CN114399092A - Three-dimensional ore finding prediction method for sandstone-type uranium ore based on underground water uranium anomaly - Google Patents

Three-dimensional ore finding prediction method for sandstone-type uranium ore based on underground water uranium anomaly Download PDF

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CN114399092A
CN114399092A CN202111623019.8A CN202111623019A CN114399092A CN 114399092 A CN114399092 A CN 114399092A CN 202111623019 A CN202111623019 A CN 202111623019A CN 114399092 A CN114399092 A CN 114399092A
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李真真
白芸
贾立城
朱鹏飞
曹珂
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Abstract

The invention belongs to the technical field of uranium ore geology, and particularly relates to a sandstone-type uranium ore three-dimensional prospecting prediction method based on underground water uranium anomaly, which is suitable for predicting and researching deep and peripheral mineralization of sandstone-type uranium ores in a three-dimensional environment. The invention comprises the following steps: step 1, collecting and arranging data; step 2, preprocessing data; step 3, constructing a three-dimensional model of the geologic body of the ore deposit and a prediction factor; step 4, determining a three-dimensional mineralization prediction calculation principle; step 5, calculating weight values of predicted elements of the ore deposit; step 6, comparing and analyzing posterior probability values; and 7, delineating the target area of the mineralization prediction. The invention provides theoretical basis and technical support for determining the ore searching target and the ore searching direction, and strives to realize new breakthrough of ore searching.

Description

Three-dimensional ore finding prediction method for sandstone-type uranium ore based on underground water uranium anomaly
Technical Field
The invention belongs to the technical field of uranium ore geology, and particularly relates to a sandstone-type uranium ore three-dimensional prospecting prediction method based on underground water uranium anomaly, which is suitable for predicting and researching deep and peripheral mineralization of sandstone-type uranium ores in a three-dimensional environment.
Background
The basic principle of deposit formation is the uneven distribution of mineralizing elements in the earth (or crust), so the deep prospecting problem can also be translated into a geochemical problem. As an important prospecting method and a direct prospecting information acquisition means, the geochemical prospecting can directly find out the regional distribution mode and the local concentration center of the mineral forming substances and indicate possible occurrence positions of the ore deposit.
Most of the sandstone-type uranium ores belong to exogenetic uranium aquatic ores, and according to the relevant theory of the uranium aquatic ores, the formation mechanism of the sandstone-type uranium ores can be summarized as follows: the uranium-containing oxygen-containing water which is stable for a long time forms good permeation and migration in the aquifer, and through the oxidation-reduction action of the reducing component in the permeable layer, on one hand, the oxidation zone is continuously propelled towards the inner direction of the basin, on the other hand, the continuous activation, migration and enrichment of uranium are promoted, and finally, the uranium is accumulated near a proper geochemical barrier to form a rolled, layered or lens-shaped uranium ore body. Therefore, in the actual ore prospecting work, the abnormal distribution area of the underground water uranium often serves as one of the core marks of the geochemical ore prospecting method.
Since the 90 s of the 20 th century, in China, in-situ leaching sandstone uranium ores are listed as the main attack direction of ore exploration, and a batch of large and oversized sandstone type uranium ores are discovered in a new generation basin in the north in sequence. By the end of 2015, sandstone-type uranium deposits account for about 15% of the total number of the proven uranium deposits, and the resource amount is the first of the four types of uranium deposit resources. The method has the advantages of large reserves, easy development, low mining cost and the like, and becomes the most important uranium ore exploration target type in China at present.
However, under the great trend that the difficulty of geological ore finding is increasing and the ore finding effect is decreasing, the ore finding exploration work enters a 'deep attack and blind finding' stage, and how to find the ore more effectively becomes one of the focus problems of common attention at home and abroad. With the great improvement of computer graphic analysis processing technology, three-dimensional visualization technology and geological big data computing capability, three-dimensional mineralization prediction research relying on computers and software platforms becomes a bright spot in the field of mineral resource prediction in recent years.
As one of the most common models for mineral resource mineralization prediction, the evidence weight model is widely applied to a multivariate information synthesis and spatial information decision support system by scholars at home and abroad, and also has a wide application field in China.
Under the background, the method is a primary ore formation prediction attempt which is carried out by combining the traditional geochemical ore finding means and the three-dimensional ore formation prediction technology according to the theoretical understanding of uranium ore formation.
Disclosure of Invention
The invention aims to provide a sandstone-type uranium ore three-dimensional ore finding prediction method based on underground water uranium anomaly, which provides theoretical basis and technical support for determining an ore finding target and an ore finding direction and strives to realize new breakthrough in ore finding.
The technical scheme adopted by the invention is as follows:
a sandstone-type uranium ore three-dimensional prospecting prediction method based on groundwater uranium anomaly comprises the following steps: step 1, collecting and arranging data; step 2, preprocessing data; step 3, constructing a three-dimensional model of the geologic body of the ore deposit and a prediction factor; step 4, determining a three-dimensional mineralization prediction calculation principle; step 5, calculating weight values of predicted elements of the ore deposit; step 6, comparing and analyzing posterior probability values; and 7, delineating the target area of the mineralization prediction.
In the step 1, the data of the mobile phone comprise ore deposit drilling data, sedimentary facies pattern diagrams, geochemical data, exploration line profile diagrams and ore deposit geological maps.
In the step 2, the preprocessing is to create a drilling database, and the database comprises a positioning table, a lithology table, sand body granularity, sand body thickness, sand body color, ore body burial depth and an analysis table of underground water uranium abnormal samples.
The step 3 specifically comprises the following steps:
3.1, constructing a three-dimensional entity model, extracting stratum, lithology, structure and mineralization information of the ore region in a classified manner, and establishing three-dimensional entity models of ore deposit geologic bodies, oxidized sand bodies, fractures, ore bodies, braided rivers and abnormal uranium heightening regions in water;
and 3.2, establishing an ore-formation prediction model, extracting ore-formation element information, and taking the ore-formation elements in the lower section of the lower Daohy Yao group, an interlayer oxidation zone, a structure, a braided river subphase and a uranium anomaly increase area in water as the ore-formation prediction factors in the research area according to the cognition of the existing ore-formation theory of the ore deposit.
In the step 4, the method specifically comprises the following steps: weight value calculation, membership degree mujtCalculating, calculating fuzzy weight value and calculating posterior probability.
The weighted value is calculated: dividing the research object into T three-dimensional cells, counting the mineral-containing information and mineral-forming information in each cell, wherein in the mineral-containing information layer, the mineral-containing elements have D number, and the mineral-free elements have
Figure BDA0003438878560000031
In the mining information map layer, if there are B units with mining predicting factors, there are no units with mining predicting factors
Figure BDA0003438878560000032
Each ore-forming prediction factor has a positive weight value and a negative weight value which are respectively marked as W+And W-The difference of C and W+-W-C denotes the degree of correlation of the predictor with the deposit, if C>0 means that the factor favors mineralization and conversely disfavors mineralization.
The positive and negative weight values:
Figure BDA0003438878560000033
in the above-mentioned formula, the compound of formula,
P(B/D)＝D∩∑B/D，
Figure BDA0003438878560000034
Figure BDA0003438878560000035
the degree of membership mujtAnd (3) calculating:
if the research area has n evidential factors, firstly, the evidential factor A is usedj(j ═ 1,2,3, …, n) with m as the attribute valuejIndividual interval class, set as Aj1And Aj2(
Figure BDA0003438878560000036
Aj1∩Aj2) And is defined as follows:
Aj1＝{x∣μjt(x)＝1}，Aj2＝{x∣μjt(x)＝0} (3)
(j＝1,2,3,…,n；t＝1,2,3,…,mj)
then
Figure BDA0003438878560000041
(j＝1,2,3,…,n；t＝1,2,3,…,mj)。
The fuzzy weight value calculation:
evidence factor AjT interval of
Figure BDA0003438878560000042
t＝1,2,3,…,mj) The fuzzy weight value of (a) is:
Figure BDA0003438878560000043
(j＝1,2,3,…,n；t＝1,2,3,…,mj)。
and calculating the posterior probability:
for the n evidence factors, the log representation of the probability odds ratio of any one haplotype k as the mineralizing unit in the study area,
Figure BDA0003438878560000044
(j＝1,2,3,…,n；t＝1,2,3,…,mj；k＝1,2,3,…,T)
Where O (D) is the prior ratio of the advantages and disadvantages of D, namely:
Figure BDA0003438878560000045
the posterior probability P of cell k is,
Figure BDA0003438878560000046
In the step 5, according to the established ore-finding prediction model, the favorable ore-forming element interval is used as an evidence layer and added into a fuzzy evidence weight layer, and the prior probability of each evidence layer and the positive-negative correlation and the weight value of each evidence layer are respectively calculated under two conditions of the uranium-containing abnormal increase value and the uranium-free abnormal increase value.
In the step 6, posterior probability value distribution maps under two conditions of uranium-containing abnormity and uranium-free abnormity are respectively calculated in three-dimensional software.
In the step 7, the known ore body model and the geological body model are superposed, the number of ore-containing blocks in the geological body is counted, and a favorable ore-forming area is defined by combining the distribution on the space.
Compared with the prior art, the invention has the beneficial effects that:
(1) according to the three-dimensional prospecting prediction method for the sandstone-type uranium ore based on the abnormal uranium in the groundwater, provided by the invention, under a three-dimensional visual environment, the most typical geochemical parameters of the uranium ore in a research area are selected according to the mineralization theory and mineralization characteristics of the uranium ore deposit, the mathematical geology and computer analysis technology is used, information such as basic geological data, geological information interpretation, the mineralization theory of the sandstone-type uranium ore, a mathematical geological operation method and the like are fused, mineralization prediction is carried out on the deep part and the periphery of a known ore body, a target region for prospecting is displayed more visually, clearly and accurately, and a theoretical basis is provided for the prospecting directions of the deep part and the periphery;
(2) according to the three-dimensional ore finding prediction method for sandstone-type uranium ores based on the groundwater uranium anomaly, provided by the invention, on the basis of the existing ore-forming theory and ore-forming characteristic research, the abnormal region with U being more than or equal to 8.06 mu g/L is taken as a special prediction factor through analysis of the uranium anomaly content value in a large number of groundwater samples in the region, the posterior probability value distribution condition in the three-dimensional ore-forming prediction is respectively calculated under the two conditions of uranium anomaly and uranium-free anomaly, and through comparative analysis research, when the uranium anomaly prediction factor participates in ore-forming prediction, the favorable ore-forming range can be better restrained, and the distribution of favorable ore-forming zones can be accurately reflected.
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FIG. 1 is a flow chart of a three-dimensional mineralization prediction technical scheme.
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.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
As shown in fig. 1, the three-dimensional prospecting prediction method for sandstone-type uranium ore based on groundwater uranium anomaly, provided by the invention, comprises the following steps:
step 1: and collecting and arranging data. And classifying, sorting and extracting useful information according to subsequent work requirements by using data information such as XX ore deposit drilling data, sedimentary phase diagram, geochemical data, exploratory line profile diagram, ore deposit geological map and the like.
Step 2: data preprocessing
A borehole database is created. The database mainly comprises a positioning table, a lithology table, sand body granularity, sand body thickness, sand body color, ore body burial depth, an analysis table of underground water uranium abnormal samples and the like, and lays a foundation for subsequent model creation, data analysis and calculation.
And step 3: three-dimensional model for constructing mineral deposit geologic body and prediction factor
Step 3.1: taking XX uranium deposit as an example, a three-dimensional solid model is constructed. And (3) extracting information such as stratum, lithology, structure, mineralization and the like of the XX mining area in a classified manner, and establishing three-dimensional entity models of mineral deposit geologic bodies, oxidized sand bodies, fractures, ore bodies, braided rivers and abnormal uranium increasing areas in water.
Step 3.2: and establishing a prospecting prediction model and extracting the information of the mineralization factors. Based on the knowledge of the existing mineralizing theory of XX ore deposit, the lower part (K) of the lower chalkiness Yaojia group2y1) As an in-water mineralization prediction factor, an interbed oxidation zone (yellow oxide sand), a structure, a braided river subphase, and an abnormal uranium increase zone in water were used (table 1).
TABLE 1 XX deposit prospecting prediction model
Figure BDA0003438878560000071
And 4, step 4: determining three-dimensional mineralization prediction calculation principles
(1) Weighted value calculation
Dividing the research object into T three-dimensional cells, and counting ore-containing information and ore-forming information in each cell. In the layer containing ore information, there are D ore containing elements, D is T-D without ore containing elements, in the layer containing ore forming information, there are B units with ore forming predicting factors, and B is T-B without ore forming factors.
Each ore-forming prediction factor has a positive weight value and a negative weight value which are respectively marked as W+And W-The difference of C and W+-W-. C denotes the degree of correlation of the predictor with the ore (or point) bed, if C>0 means that the factor favors mineralization and conversely disfavors mineralization.
Figure BDA0003438878560000081
In the above-mentioned formula, the compound of formula,
P(B/D)＝D∩∑B/D，
Figure BDA0003438878560000082
Figure BDA0003438878560000083
(2) degree of membership (. mu.)jt) Computing
If the research area has n evidential factors, firstly, the evidential factor A is usedj(j ═ 1,2,3, …, n) with m as the attribute valuejIndividual interval class, set as Aj1And Aj2(
Figure BDA0003438878560000084
Aj1∩Aj2) And is defined as follows:
Aj1＝{x∣μjt(x)＝1}，Aj2＝{x∣μjt(x)＝0} (3)
(j＝1,2,3,…,n；t＝1,2,3,…,mj)
then
Figure BDA0003438878560000085
(j＝1,2,3,…,n；t＝1,2,3,…,mj)
(3) Fuzzy weighted value calculation
Evidence factor AjT interval of
Figure BDA0003438878560000086
The fuzzy weight value of (a) is:
Figure BDA0003438878560000087
(j＝1,2,3,…,n；t＝1,2,3,…,mj)
(4) posterior probability calculation
For n evidence factors, the log representation of the odds ratio of the probability that any one haplotype k in the study area is a mineralizing unit:
Figure BDA0003438878560000091
(j＝1,2,3,…,n；t＝1,2,3,…,mj；k＝1,2,3,…,T)
where O (D) is the prior ratio of the advantages and disadvantages of D, namely:
Figure BDA0003438878560000092
the posterior probability P for cell k is:
Figure BDA0003438878560000093
and 5: XX deposit prediction element weight calculation
According to the established ore-finding prediction model, the favorable ore-forming element intervals are used as evidence layers and added into a fuzzy evidence weight layer, and the prior probability of each evidence layer and the positive-negative correlation and the weight value of each evidence layer are calculated under two conditions of uranium-containing abnormal increase values and uranium-free abnormal increase values respectively (tables 3 and 4).
Step 6: comparative analysis of posterior probability values
The posterior probability value is the probability that each favorable mineral element appears in a certain cell at the same time, and reflects the relative mineral finding probability of each cell block. The higher the probability value, the higher the probability of lump formation.
According to the calculation principle, posterior probability value distribution maps under two conditions of uranium-containing abnormity and uranium-free abnormity are calculated in three-dimensional software respectively. The comparison shows that after the influence factors of the uranium anomaly of the underground water are superposed, the posterior probability value distribution area which is beneficial to mineralization is more concentrated.
TABLE 3 weight values of evidence of ore-controlling elements under the condition of abnormal increase value of uranium in groundwater
Figure BDA0003438878560000094
Figure BDA0003438878560000101
TABLE 4 weight values of evidence of ore control factors without abnormal increase of uranium in groundwater
Item of evidence W+ S(W+) W- S(W-) C
K2y1 formation 0.554285 0.058708 -0.039 0.01793 0.593287
Braided river subphase 2.058071 0.028274 -0.42406 0.021715 2.482131
Slope belt 0.907458 0.032027 -0.21631 0.020317 1.123772
Alteration (yellow sand body) 1.344785 0.090435 -0.02747 0.017466 1.372253
Middle and fine (light) grey sandstone 1.384503 0.027421 -0.39892 0.022039 1.783425
Fracture of 0.531839 0.045044 -0.06774 0.018545 0.599576
And 7: ore-forming prediction target area delineation
And superposing the known ore body model and the geological body model, and counting the number of ore-containing blocks in the geological body. It was calculated that 60% of the known ore bodies fell in cubes with a posterior probability value of 0.65 or more. In combination with its spatial distribution, a favorable seam area is defined.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art should integrate the description, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art.

Claims (13)

1. A sandstone-type uranium ore three-dimensional prospecting prediction method based on underground water uranium anomaly is characterized by comprising the following steps: the method comprises the following steps: step (1), collecting and arranging data; step (2), data preprocessing; step (3), constructing a three-dimensional model of the geologic body of the ore deposit and a prediction factor; step (4), determining a three-dimensional mineralization prediction calculation principle; step (5), calculating weight values of predicted element of ore deposit; step (6), comparing and analyzing posterior probability values; and (7) delineating a target area for ore-forming prediction.
2. The three-dimensional prospecting prediction method for sandstone-type uranium ore based on groundwater uranium anomaly according to claim 1, characterized in that: in the step (1), the data of the mobile phone comprise ore deposit drilling data, sedimentary facies pattern diagrams, geochemical data, exploration line profile diagrams and ore deposit geological maps.
3. The three-dimensional prospecting prediction method for sandstone-type uranium ore based on groundwater uranium anomaly according to claim 2, characterized in that: in the step (2), the preprocessing is to create a drilling database, and the database comprises a positioning table, a lithology table, sand body granularity, sand body thickness, sand body color, ore body burial depth and an analysis table of underground water uranium abnormal samples.
4. The three-dimensional prospecting prediction method for sandstone-type uranium ore based on groundwater uranium anomaly according to claim 3, characterized in that: the step (3) specifically comprises the following steps:
step (3.1), constructing a three-dimensional entity model, classifying and extracting stratum, lithology, structure and mineralization information of the ore deposit, and establishing three-dimensional entity models of ore deposit geologic bodies, oxidized sand bodies, fractures, ore bodies, braided rivers and abnormal uranium increasing areas in water;
and (3.2) establishing an ore-prospecting prediction model, extracting ore-forming element information, and taking the ore-forming elements in the lower section of the lower Daohy Yao group, an interlayer oxidation zone, a structure, a braided river subphase and a uranium anomaly increase area in water as the ore-forming prediction factors in the research area according to the cognition of the existing ore-forming theory of the ore deposit.
5. The three-dimensional prospecting prediction method for sandstone-type uranium ore based on groundwater uranium anomaly according to claim 4, characterized in that: the step (4) specifically includes: weight value calculation, membership degree mujtCalculating, calculating fuzzy weight value and calculating posterior probability.
6. The three-dimensional prospecting prediction method for sandstone-type uranium ore based on groundwater uranium anomaly according to claim 5, characterized in that: the weighted value is calculated: dividing the research object into T three-dimensional cells, counting the mineral-containing information and mineral-forming information in each cell, wherein in the mineral-containing information layer, the mineral-containing elements have D number, and the mineral-free elements have
Figure FDA0003438878550000021
In the mining information map layer, if there are B units with mining predicting factors, there are no units with mining predicting factors
Figure FDA0003438878550000022
Each ore-forming prediction factor has a positive weight value and a negative weight value which are respectively marked as W+And W-The difference of C and W+-W-C denotes the degree of correlation of the predictor with the deposit, if C>0 means that the factor favors mineralization and conversely disfavors mineralization.
7. The three-dimensional prospecting prediction method for sandstone-type uranium ore based on groundwater uranium anomaly according to claim 6, characterized in that: the positive and negative weight values:
Figure FDA0003438878550000023
in the above-mentioned formula, the compound of formula,
P(B/D)＝D∩∑B/D，
Figure FDA0003438878550000024
Figure FDA0003438878550000025
8. the three-dimensional prospecting prediction method for sandstone-type uranium ore based on groundwater uranium anomaly according to claim 5, characterized in that: the degree of membership mujtAnd (3) calculating:
if the research area has n evidential factors, firstly, the evidential factor A is usedj(j ═ 1,2,3, …, n) with m as the attribute valuejIndividual interval class, set as Aj1And
Figure FDA0003438878550000026
and is defined as follows:
Aj1＝{x∣μjt(x)＝1}，Aj2＝{x∣μjt(x)＝0} (3)
(j＝1,2,3,…,n；t＝1,2,3,…,mj)
then
Figure FDA0003438878550000027
Figure FDA0003438878550000031
9. The three-dimensional prospecting prediction method for sandstone-type uranium ore based on groundwater uranium anomaly according to claim 5, characterized in that: the fuzzy weight value calculation:
evidence factor AjT interval of
Figure FDA0003438878550000032
The fuzzy weight value of (a) is:
Figure FDA0003438878550000033
10. the three-dimensional prospecting prediction method for sandstone-type uranium ore based on groundwater uranium anomaly according to claim 5, characterized in that: and calculating the posterior probability:
for the n evidence factors, the log representation of the probability odds ratio of any one haplotype k as the mineralizing unit in the study area,
Figure FDA0003438878550000034
Where O (D) is the prior ratio of the advantages and disadvantages of D, namely:
Figure FDA0003438878550000035
the posterior probability P of cell k is,
Figure FDA0003438878550000036
11. The three-dimensional prospecting prediction method for sandstone-type uranium ore based on groundwater uranium anomaly according to claim 7, characterized in that: in the step (5), according to the established ore-finding prediction model, the ore-forming element interval serving as an evidence layer is added into a fuzzy evidence weight layer, and the prior probability of each evidence layer and the positive-negative correlation and the weight value of each evidence layer are calculated under two conditions of the uranium-containing abnormal increase value and the uranium-free abnormal increase value respectively.
12. The three-dimensional prospecting prediction method for sandstone-type uranium ore based on groundwater uranium anomaly according to claim 10, characterized in that: in the step (6), posterior probability value distribution maps under two conditions of uranium-containing abnormity and uranium-free abnormity are respectively calculated in three-dimensional software.
13. The three-dimensional prospecting prediction method for sandstone-type uranium ore based on groundwater uranium anomaly according to claim 12, characterized in that: in the step (7), the known ore body model and the geological body model are superposed, the number of ore-containing blocks in the geological body is counted, and a favorable ore-forming area is defined by combining the spatial distribution.
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CN115879648A (en) * 2023-02-21 2023-03-31 中国地质科学院 Machine learning-based ternary deep mineralization prediction method and system
CN117252263A (en) * 2023-11-17 2023-12-19 核工业北京地质研究院 Visual method for prospecting model

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CN112380674A (en) * 2020-10-27 2021-02-19 核工业北京地质研究院 Deposit prediction method based on digital geological model
CN115879648A (en) * 2023-02-21 2023-03-31 中国地质科学院 Machine learning-based ternary deep mineralization prediction method and system
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