RU2539808C2 - Method of determining erosional truncation level of ore occurrences, endogenic geochemical anomalies for prospecting thereof - Google Patents

Abstract

FIELD: chemistry.

SUBSTANCE: invention relates to geochemical prospecting and can be used to determine the erosional truncation level of ore occurrences and endogenic geochemical anomalies. The method comprises collecting samples from the surface and from wells of an endogenic envelope or potential ore formation; analysing the samples for indicator elements using a quantitative precision method; based on the analysis results, calculating pair correlation coefficients and constructing ranked series of zoning elements. The erosional truncation level is determined by comparing the pair correlation coefficients and the ranked series with a reference summary table.

EFFECT: faster and more efficient determination of erosional truncation level.

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Description

The technical field to which the invention relates.

Refers to geochemical methods of prospecting ore deposits. Applicable at all stages of exploration.

The level of technology.

The closest technical solution to the claimed one is a method for determining the cutoff level of halos of gold ore deposits (AS USSR No. 681644, MKI 4 GO IV 9/00; 1977). The method includes sampling from bedrock containing ore bodies, analyzing them for the content of mineralization indicator elements, determining a multiplicative zoning coefficient representing the ratio of the product of silver, lead and tin contents to the product of copper and arsenic contents. By comparing the obtained zoning coefficient with the graphs of the zoning coefficients of the reference object, the level of erosion cut is judged.

However, in the prototype of a single cross-section in the early stages of the study of the object to determine the cut level in this way with accuracy to the tier is impossible. For this, it is necessary to have several explored horizons, including those that have crossed the ore interval, when there is no need to determine the cut level. Even deposits of the same type differ significantly in geochemical characteristics, which makes it difficult to determine the level of the ore-bearing geochemical structure by a single multiplicative index of zoning.

3.2.4.3. Disclosure of the invention.

"Of significant interest is the use of changing the nature of the correlation between elements within endogenous halos to assess the depth of an erosive section of an ore body. The use of such geochemical criteria in the near future will undoubtedly allow us to unambiguously assess the prospects of newly discovered deposits and rationally direct exploration to the most interesting objects." A.A. Beus, S.V. Grigoryan, 1975, [2].

It is known from the prior art that "the degree of ordering of the structures of anomalous geochemical fields is considered as the most important structural geochemical sign of oreogenic systems at all hierarchical levels of matter organization from ore nodes to ore bodies inclusive" [4]. Given this argument, the author constructed a model of ordered axial geochemical zonality of elements in the ore-bearing geochemical structure, which is based on extensive factual material on the polyelement and multi-tiered axial zonality of different types of ore deposits [1, Table 58, p. 216]. The model represents a successive change in the maximum concentrations of chemical elements-indicators for the decrease in mineralization. The model of axial zoning optimally for applied purposes includes 7 chemical elements (3 above-ore, 1 ore and 3 under-ore), which, in contrast to indicator elements, are called zoning elements, because they fix discrete layers of mineralization. Due to the difference in zoning elements in deposits of different types, it was necessary to abstract from the symbols of chemical elements. The zoning elements are assigned serial numbers in Arabic numerals and the names corresponding to the model tiers: distantly above-breast-1, breast-2, border-breast-3, ore-4, border-breast-5, breast-6, remote-breast-7. The axial zoning model covers the entire ore-hosting geochemical halo, several kilometers long along the fall of the endogenous geochemical halo. On the axial zonation model, positive and negative signs were visually determined for pair correlation coefficients and ranked series in decreasing average content of elements in mineralization tiers. As a result, on the model of the ore-bearing geochemical structure, 8 tiers by correlation and 13 tiers by ranked rows were established. They join, duplicate and detail each other. The level of detail is such that there are three tiers in the ranked rows per correlation tier. The results of pair correlation of zoning elements and ranked series were combined in a model of axial geochemical zonality, presented in the summary reference table No. 1. The summary table is an induced model of correlation relationships and ranked rows on the axial ordered geochemical zonality in the tiers of the ore-bearing geochemical structure. As a result of lengthy research, the sequence of using the model of the summary reference table for solving applied problems was found.

The subject of the invention is a method of using a pivot table model for solving applied problems. The table was created by the author in 1988, but it was not possible to use it in practice for applied purposes without a way to identify zoning elements from among those analyzed. Consider the design and content of the pivot table.

In the "header" of the table are seven elements of zoning. In the graphs below them are the numbers of elements that have a negative connection with them in each tier. So, in the second tier, elements 2 through 7 have a negative relationship with element 1; in tier V, elements 5 to 7 are negatively connected with elements 1 to 4. Elements 2-7, 5-7 form one subgroup, elements 1, 1-4 form another subgroup. Between subgroups, all zoning elements are negatively related. Therefore, in each subgroup the elements of zoning are positively related. This property of the model is key in using the method for solving applied problems. At first, it was the negative connections of each analyzed element with the rest that erroneously assigned a decisive role. The ranked rows are built on the model of the ordered axial zonality of the ore-bearing halo by reading the sequence of arrangement of the graphs of the content of elements in mineralization tiers. The described properties apply only to zoning elements.

In the early stages of object research, zoning elements are not yet known. Among the analyzed from 15 to 30 or more elements, as a rule, they remain in the absolute minority. But it is known that the desired object is, say, gold ore (or tin, tungsten, etc.). The main ore-forming element, for example, Au, by definition, is a zoning element under No. 4. After calculating the pair correlation coefficients from the sample of analyzed samples, the elements associated with the main ore-forming element No. 4 are positively and negatively written out from the correlation table. As a result, we obtain two subgroups of indicator elements. Next, sort the zoning elements from the indicator elements. To this end, a method has been developed that makes it possible to uniquely identify zoning elements by separately placing the correlation coefficients of each subgroup in a new correlation table. In the first subgroup should remain elements associated with Au and among themselves positively. Elements in the second subgroup must remain positively related to each other, and negatively related to the elements of the first subgroup and Au. Items that do not meet the requirement are removed as unstable. The remaining elements are zoning elements of this section. According to the presence of Au, element No. 4, in one or another subgroup, in the summary table (Table 1), the mineralization layer is found by correlation. In the initial table of precision analysis results for a sample of samples, the average elemental contents (Table 2) are normalized to the clarks of the upper part of the continental crust or to subclarks (the average contents of chemical elements in the main types of igneous rocks). The choice depends on the geological structure of the study area. From the generalized ranked series in a rank sequence, the zoning elements identified by the correlation are written out. The obtained ranked series of zoning elements, which should be seven or more, subject to the identification of paragenetic associations (the method is aimed at the seven-element model of ordered axial zonality), is combined with the formulas of the ranked series from the summary table, the symbols of the chemical elements and the tier are determined by numbers from the ranked series. The latter specifies the location of sampling in the tier by correlation. In the found tier, the position of the section relative to the ore interval and the distance to the ore body in tiers are determined by the formula of the ranked series (Table 1). The arrangement of the elements in the order of the assigned numbers represents a series of axial zoning of the object for this sample of samples. The values of the concentration of elements in the ranked row judge the likely type of ore body, prospects and the distance to it vertically. Visually, the table contains many properties of pair correlation and ranked series that contribute to solving applied problems. Thus, the study of any object in this way is carried out on the main ore-forming element.

Search problems can be solved by one sample of samples from potentially interesting sites, taken from any hypsometric section, including from the surface in the early stages of the study. On the surface, it is used to assess the prospects of ore occurrences, endogenous geochemical anomalies identified by areal surveys in open areas. In underground workings, the method is used to assess the prospects of identified geochemical halos of hidden ore bodies. In closed areas, the use of the method is associated with graded drilling, provided that the wells are introduced into dense bedrock to a depth of at least 3 m. 30 core samples are taken uniformly along the core length for precision analysis and further processing by this method. Sampling from an interval of 30 meters is recommended when drilling deep structural-exploratory wells. The summary table rigidly links all chemical elements into a system where each action and result is checked and duplicated by another action.

Short description of tables

Table 1. Summary reference table of the model of pair correlation coefficients and ranked rows of zoning elements in mineralization tiers.

Table 2. The content of chemical elements in g / t in the interval 229.8-249.0 m in the well GD-10-26, samples 20. Gorny Yuzhny plot.

Table 3. Table of pair correlation coefficients for the content of chemical elements in the well GD-10-26, interval 229.8-249.0 m, samples 20.

The implementation of the invention (technology)

A prospective assessment of the investigated object by the level of erosion cut is the main specialization of the invention. Searches and high-quality (maybe there is a deposit here or not) prospective evaluation of ore objects represent the most important stages of exploration. In the early stages of exploration, geological exploration has high demands on the quality of sampling and processing of samples. Precision types of sample analysis (atomic emission spectrometry, ISP MC, etc.) will undoubtedly increase the reliability of the results of mathematical processing: calculating pair correlation coefficients and ranked series from sample samples. The algorithm of the method is the same for any objects. The method has a tomographic property and can solve applied problems of geochemistry to a depth where mining is absent, one sample of samples.

Over the past two decades, exploration work at promising ore sites has been carried out by private organizations. Since then, intelligence results have become a trade secret. For this reason, the author was unable to obtain the materials necessary to illustrate the invention. Retrospective materials do not meet the requirements of the invention.

As an example, we took a fragment of the Valunisty ore cluster (East Chukotka, Russian Federation), the Gorny Yuzhny site with Au-Ag development, well No.GD-10-26, interval 229.8-249.0 m, sample 20 (Table 2). The reason for choosing this object is due to the classification of this well as one of the deepest on the site, full compliance with the requirements for the quality of sampling, processing and precision analysis of samples. At the prospecting stage of exploration, unpromising objects dominate. This example will allow you to quickly sort the studied objects according to the degree of prospects.

The source material for solving the tasks is a table of the results of a precision analysis of a sample of samples taken according to certain requirements. Next, specific steps provided by the method are sequentially performed.

First step. According to the table of results of precision analysis (Table 2), the following are calculated: 1) pair correlation coefficients (table 3); 2) the average content of elements according to table 2, which normalize to the clarks of the upper part of the continental crust.

Second step. From Table 3 about the ore-forming elements Au and Ag (usually they write about one main ore-forming element), we write separately the elements that are positively associated with them: Au + Ag, Cr, Cu, Li, Mo, Pb, Sb, Zn - the first subgroup; negatively: Au-Ba, Co, Mn, Ni, Sr - the second subgroup. Positive: Ag + Au, Cr, Cu, Li, Mo, Pb, Sb, Zn; negative: Ag-Ba, Co, Mn, Ni, Sr. The uniformity of the subgroups confirms the paragenetic relationship of Au and Ag (r = 0.85).

The third step solves the most important problem - identifying the elements of zoning by correlation. To do this, use the main property of zoning elements in mineralization tiers (Table 1). The property states that within the subgroups the elements are correlated positively, between the subgroups - negatively. The algorithm consists in section of the correlation table No. 3 into two separately for each subgroup.

It is easy to verify that the negative bonds are due to Mo and Pb, which have a strong positive relationship, r = 0.91. They form an independent subgroup that is not associated with the first subgroup. Cu is adjacent to the new subgroup, having a correlation coefficient of 0.78 with Pb and 0.59 with Mo. The bond of Cu with other elements of the first subgroup is much weaker. On this basis, Mo, Pb and Cu are excluded from the first subgroup, together with the elements associated with them (shown in font). The zoning elements of the first subgroup are recognized: Au, Ag, Cr, Li, Sb and Zn. Of the six elements, Sb, Li, Ag, and Cr have bonds with Au and with each other that are close to paragenetic. By the bond strength (0.49), the Zn element only approaches Li. But Li has strong ties to all elements of the subgroup. By correlation, Zn differs from the elements of the subgroup by a weak positive relationship. From any number of analyzed elements, the method identifies seven zoning elements, but there may be more of them under the condition of a paragenesis of some elements. Paragenetic associations in the first subgroup are: (Au, Ag), an Au-Ag object. The remaining elements will remain independent until the number of zoning elements is determined. Naturally, the correlation tables are never repeated, due to the natural difference in the objects of study. First of all, as a rule, elements that have the maximum number of negative links with other elements are removed. In zones of diffuse mineralization, not simple tasks happen.

To find the elements of zoning in the second subgroup, one should use the negative connection property between the subgroups. The first subgroup is known. Therefore, the removal of unstable elements associated with the first subgroup positively should be carried out only from the second subgroup or on the principle of less loss.

Table 5 Correlation of zoning elements of the first subgroup with the second subgroup Ag Cr Li Sb Zn Au Wa -0.81 -0.80 -0.88 -0.81 -0.57 -0.81 With -0.76 -0.77 -0.77 -0.65 -0.46 -0.76 Mn -0.59 -0.69 -0.57 -0.44 -0.18 -0.59 Sr -0.59 -0.69 -0.58 -0.42 -0.21 -0.59 Ni -0.03 -0.02 0.02 0.08 -0.07 -0.05

Ni having a positive relationship with Li and Sb (isolated) is excluded from the second subgroup. The zoning elements of the second subgroup are Ba, Co, Mn, Sr. A strong positive relationship between Ba and Co and Mn confirms Ba's involvement in this subgroup. Most often, Ba is attributed to the above-the-body elements. It remains to verify that all the zoning elements of the second subgroup are positively related.

Table 6 Correlation of zoning elements of the second subgroup Wa With Mn Sr Wa one 0.78 0.87 0.49 With one 0.72 0.84 Mn one 0.77 Sr one

Within both subgroups, strong positive relationships are noted. This is likely due to an insufficient number of samples in the sample. Particular attention is paid to the sign at "zero" coefficients, which can be opened on more zeros before the first significant digit after the decimal point. Negative connections between the elements of zoning of subgroups convincingly showed their antagonism. In the second subgroup, paragenetic bonds should be recognized as Mn-Ba (0.87) and Sr-Co (0.84). Their numbers are determined only in the ranked row. Thus, two twin breast elements were identified under the numbers 6 - the breast and 7 - distant-breast (Table 1). Therefore, the border-under-breast element at number 5 is part of the first subgroup and it can be Zn. Judging by the composition of the chemical elements, the first subgroup is the sternum (Ag, Sb), the second is the sternal (Co, Mn). From the pivot table, you can determine the tier by the correlation to which this sample of samples belongs, taking into account the presence of the border-pectoral element 5. This is the VI border-pectoral element in which the zoning elements (1-5) are negatively related to the elements (6- 7) (table 1).

Fourth step. The generalized ranked series of analyzed elements in concentration clarks (above element symbols) has the following form:

39.5 29.6 24.4 5.21 3,55 3.53 2.94 2,52 1.37 1.36 0.68 0.45 0.22 0.13 0.04 Sb Ag Au Pb Mo Li As Zn Mn Ba Cr Sr Cu Co Ni

The generalized row indicates a border-above-thoracic section (see Table 1). The Sb, Ag are led by the above elements, and the Co and Ni are led by the above elements. Au in the ranked row is in third position, which facilitates the diagnosis of the longline. The average content of Au 0.0975 g / t (maximum 0.48 g / t - 120 clarks) and Ag 2.77 g / t (Table 2) today does not meet the requirements of the industry. The concentration of a number of elements is increased, but not abnormal. It confirms that the object has a gold-silver specificity. Here you can interpret ZRM. With negative "concentrations" of chemical elements that differ in hundredths of clarke, the probability of errors in the construction of a ranked series increases. Elements may take up their places in the zoning row due to insufficient analysis sensitivity. All this can be exacerbated by an insufficient number of samples in the sample.

Fifth step. From the generalized ranked series, we write down all the found zoning elements in the rank sequence: Sb, (Ag, Au), Li, Zn, (Mn, Ba), Cr, (Sr, Co). We single out the elements that have a paragenetic connection. As a result, seven (!) Elements remained. The ore-forming element reached the second position. In table 1, each tier is characterized by an individual formula of a ranked row. This row is close to tiers 5 and 6. Tiers 5 and 6 are headed by elements 3 and 4 (the elements in brackets can be interchanged), followed by elements 2 or 5, and completes the distantly sub-base element 7. Formula of tier 5 - 3 (4 2) (5 1) 6 7, tier 6 - (4 3) (5 2) (6 1) 7. The choice of zoning elements is a creative process. Here you need to pay attention to any distinguishing details of the correlation analysis and ranked series. By correlation, Zn is a contender for border element # 5. It is located in a ranked row behind Au through Li. In tier 5, elements Nos. 6 (Mn, Ba) and 7 (Sr, Co) are located nearby. In our ranked row they are separated by chrome. In tier 6, ore element No. 4 is in the first bracket with element No. 3 and may occupy the second position. In the same tier, elements nos. 6 and 7 can be located through element n ° 1. Tier 6 is fully consistent with the ranked row. Let's combine the tier 6 formula with the found ranked row. Under the elements we put the No. of zoning elements corresponding to tier 6, taking into account paragenetic associations. When numbering the zoning elements in the ranked row, the elements belong to the above-breast (1, 2, 3) and to the second (5, 6, 7) elements. The formula contains 7 elements, paragenetic associations are known. Thus, zoning elements can have the following numbers:

Sb (Ag, Au) Zn Li (Mn, Ba) Cr (Sr, Co) (3 four) (5 2) (6 one) 7

The borderline-submarine Zn is united in one bracket with Li. The proximity of Zn to Li was previously noted in the correlation analysis. As a result, we have, by correlation, the tier VI of the border-submarine, and by the ranked row, the tier 6 is the upper ore-bearing (Table 1). They contradictory characterize one section, which indicates the absence in the object of an ordered axial zonality of the elements. Correlation and ranked series reflect different characteristics of the geochemical field. Correlation reveals paragenetic associations of elements, subgroups of elements positively and negatively associated with the ore-forming element and among themselves, finds zoning elements and determines the level of mineralization cutoff by correlation. The ranked series characterizes the structure of the geochemical field according to the degree of concentration of elements, refines the cutoff level and determines the axial geochemical zonality of the studied object. In a ranked row in brackets are elements that have a paragenetic relationship. They are recognized as one element. In the ranked series formula, the elements in brackets are formed as a result of the intersection of the graphs of the average contents of the elements at the point where the content of one element with a higher number increases, and the content of another with a lower number decreases. For this reason, the elements in parentheses can be interchanged. Here a property arises that allows a more detailed determination of the cutoff level and the location of sampling. If the element with the lower number (in this case, element No. 3) is located in the first bracket in front, then the sample of samples is taken in the upper half of the tier according to the ranked rows (in this case, tier No. 6). If with a large number, then in the lower half. That is, the tier in the ranked rows is divided into two sub-tiers. In each tier by correlation, there are four sub-tiers in the ranked rows.

This cross section corresponds to the SRM, which is clearly confirmed by the property of the divergence of the diagnosis of tiers according to the correlation and the ranked series and low concentrations of elements. Ore-bearing sections are characterized by abnormal contents of elements in the first half of the ranked series formulas (Table 1) and high contents of ore-forming elements in ore and boundary layers. A series of axial zoning in the interval 229.8-249.0 m can be as follows (from top to bottom):

Cr Li Sb (Ag, Au) Zn (Mn, Ba) (Sr, Co) one 2 3 four 5 6 7

The resulting series of axial zoning corresponds only to this 19.2-meter interval, it is not a number of axial zoning of the entire well and, especially, of the entire object. With ordered zonality, such a series can characterize the axial zonality of the entire object. Unstable elements and elements forming new independent subgroups, such as (Mo, Pb, Cu), by this algorithm are successfully detected and separated from zoning elements. New closely related subgroups of elements can represent independent mineralization stages, which is very important for the study of ore genesis.

Findings. As a result of the study, it can be argued that in the well to a depth of 249 m above-ground RMS was installed. There is a false reason for the limited continuation of structural search to a depth of 500 m in order to identify possible hidden mineralization. None of the studied numerous wells of a number of sections of the Valunisty ore field revealed a sub-ore cut-off level in the ranked rows. In the ore-bearing structure, it must be mandatory. The generalized ranked row and private ranks showed above-the-body ZRM. However, the ZRM cancels out the hope of identifying an ore body at a depth of up to 500 m. This conclusion is based on the absence of an ordered axial zonality. A large amount of prospecting, mining, drilling up to 250 m of all identified quartz veins, sulphidization and vein zones, was performed at the sites of the Bouldery ore cluster, but not a single object was recognized as promising. Exploration ceased as unpromising. The method 100% confirmed the results of many years and voluminous search and evaluation work. In this way, in the early stages of the study of an object from the surface, it was possible to avoid the large expenditures of material resources for prospecting and evaluating exploration work and to confine ourselves to only areal and detailed geochemical works and a rare network of mine workings (ditches).

This study was performed to determine the prospects for the deep horizons of the explored area using the tomographic properties of the method. In six sections of the Boulder ore cluster, this method investigated 10 samples from 7 ditches and 21 samples from 12 wells. All of them showed a similar result - above-the-body ZRM. High Au contents of up to 10 g / t or more have a fragmentedly interspersed nesting structure that does not form ore bodies. The absence of ordered axial zonality indicates the incompleteness of the ore-forming process.

At ore-hosting facilities, this algorithm will reliably determine the level of erosion cut of the investigated object, a number of axial zoning of the entire object, its prospects and the direction of further exploration. In this case, the mineralization cutoff level is determined (Table 1) by the field of combining one of the three tiers in the ranked rows with the tier in correlation. An ordered geochemical zonality is usually possessed by industrially promising objects.

The method has a tomographic property, efficiency, unique economic and technological efficiency.

Sampling and processing requirements.

1. Samples with homogeneous material are combined in the sample: either host rocks or metasomatites. or potentially ore formations. Mixing samples of different composition is unacceptable. Preference belongs to the latter.

2. On the surface, the number of samples (chips, ores) required for correlation analysis should be taken by “cluster” (selectively, by an irregular network, instead of the accepted rectangular or square network of sampling) using an isometric area of about 100-1000 sq.m.

3. At the search stage, samples from wells are taken from each meter without gaps. A sample of samples is formed from an interval of 30 m in depth to reduce the likelihood of clogging of the sample with samples belonging to other tiers. This allows you to increase the accuracy of determining the average boundaries of the tiers of the ore-hosting geochemical halo. During graded drilling, the well should go deeper into solid bedrock of at least 3 m. At least 30 fragmented samples arriving for precision analysis are uniformly taken from this interval.

4. At the stage of sorting out geochemical halos, samples are taken from the nuclear zones of geochemical or hydrothermal anomalies. The cores, as a rule, are characterized by the maximum erosion section of the endogenous geochemical halo brought to the surface.

Bibliography

1. Handbook of geochemical prospecting for minerals. Edited by A.P. Solovova. M .: Nedra, 1990.

2. Beus A.A., Grigoryan S.V. Geochemical methods of prospecting and exploration of solid minerals. M .: Nedra, 1975.

3. Grigoryan S.V., Ovchinnikov L.N. Scientific discovery of the USSR. The pattern of zonal distribution of indicator elements in primary geochemical halos of sulfide-containing hydrothermal ore deposits. TSB Yearbook, 1980.

4. Sokolov S.V., Shevchenko S.S. Tasks for increasing the efficiency of geochemical exploration geochemistry. Applied Geochemistry. Issue 8, Volume 2. M .: IMGRE, 2008, pp. 3-15

table 2 The content of chemical elements in g / t in the range of 229.8-249.0 m along the well GD-10-26 (KK - Clark concentration) Interval m Au Ag As Ba Co Cr Cu Li Mn Mo Ni Pb Sb Sr Zn 229.8 230.8 0.01 1 0.5 5 818 4.8 63 7.5 72.9 1442 2.7 3 fourteen 5 183.1 80.5 230.8 231.8 0.01 0.9 5 903 5.8 26 6.2 62.7 1200 3.4 2,5 12 5 196.2 86.4 231.8 232.8 0.01 1.1 5 934 5,6 43 6.5 70,2 1267 2.9 1.8 12 5 195.3 64.3 232.8 233.8 0.01 0.5 5 659 4.6 84 6.2 99,2 965 3,1 1.7 fourteen 5 138.5 99.3 233.8 235 0.01 0.5 5 953 5.9 29th 5.8 68.8 1273 four 2,4 13 10 199 89.6 23S 236 0.01 1 0.5 5 962 6.3 46 10,2 89.2 1086 4,5 3.8 16 6.9 178 114.8 236 237 0.02 0.5 5 1003 6.2 28 9,4 71.7 1231 3,5 1.7 9 5 176.1 105,2 237 238 0.12 0.5 5 1155 6.3 35 5.9 66,2 1337 3.6 1,5 eleven 5 198.2 120.9 238 239 0.01 2.2 5 961 5.5 57 5.2 81.3 1338 3.9 2,5 eighteen 7.8 163.9 338.7 239 240 0.04 1,6 5 867 6 55 10.9 91 1277 3 four 199 8 140, S 74,2 240 240.7 0.45 22.6 5 42 one 112 20,2 168.6 872 2,8 1.9 thirty 19.1 110,4 275.5 240.7 241.4 0.21 4.6 5 51 one 117 10.6 184.9 898 3 2 213 14.7 102.5 7296.8 241.4 242.2 0.17 5.5 5 521 ZD 85 31.1 80 465 8.2 2,3 5118 5 79.3 709.6 242.2 243.2 0.48 9 5 202 1,2 219 5, S 230,2 539 four 2.6 350 20.6 41.5 365.5 243.2 244.2 0,07 1,1 5 993 3.8 70 9.8 83,4 725 3,1 1,5 191 8.7 103.8 101,2 244.2 245.2 0.06 1,2 5 925 2,5 75 7 94.9 702 3.4 1,2 31 5 90.1 143.9 245.2 246.2 0.1 0.5 5 877 2.9 63 6.2 93.6 874 ZD 1.4 40 7.3 88.7 174.3 246.2 247.2 0.04 0.5 5 950 3.6 58 12.5 75.3 1130 3.2 one 89 5 105.1 198.2 247.2 248 0,03 0.9 S 977 3.8 45 16.7 73.8 1246 2.6 1.9 95 5 101.1 441.2 248 249 0.09 0.7 5 1070 4.3 40 13,2 67 1284 3,1 3.2 228 5 104.5 69.9 Average 0.0975 2.77 S 791.15 4.21 67.5 10.33 96,245 1057.55 3,555 2,195 335.15 7,905 134.79 547.5 QC 24,375 29.57 2.94 1.36 0.18 0.68 0.22 3.53 1.37 3,55 0.04 20.95 39.53 0.46 7.2

Table 3 Pair correlation coefficients of element contents along well GD-10-26, interval 229.8-249.0 m. Samples 20. Au Ag As Ba With Cr Cu Li Mn Mo Ni Pb Sb Sr Zn Au 1.00 Ag 0.85 1.00 As #DEL / 0! #DEL / 0! 1.00 Ba -0.81 -0.78 #DEL / 0! 1.00 With -0.76 -0.63 #DEL / 0! 0.78 1.00 Cr 0.84 0.58 #DEL / 0! -0.80 -0.77 1.00 Cu 0.29 0.44 #DEL / 0! -0.33 -0.34 0.09 1.00 Li 0.87 0.67 #DEL / 0! -0.88 -0.77 0.93 0,03 1.00 Mp -0.59 -0.41 #DEL / 0! 0.57 0.72 -0.69 -0.39 -0.57 1.00 Mn 0.11 0.06 #DEL / 0! -0.12 -0.01 0.11 0.59 -0.05 -0.48 1.00 Ni -0.05 -0.02 #DEL / 0! 0.00 0.33 -0.02 0.05 0.01 0.28 0.14 1.00 Pb 0.17 0.14 #DEL / 0! -0.23 -0.19 0.15 0.78 -0.03 -0.52 0.91 0.05 1.00 Sb 0.87 0.78 #DEL / 0! -0.81 -0.65 0.80 0,03 0.91 -0.44 -0.08 0.08 -0.10 1.00 Sr -0.59 -0.36 #DEL / 0! 0.49 0.84 -0.69 -0.41 -0.58 0.77 -0.16 0.21 -0.33 -0.42 1.00 Zn 0.23 0.12 #DEL / 0! -0.57 -0.46 0.30 0.08 0.49 -0.18 -0.04 -0.06 0.05 0.35 -0.21 1.00

Claims (1)

A method for determining the level of erosion cut of ore occurrences and endogenous geochemical halos for the purpose of their prospective assessment, based on the constructed model (Table 1) of the ordered axial geochemical zonality of chemical elements, by which the correlation between them and the ranked rows are visually determined, characterized in that the sample of samples selected from a surface in a “bush” way, selectively with a limited area of homogeneous material, in the wells, chips are taken from an interval of up to 30 meters, samples are analyzed using the isionic method and according to the analysis results, pair correlation coefficients are calculated, according to which two subgroups of elements are identified separately, positively and negatively associated with the main ore-forming element, the correlation results of each subgroup are placed in the correlation table in order to distinguish seven zoning elements according to the correlation property, which consists in that in each subgroup the elements of zoning are positively related to each other, negatively between the subgroups; the identified zoning elements in table 1 determine the tier, which is the cutoff level by correlation; according to the results of a precision analysis of all analyzed elements, their average contents are calculated, normalized to the clarks of the upper part of the continental crust, a ranked series is constructed by decreasing concentrations of indicator elements, from which the zoning elements found by correlation are written in a rank sequence, as a result, an individual ranked series of zoning elements is obtained, combine it with a similar formula of a ranked row in mineralization tiers (Table 1), find an identical tier that shows sets the cutoff level of the research object by the ranked row and the place of sampling; in the master reference table 1, when combining (docking) the tier according to the ranked tier with the tier by correlation, the cutoff level of the object, a number of axial zoning of the elements are determined, the prospective assessment of the object and the type of expected field are determined by the degree of concentration of indicator elements in the sample from the order of zoning; when the readings of the tiers differ by correlation and the ranked row, they conclude that there is a zone of diffuse mineralization, the absence of an ordered geochemical zonality at the object, and a negative perspective assessment of the object.