A mathematical weighting method for optimizing exploration geochemical data analysis

Abstract

The present invention relates to the technical field of data processing, and discloses a mathematical weighting method for optimizing exploration geochemical data analysis, including obtaining original data for quantitative determination of mineral anomalies; wherein the original data includes several single elements and values ​​of each single element; determining a background value according to the values ​​of each single element; determining an anomaly lower limit according to the background value and the values ​​of each single element; determining an anomaly contrast value of each single element according to the ratio of each single element value to the anomaly lower limit; and determining a weighted contrast value of each single element according to the anomaly contrast value of each single element. The present invention eliminates discrete data in the original data, thereby calculating and obtaining a background value and an anomaly lower limit; and then determining a weighted contrast value of each single element according to the anomaly contrast value, so as to unify the standard of the data group to be processed, eliminate interference, and improve the accuracy of drawing a comprehensive anomaly map, and is suitable for screening anomalies of metal minerals such as antimony and gold.

Description

Technical Field

[0001] The invention relates to the technical field of data processing, and in particular to a mathematical weighting method for optimizing exploration geochemical data analysis. Background Art

[0002] Exploration geochemistry (referred to as "geochemical exploration") is a universal and effective method for metal mineral prospecting prediction. Its core is to discover and evaluate ore-causing anomalies by analyzing geochemical element data. In recent years, with the widespread development of easily discovered ore deposits, prospecting has developed to the stage of deep exploration and blind exploration, and the requirements for anomaly evaluation methods have increased. In order to seek scientific predictions and minimize the scope of anomalies to accurately locate ore bodies, prospectors are committed to conducting objective, quantitative and precise evaluations by combining mathematics, physics, chemistry, AI and other methods.

[0003] Exploration geochemical data analysis is the evaluation of ore-causing anomalies under the coupling of background, anomalies and errors. Geochemical anomalies in different regions and under different conditions are complex, hidden, multi-solution, and are interfered with or even misled by complex factors. Therefore, although there are many methods for screening and evaluating geochemical anomalies, there is no single theoretical method that is universally applicable to all metal ores such as antimony and gold. Summary of the invention

[0004] The main purpose of the present invention is to provide a mathematical weighting method for optimizing the analysis of exploration geochemical data, aiming to solve the problem that there is no single theoretical method universally applicable to the screening of anomalies of metal minerals such as antimony and gold.

[0005] To achieve the above object, the present invention provides a mathematical weighting method for optimizing exploration geochemical data analysis, comprising:

[0006] Acquiring raw data for quantitative determination of mineral abnormalities; wherein the raw data includes several single elements and values ​​of each single element;

[0007] Determine the background value based on the value of each single element;

[0008] Determine the abnormal lower limit according to the background value and the values ​​of each single element;

[0009] Determining the abnormal contrast value of each single element according to the ratio of each single element value to the abnormal lower limit;

[0010] According to the abnormal contrast value of each single element, the weighted contrast value of each single element is determined.

[0011] Preferably, the step of determining the weighted contrast value of each single element according to the abnormal contrast value of each single element comprises:

[0012] Select one of the single elements that meets the preset conditions and determine it as the standard weight;

[0013] Determine the contribution of each single element in each collection point, and determine the standard value of each contribution according to the standard weight;

[0014] Determine the real-time weight of each single element except the one marked as the standard weight according to the standard weight and the standard value;

[0015] The weighted contrast value of each single element is determined according to the standard weight of the single element that meets the preset conditions, the real-time weight of the remaining single elements except the one marked as the standard weight, and the abnormal contrast value of each single element.

[0016] Preferably, the preset condition is the single element with the highest degree of overlap of the abnormal concentration center in the single element anomaly map formed by each single element; and the standard weight is 1.

[0017] Preferably, the calculation formula for the contribution of each single element is:

[0018] ;

[0019] in, is the contribution of the jth single element at the i-th sampling point; is the abnormal contrast value of the jth element at the ith sampling point; m is the total number of all single elements.

[0020] Preferably, the calculation formula for the standard value of each contribution is:

[0021] ;

[0022] in, is the standard value of the jth single element at the ith sampling point, The value range of is 0 to 1; The contribution of the single element with the smallest value among all the contributions of the single elements; It is the contribution of the single element with the largest value among all the contributions of the single elements.

[0023] Preferably, the calculation formula of the real-time weight of each single element is:

[0024] ;

[0025] in, is the real-time weight of the jth single element at the ith sampling point.

[0026] Preferably, the calculation formula for the weighted contrast value of each single element is:

[0027] ;

[0028] in, is the weighted contrast value of the jth single element at the ith sampling point.

[0029] Preferably, the step of determining the background value according to the values ​​of each single element comprises:

[0030] According to each of the single element values, determine the median of each of the single element values ​​and the absolute deviation of each of the single element values; according to the median of each of the single element values ​​and the absolute deviation of each of the single element values, remove discrete data in each of the single element values ​​to determine the current single element data set;

[0031] According to the current single-element data set, determine the median of the current single-element data group and the absolute deviation of the current single-element data group; according to the median of the current single-element data group and the absolute deviation of the current single-element data group, remove discrete data in the current single-element data group to determine the next single-element data set;

[0032] Until there is no discrete data in the next single element data group, the median of the single element data group is determined as the background value.

[0033] Preferably, the calculation formula of the abnormal lower limit is:

[0034] ;

[0035] in, is the abnormal lower limit of a single element; is the number of iterations; is the value coefficient; is the background value of a single element; is the absolute deviation of the single element data set after the nth iteration.

[0036] Preferably, the step of determining the abnormal contrast value of each single element according to the ratio of each single element value to the abnormal lower limit comprises:

[0037] According to the ratio of each of the single element values ​​to the lower limit of abnormality, determining whether the ratio is greater than one;

[0038] When the ratio is greater than or equal to one, the single element value is defined as an abnormal contrast value;

[0039] When the ratio is less than one, the single element value is eliminated.

[0040] By eliminating discrete data in the original data, the data group to be processed is determined from the original data, so as to calculate the background value and the lower limit of the anomaly; then the weighted contrast value of each single element is determined by the anomaly contrast value to achieve the unification of the standard of the data group to be processed, eliminate interference, and improve the accuracy of drawing the comprehensive anomaly map, which is suitable for the screening of anomalies of metal minerals such as antimony and gold. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A schematic flow chart of the mathematical weighting method for optimizing exploration geochemical data analysis according to the present invention.

[0042] Figure 2 This is a comparison table of the background value and anomaly lower limit calculation method of stream sediment data in Yuntaishan area, Anhua, Yiyang, Hunan;

[0043] Figure 3 This is a brief table of the geological characteristics of typical antimony deposits in the central Hunan metallogenic province.

[0044] Figure 4 This is a simple geological map of Hunan Province;

[0045] Figure 5 This is a simple map of mineral geology in the Yuntaishan area of ​​Anhua, Yiyang, Hunan.

[0046] Figure 6 This is a diagram of regional enrichment coefficients of stream sediment geochemistry at different regional scales.

[0047] Figure 7 This is a comprehensive anomaly map of the Yuntaishan area in Anhua, Yiyang, Hunan using the contrast method; a is the 2x contrast method; b is the 2x weighted contrast; the circle represents the 2n contrast multiple; the blue dots are antimony ore. DETAILED DESCRIPTION

[0048] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0049] In the subsequent description, the suffixes such as "module", "component" or "unit" used to represent elements are only used to facilitate the description of the present invention, and have no specific meanings. Therefore, "module", "component" or "unit" can be used in a mixed manner.

[0050] See also Figure 1 To achieve the above purpose, a mathematical weighting method for optimizing exploration geochemical data analysis in a first embodiment of the present invention includes:

[0051] Step S10, obtaining raw data for quantitative determination of mineral abnormalities; wherein the raw data includes several single elements and the values ​​of each single element;

[0052] Step S20, determining the background value according to the values ​​of each single element;

[0053] Step S30, determining the lower limit of abnormality according to the background value and the values ​​of each single element;

[0054] Step S40, determining the abnormal contrast value of each single element according to the ratio of each single element value to the abnormal lower limit;

[0055] Step S50: determining the weighted contrast value of each single element according to the abnormal contrast value of each single element.

[0056] By eliminating discrete data from the original data, the data group to be processed is determined from the original data, so as to calculate the background value and the lower limit of the anomaly; then the weighted contrast value of each single element is determined by the anomaly contrast value to achieve the unification of the standard of the data group to be processed, eliminate interference, and improve the accuracy of drawing the comprehensive anomaly map, which is suitable for the screening of anomalies of metal minerals such as antimony and gold.

[0057] The mathematical weighting method for optimizing exploration geochemical data analysis proposed in the second embodiment of the present invention is based on the first embodiment, step S50, comprising:

[0058] Step S51, selecting one of the single elements that meets the preset conditions and determining it as the standard weight;

[0059] Step S52, determining the contribution of each single element in each collection point, and determining the standard value of each contribution according to the standard weight;

[0060] Step S53, determining the real-time weight of each single element except the one marked as the standard weight according to the standard weight and the standard value;

[0061] Step S54, determining the weighted contrast value of each single element according to the standard weight of the single element that meets the preset conditions, the real-time weight of each single element except the one marked as the standard weight, and the abnormal contrast value of each single element.

[0062] Steps S51 to S54 successively complete the determination of prospecting element weights (i.e., determination of standard weights), determination of the contribution of each single element at each sampling point, standardized contribution (to eliminate dimensional differences, unify scales, and determine each standard value based on standard weights), element weighting (i.e., real-time weights), and data unification (i.e., determination of weighted contrast values), complete data standardization, improve the accuracy of drawing comprehensive anomaly maps, and are applicable to anomaly screening of all maps and mineral types.

[0063] The mathematical weighting method for optimizing exploration geochemical data analysis proposed in the third embodiment of the present invention is based on the second embodiment, and the preset condition is the single element with the highest degree of overlap of the anomaly concentration center in the single element anomaly map formed by each single element; the standard weight is 1.

[0064] The standard weight is the standard weight for prospecting, and the weight of the prospecting target element is set to 1.

[0065] The mathematical weighting method for optimizing the analysis of exploration geochemical data proposed in the fourth embodiment of the present invention is based on the third embodiment, and the calculation formula for the contribution of each single element is:

[0066] ;

[0067] in, is the contribution of the jth single element at the i-th sampling point; is the abnormal contrast value of the jth element at the ith sampling point; m is the total number of all single elements.

[0068] The mathematical weighting method for optimizing the analysis of exploration geochemical data proposed in the fifth embodiment of the present invention is based on the fourth embodiment, and the calculation formula of the standard value of each contribution degree is:

[0069] ;

[0070] in, is the standard value of the jth single element at the ith sampling point, The value range of is 0 to 1; The contribution of the single element with the smallest value among all the contributions of the single elements; It is the contribution of the single element with the largest value among all the contributions of the single elements.

[0071] The mathematical weighting method for optimizing the analysis of exploration geochemical data proposed in the sixth embodiment of the present invention is based on the fifth embodiment, and the calculation formula of the real-time weight of each single element is:

[0072] ;

[0073] in, is the real-time weight of the jth single element at the ith sampling point.

[0074] The mathematical weighting method for optimizing the analysis of exploration geochemical data proposed in the seventh embodiment of the present invention is based on the sixth embodiment, and the calculation formula of the weighted contrast value of each single element is:

[0075] ;

[0076] in, is the weighted contrast value of the jth single element at the ith sampling point.

[0077] The mathematical weighting method for optimizing the analysis of exploration geochemical data proposed in the eighth embodiment of the present invention is based on any one of the second to seventh embodiments, and step S20 includes:

[0078] Step S21, determining the median of each single element value and the absolute deviation of each single element value according to each single element value; eliminating discrete data in each single element value according to the median of each single element value and the absolute deviation of each single element value, and determining the current single element data set;

[0079] Step S22, determining the median of the current single element data group and the absolute deviation of the current single element data group according to the current single element data set; removing discrete data in the current single element data group according to the median of the current single element data group and the absolute deviation of the current single element data group, and determining the next single element data set;

[0080] Step S23, until there is no discrete data in the next single element data group, the median of the single element data group is determined as the background value.

[0081] Specifically, the value obtained by subtracting three times the absolute deviation from the median is used as the lower limit of the current single-element data set, the value obtained by adding three times the absolute deviation from the median is used as the upper limit of the current single-element data set, and the value of each single element between the lower limit of the current single-element data set and the upper limit of the current single-element data set is used as the next single-element data set. The outliers of 20 test elements were eliminated by adding or subtracting three times the absolute deviation, accounting for 0.49% to 2.57% of the total number of samples, indicating that the elimination of outliers has almost no effect on the representativeness of the data. Therefore, it is most objective to calculate the background value by adding or subtracting three times the absolute deviation from the median.

[0082] The mathematical weighting method for optimizing the analysis of exploration geochemical data proposed in the ninth embodiment of the present invention is based on any one of the second to seventh embodiments, and the calculation formula of the lower limit of the anomaly is:

[0083] ;

[0084] in, is the abnormal lower limit of a single element; is the number of iterations; is the value coefficient; is the background value; is the absolute deviation of the single element data set after the nth iteration.

[0085] Specifically, the value of K is manually set according to the actual situation of the original data, and the value range of K is 1.5 to 3.

[0086] Using background values ​​for iterative optimization can weaken the impact of outliers and more accurately reflect the degree of data dispersion.

[0087] The mathematical weighting method for optimizing the analysis of exploration geochemical data proposed in the tenth embodiment of the present invention is based on any one of the first to seventh embodiments, and the step of determining the abnormal contrast value of each single element according to the ratio of each single element value to the abnormal lower limit includes:

[0088] According to the ratio of each single element value to the lower limit of abnormality, it is determined whether the ratio is greater than one;

[0089] When the ratio is greater than or equal to one, the single element value is defined as an abnormal contrast value;

[0090] When the ratio is less than one, the single element value is eliminated.

[0091] The data of single elements without abnormalities are eliminated and further optimized.

[0092] Take the Yuntaishan area in Anhua, Yiyang, Hunan as an example:

[0093] like Figures 3 to 5 As shown in Figure 2, there are more than 170 antimony (gold-tungsten) deposits scattered across the Yuntaishan area of ​​Anhua, Yiyang, Hunan, with different resource combinations such as antimony-gold-tungsten, antimony-tungsten, and single antimony as prominent features (see Figure 4 ), such as the antimony (gold and tungsten) deposits in Xikuangshan, Woxi, Zhazixi, Banxi, and a large number of antimony deposits such as Guanyintang, Tongxin, and Huabanxi, the antimony prospecting potential is huge.

[0094] Antimony ore-bearing strata are extensive and lithologically diverse. From old to new, they are respectively located in the Neoproterozoic Banxi Group shallow metamorphic volcanic-clastic rock formation (such as Woxi, Zhazixi, Banxi), the Sinian Jinjiadong Formation and Liuchapo Formation siliceous rock-carbonate rock formation (such as Guanyintang), the Cambrian Niutitang Formation carbonaceous slate intercalated with siliceous rock formation (such as Zengjiaxi), the Ordovician Qiaotingzi Formation slate formation (such as Huabanxi), the Devonian Shetianqiao Formation (silicified) carbonate rock formation (such as Xikuangshan) (see Figure 3 ).

[0095] Granite bodies are distributed along the southern edge of the Xuefeng arc tectonic belt and are rare in the Xuefeng belt; intermediate-basic vein rocks (diabase, lamprophyre veins) are often revealed in the cores of the ore deposits. The sedimentary strata of the Neoproterozoic Qingbaikou Period, Nanhua Period, Sinian Period and Early Paleozoic in this area have all suffered regional low-level or very low-level metamorphism, which may be caused by the Wuling Movement and the Caledonian Movement.

[0096] The central Hunan region mainly develops NE-trending and NW-trending fault structures, and locally develops NS-trending and nearly EW-trending secondary faults of different orders. The deep and large faults in the basement mainly appear in the NE-trending form, controlling the basic framework of the region; the parallel secondary NE faults and the NW-trending ductile shear faults jointly control the formation of mineral deposits. The folds in the region are mainly compound anticlines with NE as the axis. The folds in the northern syncline are complete in shape and have clear axis traces, while the anticline is cut and reversed by faults and is severely damaged (see Figure 5, where RCC1=Yuntaishan background value in Anhua, Yiyang, Hunan / national background value; RCC2=Dajinping background value / national background value; RCC3=Yangtze platform background value / national background value). The ore deposits in the Precambrian in this area, such as Zhazixi and Tongxin antimony (tungsten) mines, are mainly controlled by NE-trending thrust-nappe faults in monocline strata, and are ore-bearing in NE-trending secondary NWW-trending secondary faults. The antimony deposits in the Paleozoic, such as Guanyintang and Huabanxi, are usually ore-bearing at the superposition of the anticline axis and the NE / NWW fault.

[0097] 907km of river sediment survey in Yuntaishan area of ​​Yiyang, Anhua, Hunan 2 , the sampling particle size is 10 to 60 mesh, and the sampling medium is sandy. According to the distribution pattern of the water system and the geographical features, the sampling points are arranged with the goal of controlling ≥75% of the catchment area; the sampling points are usually designed in the primary water system, and when the primary water system is greater than 500m, the secondary water system control points are added. When sampling, choose the section where the water flow slows down and various particle sizes are easy to converge, so that the proportion of each particle size in the sample is in a natural mixed state, and remove silt, clay and organic matter; 3 to 5 samples are collected within 20 to 30 meters along the flow line to form a sample, and a total of 3,897 samples are collected, with a sampling density of 4.3 points / km2.

[0098] The samples selected 20 elements, including gold (Au), silver (Ag), copper (Cu), lead (Pb), zinc (Zn), arsenic (As), antimony (Sb), mercury (Hg), tungsten (W), tin (Sn), molybdenum (Mo), bismuth (Bi), cobalt (Co), nickel (Ni), chromium (Cr), cadmium (Cd), fluorine (F), barium (Ba), manganese (Mn) and vanadium (V). Among them, Au, W, Cd, Mo, Pb, Cu, Bi and Co elements were analyzed by inductively coupled plasma mass spectrometry, Ni, Ba, Zn, Mn and V elements were analyzed by inductively coupled plasma atomic emission spectrometry, V and Cr elements were analyzed by X-ray fluorescence spectrometry, As and Sb elements were analyzed by atomic fluorescence spectrometry, Ag and Sn elements were analyzed by AC arc-emission spectrometry, and F element was analyzed by ion selective electrode method.

[0099] The quality of field sampling was checked by repeated sampling. 150 samples were randomly repeated, accounting for 3.8% of the total number of samples, of which 138 were qualified, with a qualified rate of 92%. Four national first-level standard materials for stream sediments were selected as monitoring of accuracy and precision. The password was inserted in each analysis batch (a batch of 50 samples) and analyzed together with the samples. A total of 366 samples were inserted in this sample test item. The logarithmic deviation △lgC and standard deviation of the measured values ​​of the four standard materials and the standard values ​​were calculated to measure the accuracy and precision of sample analysis. The mean values ​​of accuracy and precision of daily analysis are within the monitoring limit. The first-time qualified rates of accuracy and precision are both 100%. The reporting rate of each element is greater than 99.1%, the qualified rate of internal inspection is greater than 99.1%, and the qualified rate of abnormal spot checks is greater than 99.6%, which meets the requirements of the specification and the analysis results are accurate.

[0100] Obtained through steps S10 to S30 Figure 2 Chinese data.

[0101] in, Figure 2 The Au content is 10 -9 , Hg content is 10 -9 The content of other elements is 10 -6 .

[0102] According to step S51, in the single element anomaly map, Sb and W are well matched with the Zhazixi antimony and tungsten, the abnormal concentration center overlaps more, and has extremely high abnormal values; Ag, As, Au, Ba, Cd, Hg, Ni and Zn element anomalies are well matched, located on the east side of the Zhazixi antimony mine, indicating element migration; Sb and W are well matched with the Tongxin antimony mine. Sb, Hg, Cd, and Zn are well matched with the Guanyintang antimony mine; Sb, Co, Pb, and Zn are well matched with the Banqiaoxi antimony mine, and the abnormal concentration center overlaps more. Therefore, it is determined that the element with the largest weight in this area is Sb, and the weight of the Sb element is set to 1, indicating the decisive influence of the Sb element anomaly.

[0103] Then, according to step S52 to step S54, the weighted contrast value of each single element is determined.

[0104] The weighted contrast values ​​of 20 single elements in a single sampling point Add together to get the total weighted contrast value Among them, the weight of Sb element is 1, and the weighted contrast value is the abnormal contrast value a Sb ,

[0105] ;

[0106] Among them, m is the single element type of each sampling point.

[0107] Then, according to the weighted contrast values ​​obtained from step S52 to step S54, a plot is drawn based on the weighted contrast values ​​and with an appropriate step length, and finally a geochemical result map is obtained to solve the related problems existing in previous maps (for example, the element combination anomaly method is usually taken from the empirical model of large / super-large deposits, and whether this experience has the wide applicability to guide the exploration of small and medium-sized deposits in the same mining field is questionable; the traditional hand-drawn delineation of comprehensive anomalies is completely dependent on the understanding and drawing level of technical personnel, and the anomaly delineation range is too large and the error is large; the existing data analysis method process is based on experience and has path dependence, and has not been systematically demonstrated to have errors or interference, and the accuracy is problematic). Figure 6 As shown in the figure, after excluding the interference of the catchment basin, the weighted contrast comprehensive anomaly map is consistent with the known mineral deposits and better shows the antimony anomaly concentration zoning and law, proving the reliability of the mathematical weighting method.

[0108] A set of mathematical weighting methods is optimized for the analysis of exploration geochemical data. In the drawing of geochemical maps, more reasonable parameters are provided, and the contribution of different elements to mineral exploration is distinguished and weighted, and the result maps are drawn. The mathematical weighting method can solve the problems existing in traditional methods, accurately and objectively reflect effective mineral-induced anomalies, reduce errors and interference, and is generally applicable to polymetallic minerals such as antimony and gold.

[0109] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a computer-readable storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for enabling a terminal device to enter the method described in each embodiment of the present invention.

[0110] In the description of this specification, the description with reference to the terms "an embodiment", "another embodiment", "other embodiments", or "first embodiment to Xth embodiment" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, method steps or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

Claims

1. A mathematical weighting method for optimizing the analysis of exploration geochemical data, characterized in that: include: Acquiring raw data for quantitative determination of mineral abnormalities; wherein the raw data includes several single elements and values ​​of each single element; Determine the background value based on the value of each single element; Determine the abnormal lower limit according to the background value and the values ​​of each single element; Determining the abnormal contrast value of each single element according to the ratio of each single element value to the abnormal lower limit; According to the abnormal contrast value of each single element, the weighted contrast value of each single element is determined, and the map is drawn according to the weighted contrast value to finally obtain the geochemical result map; The step of determining the weighted contrast value of each single element according to the abnormal contrast value of each single element comprises: Select one of the single elements that meets the preset conditions and determine it as the standard weight; Determine the contribution of each single element in each collection point, and determine the standard value of each contribution according to the standard weight; Determine the real-time weight of each single element except the one marked as the standard weight according to the standard weight and the standard value; Determine the weighted contrast value of each single element according to the standard weight of the single element that meets the preset conditions, the real-time weight of each single element except the one marked as the standard weight, and the abnormal contrast value of each single element; The preset condition is the single element with the highest degree of superposition of the abnormal concentration center in the single element anomaly map formed by each single element; wherein the standard weight is 1; The calculation formula of the contribution of each single element is: ； in, is the contribution of the jth single element at the i-th sampling point; is the abnormal contrast value of the jth element at the i-th sampling point; m is the total number of all single elements; The calculation formula for the standard value of each contribution is: ； in, is the standard value of the jth single element at the ith sampling point, The value range of is 0 to 1; The contribution of the single element with the smallest value among all the contributions of the single elements; The contribution of the single element with the largest value among all the contributions of the single elements; The calculation formula for the real-time weight of each single element is: ； in, is the real-time weight of the jth single element at the ith sampling point; The calculation formula of the weighted contrast value of each single element is: ； in, is the weighted contrast value of the jth single element at the ith sampling point.

2. The mathematical weighting method for optimizing exploration geochemical data analysis according to claim 1, characterized in that: The step of determining the background value according to the values ​​of each single element comprises: According to each of the single element values, determine the median of each of the single element values ​​and the absolute deviation of each of the single element values; according to the median of each of the single element values ​​and the absolute deviation of each of the single element values, remove discrete data in each of the single element values ​​to determine the current single element data set; According to the current single-element data set, determine the median of the current single-element data group and the absolute deviation of the current single-element data group; according to the median of the current single-element data group and the absolute deviation of the current single-element data group, remove discrete data in the current single-element data group to determine the next single-element data set; Until there is no discrete data in the next single element data group, the median of the single element data group is determined as the background value.

3. The mathematical weighting method for optimizing exploration geochemical data analysis according to claim 1, characterized in that: The calculation formula of the abnormal lower limit is: ； in, is the lower limit of the anomaly of a single element; is the number of iterations; is the value coefficient; is the background value of a single element; is the absolute deviation of the single element data set after the nth iteration.

4. The mathematical weighting method for optimizing exploration geochemical data analysis according to claim 1, characterized in that: The step of determining the abnormal contrast value of each single element according to the ratio of each single element value to the abnormal lower limit comprises: According to the ratio of each of the single element values ​​to the lower limit of abnormality, determining whether the ratio is greater than one; When the ratio is greater than or equal to one, the single element value is defined as an abnormal contrast value; When the ratio is less than one, the single element value is eliminated.

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