also Figure 2 The present invention also provides a system for quickly delineating a tin ore prospecting target area, and the system for quickly delineating a tin ore prospecting target area is used to implement the above-mentioned method for quickly delineating a tin ore prospecting target area, comprising:

[0122] The sample collection module is used to set the existing tin mine as the target area, evenly calibrate N sampling points in each target area, dig the surface soil and rocks of the sampling points as samples, and record the geographical location, rock type, ore deposit type and geomorphic data of the samples;

[0123] The geomorphic feature analysis module is used to analyze the geomorphic data of the sample, generate the terrain complexity index, and combine the rock type and deposit type of the sample to obtain the comprehensive index of the sample;

[0124] A geochemical data acquisition module is used to acquire geochemical data of samples in the target area by laser ablation-inductively coupled plasma mass spectrometry technology, wherein the geochemical data of samples in the target area include the concentrations of tin, copper, lead and zinc elements, and calculate the relative abundance of each element;

[0125] The data preprocessing module is used to calculate the relative abundance mean and standard deviation of all samples, standardize the relative abundance of each element, integrate the standardized data into a data set, and divide it into a training set and a validation set;

[0126] The spatial distribution model building module is used to analyze spatial distribution based on the geographic information system, build a spatial distribution model, input the relative abundance of each element in the training set, combine the comprehensive indicators of the sample, obtain the spatial autocorrelation index of each element as a label, and verify the spatial distribution model;

[0127] The potential target area screening module is used to screen out the area to be tested based on the geomorphic and topographic data of the target area, obtain samples from the area to be tested and collect relevant data to input into the spatial distribution model, sort the predicted spatial autocorrelation indicators, and screen the target area with high tin ore potential.

[0128] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0129] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0130] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0131] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be covered by the protection scope of the present application.

Claims

1. A method for quickly delineating a tin ore prospecting target area, characterized in that: The specific steps include: Step 1: Set the existing tin mine as the target area, evenly calibrate N sampling points in each target area, dig the surface soil and rocks of the sampling points as samples, and record the geographical location, rock type, ore deposit type and geomorphic data of the samples; Step 2: Analyze the geomorphic data of the target area, generate a terrain complexity index, and combine the rock type and deposit type of the sample to obtain a comprehensive index of the sample; Step 3: Obtaining geochemical data of samples in the target area by laser ablation-inductively coupled plasma mass spectrometry technology, wherein the geochemical data of samples in the target area include the concentrations of tin, copper, lead, and zinc elements, and calculating the relative abundance of each element; Step 4: Calculate the relative abundance mean and standard deviation of all samples, standardize the relative abundance of each element, integrate the standardized data into a data set, and divide it into a training set and a validation set; Step 5: Analyze the spatial distribution based on the geographic information system, build a spatial distribution model, input the relative abundance of each element in the training set, combine the comprehensive indicators of the sample, obtain the spatial autocorrelation index of each element as a label, and verify the spatial distribution model; Step 6: Select the area to be tested based on the geomorphic and topographic data of the target area, obtain samples from the area to be tested and collect relevant data to input into the spatial distribution model, sort the predicted spatial autocorrelation indicators, and screen the target area with high tin mining potential.

2. The method for rapidly delineating a tin ore prospecting target area according to claim 1, characterized in that: An area where tin ore is known to be distributed is selected, and the boundary of the target area is drawn using geographic information system software. Systematic sampling is performed using a grid sampling method. 0-10 cm deep surface soil and rocks at each sampling point are excavated as samples, 50 grams of samples are collected, and the position of the Nth sample is calibrated as N(x, y), where x is the latitude of the position, and y is the longitude of the position. A rock type index is determined based on the rock type, and a deposit type index is determined based on the mineral type. The rock types include granite, metamorphic rock, volcanic rock, quartzite, and sedimentary rock. The deposit types include hydrothermal deposits, magmatic deposits, metamorphic deposits, sedimentary deposits, volcanic rock deposits, and placer deposits. The geomorphological and topographic data include contour lines and topographic line data of the area. The specific data of the contour lines are the density of the contour lines, the height of the highest point and the height of the lowest point corresponding to the contour lines, and the specific data of the topographic lines are the density of the topographic lines, the height of the highest point and the height of the lowest point corresponding to the topographic lines.

3. The method for quickly delineating a tin ore prospecting target area according to claim 2, characterized in that: The logic for obtaining the comprehensive indicators of samples is: The formula for obtaining the contour density is: Among them, D i is the contour density of the area where the i-th sample is located, M i is the number of contour lines in the area where the i-th sample is located, L i is the perimeter of the area where the i-th sample is located; The formula for obtaining terrain line density is: Among them, F i represents the topographic line density of the area where the i-th sample is located, LF i is the total length of the terrain line in the area where the i-th sample is located, A i is the area of ​​the region where the i-th sample is located; The formula for obtaining the terrain complexity index is: Among them, S i is the terrain complexity index of the area where the i-th sample is located, H 1 maxi is the height of the highest point of the topographic line in the area where the i-th sample is located, H 1 mini is the height of the lowest point of the terrain line in the area where the i-th sample is located, H 2 maxi is the height of the highest point of the contour line in the area where the i-th sample is located, H 2 mini is the height of the lowest point of the contour line in the area where the i-th sample is located; The formula for obtaining the comprehensive index of the sample is: Q i =ω1*R q i +ω2*O q i +ω3*S i Among them, Q i is the comprehensive index of the i-th sample, R q i is the rock type index of the ith sample, O q i is the deposit type index of the i-th sample, S i is the terrain complexity index of the i-th sample, ω1, ω2, ω3 are weight coefficients, ω2>ω1>ω3 and ω1+ω2+ω3=1.

4. The method for quickly delineating a tin ore prospecting target area according to claim 3, characterized in that: The logic behind calculating the relative abundance of each element is: Using a laser ablation instrument, the sample surface is ablated by a laser beam to generate an aerosol, which is introduced into the inductively coupled plasma through a catheter and ionized at high temperature. The mass-to-charge ratio of different ions is measured and the concentration of the element is calculated based on the specific peak intensity. The standard curve method is used for quantitative analysis of the element concentration. By measuring standard samples of known concentration, the relationship between the concentration and the corresponding mass spectrometry signal intensity is established. The specific formula based on the standard curve is: Y=δX+b Where Y is the mass spectrometry signal intensity, X is the known concentration, δ is the slope, which represents the signal change caused by each unit concentration change, and b is the intercept, which represents the signal when the concentration is 0; The specific formula for obtaining the relative abundance of each element is: The tin, copper, lead and zinc elements in the samples are labeled 1, 2, 3 and 4 respectively, and the concentration of the ath element in the i-th sample is labeled a∈[1,4], is the relative abundance of the ath element in the ith sample.

5. The method for quickly delineating a tin ore prospecting target area according to claim 4, characterized in that: The specific logic for normalizing the relative abundance of each element is: The formula for obtaining the mean relative abundance of each element is: in, is the mean relative abundance of the element in the i-th sample, n is the number of elements, which is 4 here; The formula used to obtain the standard deviation of relative abundance is: Among them, σ i is the standard deviation of the relative abundance of the ith sample, n is the number of elements, which is 4 here; The formula for normalizing the relative abundance of each element is: in, is the standardized value of the relative abundance of element a in the i-th sample.

6. The method for quickly delineating a tin ore prospecting target area according to claim 5, characterized in that: The formula for obtaining the spatial autocorrelation index for each element is: Among them, I i is the spatial autocorrelation index of the ith sample, N is the number of samples, W is the sum of weights, η1 is the spatial weight of relative abundance, η2 is the spatial weight of the comprehensive index, η1>η2>0.

7. The method for quickly delineating a tin ore prospecting target area according to claim 6, characterized in that: The logic behind screening target areas with high tin potential is: By comparing with the contour line density, contour line height difference, terrain line density and terrain line height difference of the target area, if the total difference is lower than the preset similarity threshold, the area is set as the area to be tested; if the total difference is higher than the preset similarity threshold, the area is judged as a non-area to be tested; Collect samples from the area to be tested and divide them into N parts. Calculate the comprehensive indicators and relative abundance values ​​of the elements of the samples to be tested and input them into the spatial distribution model. Then sort the predicted spatial autocorrelation indicators and calibrate the sample areas corresponding to the top three spatial autocorrelation indicators as target areas with high tin ore potential.

8. A system for rapidly delineating a tin ore prospecting target area, the system being used to execute the system for rapidly delineating a tin ore prospecting target area as claimed in any one of claims 1 to 7, characterized in that: include: The sample collection module is used to set the existing tin mine as the target area, evenly calibrate N sampling points in each target area, dig the surface soil and rocks of the sampling points as samples, and record the geographical location, rock type, ore deposit type and geomorphic data of the samples; The geomorphic feature analysis module is used to analyze the geomorphic data of the sample, generate the terrain complexity index, and combine the rock type and deposit type of the sample to obtain the comprehensive index of the sample; A geochemical data acquisition module is used to acquire geochemical data of samples in the target area by laser ablation-inductively coupled plasma mass spectrometry technology, wherein the geochemical data of samples in the target area include the concentrations of tin, copper, lead and zinc elements, and calculate the relative abundance of each element; The data preprocessing module is used to calculate the relative abundance mean and standard deviation of all samples, standardize the relative abundance of each element, integrate the standardized data into a data set, and divide it into a training set and a validation set; The spatial distribution model building module is used to analyze spatial distribution based on the geographic information system, build a spatial distribution model, input the relative abundance of each element in the training set, combine the comprehensive indicators of the sample, obtain the spatial autocorrelation index of each element as a label, and verify the spatial distribution model; The potential target area screening module is used to screen out the area to be tested based on the geomorphic and topographic data of the target area, obtain samples from the area to be tested and collect relevant data to input into the spatial distribution model, sort the predicted spatial autocorrelation indicators, and screen the target area with high tin ore potential.

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