CN112364303A - Ore finding target area delineating method and system based on geochemical data - Google Patents
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Abstract
The invention relates to a method and a system for delineating a target area of an ore exploration based on geochemical data, which belong to the field of prediction of ore exploration. The invention provides a new geochemical data processing method by combining a principal component analysis method with the existing regression method, and the target area of the given ore can be accurately defined according to the scheme, thereby improving the accuracy of the prediction of the formed ore.
Description
Technical Field
The invention relates to the field of mining prediction, in particular to a method and a system for delineating a target area of a mine finding target based on geochemical data.
Background
The target area delineation of the ore is a key step of mineral exploration and has strategic and tactical significance. A large amount of mineral resources have been discovered internationally through the work of geochemical exploration, which is a common method of mineral exploration.
The predecessors determine the lower limit of the abnormality by different data processing methods, so as to define the geochemical abnormality and provide a basis for defining the target area of the ore exploration. Common methods include a mean value + 2-fold standard deviation method, a concentration-area fractal method, and the like. The methods usually only consider one or a plurality of element information, the information mining depth of the reaction of the method on the survey data set is not enough, and the result of finding the mine is often not accurate.
Disclosure of Invention
The invention aims to provide a method and a system for delineating an ore-finding target area based on geochemical data, which combine a principal component analysis method and a regression method and improve the accuracy of the delineation of the ore-finding target area.
In order to achieve the purpose, the invention provides the following scheme:
a method for delineating a target area for prospecting based on geochemical data comprises the following steps:
acquiring geochemical data of a region to be processed;
performing principal component analysis according to the geochemical data, determining target geochemical element variables and obtaining factor scores of each principal component;
performing linear regression analysis on the target geochemical element variable and the factor scores of the main components to obtain a residual error;
determining a residual error background value by using a concentration-area fractal method according to the residual error;
carrying out interpolation processing on the residual error to obtain a contour map or a grid map;
re-classifying the contour map or the grid map according to the residual background value to obtain an ore-finding target area; the ore finding target area is an area with a residual value higher than the residual background value in the contour map or an area with a residual value higher than the residual background value in the grid map.
Optionally, after the acquiring the geochemical data of the area to be processed, the method further comprises: performing data cleaning on the geochemical data;
the specific process of performing data cleansing on the geochemical data comprises the following steps:
acquiring the geochemical data;
comparing the geochemical data with the detection limit to obtain data higher than the detection limit and data lower than the detection limit;
replacing the data below the detection limit with 1/2 of the detection limit to obtain replacement data;
and forming the data above the detection limit and the replacement data into cleaned geochemical data.
Optionally, the performing principal component analysis according to the geochemical data to determine a target geochemical element variable and obtain a factor score of each principal component specifically includes:
performing principal component analysis on the geochemical data by using SPSS software, R software or GeoDa software to obtain the correlation between each principal component and the target geochemical element variable and generate a lithotripsy graph and a factor load graph;
determining the optimal principal component number according to two indexes that the number of variables with characteristic values larger than 1 and the variance ratio of the accumulated interpretation of each principal component are larger than 60% in the lithotripsy graph; the accumulated interpretation of each principal component is the sum of the ratio of the explained variance of each principal component and the overall variance;
determining the geochemical variables forming each factor according to the variable of which the ordinate value is more than 1 in the factor load graph;
and calculating the factor score of each principal component by using rgr package, SPSS or GeoDa software in the R language according to the optimal principal component number and the geochemical variables of each factor.
Optionally, the determining, according to the residual error, a residual error background value by using a concentration-area fractal method specifically includes:
generating a concentration-area graph by utilizing a caplot function in rgr packages of the R language according to the residual error;
and determining a residual background value according to the inflection point of the concentration-area diagram.
An ore target delineation system based on geochemical data, the ore target delineation system comprising:
the data acquisition module is used for acquiring geochemical data of the area to be processed;
the principal component analysis module is used for performing principal component analysis according to the geochemical data, determining a target geochemical element variable and obtaining a factor score of each principal component;
the linear regression analysis module is used for carrying out linear regression analysis on the target geochemical element variable and the factor scores of the main components to obtain a residual error;
the residual error background value determining module is used for determining a residual error background value by utilizing a concentration-area fractal method according to the residual error;
the interpolation processing module is used for carrying out interpolation processing on the residual error to obtain a contour map or a grid map;
the reclassification module is used for reclassifying the contour map or the grid map according to the residual background value to obtain an ore searching target area; the ore finding target area is an area with a residual value higher than the residual background value in the contour map or an area with a residual value higher than the residual background value in the grid map.
Optionally, the system for delineating the target area for finding the mine further comprises: a data cleaning module;
the data cleaning module is respectively connected with the data acquisition module and the principal component analysis module;
the data cleaning module specifically comprises:
a data acquisition unit for acquiring the geochemical data;
the data comparison unit is used for comparing the geochemical data with the detection limit to obtain data higher than the detection limit and data lower than the detection limit;
a data replacement unit for replacing the data below the detection limit with 1/2 of the detection limit to obtain replacement data;
a cleaned geochemical data construction unit for constructing the data above the limit of detection and the replacement data into cleaned geochemical data.
Optionally, the principal component analysis module specifically includes:
the graph generation unit is used for carrying out principal component analysis on the geochemical data by utilizing SPSS software, R software or GeoDa software to obtain the correlation between each principal component and the target geochemical element variable and generate a lithotripsy graph and a factor load graph;
the optimal principal component number determining unit is used for determining the optimal principal component number according to two indexes that the variable number of the lithotripsy graph with the characteristic value larger than 1 and the variance ratio of the accumulated interpretation of each principal component are larger than 60%; the accumulated interpretation of each principal component is the sum of the ratio of the explained variance of each principal component and the overall variance;
a geochemical variable determining unit for forming each factor, for determining the geochemical variable forming each factor according to the variable of which the ordinate value is more than 1 in the factor load graph;
and a factor score calculating unit for calculating the factor score of each principal component by using rgr package, SPSS or GeoDa software in R language according to the optimal number of principal components and the geochemical variables of each factor.
Optionally, the residual background value determining module specifically includes:
a density-area map generating unit for generating a density-area map using a caplot function in rgr package in the R language from the residual error;
and the residual background value determining unit is used for determining a residual background value according to the inflection point of the concentration-area diagram.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects: the invention combines a principal component analysis method and a linear regression method, provides a new geochemical data processing method and a system, and can accurately define the target area of the ore formation according to the scheme and improve the accuracy of the prediction of the ore formation.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a schematic flow chart of a method for delineating a target area of an ore-exploration target based on geochemical data according to the present invention;
FIG. 2 is a lithograph of principal component analysis;
FIG. 3 is a factor load graph;
fig. 4 is a schematic diagram of a system for delineating a target area for an ore exploration based on geochemical data provided by the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the objects so described are interchangeable under appropriate circumstances. Furthermore, the terms "comprising" and "having," as well as any variations thereof, are intended to cover non-exclusive inclusions.
In this patent document, the drawings discussed below and the embodiments used to describe the principles of the present disclosure are by way of illustration only and should not be construed in any way to limit the scope of the present disclosure. Those skilled in the art will understand that the principles of the present invention may be implemented in any suitably arranged system. Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. Further, a terminal according to an exemplary embodiment will be described in detail with reference to the accompanying drawings. Like reference symbols in the various drawings indicate like elements.
The terms used in the description of the present invention are only used to describe specific embodiments, and are not intended to show the concept of the present invention. Unless the context clearly dictates otherwise, expressions used in the singular form encompass expressions in the plural form. In the present specification, it is to be understood that terms such as "comprising," "having," and "containing" are intended to specify the presence of stated features, integers, steps, acts, or combinations thereof, as taught in the present specification, and are not intended to preclude the presence or addition of one or more other features, integers, steps, acts, or combinations thereof. Like reference symbols in the various drawings indicate like elements.
The invention aims to provide a method and a system for improving the delineation accuracy of an ore-finding target area.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Fig. 1 is a schematic flow chart of a method for delineating a target area of an ore exploration target based on geochemical data, which specifically includes:
step 101: geochemical data of the area to be treated is acquired.
Step 102: and performing principal component analysis according to the geochemical data, determining target geochemical element variables and obtaining factor scores of the principal components.
Step 103: and carrying out linear regression analysis on the target geochemical element variable and the factor scores of the main components to obtain a residual error.
Step 104-1: and determining a residual error background value by using a concentration-area fractal method according to the residual error.
Step 104-2: and carrying out interpolation processing on the residual error to obtain a contour map or a grid map.
Step 105: re-classifying the contour map or the grid map according to the residual background value to obtain an ore-finding target area; the ore finding target area is an area with a residual value higher than the residual background value in the contour map or an area with a residual value higher than the residual background value in the grid map.
The process of linear regression analysis is described again with gold as an example:
and introducing the gold element content and the scores of the main component factors into the Rstudio.
And calling rlm functions in the MASS package, taking gold elements as dependent variables, and performing linear regression analysis by taking each principal component factor as an independent variable.
The term Residual returned by the above calculation result is the Residual error. I.e. the difference between the original content of gold element and the calculated value according to the linear regression analysis equation, i.e. the difference between the actual value and the estimated value.
When the residual error is interpolated, the common kriging method or the distance square inverse ratio method is selected.
According to the method, a residual error is obtained through principal component analysis and linear regression, then a residual error background value is determined according to the residual error, interpolation processing is carried out to obtain a contour map or a grid map, and finally an ore finding target area is defined according to comparison between the residual error background value and a residual value in the contour map or a residual value in the grid map.
The method for delineating the target area of the ore exploration based on the geochemical data further comprises data cleaning, and the process specifically comprises the following steps:
acquiring the geochemical data.
And comparing the geochemical data with the detection limit to obtain data higher than the detection limit and data lower than the detection limit.
Replacing the data below the detection limit with 1/2 of the detection limit results in replacement data.
And forming the data above the detection limit and the replacement data into cleaned geochemical data.
For collected data, data cleaning can be performed firstly, data with large deviation is eliminated, the cleaned geochemical data are obtained, then principal component analysis is performed on the cleaned geochemical data, control is performed on the aspect of data, the usability of the data is improved, and the accuracy of final target area delineation for finding the mine is improved.
In the specific implementation process, the SPSS software, the R software or the GeoDa software is used for carrying out principal component analysis to obtain the factor score of each principal component.
Fig. 2 and 3 are a principal component analysis lithotripsy map and a factor load map, respectively, generated by principal component analysis of the geochemical data using SPSS software or R software.
Then determining the optimal principal component number according to two indexes of the variable number with the characteristic value larger than 1 and the variance ratio of the accumulated explanation of each principal component larger than 60% in the lithotripsy graph; the principal component accumulations are interpreted as the sum of the variance of each principal component interpretation and the ratio of the overall variance.
And determining the geochemical variables forming each factor according to the variable with the ordinate value being more than 1 in the factor load diagram.
And calculating the factor score of each principal component by using rgr packet, SPSS software or GeoDa software in the R language according to the optimal principal component number and the geochemical variables of each factor.
The process of determining the residual background value by using the concentration-area fractal method (C-A) is to generate a concentration-area graph by using a capplot function in rgr packages of R language and then determine the residual background value according to the inflection point of the concentration-area graph. And importing the residual contour map or the grid map into GIS software, adopting a reclassification function of the GIS, and setting the area of the residual value in the contour map or the residual value in the grid map higher than the background value as warm color and the area of the residual value lower than the background value as cold color according to the residual background value. The warm color area is an abnormal area of the residual value, namely the target area for finding the ore.
And carrying out space comparison analysis on the obtained ore target area and the ore deposit (point) file on a GIS platform, determining the number n of the ore deposits (points) in the ore target area, determining the ratio of n to the total ore deposit (point) number as a success rate, and if the success rate is more than 50%, indicating that the prediction success rate is higher. According to experimental results, the invention obtains residual errors by utilizing principal component analysis and linear regression, provides a new geochemical data processing method, can accurately define the target area of the ore formation according to the scheme, improves the accuracy of the prediction of the ore formation, and has the success rate higher than 50 percent.
Fig. 4 is a system for delineating a target area for prospecting based on geochemical data, which comprises: the system comprises a data acquisition module 201, a data cleaning module 202, a principal component analysis module 203, a linear regression analysis module 204, a residual background value determination module 205, an interpolation processing module 206 and a reclassification module 207.
The data acquisition module 201 is used for acquiring geochemical data of the area to be processed.
The data cleaning module 202 is configured to pre-process the geochemical data of the area to be processed to obtain cleaned geochemical data.
The principal component analysis module 203 is configured to perform principal component analysis according to the cleaned geochemical data, determine a target geochemical element variable, and obtain a factor score of each principal component.
The linear regression analysis module 204 is configured to perform linear regression analysis on the target geochemical element variables and the factor scores of the principal components to obtain a residual error.
The residual background value determining module 205 is configured to determine a residual background value according to the residual by using a concentration-area fractal method.
And the interpolation processing module 206 is configured to perform interpolation processing on the residual error to obtain a contour map or a grid map.
The reclassification module 207 is configured to reclassify the contour map or the grid map according to the residual background value to obtain an ore-searching target area; the ore finding target area is an area with a residual value higher than the residual background value in the contour map or an area with a residual value higher than the residual background value in the grid map.
The data cleaning module 202 specifically includes:
a data acquisition unit for acquiring the geochemical data.
And the data comparison unit is used for comparing the geochemical data with the detection limit to obtain data higher than the detection limit and data lower than the detection limit.
And a data replacement unit for replacing the data below the detection limit with 1/2 of the detection limit to obtain replacement data.
A cleaned geochemical data construction unit for constructing the data above the limit of detection and the replacement data into cleaned geochemical data.
The principal component analysis module 203 specifically includes:
and the graph generation unit is used for carrying out principal component analysis on the geochemical data by utilizing SPSS software, R software or GeoDa software to obtain the correlation between each principal component and the target geochemical element variable and generate a lithotripsy graph and a factor load graph.
The optimal principal component number determining unit is used for determining the optimal principal component number according to two indexes that the variable number of the lithotripsy graph with the characteristic value larger than 1 and the variance ratio of the accumulated interpretation of each principal component are larger than 60%; the principal component accumulations are interpreted as the sum of the variance of each principal component interpretation and the ratio of the overall variance.
And a geochemical variable determining unit for determining the geochemical variable forming each factor according to the variable of which the ordinate value is more than 1 in the factor load graph.
And a factor score calculating unit for calculating the factor score of each principal component by using rgr package, SPSS or GeoDa software in R language according to the optimal number of principal components and the geochemical variables of each factor.
The residual background value determining module 205 specifically includes:
and a density-area map generating unit for generating a density-area map by using a caplot function in rgr package of the R language according to the residual error.
And the residual background value determining unit is used for determining a residual background value according to the inflection point of the concentration-area diagram.
The system for delineating the target area of the ore exploration based on the geochemical data corresponds to the method for delineating the target area of the ore exploration based on the geochemical data, and can also accurately delineate the target area of the ore exploration and improve the accuracy of the prediction of the ore exploration.
For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (8)
1. A method for delineating a target area for prospecting based on geochemical data is characterized by comprising the following steps:
acquiring geochemical data of a region to be processed;
performing principal component analysis according to the geochemical data, determining target geochemical element variables and obtaining factor scores of each principal component;
performing linear regression analysis on the target geochemical element variable and the factor scores of the main components to obtain a residual error;
determining a residual error background value by using a concentration-area fractal method according to the residual error;
carrying out interpolation processing on the residual error to obtain a contour map or a grid map;
re-classifying the contour map or the grid map according to the residual background value to obtain an ore-finding target area; the ore finding target area is an area with a residual value higher than the residual background value in the contour map or an area with a residual value higher than the residual background value in the grid map.
2. The method for delineating a target area for prospecting based on geochemical data as set forth in claim 1, wherein after said acquiring the geochemical data of the area to be treated, the method further comprises: performing data cleaning on the geochemical data;
the specific process of performing data cleansing on the geochemical data comprises the following steps:
acquiring the geochemical data;
comparing the geochemical data with the detection limit to obtain data higher than the detection limit and data lower than the detection limit;
replacing the data below the detection limit with 1/2 of the detection limit to obtain replacement data;
and forming the data above the detection limit and the replacement data into cleaned geochemical data.
3. The method for delineating a target area for prospecting based on geochemical data as set forth in claim 1, wherein the step of performing principal component analysis based on the geochemical data to determine the variables of the target geochemical elements and obtaining the factor score of each principal component comprises:
performing principal component analysis on the geochemical data by using SPSS software, R software or GeoDa software to obtain the correlation between each principal component and the target geochemical element variable and generate a lithotripsy graph and a factor load graph;
determining the optimal principal component number according to two indexes that the number of variables with characteristic values larger than 1 and the variance ratio of the accumulated interpretation of each principal component are larger than 60% in the lithotripsy graph; the accumulated interpretation of each principal component is the sum of the ratio of the explained variance of each principal component and the overall variance;
determining the geochemical variables forming each factor according to the variable of which the ordinate value is more than 1 in the factor load graph;
and calculating the factor score of each principal component by using rgr package, SPSS or GeoDa software in the R language according to the optimal principal component number and the geochemical variables of each factor.
4. The method for delineating a target area for prospecting based on geochemical data as set forth in claim 1, wherein the determining a background value of the residual by a concentration-area fractal method according to the residual specifically comprises:
generating a concentration-area graph by utilizing a caplot function in rgr packages of the R language according to the residual error;
and determining a residual background value according to the inflection point of the concentration-area diagram.
5. A target area delineation system for prospecting based on geochemical data, the system comprising:
the data acquisition module is used for acquiring geochemical data of the area to be processed;
the principal component analysis module is used for performing principal component analysis according to the geochemical data, determining a target geochemical element variable and obtaining a factor score of each principal component;
the linear regression analysis module is used for carrying out linear regression analysis on the target geochemical element variable and the factor scores of the main components to obtain a residual error;
the residual error background value determining module is used for determining a residual error background value by utilizing a concentration-area fractal method according to the residual error;
the interpolation processing module is used for carrying out interpolation processing on the residual error to obtain a contour map or a grid map;
the reclassification module is used for reclassifying the contour map or the grid map according to the residual background value to obtain an ore searching target area; the ore finding target area is an area with a residual value higher than the residual background value in the contour map or an area with a residual value higher than the residual background value in the grid map.
6. The system for target prospecting delineation based on geochemical data as set forth in claim 5, wherein the system for target prospecting delineation further comprises: a data cleaning module;
the data cleaning module is respectively connected with the data acquisition module and the principal component analysis module;
the data cleaning module specifically comprises:
a data acquisition unit for acquiring the geochemical data;
the data comparison unit is used for comparing the geochemical data with the detection limit to obtain data higher than the detection limit and data lower than the detection limit;
a data replacement unit for replacing the data below the detection limit with 1/2 of the detection limit to obtain replacement data;
a cleaned geochemical data construction unit for constructing the data above the limit of detection and the replacement data into cleaned geochemical data.
7. The system for delineating a target area for prospecting based on geochemical data as set forth in claim 5, wherein the principal component analysis module comprises:
the graph generation unit is used for carrying out principal component analysis on the geochemical data by utilizing SPSS software, R software or GeoDa software to obtain the correlation between each principal component and the target geochemical element variable and generate a lithotripsy graph and a factor load graph;
the optimal principal component number determining unit is used for determining the optimal principal component number according to two indexes that the variable number of the lithotripsy graph with the characteristic value larger than 1 and the variance ratio of the accumulated interpretation of each principal component are larger than 60%; the accumulated interpretation of each principal component is the sum of the ratio of the explained variance of each principal component and the overall variance;
a geochemical variable determining unit for forming each factor, for determining the geochemical variable forming each factor according to the variable of which the ordinate value is more than 1 in the factor load graph;
and a factor score calculating unit for calculating the factor score of each principal component by using rgr package, SPSS or GeoDa software in R language according to the optimal number of principal components and the geochemical variables of each factor.
8. The system for delineating a target area for prospecting based on geochemical data as set forth in claim 5, wherein the residual background value determination module comprises:
a density-area map generating unit for generating a density-area map using a caplot function in rgr package in the R language from the residual error;
and the residual background value determining unit is used for determining a residual background value according to the inflection point of the concentration-area diagram.
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