458 results about "Mineral deposit" patented technology

The invention provides an innovative deep concealed ore deposit detection method, which comprehensively utilizes geology, geophysics, geochemistry and remote sensing technologies, and realizes effective integration of multi-source geological data by developing an advanced data fusion algorithm. According to the method, data collected by geological survey, wide-area electromagnetic method exploration, hydrocarbon-mercury superposition halo analysis and aviation hyperspectral remote sensing are subjected to standardized preprocessing, so that the consistency and accuracy of the data are ensured; and then, deep analysis is carried out on the fused data by utilizing machine learning and statistical analysis technologies so as to identify and predict mineralization modes and abnormal regions. Finally, a three-dimensional geologic model is constructed, the form and distribution of an ore deposit are visually displayed, and a scientific basis is provided for geological exploration. The method is characterized in that a multi-source data fusion technology and mineralization mode identification automation and precision are realized, so that the efficiency and the accuracy of deep hidden ore deposit detection are remarkably improved.

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 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 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 discloses a continuous deflecting coring method for realizing wire-line coring orientation, which relates to the technical field of drilling, and specifically comprises the following steps of: selecting a bent screw drill and a matched wire-line coring tool according to geological conditions and a designed drilling track, assembling and connecting the bent screw drill and the matched wire-line coring tool, and putting the bent screw drill and the matched wire-line coring tool into a drilling hole; in the drilling process, the hole bottom power drilling tool provides drilling power, a bent angle of the bent screw drilling tool enables a drilled hole to be inclined according to the design direction, and a rotor cavity of the hollow screw drilling tool allows an internal assembly and a core barrel to pass through. According to the continuous deflecting coring method for wire-line coring orientation, the high-precision directional drilling technology and the wire-line coring technology are organically combined, the problem of exploration of irregular deposited ore deposits and concealed ore deposits is solved, the precision and efficiency of geological exploration are improved, and by adopting the bent screw drill and the matched wire-line coring tool, the geological exploration efficiency is improved. Continuous directional drilling and continuous wire-line coring are carried out at the same time, the number of times of drill lifting is reduced, and the auxiliary time is shortened.

The invention relates to the technical field of mineral deposit data, in particular to a digitalized acquisition optimization method for mineral deposit information data. Based on geological evolution historical data of the mining area, a three-dimensional geological model is established, and formation and change of an ore deposit in different evolution stages are simulated; dynamically simulating key parameters of the ore deposit; according to prediction of the geologic model, adjusting acquisition parameters; setting a layout scheme of a sensor array in combination with a geological evolution simulation model; the sensor array adjusts the acquisition angle, direction and sensing area in real time through a built-in adaptive algorithm; carrying out real-time synchronous acquisition on multi-modal data from different sensors, carrying out feature extraction through a deep learning model, and identifying an association mode of each type of data; in the data fusion process, noise and redundant data are eliminated; the acquired data are analyzed in real time through an anomaly detection module; according to geological simulation data and a deployment scheme of acquisition equipment, an acquisition path and a strategy are designed.

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 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 relates to the technical field of underground mining of ore deposits, in particular to an upward layered filling mining method for a gently-inclined medium-thick ore body in-vein accurate mining pseudo-inclined approach. According to the method, the interior of a middle section is divided into panels in the pseudo-inclined direction of the ore body trend, and one panel is arranged between two in-vein accurate mining ramps; the in-vein accurate mining slope ramp is arranged on an ore body bottom plate and is arranged in a pseudo-inclined mode relative to the inclination angle direction of an ore body. And according to stoping conditions, false-inclined drifts with different gradients are arranged in the subsections to carry out layered mining from bottom to top. According to the method, pseudo-inclined drift mining is adopted, the number of stopes in the subsections is increased, and the mining-cutting ratio is reduced. The height of the drift of the pseudo-inclined chamber is lower than the height of the subsection roadway of the subsection or the level of the subsection roadway of the subsection, and the work amount of retaining wall manufacturing is reduced in the first and second layered stoping and filling processes. No connection way is arranged between the subsection roadway and the ore body, and pseudo-inclined drifts with different gradients are directly used for mining in subsections, so that the number of stopes is effectively increased, and the mining intensity is improved.

The invention relates to the technical field of data analysis, in particular to a multi-source data-based concealed vanadium titano-magnetite bed target area delineation method and system, which comprehensively considers various factors possibly influencing drilling, such as geological condition complexity and drill bit wear risk, and has relatively low potential risks in various aspects of trajectory selection. The probability of unexpected conditions such as drill bit damage and borehole wall collapse in the drilling process can be effectively reduced, smooth drilling work is guaranteed, the drilling effect abnormity prediction result and the difficulty abnormity reflect the advantages and disadvantages of the drilling track from different angles, and the drilling efficiency is improved. The drilling effect anomaly prediction considers the influence of various abnormal conditions possibly occurring in the drilling process on the final drilling result, the difficulty anomaly focuses on the drilling difficulty of the trajectory, the two are fused and analyzed, the feasibility and the risk degree of each trajectory are evaluated more comprehensively and accurately, and the prediction accuracy is improved. And the influence degree of the track drilling process on ore deposit target area detection is reduced.

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 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 discloses an efficient ion adsorption type rare earth ore deposit prospecting exploration method which comprises the following steps: 1) delineating a prospecting prospecting area indoors through a geochemical exploration weak anomaly extraction technology; 2) investigating the rare earth mineralization enrichment law and the characteristics of rare earth minerals and clay minerals in the prospecting prospective area, carrying out large-scale geological mapping in the field, and delineating a prospecting target area; and 3) quickly positioning and evaluating the rare earth ore body through a field on-site manual percussion drill technology. According to the method, through the technical combination of the rare earth enrichment mechanism, the mineralogy, the chemical exploration weak anomaly extraction technology and the field rapid evaluation technology, rapid prospecting exploration is achieved, the prospecting efficiency and success rate of the rare earth ore are greatly improved, the time is shortened, the procedure is simplified, and the cost is greatly reduced.

The invention relates to a mineralization prediction method for synthesizing rare data based on a mineralization space structure. The method comprises the following steps: collecting and preprocessing geological data based on a prediction demand; based on the geological background of the to-be-studied area, constructing a metallogenic prediction model, determining a prediction variable and creating a prediction layer; performing mineralization space structure analysis, synthesizing a preset number of prediction variables of rare data by combining the prediction variables of the to-be-studied area, and further generating a plurality of training data sets; adopting a plurality of training data sets to respectively train the constructed metallogenic prediction model so as to predict the metallogenic probability of the to-be-researched area; and performing performance evaluation on the metallogenic prediction model, and delineating a prospecting target region based on a prediction result of the metallogenic prediction model with relatively good performance. According to the metallogenic prediction method disclosed by the invention, the nuclear density analysis is carried out on the space distribution of the known ore deposit, so that a certain number of positive samples can be synthesized under the condition of considering the geological connotation, the training of the metallogenic prediction model is facilitated, and the prospecting prediction precision is improved.

The invention discloses a determination method for different origins of metallogenic fluids in a mountain-building type gold deposit in the south of Jiangsan. According to the method, through innovative sample collection and pretreatment, high-resolution sampling and fine treatment are carried out on specific parts of an ore deposit; advanced fluid inclusion comprehensive analysis is adopted, and inclusion information is accurately obtained in combination with multiple technologies; high-precision stable isotope determination and innovative interpretation in combination with a regional database are applied; element geochemical deep analysis and innovation index application are carried out, and SR-XRF and a machine learning algorithm are introduced; and finally, through comprehensive data fusion and intelligent analysis, constructing an intelligent platform and drawing a three-dimensional evolution model. The method can effectively integrate multi-source data, accurately determine the origin of the ore-forming fluid, overcome the limitation of a traditional method, improve accuracy and reliability, provide powerful support for deep exploration of ore deposit causes and prospecting exploration, and have important theoretical and practical significance.

The invention discloses a data-mode-driven artificial intelligence model construction method for mineral product prediction, and relates to the field of earth science, and the method mainly comprises the steps: determining source, transportation and storage substitution indexes according to a mineralization system; assembling a multi-source earth science data set; constructing a source, transportation and storage branch artificial intelligence model; establishing a power law function between the ore deposit space distribution density and the key ore control element distance; adding the power law function into a hidden layer of the artificial intelligence model, and constructing a metallogenic mode constraint artificial intelligence model; inputting the multi-source earth scientific data set into a source, transport and storage branch artificial intelligence model, and extracting a source, transport and storage alternative index layer; and inputting the layers into a metallogenic mode constraint artificial intelligence model, and delineating a metallogenic prospective area. By implementing the data-mode driven artificial intelligence model construction method for mineral product prediction, the interpretability and generalization ability of the artificial intelligence model for mineral product prediction can be improved, and the precision of predicting the metallogenic prospective area is improved.

The invention discloses an experimental device and method for controlling migration and mineralization of ore-forming fluid in a wrinkle deformation process, and belongs to the technical field of ore deposit geology. The device comprises an ore liquid synthesis unit and a mechanical deformation simulation and mineralization analysis unit. The mechanical deformation simulation unit comprises a box body, an extrusion deformation system, a liquid injection system and a heating temperature control system, and can synchronously realize visual analysis of structure extrusion, fluid injection and mineralization precipitation at high temperature. The experimental method comprises the following steps: firstly, preparing a simulated metallogenic fluid containing FeS2 (pyrite); laying simulated surrounding rock and wrinkles in the box body, arranging a separation layer, and heating; extruding the sand layer and injecting fluid to simulate a mineralization process; and slicing, sampling and analyzing after model consolidation, and establishing a mineralization space distribution model. The device is simple in structure and convenient to operate, the whole process of fold extrusion, crack extension, fluid migration and mineral precipitation can be repeatedly represented, and an experimental basis is provided for hydrothermal deposit mineralization mechanism research and prospecting prediction.

The invention relates to a gold mine three-dimensional modeling and target prediction method based on multi-source data fusion. Aiming at the problems of low grade and large burial depth span of the layered hydrothermal gold deposit and two-dimensional limitation and distortion caused by single-source data existing in a traditional modeling method, a three-dimensional joint database is constructed by integrating multi-source data. According to the technical scheme, a three-dimensional joint database is utilized, earth surface, geological stratum, fault occurrence and trend information is determined, and a three-dimensional earth surface and structure model is constructed; based on an explicit and implicit combined modeling method, three-dimensional space distribution of two-long-spot rocks is determined, and a three-dimensional lithologic model is constructed; a structure-lithology coupling constraint modeling method is innovatively adopted, and a three-dimensional grade model is constructed by utilizing an implicit modeling method under the common constraint of a structure model and a lithology model; and finally, target area delineation is carried out according to the three-dimensional geologic model. Compared with a traditional method, the method has the advantages that the problem of distortion of model construction caused by a single data type is effectively solved, and accurate depiction of the ore body is realized. And the constraint of the cause mode on the three-dimensional model is highlighted, so that the target region delineation is more in line with geological knowledge.

The invention discloses a tungsten deposit deep edge metallogenic prediction method based on machine learning, and particularly relates to the technical field of geological prediction and data processing. The method comprises the following steps: acquiring multi-source geological data, constructing a multi-dimensional space grid, and dividing candidate prediction units; quartz vein density, alteration indexes, geochemical combination anomaly weights and high-frequency magnetic anomaly waveform features are extracted, and an ore control feature tensor matrix is constructed; extracting a spatial dependency relationship among the candidate units based on a graph neural network, constructing a metallogenic potential prediction model, and outputting a metallogenic probability graph and a metallogenic hot spot graph; model parameters and feature weights are dynamically optimized through spatial superposition analysis and an abnormal response recognition mechanism; according to the method, the precision and efficiency of deep edge tungsten ore prospecting can be remarkably improved, and good self-adaptability and popularization and application value are achieved.

The invention relates to an ore control element extraction and weight determination method based on a knowledge graph, and the method comprises the following steps: constructing a geological mineral knowledge graph: collecting geological text data, extracting entities and semantic relationships in the geological text data, and constructing the geological mineral knowledge graph; network analysis and simplification: utilizing a community clustering algorithm to divide an ore deposit, and combing and simplifying a complex geological knowledge map in combination with a modularity algorithm process; subgraph generation: constructing a series of subgraphs according to community categories of nodes, and forming an information set which completely and structurally represents specific geologic features and metallogenic conditions; weight calculation and integration: quantifying the indicating significance of different geological entities on ore deposit prospecting through an entity-relation weight result, and defining the weight of ore control elements; and element screening: sorting according to the weight values, and rapidly screening out geological entities which have important influence on ore deposit mineralization as ore control elements. According to the invention, an intelligent and automatic decision support tool is provided for geological prospecting work.

The invention relates to the technical field of mineral resource exploration in geology, in particular to a method for quantitatively detecting the denudation preservation condition of mineral resources based on thermal chronology. Constructing a thermal evolution history of the target ore deposit in a set time period based on thermal chronology; dividing a stable cooling time period of the target ore deposit in an evolution history in a set time period; geologic characteristic parameters and thermal chronology temperature parameters of the target ore deposit in the stable cooling time period are obtained, a thermal simulation curve is established according to the thermal chronology temperature parameters, and a second rise value and a second stripping value of the target ore deposit in the stable cooling time period are obtained according to the geologic characteristic parameters and the thermal simulation curve; and carrying out quantitative analysis on the resource preservation condition of the target ore deposit according to the first rising value and the first stripping value of the target ore deposit. According to the method provided by the invention, denudation and uplift degree analysis of the ore deposit is carried out on the basis of thermal chronology data, accurate analysis data can be obtained, and quantitative evaluation of the storage condition of the ore deposit can be better realized.

The invention provides a skarn type polymetallic deposit prospecting exploration method and system based on three-dimensional modeling, and relates to the field of geological prospecting, and the method comprises the steps: obtaining deposit data of an area where a deposit is located, and carrying out the preprocessing of the data of the mined skarn type polymetallic deposit; selecting a multi-scale convolutional neural network as a deep learning model for training so as to predict the position where an ore deposit possibly exists in the unmined area; generating a geologic feature coefficient according to the predicted geologic features of the unmined area; generating a mineral characteristic coefficient through the mineral characteristic data of the three-dimensional model; comparing the mineral characteristic coefficient with a preset weight, and judging whether tungsten-tin ore exists or not; generating a mineral type judgment coefficient according to the content of mineral elements in the sample; generating a comprehensive prediction value through the geologic characteristic coefficient and the mineral characteristic coefficient, and judging the type of the ore deposit according to the comprehensive prediction value and the type judgment coefficient. The method improves the accuracy and efficiency of ore deposit prediction.

The invention discloses a geophysical three-dimensional visualization and geologic model construction system, which belongs to the technical field of geophysical data processing and three-dimensional geologic modeling and comprises a multi-source data acquisition module, a volume rendering module, an interactive segmentation module, an uncertainty expression module, a multi-scale fusion module, an attribute interpolation module and a model construction module. Multi-source geophysical data are converted into a visual three-dimensional visual model through a volume rendering technology, an interactive segmentation algorithm is adopted to accurately extract a geologic body boundary, an uncertainty expression mechanism is innovatively introduced to quantify the reliability of the model, and a multi-scale fusion technology is integrated to realize seamless connection from a regional structure to an ore deposit fine structure. The Kriging interpolation functional product physical property parameter three-dimensional distribution field is provided, the spatial cognitive ability and the decision-making efficiency under the complex geological condition are remarkably improved, and a powerful visual analysis platform is provided for geological exploration and resource evaluation.

The invention discloses a hydrothermal vein type gold deposit alteration zoning remote sensing identification method, and the method specifically comprises the following steps: S1, carrying out multi-platform remote sensing cooperative interpretation, and obtaining the initial alteration zoning information of a regional scale. According to the hydrothermal vein type gold deposit alteration zoning remote sensing identification method, through organic combination of multi-platform remote sensing cooperative interpretation and unmanned aerial vehicle fine mineral mapping, cross-scale detection from regional scale preliminary alteration zoning identification to target region scale alteration lithofacies accurate delineation is realized; the problems that a traditional remote sensing method is single in scale and insufficient in precision in alteration zoning recognition are effectively solved. According to the method, the complementation advantages of multi-temporal optical remote sensing, synthetic aperture radar and thermal infrared remote sensing data are utilized, accurate recognition of key altered minerals is achieved in combination with hyperspectral data of the unmanned aerial vehicle, and the certainty of alteration zoning boundaries and the accuracy of lithofacies classification are remarkably improved.

The invention provides a downward parallel medium-length hole sublevel filling mining method for a low-grade broken ore body, belongs to the technical field of mining, and solves the problems that a traditional mining method is low in mining efficiency and high in cost under complex geological conditions. Downward parallel medium-length holes are adopted in each section for drilling and blasting, efficient stoping is achieved in cooperation with remote control ore removal and supporting equipment, an interbed filling technology is adopted in a goaf to be combined with a reinforcing mesh structure to form an artificial roof, stress and displacement changes of a filling body are monitored in real time through a ground pressure monitoring system, and the stoping sequence and supporting parameters are optimized. According to the method, the efficiency and safety problems of a traditional mining method in low-grade and broken ore deposit and three-under resource mining are solved, large-scale, low-cost, safe and efficient mining is achieved, and the method is suitable for ore body mining under complex geological conditions.

The invention provides a method and a system for delineating a mineralization center in a porphyry-skarn ore deposit based on short-wave infrared spectroscopy, and relates to the technical field of ore deposit mineralization centers. Short-wave infrared spectroscopy data and time sequence analysis are combined, and time sequence analysis and a dynamic mineralization probability distribution model are introduced, so that the mineralization center of the porphyry-skarn ore deposit is delineated. A dynamic mineralization potential prediction framework is constructed by combining the hydrothermal activity temperature calculated by the oxygen isotope fractionation effect, the mineralization process can be dynamically simulated, and spatial and temporal distribution prediction of a target mineral mineralization center is generated. By introducing the time dimension, combining the mineralization stage division and oxygen isotope temperature inversion, and combining the three-dimensional geologic model and the dynamic prediction technology, the dynamic change of the mineralization environment can be reflected more accurately, and the prediction precision is improved. Therefore, resource allocation is effectively optimized, unnecessary exploration operation is reduced, and accurate guidance and scientific basis are provided for mining area exploration.

The invention discloses a manganese ore deposit exploration effect evaluation method and system based on a spread spectrum induced polarization method, and relates to the technical field of deposit exploration. The method comprises the following steps: constructing a three-dimensional geologic model of a mining area, initially arranging an exploration unit and acquiring actual exploration data, inverting the actual exploration data to generate an initial geologic profile map, performing exploration simulation in the three-dimensional geologic model and acquiring simulated exploration data, acquiring a distortion index and a spatial influence degree of the actual exploration data and constructing an exploration correction model; the exploration unit is reset, corrected exploration data are obtained, and inversion is carried out on the corrected exploration data to generate a corrected geological profile map; the effectiveness of various data obtained in the ore deposit exploration process can be improved, the distribution condition of an ore deposit can be better reflected, and then the accuracy of ore deposit exploration is enhanced.

The invention provides a prospecting model generation and prospecting method, device and system based on intrinsic characteristics, and belongs to the technical field of mineral resource exploration, and the method comprises the steps: obtaining vibration signals which are collected by an optical resonance type acousto-optic sensor and are fed back after vibration excitation is applied to mineral resources with different characteristics, and the characteristics comprise types, grades, structures and reserves; performing iterative training on an initial model by taking a machine learning algorithm as the initial model, taking the vibration signal as input and taking different features as output; and outputting the completely trained initial model as a final prospecting model. The technical problem that underground deep mineral resource information is difficult to accurately obtain in the prior art is effectively solved.

The invention relates to the technical field of ore deposit geological exploration, in particular to a method for judging the composite mineralization of a magma hydrothermal system, which comprises the following steps: 1) field geological survey and total factor sampling; 2) screening characteristic minerals and identifying lithofacies; (3) feature mineral mineralization generation division and cause preliminary exploration; 4) in-situ microcell geochemical analysis; (5) geochemically verifying the formation cause of the ore deposit; 6) analyzing an element zoning mode; and 7) reconstructing the composite mineralization process. According to the method, lithofacies discrimination, mineral geochemical analysis and mineral internal element spatial distribution (mapping / plane scanning) are organically combined, a multi-scale and multi-criterion synergistic composite mineralization recognition system is constructed, the magma hydrothermal system mineralization type can be effectively recognized, and then the composite mineralization process is reconstructed. The problem of lithofacies and geochemical splitting in traditional analysis is solved, and key technical support is provided for complex magma hydrothermal cause deposit analysis and deep prospecting prediction.

The invention discloses a short-distance multi-ore-bed potassic salt ore large-section long-strip comprehensive mechanized mining method, and belongs to the technical field of potassic salt ore deposit mining. The method comprises the steps that a centralized transportation roadway is arranged on an upper head mining layer, an auxiliary transportation roadway is arranged in a stable salt rock interlayer between ore layers, and combined development is achieved; arranging large-section long strip chambers in the ore blocks along the inclination direction, and reserving permanent spacing strip pillars to maintain the stope to be stable; a chamber is cut and formed at a time by a double-arm large-mining-height mining machine, and efficient stoping is realized by matching with a continuous transportation system; multiple ore beds are mined in a coordinated mode from top to bottom in sequence, and the ore block air return way and the ore block air return way of the upper ore bed are staggered by 20 m or above so as to avoid stress superposition; a full-air-pressure ventilation system combining a press-in type and a draw-out type is constructed; natural supporting is achieved through permanent spacing strip pillars and natural top and bottom plates, safety is guaranteed through a micro-seismic and top plate monitoring system, and the goaf is backfilled with tail salt slurry to achieve green mining. According to the method, safe, efficient and high-recovery-rate mining of the short-distance multi-ore-bed sylvite ore is achieved.