CN111090709A - Big data geological analysis method for sandstone-type uranium ore mineralization prediction - Google Patents
Big data geological analysis method for sandstone-type uranium ore mineralization prediction Download PDFInfo
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Abstract
The invention relates to the technical field of sandstone-type uranium ore mineralization prediction, and particularly discloses a big data geological analysis method for sandstone-type uranium ore mineralization prediction. The method specifically comprises the following steps: 1. collecting data and preprocessing to form a database; 2. establishing a sandstone-type uranium ore prospecting model; 3. carrying out technical analysis and effective information extraction on main ore control factors and ore finding marks of a sandstone-type uranium ore area to be searched; 4. and predicting sandstone uranium ores. According to the big data geological analysis method for sandstone-type uranium ore mineralization prediction, geological features are comprehensively summarized, a big data platform is used, ore control conditions and ore exploration marks of sandstone-type uranium ores are considered, and the method is combined with digital geology, a database technology, a modeling technology and a visualization technology to form combination of a geological technology and a computer big data technology, is a new technology for the current ore exploration prediction, and can be applied to initial prediction of the ore exploration of the type.
Description
Technical Field
The invention belongs to the technical field of sandstone-type uranium ore mineralization prediction, and particularly relates to a big data geological analysis method for sandstone-type uranium ore mineralization prediction.
Background
At present, the ore forming prediction methods are more and mainly biased to directions such as an ore forming rule, an ore finding mode, ore forming characteristics and the like, and although the directions are important factors of ore forming prediction, the method has no technical limitation and is in short of consideration for research factors of digital geology. Therefore, a big data geological analysis technology is needed, which combines the deposit science, the geology and the big data technology, summarizes the ore forming rule and the ore forming mode, establishes a regional ore forming model, establishes a mathematical model as many as possible, continuously excavates geological, geophysical prospecting, chemical prospecting and remote sensing information, defines and predicts a prospect area of the ore forming according to the regional ore forming model and actual exploration data, and realizes the organic combination of the mathematics and the geology. The big data geological analysis technology not only contains the content of digital geology, but also considers geological laws and a mine finding model, so that the mine finding work tends to be quantitative and informationized. Therefore, a large data analysis technique for uranium mineralization prediction is required.
Disclosure of Invention
The invention aims to provide a big data geological analysis method for sandstone-type uranium ore mineralization prediction, which solves the quantification and informatization of the sandstone-type uranium ore prospecting work by using big data.
The technical scheme of the invention is as follows: a big data geological analysis method for sandstone-type uranium deposit mineralization prediction specifically comprises the following steps:
step 1, collecting data and preprocessing to form a database;
step 1.1, determining a region of sandstone-type uranium ores to be searched, and collecting and obtaining geological, mineral products, hydrogeology, drilling and physical and chemical exploration data of the region;
step 1.2, classifying, screening and preprocessing the collected data, converting different data formats and establishing a plurality of databases;
step 2, establishing a sandstone-type uranium ore prospecting model;
2.1, screening effective and favorable information by using the relevant data information collected in the step 1;
2.2, establishing a sandstone-type uranium ore prospecting model by utilizing the screened favorable information and combining with an ore-forming geological background of the uranium ore to be searched;
step 3, carrying out technical analysis and effective information extraction on main ore control factors and ore finding marks of the sandstone-type uranium ore area to be searched;
step 4, predicting sandstone uranium ores;
and (3) compiling visual drawings and predicting and evaluating the main ore control factors and the ore finding sign information extracted in the step (3) and later-stage ore formation prediction factors by combining variable value characteristics, ore body plane positioning prediction and ore body vertical positioning prediction.
The specific steps of establishing the sandstone-type uranium ore prospecting model in the step 2 are as follows:
2.1, screening effective and favorable information by using the relevant data information collected in the step 1;
screening the relevant data information collected in the step 1 to obtain effective and favorable information such as sandstone-type uranium ore-forming rules, ore control factors, ore finding marks, ore-forming modes and the like;
2.2, establishing a sandstone-type uranium ore prospecting model by utilizing the screened favorable information and combining with an ore-forming geological background of the uranium ore to be searched;
on the basis of obtaining effective and favorable information such as a sandstone-type uranium ore formation rule, an ore control factor, an ore formation mark, an ore formation mode and the like, analyzing an ore formation geological background of an ore formation area to be found, obtaining ore formation characteristics, and establishing a sandstone-type uranium ore finding model.
The mineral plane positioning prediction map in the step 4 mainly comprises a sand dispersion system map, a stratum parameter map, a sedimentation system map, a structural grid map, a rock geochemistry map, a hydrogeology map and a physical and chemical exploration comprehensive result map, and the mineral vertical positioning prediction map mainly comprises a section map, a structural section map, a vertical sequence map and a physical and chemical exploration type section map.
The step 3 specifically comprises:
step 3.1, analyzing and extracting information of uranium source conditions;
step 3.2, carrying out information analysis and extraction on the structure ore control condition;
3.3, analyzing and extracting information of the stratum ore control condition;
step 3.4, analyzing and extracting information of the deposition system;
step 3.5, analyzing and extracting information of the sand body conditions;
step 3.6, analyzing and extracting information of the shielding condition;
step 3.7, analyzing and extracting information of the oxidation zone;
step 3.8, carrying out information analysis and extraction on uranium mineralization;
step 3.9, analyzing and extracting information of the hydrogeology;
step 3.10, analyzing and extracting information of the paleoclimate;
and 3.11, analyzing and extracting information of the prospecting marks reflected by the geophysics, the geochemistry and remote sensing.
The step 3 specifically comprises:
step 3.1, analyzing and extracting information of the uranium source conditions, and drawing an analysis result chart of the uranium source conditions according to the extracted uranium source conditions;
3.2, analyzing and extracting information of the construction ore control condition, and drawing a construction trellis diagram, an earthquake section explanation diagram and a construction section diagram;
3.3, carrying out information analysis and extraction on the stratum ore control conditions to obtain a stratum contrast chart, a stratum thickness chart, a stratum buried depth chart and a stratum elevation chart, and obtaining a spatial distribution rule of uranium-bearing rock series;
step 3.4, analyzing and extracting information of the sedimentary system to obtain sedimentary boundary, material source direction, geographic landform of the palea area, lithology of a target layer, existing sedimentary system, sedimentary facies type and boundary, and main fracture structure information;
step 3.5, carrying out information analysis and extraction on the sand body conditions to obtain the spatial configuration relation of sand body thickness plane distribution and sand body heterogeneity parameter plane distribution in uranium mineralization so as to form a sand body thickness graph, a sand content graph, a granularity distribution graph, a partition layer thickness graph and a sand body layer number graph;
step 3.6, analyzing and extracting information of the shielding conditions, and drawing a top and bottom plate buried depth map and a top and bottom plate thickness map;
3.7, analyzing and extracting information of the oxidation zone to obtain an oxide sand body equal thickness diagram, an oxide sand body percentage content diagram, a typical rock geological section diagram and a rock geochemistry diagram;
step 3.8, carrying out information analysis and extraction on uranium mineralization, and analyzing uranium mineralization rules to obtain a three-dimensional geological map;
step 3.9, analyzing and extracting information of hydrogeology to obtain hydrogeology information;
step 3.10, analyzing and extracting information of the ancient climate, and drawing a red layer distribution diagram, a dark mudstone distribution diagram and an organic matter distribution diagram;
and 3.11, analyzing and extracting information of the prospecting marks reflected by the geophysics, the geochemistry and the remote sensing, and drawing a remote sensing interpretation graph, an electrical method section interpretation graph, an earthquake section interpretation graph, a logging curve and a radon measurement abnormal interpretation graph.
And 3.1, analyzing the uranium source conditions, and obtaining the ore-forming prediction factors of the uranium source conditions, namely rock mass, enrichment and uranium emigration.
The specific steps of carrying out information analysis and extraction on the structure ore control condition in the step 3.2 are as follows: acquiring main unconformity interface structure data by combining a large amount of collected seismic section interpretation data and construction data with field and core observation data, and identifying and acquiring the unconformity interface of the sandstone-type uranium ore area to be searched by using the seismic reflection terminal characteristics; identifying and obtaining the geometric and mechanical properties of the boundary fault of each level of structure unit; from the perspective of structure control deposition, the partitioning of the stratigraphic units of the main structural sequence is analyzed, and the mineralization prediction factors of the stratigraphic units are the structure types, the structure development characteristics, the mineral control structures and the structure favorable directions.
The step 3.3 comprises the following specific steps: the mineralization prediction factor of the stratum mineral control condition is an isochronous stratum framework and a stratum structure; according to sporopollen data, intensive drilling rock core data, well logging curve forms and vertical sequence structures obtained through analysis and testing, key sequence interfaces and mark layers in uranium-bearing strata series and uranium-bearing rock series are identified, sequence stratum units are divided, regional drilling and seismic profile sequence stratum comparison are carried out, and uranium-bearing rock series isochronous stratum grillage is established.
The step 3.4 comprises the following specific steps: on the basis of research on uranium-bearing rock series isochronous stratigraphic grids in a database, obtaining a target layer deposition thickness diagram, a single-hole causal phase analysis diagram, a vertical sequence diagram, a drilling hole columnar comparison diagram, a deposition system diagram, a source system diagram and a structural fracture distribution diagram; the deposition system mineralization prediction factor is an ancient source.
The step 3.7 is specifically as follows: the method comprises the steps of bringing data of the color, the structure, the granularity, the main cementation type, the cementation degree, the water permeability, organic matters, sulfides and the like of sandstone compiled by a drill core into a database, establishing a spatial distribution characteristic of an oxidation zone of a target layer, performing three-dimensional mapping of the oxidation zone, dividing the oxidation zone, an oxidation-reduction transition zone and a reduction zone of the sandstone of the target layer, and obtaining an equal-thickness map of an oxidized sand body, a percentage content map of the oxidized sand body, a typical rock geological profile and a rock geochemistry map; analyzing the spatial distribution rule of the paleo-interlayer oxidation zone on the basis of the information, and predicting a regional paleo-interlayer oxidation zone front line; the mineralization predictor of the oxidation zone conditions is the oxidation zone type, scale and spatial distribution thereof.
The invention has the following remarkable effects: according to the big data geological analysis method for sandstone-type uranium ore mineralization prediction, geological features are comprehensively summarized, a big data platform is used, ore control conditions and ore exploration marks of sandstone-type uranium ores are considered, and the method is combined with digital geology, a database technology, a modeling technology and a visualization technology to form combination of a geological technology and a computer big data technology, is a new technology for the current ore exploration prediction, and can be applied to initial prediction of the ore exploration of the type.
Detailed Description
A big data geological analysis method for sandstone-type uranium deposit mineralization prediction specifically comprises the following steps:
step 1, collecting data and preprocessing to form a database;
step 1.1, determining a region of sandstone-type uranium ores to be searched, and collecting and obtaining geological, mineral products, hydrogeology, drilling and physical and chemical exploration data of the region;
step 1.2, classifying, screening and preprocessing the collected data, converting different data formats and establishing a plurality of databases;
step 2, establishing a sandstone-type uranium ore prospecting model;
2.1, screening effective and favorable information by using the relevant data information collected in the step 1;
screening the relevant data information collected in the step 1 to obtain effective and favorable information such as sandstone-type uranium ore-forming rules, ore control factors, ore finding marks, ore-forming modes and the like;
2.2, establishing a sandstone-type uranium ore prospecting model by utilizing the screened favorable information and combining with an ore-forming geological background of the uranium ore to be searched;
on the basis of obtaining effective and favorable information such as a sandstone-type uranium ore formation rule, an ore control factor, an ore finding mark, an ore forming mode and the like, analyzing an ore forming geological background of an ore forming area to be found, obtaining ore forming characteristics, and establishing a sandstone-type uranium ore finding model;
step 3, carrying out technical analysis and effective information extraction on main ore control factors and ore finding marks of the sandstone-type uranium ore area to be searched;
step 3.1, analyzing and extracting information of uranium source conditions;
analyzing the uranium source conditions to obtain ore formation prediction factors such as rock mass, enrichment, uranium emigration and the like, and drawing and obtaining a uranium source condition analysis result diagram according to the extracted uranium source conditions;
step 3.2, carrying out information analysis and extraction on the structure ore control condition;
acquiring main unconformity interface structure data by combining a large amount of collected seismic section interpretation data and construction data with field and core observation data, and identifying and acquiring the unconformity interface of the sandstone-type uranium ore area to be searched by using the seismic reflection terminal characteristics; identifying and obtaining the geometric and mechanical properties of the boundary fault of each level of structure unit; from the angle of structure control deposition, analyzing the division of the stratigraphic units of the main structural sequence, wherein the mineralization prediction factors are the structure type, the structure development characteristics, the mineral control structure and the structure favorable direction; drawing a structural grid diagram, a seismic profile interpretation diagram and a structural section diagram through the information extraction;
3.3, analyzing and extracting information of the stratum ore control condition;
identifying key sequence interfaces and mark layers in uranium-bearing strata and uranium-bearing rock series according to sporopollen data, intensive drilling rock core data, well logging curve forms and vertical sequence structures obtained by analysis and test, dividing sequence stratum units, performing regional drilling and seismic profile sequence stratum comparison, and establishing uranium-bearing rock series isochronous stratum grillage;
the mineralization prediction factor of the stratum mineral control condition is an isochronous stratum framework and a stratum structure; on the basis of statistics of a large amount of data of a sandstone-type uranium ore area to be searched, obtaining spatial distribution series diagrams of uranium-bearing rock systems, such as a stratum contrast diagram, a stratum thickness diagram, a stratum buried depth diagram, a stratum elevation diagram and the like, and obtaining a spatial distribution rule of the uranium-bearing rock systems;
step 3.4, analyzing and extracting information of the deposition system;
on the basis of research on uranium-bearing rock series isochronous stratigraphic grids in a database, obtaining a target layer deposition thickness diagram, a single-hole causal phase analysis diagram, a vertical sequence diagram, a drilling hole columnar comparison diagram, a deposition system diagram, a source system diagram and a structural fracture distribution diagram;
the deposition system mineralization prediction factor is an ancient source; the extracted information comprises sedimentary boundaries, material source directions, geographic landforms of the paleo-land regions, lithology of target layers, existing sedimentary systems, sedimentary phase types and boundaries, main fracture structures and the like, and reflects the relationship between the most favorable current mineralizing phase zone, the causative phase and uranium mineralization;
step 3.5, analyzing and extracting information of the sand body conditions;
the mineralization prediction factor of the sand body condition is the sand body distribution heterogeneity characteristic; obtaining the relationship among the sand body thickness, the sand body granularity, the thickness and the quantity of the barrier layer, the sand body causative phase and the uranium mineralization probability through data statistics; according to the analysis of the structure, permeability, water-bearing property, heterogeneity and diagenesis of the ore-bearing aquifer sand body, obtaining the spatial configuration relation of the sand body thickness plane distribution and the sand body heterogeneity parameter plane distribution in uranium mineralization, and forming a sand body thickness graph, a sand content rate graph, a particle size distribution graph, a partition layer thickness graph and a sand body layer number graph;
step 3.6, analyzing and extracting information of the shielding condition;
extracting according to shielding condition information, and drawing a top and bottom plate buried depth map and a top and bottom plate thickness map;
step 3.7, analyzing and extracting information of the oxidation zone;
the method comprises the steps of bringing data of the color, the structure, the granularity, the main cementation type, the cementation degree, the water permeability, organic matters, sulfides and the like of sandstone compiled by a drill core into a database, establishing a spatial distribution characteristic of an oxidation zone of a target layer, performing three-dimensional mapping of the oxidation zone, dividing the oxidation zone, an oxidation-reduction transition zone and a reduction zone of the sandstone of the target layer, and obtaining an equal-thickness map of an oxidized sand body, a percentage content map of the oxidized sand body, a typical rock geological profile and a rock geochemistry map; analyzing the spatial distribution rule of the paleo-interlayer oxidation zone on the basis of the information, and predicting a regional paleo-interlayer oxidation zone front line;
the mineralization prediction factor of the oxidation zone condition is the type, scale and spatial distribution of the oxidation zone;
step 3.8, carrying out information analysis and extraction on uranium mineralization;
the method comprises the following steps of counting parameters such as ore body form, thickness, grade, buried depth, elevation and lithology of each ore deposit by utilizing a database, analyzing uranium mineralization rules by combining ore control factors such as ore-containing sand body thickness, heterogeneity, ancient interlayer oxidation zone development condition, primary and secondary reduction capability and the like, and obtaining a three-dimensional geological map;
step 3.9, analyzing and extracting information of the hydrogeology;
acquiring hydrogeological information, wherein long-term and stable groundwater infiltration is beneficial to an interzone oxidation zone and intermountain basin type uranium mineralization, and for ancient river channel type sandstone uranium ores, the formed uranium ores are damaged by the long-term infiltration, and the uranium ores are adversely affected;
step 3.10, analyzing and extracting information of the paleoclimate;
for sandstone uranium ores, the ancient climate conditions of the ore formation are warm and humid ancient climate conditions in the sediment stage and arid-semiarid ancient climate conditions in the ore formation stage, so that the sediment sand body is ensured to contain rich organic matters, the ancient groundwater in the ore formation stage is enriched with oxygen, and a redbed distribution diagram, a dark mudstone distribution diagram and an organic matter distribution diagram are extracted and drawn through the ancient climate information;
step 3.11, analyzing and extracting information of the prospecting marks reflected by the geophysics, the geochemistry and remote sensing;
summarizing the mineral exploration marks discovered by remote sensing, an electrical method, an earthquake, well logging, radon measurement and the like, analyzing the relation between the mineral exploration marks and uranium mineralization, and drawing a remote sensing interpretation graph, an electrical method section interpretation graph, an earthquake section interpretation graph, a well logging curve and a radon measurement abnormal interpretation graph;
step 4, predicting sandstone uranium ores;
and (3) compiling and predicting visual graphs and evaluating the main ore control factors and the ore finding mark information extracted in the step (3) and later-stage ore formation prediction factors by combining variable value characteristics, ore body plane location prediction and ore body vertical location prediction, wherein the ore body plane location prediction graphs mainly comprise a sand dispersion system graph, a stratum parameter graph, a sedimentation system graph, a structural grid graph, a rock geochemistry graph, a hydrogeology graph and a physical and chemical exploration comprehensive result graph, and the ore body vertical location prediction graphs mainly comprise a section graph, a structural section graph, a vertical sequence graph and a physical and chemical exploration type section graph.
Claims (10)
1. A big data geological analysis method for sandstone-type uranium deposit mineralization prediction is characterized by comprising the following steps: the method specifically comprises the following steps:
step 1, collecting data and preprocessing to form a database;
step 1.1, determining a region of sandstone-type uranium ores to be searched, and collecting and obtaining geological, mineral products, hydrogeology, drilling and physical and chemical exploration data of the region;
step 1.2, classifying, screening and preprocessing the collected data, converting different data formats and establishing a plurality of databases;
step 2, establishing a sandstone-type uranium ore prospecting model;
2.1, screening effective and favorable information by using the relevant data information collected in the step 1;
2.2, establishing a sandstone-type uranium ore prospecting model by utilizing the screened favorable information and combining with an ore-forming geological background of the uranium ore to be searched;
step 3, carrying out technical analysis and effective information extraction on main ore control factors and ore finding marks of the sandstone-type uranium ore area to be searched;
step 4, predicting sandstone uranium ores;
and (3) compiling visual drawings and predicting and evaluating the main ore control factors and the ore finding sign information extracted in the step (3) and later-stage ore formation prediction factors by combining variable value characteristics, ore body plane positioning prediction and ore body vertical positioning prediction.
2. The big data geological analysis method for sandstone-type uranium ore mineralization prediction according to claim 1, wherein the big data geological analysis method comprises the following steps: the specific steps of establishing the sandstone-type uranium ore prospecting model in the step 2 are as follows:
2.1, screening effective and favorable information by using the relevant data information collected in the step 1;
screening the relevant data information collected in the step 1 to obtain effective and favorable information such as sandstone-type uranium ore-forming rules, ore control factors, ore finding marks, ore-forming modes and the like;
2.2, establishing a sandstone-type uranium ore prospecting model by utilizing the screened favorable information and combining with an ore-forming geological background of the uranium ore to be searched;
on the basis of obtaining effective and favorable information such as a sandstone-type uranium ore formation rule, an ore control factor, an ore formation mark, an ore formation mode and the like, analyzing an ore formation geological background of an ore formation area to be found, obtaining ore formation characteristics, and establishing a sandstone-type uranium ore finding model.
3. The big data geological analysis method for sandstone-type uranium ore mineralization prediction according to claim 1, wherein the big data geological analysis method comprises the following steps: the mineral plane positioning prediction map in the step 4 mainly comprises a sand dispersion system map, a stratum parameter map, a sedimentation system map, a structural grid map, a rock geochemistry map, a hydrogeology map and a physical and chemical exploration comprehensive result map, and the mineral vertical positioning prediction map mainly comprises a section map, a structural section map, a vertical sequence map and a physical and chemical exploration type section map.
4. The big data geological analysis method for sandstone-type uranium ore mineralization prediction according to claim 1, wherein the big data geological analysis method comprises the following steps: the step 3 specifically comprises:
step 3.1, analyzing and extracting information of uranium source conditions;
step 3.2, carrying out information analysis and extraction on the structure ore control condition;
3.3, analyzing and extracting information of the stratum ore control condition;
step 3.4, analyzing and extracting information of the deposition system;
step 3.5, analyzing and extracting information of the sand body conditions;
step 3.6, analyzing and extracting information of the shielding condition;
step 3.7, analyzing and extracting information of the oxidation zone;
step 3.8, carrying out information analysis and extraction on uranium mineralization;
step 3.9, analyzing and extracting information of the hydrogeology;
step 3.10, analyzing and extracting information of the paleoclimate;
and 3.11, analyzing and extracting information of the prospecting marks reflected by the geophysics, the geochemistry and remote sensing.
5. The big data geological analysis method for sandstone-type uranium ore mineralization prediction according to claim 4, wherein the big data geological analysis method comprises the following steps: the step 3 specifically comprises:
step 3.1, analyzing and extracting information of the uranium source conditions, and drawing an analysis result chart of the uranium source conditions according to the extracted uranium source conditions;
3.2, analyzing and extracting information of the construction ore control condition, and drawing a construction trellis diagram, an earthquake section explanation diagram and a construction section diagram;
3.3, carrying out information analysis and extraction on the stratum ore control conditions to obtain a stratum contrast chart, a stratum thickness chart, a stratum buried depth chart and a stratum elevation chart, and obtaining a spatial distribution rule of uranium-bearing rock series;
step 3.4, analyzing and extracting information of the sedimentary system to obtain sedimentary boundary, material source direction, geographic landform of the palea area, lithology of a target layer, existing sedimentary system, sedimentary facies type and boundary, and main fracture structure information;
step 3.5, carrying out information analysis and extraction on the sand body conditions to obtain the spatial configuration relation of sand body thickness plane distribution and sand body heterogeneity parameter plane distribution in uranium mineralization so as to form a sand body thickness graph, a sand content graph, a granularity distribution graph, a partition layer thickness graph and a sand body layer number graph;
step 3.6, analyzing and extracting information of the shielding conditions, and drawing a top and bottom plate buried depth map and a top and bottom plate thickness map;
3.7, analyzing and extracting information of the oxidation zone to obtain an oxide sand body equal thickness diagram, an oxide sand body percentage content diagram, a typical rock geological section diagram and a rock geochemistry diagram;
step 3.8, carrying out information analysis and extraction on uranium mineralization, and analyzing uranium mineralization rules to obtain a three-dimensional geological map;
step 3.9, analyzing and extracting information of hydrogeology to obtain hydrogeology information;
step 3.10, analyzing and extracting information of the ancient climate, and drawing a red layer distribution diagram, a dark mudstone distribution diagram and an organic matter distribution diagram;
and 3.11, analyzing and extracting information of the prospecting marks reflected by the geophysics, the geochemistry and the remote sensing, and drawing a remote sensing interpretation graph, an electrical method section interpretation graph, an earthquake section interpretation graph, a logging curve and a radon measurement abnormal interpretation graph.
6. The big data geological analysis method for sandstone-type uranium ore mineralization prediction according to claim 5, wherein the big data geological analysis method comprises the following steps: and 3.1, analyzing the uranium source conditions, and obtaining the ore-forming prediction factors of the uranium source conditions, namely rock mass, enrichment and uranium emigration.
7. The big data geological analysis method for sandstone-type uranium ore mineralization prediction according to claim 5, wherein the big data geological analysis method comprises the following steps: the specific steps of carrying out information analysis and extraction on the structure ore control condition in the step 3.2 are as follows: acquiring main unconformity interface structure data by combining a large amount of collected seismic section interpretation data and construction data with field and core observation data, and identifying and acquiring the unconformity interface of the sandstone-type uranium ore area to be searched by using the seismic reflection terminal characteristics; identifying and obtaining the geometric and mechanical properties of the boundary fault of each level of structure unit; from the perspective of structure control deposition, the partitioning of the stratigraphic units of the main structural sequence is analyzed, and the mineralization prediction factors of the stratigraphic units are the structure types, the structure development characteristics, the mineral control structures and the structure favorable directions.
8. The big data geological analysis method for sandstone-type uranium ore mineralization prediction according to claim 5, wherein the big data geological analysis method comprises the following steps: the step 3.3 comprises the following specific steps: the mineralization prediction factor of the stratum mineral control condition is an isochronous stratum framework and a stratum structure; according to sporopollen data, intensive drilling rock core data, well logging curve forms and vertical sequence structures obtained through analysis and testing, key sequence interfaces and mark layers in uranium-bearing strata series and uranium-bearing rock series are identified, sequence stratum units are divided, regional drilling and seismic profile sequence stratum comparison are carried out, and uranium-bearing rock series isochronous stratum grillage is established.
9. The big data geological analysis method for sandstone-type uranium ore mineralization prediction according to claim 5, wherein the big data geological analysis method comprises the following steps: the step 3.4 comprises the following specific steps: on the basis of research on uranium-bearing rock series isochronous stratigraphic grids in a database, obtaining a target layer deposition thickness diagram, a single-hole causal phase analysis diagram, a vertical sequence diagram, a drilling hole columnar comparison diagram, a deposition system diagram, a source system diagram and a structural fracture distribution diagram; the deposition system mineralization prediction factor is an ancient source.
10. The big data geological analysis method for sandstone-type uranium ore mineralization prediction according to claim 5, wherein the big data geological analysis method comprises the following steps: the step 3.7 is specifically as follows: the method comprises the steps of bringing data of the color, the structure, the granularity, the main cementation type, the cementation degree, the water permeability, organic matters, sulfides and the like of sandstone compiled by a drill core into a database, establishing a spatial distribution characteristic of an oxidation zone of a target layer, performing three-dimensional mapping of the oxidation zone, dividing the oxidation zone, an oxidation-reduction transition zone and a reduction zone of the sandstone of the target layer, and obtaining an equal-thickness map of an oxidized sand body, a percentage content map of the oxidized sand body, a typical rock geological profile and a rock geochemistry map; analyzing the spatial distribution rule of the paleo-interlayer oxidation zone on the basis of the information, and predicting a regional paleo-interlayer oxidation zone front line; the mineralization predictor of the oxidation zone conditions is the oxidation zone type, scale and spatial distribution thereof.
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| CN112580119A (en) * | 2020-11-20 | 2021-03-30 | 核工业二〇八大队 | Method for compiling geological map of in-situ leaching sandstone type uranium ore series |
| CN113109889A (en) * | 2021-04-25 | 2021-07-13 | 东华理工大学 | Sandstone-type uranium ore prospecting method based on 'two-stage and two-mode' mineralization model |
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| CN113279748A (en) * | 2021-06-21 | 2021-08-20 | 吉林大学 | Method for identifying zonal uranium-bearing layers of vertical underground space of computer |
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| CN113279748B (en) * | 2021-06-21 | 2022-04-29 | 吉林大学 | Method for identifying zonal uranium-bearing layers of vertical underground space of computer |
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