CN111062544A - Prediction method for uranium mineralization distant scenic region - Google Patents
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- 229910052770 Uranium Inorganic materials 0.000 title claims abstract description 88
- JFALSRSLKYAFGM-UHFFFAOYSA-N uranium(0) Chemical compound [U] JFALSRSLKYAFGM-UHFFFAOYSA-N 0.000 title claims abstract description 88
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- 230000002349 favourable effect Effects 0.000 claims description 8
- 238000000638 solvent extraction Methods 0.000 claims description 7
- 239000004576 sand Substances 0.000 claims description 4
- 102100039789 Ras-related protein M-Ras Human genes 0.000 claims description 3
- 210000003484 anatomy Anatomy 0.000 claims description 2
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- 241000282414 Homo sapiens Species 0.000 description 3
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- 239000010438 granite Substances 0.000 description 1
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Abstract
The invention belongs to the technical field of uranium ore exploration, and particularly relates to a prediction method of a uranium mineralization scenic spot. The invention comprises the following steps: determining a principle and a method for predicting a uranium distant scene area; step two, establishing a prediction model; step three, determining uranium mineralization factor characteristics; step four, improving the prediction element characteristics of uranium mineralization; and step five, delineating the uranium-forming ore distant scenic region. The method can efficiently, quickly and objectively evaluate the uranium ore-forming potential of one area, improve the ore-finding hit rate and accelerate the ore-finding speed.
Description
Technical Field
The invention belongs to the technical field of uranium ore exploration, and particularly relates to a prediction method of a uranium mineralization scenic spot.
Background
The uranium resource is a dual-purpose resource for military and civil use. With the rapid development of national economy and particularly with the rapid development of nuclear power, the demand of uranium ores is increasing, and uranium ore resources become important pillars for the sustainable development of nuclear power. Prediction is a requirement for the development of human beings, and as human beings develop, the requirement is penetrated into various industries. With the rapid development of modern science and technology and the increasing demand of human beings on mineral resources, the ore-finding work is turned from surface ore, shallow ore and easily-identified ore to the search of blind ore and difficultly-identified ore, the ore-formation prediction is an important mark of the current science and technology ore-finding and is also one of the requirements of the current society on geological work, and the ore-formation prediction is a leading edge and a hotspot in the field of research on the ore-formation. With the cross penetration of nonlinear statistics, spatial statistics, computer technology, spatial informatics and other related subjects, the mining prediction evaluation is developed from the traditional qualitative prediction evaluation to the current model-based quantitative prediction evaluation, and from the traditional simple analogy to the utilization of the geoscience comprehensive information mainly based on the mining and fusion of complex geoscience comprehensive data, and is also a research field which is very concerned in the geoscience fields of current international deposit geology, mathematical geology, exploration geochemistry, exploration geophysical exploration, geoscience information and the like. The deep and peripheral parts of the exploration new area with no outcrop display and complicated objective conditions and the old mine with higher working degree are the main areas for finding mines in the future. Therefore, the prospect area of the ore is defined through the ore forming prediction, the key section of the exploration work is provided or a specific exploration project is deployed, and a scientific basis is provided for the overall planning of the development and utilization work of mineral resources.
Disclosure of Invention
The technical problems solved by the invention are as follows:
aiming at the defects of the prior art, the method for predicting the uranium mineralization distant scenic region is provided, the uranium mineralization potential of one region can be efficiently, quickly and objectively evaluated, the prospecting hit rate is improved, and the prospecting speed is accelerated.
The technical scheme adopted by the invention is as follows:
a prediction method of a uranium mineralization distant scene area comprises the following steps:
determining a principle and a method for predicting a uranium distant scene area;
step two, establishing a prediction model;
step three, determining uranium mineralization factor characteristics;
step four, improving the prediction element characteristics of uranium mineralization;
and step five, delineating the uranium-forming ore distant scenic region.
The method comprises the steps of firstly determining a principle and a method for determining uranium prospect prediction, wherein the prospect prediction must adhere to the following principles that ① is the largest in possibility of finding ore beds and the smallest in possibility of missing ores in a defined prediction region, ② is a model comparison method for defining prediction regions of different prediction types, ③ is a principle that when multiple kinds of information are jointly used, the prediction regions are determined according to ground, physical, chemical and remote mineral prediction element information comprehensive signs based on geological information, ④ scale equivalence criteria, namely that basic data participating in prediction and a prediction target are on the same horizontal scale, geological structure special drawings, materialization remote sand abnormality, inference interpretation drawings and the like should be projected uniformly, and the adopted method is mainly based on technical requirements for uranium mine resource evaluation and related specifications of national uranium mine resource evaluation projects.
In the second step, a uranium mineralization prediction model is established by finely researching geophysical prospecting data of a research area, analyzing the compactness of geophysical prospecting elements and mineralization and determining the characteristics of the mineralization elements and prediction elements of uranium mineralization in the area.
And in the third step, the system collects and collates research data and results of foremen in the working area, and determines the mineralizing factor information which can be utilized in the prediction area and can participate in prediction through the anatomy of typical uranium deposit in the working area.
In the fourth step, on the basis of research on uranium ore-forming elements, comprehensive information such as superposition, transformation, remote and the like forms prediction elements. And the characteristics of the prediction elements of uranium mineralization in the prediction region are further improved, and the prediction elements are divided into three necessary, important and secondary elements according to the mineralization elements and the importance of the prediction elements related to corresponding mineralization.
The method comprises the steps of determining a minimum prediction area through the division of a prediction unit, wherein the division prediction unit is mainly used for gridding the determined prediction area on the basis of early prediction area delineation, namely a geologic body + grid unit method, highlighting mining key information in the optimization of the minimum prediction area, suppressing interference information, eliminating abnormal multi-solution and improving the reliability of a mineral product prediction result, MRAS software is used for carrying out extraction, quantification and other operations on variables of the prediction elements, a characteristic analysis method is adopted for carrying out gridding segmentation on the prediction area by 1km multiplied by 1km, typical mineral deposits in the area are used as a model, mineral forming elements and prediction element data are selected, a similarity coefficient method is adopted for carrying out variable selection, a similarity coefficient 0.3 is used as a threshold value, a vector length method (square sum method) is used as a variable weight calculation method, the mining interest degree calculation is carried out according to the calculation result analysis of a mark weight coefficient, the mining interest degree calculation is carried out after the mining interest degree of each distant area is calculated, the mining probability of the mining forming area is eliminated, the probability of the region is less than 0.3, the region is determined according to the principle of the mining interaction of the geological region, the probability of the high mining area, the region classification rule of the mining area, the mining probability of the mining area is determined, the mining area, the probability of the region classification is determined according to the specific classification rule of the high probability of the mining area, the mining area classification rule of the mining area, the mining area is determined, the mining area.
And finally, partitioning the mining prospect area on the basis of minimum prediction area partitioning and optimization, comprehensively analyzing factors such as mining geological conditions, mineralization intensity, mining information concentration degree and resource potential and the like by combining mining elements and prediction information, and finally partitioning the prediction area into I, II and II levels by optimization. Grade I mining prospect: the method has favorable geological conditions of uranium mineralization, uranium ore points or better industrial uranium mineralization can be found in a working area, main ore finding marks are obvious, good geophysical prospecting and chemical prospecting abnormity display is realized, the coincidence degree of various abnormity is high, the resource potential of the prediction area is considered to be large through analysis, medium-sized or large-sized uranium ore deposits can be generated, and the mineralization profitability (mineralization probability) of the minimum prediction area is more than 0.8. Grade II mining prospect: the prediction region has favorable uranium mineralization geological conditions, uranium ore points or better uranium mineralization can be found in the working region, main ore finding marks are obvious, good geophysical prospecting and chemical prospecting abnormity display is achieved, the degree of coincidence of various abnormity is high, analysis shows that the prediction region has better resource potential, and small or medium-sized uranium ore deposits can be possibly caused. The minimum prediction area mineralization profitability (mineralization probability) is between 0.60.8. Grade III mineral-forming distant scenic areas: the method has favorable geological conditions of uranium mineralization or favorable abnormal display of geophysical prospecting and chemical prospecting, is unobvious in mineralization, has a certain mineral prospecting mark, has common or single abnormal type of various geophysical prospecting and chemical prospecting abnormalities, and is worthy of further geological work by analyzing and considering that the uranium deposit is possibly found in the prediction region. The minimum prediction area mineralization profitability (mineralization probability) is 0.5-0.6.
The invention has the beneficial effects that:
(1) the method can efficiently, quickly and objectively evaluate the uranium mineralization potential of one area, can quickly establish a uranium ore prospecting target area, improves the prospecting hit rate, accelerates the prospecting speed, and provides technical support for uranium ore deposit prospecting and prospecting in the area;
(2) the method has the advantages of wide coverage, good timeliness, strong applicability and high accuracy. Has important guiding function for uranium mine prospecting in China and has wide popularization and application prospect.
Detailed Description
The present invention will be described in further detail with reference to the following examples:
the invention provides a prediction method of a uranium mineralization distant scenic spot, which comprises the following steps:
determining a principle and a method for predicting a uranium distant scene area;
① the principle of maximum possibility of finding ore deposit and minimum possibility of missing ore in a delineated forecast area, ② a model comparison method is used to delineate forecast areas of different forecast types, ③ when multiple kinds of information are jointly used, the forecast areas are determined according to geological information-based ground, physical, chemical and remote mineral forecast element information comprehensive signs, ④ scale equivalence criteria, namely that basic data participating in forecast and a forecast target are on the same horizontal scale, geological structure thematic map, remote materialization gravity sand abnormity, inference interpretation map and the like, and the adopted method is mainly based on the technical requirements for uranium mine resource potential evaluation and the relevant specifications of national uranium mine resource potential evaluation project.
Step two, establishing a prediction model;
through fine research on geophysical prospecting data in a research area, the compactness of geophysical prospecting elements and mineralization in the research area is analyzed, and a uranium mineralization geology-materialization remote prediction model is established through determining the characteristics of the mineralization elements and prediction elements of uranium mineralization in the research area.
Through the analysis of the characteristics of the typical ore forming elements and the prediction elements of certain types of ore deposits or ore points, the uranium mineralization geology-materialization remote prediction model is established. And then, establishing uranium mineralization prediction elements and prediction elements through collection or actual measurement, and comparing the uranium mineralization prediction elements and the prediction elements with a prediction model to define an ore-forming distant scene. I.e. a process of constructing a prediction model from points (building a prediction model) and surfaces (delineating a prospect).
Step three, determining uranium mineralization factor characteristics;
on the basis of collecting and organizing research data and results of foremen in a working area by a system and combining with the latest progress of uranium ore exploration in the area, the regional uranium geological ore conditions are analyzed through the research on typical uranium ore deposits in the research area, and key ore control factors of the typical ore deposits are summarized. The mineral forming elements which can be used in the prediction area and can participate in prediction are mainly granite rock mass, structure, hydrothermal alteration, lithologic contact interface, uranium mineralization information and the like.
Step four, improving the prediction element characteristics of uranium mineralization;
on the basis of research on uranium mineralization elements, comprehensive information such as superposition, transformation, remote control and the like forms prediction elements. The project group collects 1:5 ten thousand of aerial geophysical prospecting survey data in the research area, and combines with the geochemical anomaly, radioactive hydration and ground gamma anomaly data of the water system sediments collected by the potential evaluation project, so that the prediction element of uranium mineralization in the prediction area is further perfected. Through the description of the characteristics of each mineral forming element and the prediction element, the importance of each mineral forming element, prediction element and corresponding mineral forming action is necessarily divided into three types of necessary, important and secondary elements (table 1).
And step five, delineating the uranium-forming ore distant scenic region.
The basis of the minimum prediction area delineation is the partitioning of the prediction units. The prediction unit division is mainly based on the early prediction area delineation, and gridding the delineated prediction area, namely a geologic body + grid unit method. The optimization of the minimum prediction area should highlight the key mining information, suppress interference information, eliminate abnormal multi-solution and improve the reliability of the mineral prediction result.
The definition of the predicted distant scene area adopts a comprehensive information geological unit method. The geological unit method of comprehensive information is a general term for a method of calculating the mineralization profitability of each prediction unit by using geological comprehensive information and dividing the minimum prediction area based on the mineralization profitability of the unit. The prediction mainly comprises the steps of calculating the mineralization profitability by using a characteristic analysis method and delineating a distant scenic spot. Meanwhile, the far-field area is adjusted by adopting a Delphi method.
TABLE 1 prediction element table for diagenetic prospect of research area
And constructing 7 variable delineating minimum prediction areas according to the characteristic analysis of the uranium mineralization element and the characteristic analysis of the uranium mineralization prediction element. The prediction element variables are extracted and quantified by MRAS software. The prediction region is divided into 1km x 1km grids by adopting a characteristic analysis method, typical ore deposits in the region are used as a model, comprehensive navigation abnormity, uranium deposit (point), uranium-rich rock mass, ground gamma abnormity, water system sediment U element abnormity, uranium in water, radon abnormity, fracture buffer data and the like are selected, a similarity coefficient method is adopted for variable selection, a similarity coefficient 0.3 is used as a threshold value, a vector length method (sum of squares method) is used as a variable weight calculation method, and the mineralization favorability calculation is carried out according to the calculation result analysis of the mark weight coefficient. And after the mining profitability of each distant scenic region is calculated, the distant scenic regions with the mining probability less than 0.3 are removed. And (4) determining the classification of each distant scenic region comprehensively according to the mining probability of more than 0.3 and the combination of element matching conditions, specific mining geological conditions, mineralization abnormity and the like according to the mining probability. When multiple kinds of information are used jointly, determining a prediction area by a comprehensive mark of the geological, physical, chemical and remote mineral prediction element information based on geological information; the scale equivalence criterion is that basic data participating in prediction and a prediction target are on the same horizontal scale, and geological structure thematic images, materialized remote sand anomaly and inference interpretation images and the like are projected in a unified mode.
And finally, dividing the mining prospect on the basis of minimum prediction area division and optimization, comprehensively analyzing factors such as mining geological conditions, mineralization intensity, concentration degree of mining information, resource potential and the like by combining mining elements and prediction information, and finally predicting 2 pieces of grade I prospect, 3 pieces of grade II prospect and 5 pieces of grade III prospect through optimization.
The present invention has been described in detail with reference to the embodiments, but the present invention is not limited to the embodiments, and various changes can be made without departing from the gist of the present invention within the knowledge of those skilled in the art. The prior art can be adopted in the content which is not described in detail in the invention.
Claims (8)
1. A prediction method of a uranium mineralization distant view area is characterized by comprising the following steps: the method comprises the following steps:
determining a principle and a method for predicting a uranium distant scene area; step two, establishing a prediction model; step three, determining uranium mineralization factor characteristics; step four, improving the prediction element characteristics of uranium mineralization; and step five, delineating the uranium-forming ore distant scenic region.
2. The method for predicting a uranium mineralization prospect according to claim 1, wherein: in the first step, the following principle is adhered to in the distant scene prediction: in a delineated prediction area, the principle that the probability of finding an ore deposit is the largest and the probability of missing the ore is the smallest is found; using a model comparison method to define prediction areas of different prediction types; when multiple kinds of information are used jointly, determining a prediction area by a comprehensive mark of the geological, physical, chemical and remote mineral prediction element information based on geological information; the scale equivalence criterion is that basic data participating in prediction and a prediction target are on the same horizontal scale, and geological structure thematic images, materialized remote sand anomaly and inference interpretation images and the like are projected in a unified mode.
3. The method for predicting a uranium mineralization prospect according to claim 1, wherein: in the first step, the adopted method is based on the related specifications of the technical requirement for uranium ore resource potential evaluation and the project of national uranium ore resource potential evaluation.
4. The method for predicting a uranium mineralization prospect according to claim 1, wherein: in the second step, a uranium mineralization prediction model is established by finely researching geophysical prospecting data of a research area, analyzing the compactness of geophysical prospecting elements and mineralization and determining the characteristics of the mineralization elements and prediction elements of uranium mineralization in the area.
5. The method for predicting a uranium mineralization prospect according to claim 4, wherein: and in the third step, the system collects and collates research data and results of foremen in the working area, and determines the mineralizing factor information which can be utilized in the prediction area and can participate in prediction through the anatomy of typical uranium deposit in the working area.
6. A prediction method of a uranium mineralization prospect according to claim 5, wherein: in the fourth step, on the basis of research on uranium ore forming elements, comprehensive information such as superposition, chemical conversion, remote conversion and the like forms prediction elements; and the characteristics of the prediction elements of uranium mineralization in the prediction region are further improved, and the prediction elements are divided into three necessary, important and secondary elements according to the mineralization elements and the importance of the prediction elements related to corresponding mineralization.
7. The method for predicting a uranium mineralization prospect according to claim 6, wherein: in the fifth step, a minimum prediction area is defined through the division of the prediction unit; the prediction unit division is mainly based on the early prediction area delineation, and gridding the delineated prediction area, namely a geologic body + grid unit method. The optimization of the minimum prediction area should highlight the key information of the mineral formation, suppress the interference information, eliminate the abnormal multi-solution and improve the reliability of the mineral prediction result; the MRAS software is used for extracting and quantifying the prediction element variables; the prediction region is subjected to 1km multiplied by 1km gridding segmentation by adopting a characteristic analysis method, a typical ore deposit in the region is used as a model, mineralization element data and prediction element data are selected, a similarity coefficient method is adopted for variable selection, a similarity coefficient 0.3 is used as a threshold value, a vector length method is used as a variable weight calculation method, and mineralization favorable degree calculation is carried out according to the calculation result analysis of a mark weight coefficient. And after the mining profitability of each distant scenic region is calculated, the distant scenic regions with the mining probability less than 0.3 are removed. The remote scenic spots with the mineralization probability larger than 0.3 comprehensively determine the classification of each remote scenic spot according to the mineralization probability and the combination of element matching conditions, specific mineralization geological conditions, mineralization abnormity and the like; when the forecast distant view area is determined, man-machine interactive determination is adopted; and finally, partitioning the mining prospect area on the basis of minimum prediction area partitioning and optimization, comprehensively analyzing factors of mining geological conditions, mineralization intensity, mining information concentration degree and resource potential size by combining mining elements and prediction information, and finally partitioning the prediction area into I, II and II levels by optimization.
8. The method for predicting a uranium mineralization prospect according to claim 7, wherein: grade I mining prospect: the prediction region resource has the advantages that the prediction region resource has high potential, medium or large uranium deposit possibly exists, and the minimum prediction region mineralization profitability reaches more than 0.8; grade II mining prospect: the prediction region has favorable uranium mineralization geological conditions, uranium ore points or better uranium mineralization can be found in the working region, main ore finding marks are obvious, good geophysical prospecting and chemical prospecting abnormity display is achieved, the degree of coincidence of various abnormity is high, analysis shows that the prediction region has better resource potential, and small or medium-sized uranium ore deposits can be possibly caused; the minimum prediction area mineralization profitability is between 0.60.8; grade III mineral-forming distant scenic areas: the method has favorable geological conditions of uranium mineralization or favorable abnormal display of geophysical prospecting and chemical prospecting, has unobvious mineralization phenomenon, but has a certain mineral prospecting mark, the abnormal coincidence degree of various geophysical prospecting and chemical prospecting is common or the abnormal type is single, and analysis shows that the prediction region is likely to find uranium deposits and is worthy of further geological work; the minimum prediction area mineralization profitability is 0.5-0.6.
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| CN114384601A (en) * | 2021-12-28 | 2022-04-22 | 核工业北京地质研究院 | Method for delineating uranium into ore-forming scenic spot by utilizing Pb isotope in water |
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