484 results about "Metallogeny" patented technology

The invention relates to a knowledge graph construction and intelligent prospecting prediction method based on multi-source heterogeneous geological data. The method comprises the steps that geological data information is acquired and preprocessed, and a geological information database is formed; geologic entities, attributes of the geologic entities and mutual relations of the geologic entities in the geologic information database are recognized through the natural language processing technology, and a geologic knowledge graph is constructed; training and optimizing the prediction model to obtain a metallogenic prediction model; and obtaining a prediction result of the metallogenic potential area by using the metallogenic prediction model, and generating a metallogenic analysis report. According to the method, the geological data quality is improved through data preprocessing, the knowledge graph is constructed to integrate geological knowledge, the deep learning model is utilized to accurately extract and predict the metallogenic characteristics, and finally the metallogenic analysis report is generated, so that the prospecting efficiency is improved, the cost is reduced, and the decision scientificity is enhanced.

The invention discloses a prospecting target area prediction method and system based on geological three-dimensional modeling, and relates to the technical field of mineral resource exploration, and the method comprises the steps: obtaining geological, geophysical, geochemical and remote sensing data of a target area, carrying out the preprocessing, generating a modeling data set, and carrying out the geological modeling; constructing a lithology classification model by combining the three-dimensional geologic model with deep learning, and extracting shallow lithology features to predict the deep lithology of the target area; screening metallogenic factors according to the prediction result of the deep lithology of the target area, the deep geophysical data and the three-dimensional geologic model, and generating a metallogenic prediction factor set; and establishing a prospecting prediction model based on the graph convolutional network, importing the metallogenic prediction factor set to obtain a metallogenic distribution prediction result, and carrying out three-dimensional prospecting target area delineation. According to the method, deep lithologic stratum prediction is carried out through multi-source geological data and geological three-dimensional modeling, and target region delineation is carried out by using the graph convolutional neural network, so that the efficiency and precision of prospecting target region prediction are improved, and the exploration cost is reduced.

The invention relates to the field of geological exploration, in particular to an intelligent prospecting prediction method and system for an ore deposit three-dimensional geological model, a terminal and a medium. The method comprises the steps of obtaining multi-source geological data of a target area to construct an ore deposit three-dimensional geological model, inputting the ore deposit three-dimensional geological model into a trained intelligent prospecting prediction model for ore-forming potential analysis, and optimizing the model or generating an intelligent prospecting prediction scheme according to a predicted resource quantity confidence degree condition; when the model is constructed, three-dimensional inversion calculation, element anomaly field construction and the like are carried out, the model can be optimized through transfer learning, exploration data can be accessed in real time to realize dynamic updating, and a multi-target optimization model is established to output an exploration scheme; the invention also relates to a corresponding system, a terminal and a storage medium. The method achieves the technical effects of improving the accuracy and efficiency of prospecting prediction, dynamically optimizing the model according to the actual situation, reasonably planning the exploration scheme, and reducing the exploration cost and risk.

The invention discloses an altered mineral analysis-based prospecting target prediction method and system, and relates to the technical field of prospecting target prediction. An altered mineral analysis-based prospecting target prediction system comprises a data acquisition module, a clustering analysis module, an alteration combination discrimination module, a spatial modeling module, a space-time coupling module and a metallogenic evaluation module. According to the method, altered minerals and symbiotic combinations of the altered minerals are subjected to layered clustering treatment by introducing mineral thermodynamic phase diagram constraints, multi-stage superposed alteration information in a complex structure area is effectively analyzed, and a mineral symbiotic combination structure model with cause difference expression ability is established; by constructing cause period labels and forming a time sequence decoupling model, systematic distinguishing of alteration bodies formed under the mineralization effect of different times is achieved, and a time sequence basis is provided for identification of the multi-stage mineralization process.

The invention discloses a mineral resource intelligent prediction method and system based on multi-source heterogeneous data fusion and deep learning, and the method comprises the steps: collecting and preprocessing multi-source heterogeneous data, and carrying out the standardization processing to form a structured data set; multi-source heterogeneous data fusion: realizing data layer space registration and feature layer weight dynamic allocation through an attention mechanism multi-modal fusion module, and outputting a high-dimensional metallogenic feature vector; constructing a CNN-LSTM mixed deep learning model and completing initialization training, and outputting an initial mineralization probability graph; and establishing a dynamic updating engine, performing model increment training based on transfer learning, correcting the mineralization probability through positive and negative sample reinforcement learning in combination with a newly added data type, and outputting a time sequence dynamic mineralization probability graph. According to the method, mineralization probability dynamic evaluation and risk quantitative updating are realized, the prediction precision and the model updating efficiency are improved, the method is adaptive to a multi-stage exploration scene, and accurate real-time support is provided for exploration decision making.

The invention discloses a multi-factor prospecting prediction method suitable for tin polymetallic ore, and relates to the technical field of geological science. The prospecting prediction method comprises the following steps: collecting data; fusing multi-source data; extracting and analyzing mineralization information; constructing a comprehensive prediction model; and predicting mineralization. According to the method, a potential tin polymetallic ore deposit area is preliminarily selected by comprehensively considering multi-source information such as geology, geophysics, geochemistry and remote sensing, drilling data and profile data are collected in the area, the drilling data and the profile data are utilized to construct a comprehensive prediction model, and the model is combined with advanced algorithms such as geostatistics and machine learning, so that the prediction accuracy of the tin polymetallic ore deposit area is improved. The multi-source data is efficiently integrated, and a three-dimensional visualization result is provided, so that the position and the scale of a potential ore body can be more accurately predicted, and the success rate of prospecting is improved.

The embodiment of the invention provides a mineral target area intelligent delineation method and system based on multi-source heterogeneous geoscience data, and relates to the technical field of mineral resource exploration, and the method comprises the steps: dividing a multi-source heterogeneous geoscience data set comprising geological structure, geochemistry, geophysics and remote sensing image data into a plurality of data modules according to a geological action influence range; each data module records spatial distribution and attribute information, then a dynamic mapping relation between the data modules and a mineral product mineralization mechanism is constructed, a mineralization association chain between the data modules is generated based on the dynamic mapping relation, a cooperative change rule of nodes and connection paths is defined, then a target region feature set conforming to the mineralization association chain is screened, and a target region feature set is obtained; and finally, according to a collaborative change rule, judging the integrating degree of a target region feature set space unit and a mineralization condition, dynamically adjusting a space boundary range, and generating a mineral target region delineation result, thereby comprehensively utilizing multi-source data, deeply mining a relationship with a mineralization mechanism, and improving the accuracy and reliability of mineral target region delineation.

The invention discloses a metal ore body identification method based on remote sensing interpretation, relates to the technical field of mineral resource exploration, and aims to solve the problems of low identification precision, neglect of geological laws and poor generalization caused by dependence on single remote sensing data in the prior art. After standardization processing, spectrum and texture features are fused to generate a composite vector; extracting a multi-scale mineralization signal by using a convolutional neural network, and interpreting and constructing an ore control area in combination with a terrain gradient and a curvature; alteration zoning is identified through spectrum angle matching, and a favorable mineralization area is determined by combining lithology combination analysis; and dynamically weighting geological elements by adopting a deep learning fusion network, outputting an ore body position according to a comprehensive score, and finally optimizing a boundary through spatial clustering and morphological filtering. The method significantly improves the automation degree and reliability of ore body identification in a complex environment, and is suitable for metal mineral exploration target area delineation.

The invention relates to the technical field of geological exploration, provides a gold ore metallogenic three-dimensional prediction method and system based on structure information fusion, and breaks through the limitation that a traditional three-dimensional modeling method stops in the aspect of geometric description through fusion processing of multi-source data such as geological structures, ore body evolution processes and geochemical anomalies. Ore control structure information is fused with a geochemical trend and a space structure for the first time, a structure-geochemistry-ore body form collaborative prediction mechanism is realized, and blind ore recognition and peripheral prospecting capabilities are effectively enhanced. Meanwhile, a target region division mechanism based on multi-source layer overlapping is constructed, the credibility and precision of a prediction result are remarkably improved, and the prospecting requirement of a high-work-degree gold mining area is met. By adopting a mode of combining engineering modeling and mid-segment graph modeling, space errors generated by traditional interpolation modeling in a data sparse or form complex area are effectively avoided, and the authenticity and continuity of an ore body structure are improved.

The invention relates to the technical field of mineral resource exploration. The prospecting method, device and equipment based on the multi-source geological relation data and the medium are provided, the method comprises the steps that space-time alignment and standardization processing are conducted on obtained geological historical evolution data, geophysical field data, geochemical migration data and remote sensing alteration information, and a dynamic knowledge graph is generated; performing mineralization stage division processing on the geological historical evolution data to obtain a mineralization stage division result; integrating the fluid migration space-time path network, performing three-dimensional dynamic modeling processing, and generating a staged three-dimensional metallogenic evolution model; extracting a stage-specific geological mark combination from the staged three-dimensional metallogenic evolution model, performing knowledge reasoning processing based on a preset historical ore deposit rule base, and outputting an ore prospecting target region and a metallogenic process constraint basis which meet a preset confidence coefficient condition, so as to improve the precision of a structural model, generate a staged fluid dynamic field, and improve the precision of the metallogenic process. And the target region prediction confidence is enhanced.

The invention relates to the technical field of mineral resource prediction and analysis, and discloses a regional mineral resource prediction and analysis method and system, and the method comprises the steps: carrying out the collection and standardization, and constructing a standardized physical data set; organizing the physical parameters in a spatial dimension, and constructing a multi-dimensional tensor structure; tensor evolution modeling is carried out to generate tensor time sequence data; obtaining an optimal weight combination according to geological unit division; calculating the mineralization probability of each space unit; evaluating the credibility of the mineralization probability result, and outputting a mineralization probability graph and a credibility scoring graph; the system comprises a data acquisition and standardization module, a tensor modeling module, an evolution modeling module, a feature optimization module, a probability prediction module, a credibility evaluation module and a visual output module. According to the method, a space-parameter joint expression mode based on a four-order tensor structure is introduced, various kinds of physical field data are subjected to integrated processing in a unified space framework, and a data model reflecting multi-dimensional geological response characteristics is effectively constructed.

The invention relates to a geological mineral exploration data extraction method which comprises the following steps: S1, data acquisition: acquiring multi-source geological data through scientific drilling, remote sensing images and a geological radar; according to the method, through scientific drilling, remote sensing image and geological radar multi-source data collection, in combination with data preprocessing, feature extraction and three-dimensional model construction, massive geological data can be rapidly obtained and processed, and accurate positioning of mineral resources is achieved; the remote sensing image is combined to identify surface mineralization abnormity, the problem of surface and deep data separation in a traditional exploration method is effectively solved, meanwhile, the data preprocessing module ensures consistency and high-precision fusion of data from different sources through cleaning, format unification and geographical registration, and the data preprocessing module analyzes abundance and distribution rules of main metallogenic elements to obtain the data of different sources. And identifying combinations of elements closely related to mineralization.

The invention belongs to the technical field of data processing, and particularly relates to a rutile type titanium ore prospecting model construction method. Comprising the following steps: collecting remote sensing time sequence, real-time geophysical prospecting and geochemical data, carrying out geological causal feature analysis after standardization so as to construct a metallogenic causal graph, and meanwhile, collecting anti-fact features to generate virtual mineralization feature vectors; a prospecting model comprising an input layer, a weight optimization layer (comprising a causal attention module and a particle swarm anti-fact comparison module) and a mineralization probability output layer is constructed, and a high-frequency data acquisition mechanism is triggered with assistance of a metallogenic event threshold. According to the method, the data reliability and the model generalization ability are improved, the mineralization probability calculation precision and the potential mineralization target region judgment accuracy are remarkably improved, and a scientific support is provided for efficient prospecting of rutile type titanium ore.

The invention relates to the technical field of multi-source information analysis, in particular to a niobium-tantalum metal ore metallogenic evaluation system based on multi-source information analysis, which comprises a geologic structure association module, a mineral distribution interpretation module, a metallogenic environment adaptation module, a spatial feature analysis module and a potential region judgment module. According to the method, by introducing a multi-source data analysis and fusion method, the evaluation precision and comprehensive capability of resource exploration are effectively improved, analysis after information fusion is combined with relevance and spatial modes of different data types, it is ensured that mineralization potential evaluation is more accurate, the limitation of a single data source and manual analysis is overcome, and the method is suitable for popularization and application. According to the method, the identification precision and reliability of the mineralization law are improved, the potential area can be identified more accurately, resource potential analysis is optimized in combination with the adaptability of the mineralization environment, the efficiency and accuracy of determining the mineralization area are remarkably improved, the problems of information isolation and analysis deviation in a traditional method are avoided, and the scientificity and the practical application value of the exploration process are enhanced.

The invention belongs to the technical field of mineral resource exploration, and provides a multi-source remote sensing data and AI combined copper ore exploration method and system, and the method comprises the following steps: obtaining multi-source remote sensing data of a target region through a plurality of remote sensing devices; preprocessing the multi-source remote sensing data to obtain fusion data; the fusion data are analyzed through an AI algorithm, and mineralization alteration areas and geological structure information are obtained through recognition; performing overlay analysis on the mineralization alteration area and the known geochemical anomaly area, analyzing the spatial relationship between the mineralization area and the structure in combination with the geological structure information, and judging the favorable mineralization part of the copper ore to obtain an analysis result; performing field investigation on the potential copper ore area determined by the analysis result, collecting rock samples for laboratory analysis, and verifying the accuracy of the analysis result; according to the method, the multi-source remote sensing data and the AI technology are comprehensively utilized, the target area is rapidly analyzed, the potential copper ore area is positioned, the workload of blind exploration is reduced, and the exploration efficiency is improved.

The invention discloses a three-dimensional prospecting prediction method and system and a storage medium, and relates to the technical field of geological prospecting. The method comprises the following specific steps: collecting multi-source geological data in a target mining area, and establishing a geological database; performing data format standardization processing on the geological database to obtain preprocessed data; constructing a three-dimensional geologic model based on the preprocessed data; carrying out quantitative analysis on the three-dimensional geologic model, and extracting metallogenic favorable information; carrying out numerical simulation on the metallogenic process of the target mining area by utilizing a three-dimensional metallogenic process numerical simulation method, and extracting numerical simulation variable information; the metallogenic favorable information and the numerical simulation variable information are fused, and a three-dimensional comprehensive prospecting prediction model is constructed; and predicting a prospecting target area according to the three-dimensional comprehensive prospecting prediction model to obtain a prospecting prediction result. According to the method, a three-dimensional modeling and multi-source data fusion method is utilized, a new direction is provided for the field of prospecting prediction research, and the method has very wide application prospects.

The invention discloses a satellite-air-ground-well multi-method collaborative shallow coverage area copper-gold ore exploration method, and relates to the technical field of mineral resource exploration, regional alteration mineral information is extracted in a shallow coverage area, and a porphyry type copper-gold ore prospecting prospective area is determined according to alteration mineral space distribution and zoning characteristics thereof; in the prospecting prospective area, a key exploration area is selected according to metallogenic geological conditions, aviation geophysical prospecting and aviation hyperspectral remote sensing investigation are carried out, and a prospecting favorable area is delineated; performing prospecting prediction on related ore types in the favorable prospecting area, and delineating a prospecting target area; determining a new drilling position in the target area; drilling verification and well logging are carried out, ground-well geophysical prospecting is carried out to describe the spatial form of the metallogenic geologic body, and the prospecting effect is expanded. According to the method, the favorable prospecting area and the prospecting target area can be more accurately delineated, the spatial form of the ore body is finely delineated, a reliable basis is provided for prospecting of the porphyry type copper-gold ore, and the prospecting success rate and efficiency of the porphyry type copper-gold ore in the shallow coverage area are greatly improved.

The invention provides an active and passive source metal mine seismic exploration method, which comprises the following steps of: acquiring geological exploration data of a target area, and analyzing and judging to obtain a metallogenic favorable part of the target area; obtaining seismic geologic features of the target area and distribution features of natural field sources; according to the acquired geological exploration data, the passive source seismometers are arranged in a grid mode in a target area to form a passive source detection grid; the active source seismographs are arranged in a cross shape at the favorable metallogenic part to form two active source detection lines; artificial source seismic waves are excited, active source seismic data of the active source seismograph and passive source seismic data of the passive source seismograph are collected, and after the artificial source seismic waves are excited, the passive source seismic data of the passive source seismograph are continuously collected. The problem of active and passive source seismic data fusion acquisition is solved, the exploration cost is reduced, and the working efficiency and the detection precision are improved.

The invention discloses an intelligent prospecting prediction method based on a three-in-one metallogenic prediction theory, and relates to the technical field of prospecting prediction, and the method comprises the steps: determining various geological elements formed by a regional control ore deposit, obtaining data related to the elements formed by the regional control ore deposit, and storing the data in a database; comprising geological survey, engineering exploration, geophysics, geochemistry and remote sensing data; performing data preprocessing on the geological element data and dividing the geological element data into a plurality of categories; unsupervised learning is carried out on the geological data according to a deep learning algorithm, and the geological structure of the mining area is described in detail; in the areas with relatively high reconstruction errors, selecting the areas with relatively high geochemical anomaly and geophysical anomaly indication variables or reconstruction error values, comparing the selected areas with known typical ore deposits to determine the correlation of space structures, and extracting ore-forming favorable anomaly feature information from the selected areas; and the extracted abnormal information is matched with various geological elements to delineate the target region, so that the accuracy and efficiency of prospecting prediction are improved.

The invention relates to the technical field of geological data processing, in particular to a prospecting method and system based on geological text data, and the method comprises the following steps: obtaining exploration drilling data, extracting lithologic description, mineral composition and fracture filling conditions of a rock core, calculating the correlation index of drilling depth and mineralization thickness, screening the change trend of ore grade, and obtaining the geological text data. And obtaining mining area borehole lithology distribution data. According to the method, by deeply analyzing drilling data and lithologic characteristics, accurately recognizing a mineralized fluid accumulation area and improving the prediction precision of an ore body occurrence position, boundary control of a mineralized zone is optimized through measurement and calculation of spatial homogeneity, the extension precision of the mineralized zone is enhanced, scientific adjustment of a prospecting range is ensured through detailed analysis of altered mineral characteristics, and the method is suitable for large-scale popularization and application. The reasonability of demarcation of the prospecting target area is improved, multi-dimensional data and parameter analysis are integrated, a complete prospecting logic chain is constructed, and mineral product prediction precision and resource exploration efficiency are remarkably improved.

The invention discloses a deep concealed ore deposit detection method based on multi-source geological data fusion, and the method comprises the following steps: 1, carrying out a dynamic multi-source data fusion algorithm: introducing a fuzzy logic algorithm, dynamically adjusting the data fusion weight according to the feature significance of different geological units, and developing a cross-scale feature pyramid network, hierarchical feature extraction and fusion are carried out on different detection depth data; 2, optimizing an intelligent model based on prior knowledge; step 3, constructing a real-time interactive three-dimensional modeling system; 4, establishing an efficient multi-means verification system; and step 5, intelligent integration of the exploration process. According to the method, multi-source data are fused through fuzzy logic dynamic weight adjustment, the mineralization mode and the reinforcement learning optimization model are combined, three-dimensional modeling and multi-means combined verification are updated in real time, and the effects of accurate fusion of the multi-source data, dynamic model adjustment and optimization, efficient and accurate modeling, short verification period and low cost are achieved; and the detection efficiency and scale of the deep concealed ore deposit are improved.

The invention discloses a brine type potassic salt ore detection method based on a comprehensive geophysical technology, and relates to the field of geophysical detection and strategic mineral resources, the method comprises the following steps: adopting an audio magnetotelluric sounding technology to obtain audio magnetotelluric sounding data; determining a stratum resistivity profile of the audio magnetotelluric sounding line according to the audio magnetotelluric sounding data; acquiring shallow seismic exploration data of the same survey line by adopting a shallow seismic exploration technology; determining a seismic stack section according to the shallow seismic exploration data; the stratum resistivity profile and the seismic stack profile are combined to jointly reveal the stratum structure and construction characteristics of the research area; based on the stratum structure and construction characteristics, according to the low resistance abnormity of the stratum resistivity profile and the strong reflection event characteristics of the seismic stack profile, the sylvite mineralization favorable area and the brine reservoir interval are comprehensively detected, and the brine type sylvite ore identification precision can be improved.

The invention discloses a method for evaluating the mineralization potential of porphyry copper-(gold-molybdenum) ore. The evaluation method comprises the following steps: determining candidate rock masses with relatively high mineralization potential according to an oxygen fugacity value of magma zircon and / or a magma water content value of hornblende in a rock sample in an evaluation area; the aluminum saturation index ASI of the candidate rock mass is measured and calculated, the distribution coefficient and the distribution coefficient ratio of Cu, Au and Mo between fluid and melt are determined according to the ASI, simulation calculation is conducted through a Rayleigh fractionation model according to the distribution coefficient and / or the distribution coefficient ratio, and the content ratio of Au to Cu to Mo to Cu of the candidate ore body is obtained. According to the method, the mineralization potential of the porphyry copper ore and the enrichment degree and grade of Cu, Au and Mo of potential ore bodies can be rapidly and accurately evaluated.

The invention discloses a multi-source remote sensing rare earth ore prospecting method and system fused with pteridophyte ore showing, and belongs to the technical field of mineral resource exploration. Weathering crust type rare earth ore mineralization factor remote sensing features are obtained through multi-source remote sensing data, a potential area is preliminarily delineated, an unmanned aerial vehicle carrying a VNIR camera is deployed to obtain a high-resolution image, and the high-resolution image is subjected to image mapping; and comprehensively extracting fern distribution information according to texture, form and spectral indexes, and down-sampling a fern coverage result to a resolution consistent with that of other features to form a fern coverage layer. And constructing a multi-source remote sensing matrix fusing the fiddlehead coverage map layer and the mineralization factor characteristics, and predicting the rare earth mineralization probability and optimizing the potential region selection through sample training and global reasoning. According to the method, the positioning precision and exploration efficiency of the weathering crust rare earth ore are remarkably improved through coupling of the biological indicator factor (pteridophyte) and the traditional rock-mineral-structure-landform ore showing factor.

The invention discloses a magmatic rock mineral analysis method and system based on geological images, and relates to the technical field of mineral analysis. A magmatic rock mineral analysis system based on geological images comprises a magmatic rock feature analysis module and a magmatic rock comprehensive analysis module. According to the method, the magmatic rock mineral image and the magmatic rock geological auxiliary data are fused, so that the mineralization evolution history and the future mineralization potential of the magmatic rock can be disclosed; high-precision automatic recognition and classification of minerals in magmatic rocks are achieved through the mineral classification model, manual intervention is reduced, and the recognition efficiency and accuracy are improved; the extracted mineral crystallization characteristics are integrated with the oxygen fugacity characteristics, so that the conjoint analysis of the physical structure and the chemical property of the mineral is realized, and more comprehensive data support is provided for subsequent geological evolution research and mineral product prediction.

The invention discloses a skarn type deposit three-dimensional metallogenic prediction method, system and equipment and a medium, and relates to the technical field of mineral exploration. The method comprises the following steps: collecting and sorting geological information of a to-be-studied area and a surrounding area; according to the collected information, performing gravity-magnetic three-dimensional physical property inversion and lithology mapping; carrying out gravity-magnetic three-dimensional comprehensive geological modeling by adopting a discrete body inversion method; on the basis of the constructed model, performing three-dimensional metallogenic favorable contrast prediction; constructing a three-dimensional mineralization comprehensive prediction model based on the mineralization favorable degree value; and carrying out target region delineation and verification by using the three-dimensional metallogenic comprehensive prediction model to complete three-dimensional metallogenic prediction under the support of regional gravity and magnetic data. The method has the advantages of wider prediction range, high prediction reliability and the like.

The invention discloses a method for constructing a large mineralization potential evaluation model based on LLM, and relates to the field of models.The method for constructing the large mineralization potential evaluation model based on LLM comprises the following steps that 1, a mineral geological map file is converted into a structured JSON format data set; step 2, constructing cue words, wherein the cue words at least comprise geological information extraction cue words, function task cue words and entity, relation and attribute extraction cue words; compared with the prior art, the method has the beneficial effects that the large mineralization potential evaluation model constructed by the method realizes text and map multi-mode mineral product geological map information identification and analysis, automatic mineralization geological feature analysis, mineralization feature information extraction and mineralization potential evaluation; the problems that in the prior art, man-made subjective influence exists, professional knowledge dependence is high, the geological information recognition accuracy rate in the recognition process is low, and information is lost during knowledge retrieval are solved.

The invention discloses an ion adsorption type rare earth ore prospecting method based on a multi-element composite mineralization mode, and belongs to the technical field of rare earth ore geological exploration. The method comprises the following steps: firstly, collecting the existing exploration and research data of the known granite weathered crust type rare earth deposit; analyzing the ore-forming basic elements of the known granite weathering crust ion adsorption type rare earth ore deposit; then field geological survey and sample collection are carried out on the known granite weathered crust ion adsorption type rare earth ore deposit; determining each metallogenic mode element by utilizing analysis test data and field survey data; analyzing the formation cause of the ore deposit, establishing a prospecting mark, and constructing a multi-component composite mineralization mode of the granite weathering crust type rare earth ore deposit. And finally, prospecting target area prediction is carried out. For the known high-altitude granite weathering crust ion adsorption type rare earth deposit, multiple exploration technologies are organically fused, the special environment of the high-altitude area is optimized, a multi-element composite mineralization mode is constructed, and brand-new theoretical guidance and technical means are provided for prospecting of ion adsorption type rare earth ore in the high-altitude area.

The invention relates to the technical field of big data analysis, and discloses a prospecting target area positioning method and system based on big data, and the method comprises the steps: collecting multi-source exploration data in real time through distributed nodes, completing coordinate normalization, semantic alignment and time synchronization through a spatial heterogeneous data flow engine, and generating a standardized incremental data block; performing local feature sensitivity analysis based on the historical model library, identifying a newly added feature dimension, and performing parameter increment updating by adopting a sliding window gradient descent method; inputting the updated model into a target evolution model driven by a Bayesian space-time probability field, and dynamically calculating the metallogenic probability of each space grid in combination with a stress field, an element migration path and historical verification data; and generating high, medium and low three-level target area maps according to probability sorting, and pushing the high, medium and low three-level target area maps to a three-dimensional visual decision terminal. According to the method, minute-level dynamic response of the target region under triggering of newly-added data is realized, computing resource consumption is reduced to be less than 5% of that of an original system, and prospecting efficiency and abnormal region identification timeliness are improved.

The invention provides a sandstone type uranium ore prospecting method based on a tectonic unit boundary, and the method comprises the steps: obtaining the geological data of a sedimentary basin, determining the spatial distribution and the tectonic and stratum characteristics of tectonic units in the sedimentary basin, and determining the types of beneficial metallogenic tectonic units according to the spatial distribution and the tectonic and stratum characteristics of the tectonic units; and determining a first-level exploration target region of the sandstone type uranium mine by combining the gravity data and / or seismic data and / or oil and gas bearing conditions of the favorable metallogenic structure units for different types of favorable metallogenic structure units. According to the method, on the basis of deep analysis of uranium-controlled metallogenic characteristics of the tectonic unit boundary, the upheaval and fracture of the tectonic unit boundary are taken as important marks for prospecting, and geological and geophysical prospecting methods are combined, so that a novel efficient and low-cost prospecting method is formed, an optimal target of a sandstone type uranium ore prospecting area can be accurately locked, and the prospecting efficiency of the sandstone type uranium ore prospecting area is improved. The blindness in the prospecting process can be obviously reduced, and the exploration efficiency is improved.