1081 results about "Maceral" patented technology

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 provides a deep geologic body occurrence characteristic quantitative representation modeling method and system, and the model focuses on the multi-physics field occurrence environment of rock mass material composition, structural characteristics, stress distribution and the like under the continuous mining condition of a deep underground metal mine. An information expression framework capable of crossing a'microcosmic-experimental-engineering 'multi-level spatial scale is constructed, microcosmic rock core mineral components and crack information, laboratory mechanical response parameters and structural surface shear characteristics and macroscopic fault system and stress disturbance data reflected by microseismic events are introduced, a heterogeneous data fusion method is comprehensively applied, and a microcosmic-experimental-engineering multi-level spatial scale is constructed. A three-dimensional tensor model with dynamic evolution capability and physical interpretation capability is established, high-precision, dynamic and multi-scale comprehensive modeling of a complex deep geologic body occurrence environment is realized, and the model has the characteristics of clear information hierarchy, high fusion precision, strong physical interpretability and the like. And dynamic perception and scientific research and judgment of geologic mass mechanics and structure states can be realized in a complex deep environment.

The invention belongs to the technical field of geological information processing, and discloses a geological mineral exploration data extraction system which comprises the following steps: constructing an air-ground-hole three-in-one acquisition network, and respectively acquiring earth surface mineral spectrum data, seismic longitudinal wave and transverse wave reflection data and rock core main quantity and trace element composition data; processing the collected data to form a five-dimensional data cube containing space coordinates, spectrum parameters, physical property parameters, element parameters and time indexes, performing physical layer attribute extraction on the five-dimensional data cube, performing analysis to obtain a wave impedance value and a lithology category probability array, performing semantic layer attribute extraction on the five-dimensional data cube, and performing semantic layer attribute extraction on the five-dimensional data cube; an alteration type probability array is obtained through analysis, an alteration zoning graph layer is generated, the mineralization potential index and a five-dimensional data cube are fused, a four-dimensional dynamic database is constructed, a mineralization potential prediction graph layer and a drilling priority graph are generated based on the four-dimensional dynamic database, and therefore the decision-making level of ore body drilling deployment is improved.

The invention discloses a deep resource fluidized mining disturbance effect evaluation model under a multi-field coupling effect, and the method specifically comprises the following steps: constructing a multi-field coupling parameter system: collecting geologic body basic parameters, covering rock mass mechanical parameters, thermal physical parameters, fluid parameters and chemical parameters in deep three-high, high ground stress, high ground temperature and high karst water pressure environments, and establishing a multi-field coupling parameter system; the method comprises the following steps: establishing a dynamic parameter database, realizing real-time updating of parameters along with a mining process, establishing a heat-flow-force-chemical full-coupling mathematical model, introducing the influence of a rock plastic damage correction term quantification temperature on heat conduction efficiency, associating a dynamic mapping relation between mineral reaction and rock physical property parameters, and establishing a dynamic parameter database. Simplification errors of a traditional model on multi-field effects are thoroughly eliminated, chained interaction of temperature, fluid, stress and chemical processes in a deep three-high environment is accurately described, a model prediction result better fits an actual mining working condition, and prediction deviation is greatly reduced.

The invention discloses a rock crack evolution numerical simulation method based on data analysis, and relates to the technical field of rock mechanics engineering numerical simulation, and the method comprises the following steps: S1, obtaining microstructure data of a target rock, including a CT scanning image, an SEM image and mineral energy spectrum data; and S2, constructing a spatial distribution dynamic mechanical parameter field based on the microstructure data. According to the rock crack evolution numerical simulation method based on data analysis, a dynamic mechanical parameter field driven by a microstructure is constructed, so that the inherent defect that rock is simplified into a homogeneous material in a traditional method is overcome; microscopic characteristics such as mineral hardness gradient, grain boundary strength distribution and pore morphology are effectively quantified into an elastic modulus field, a tensile strength field and a fracture energy field which are spatially distributed, so that the numerical prediction of crack initiation and expansion truly reflects the inherent heterogeneity of the rock for the first time.

The invention provides a mineral leaching property analysis method, which belongs to the field of process mineralogy, and comprises the following steps: crushing and enriching a sample to be detected, and selecting single mineral particles to obtain target mineral particles; the preparation method comprises the following steps: coating a sample preparation grinding tool with epoxy resin glue, adding target mineral particles, and carrying out curing and grinding treatment to obtain a primary sample; cutting the primary sample, placing the grinding surface downwards and the three wear-resistant alloys at the bottom of a sample preparation grinding tool, injecting epoxy resin glue, curing to form a composite sample, accurately grinding, polishing, performing carbon spraying treatment, performing first automatic mineralogical analysis, measuring the area of a target mineral, cleaning, and performing leaching treatment to obtain a treated sample; and after solidification, accurate grinding and polishing and carbon spraying treatment, secondary automatic mineralogical analysis is carried out, the area of the residual target mineral is measured, and the leaching index of the target mineral is calculated. Reliable technical support is provided for mineral processing technology optimization and resource evaluation, and the method is particularly suitable for development of efficient leaching technologies of precious metal, rare earth and the like.

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 provides a method for detecting the porosity of in-situ dump-leached ore, and belongs to the technical field of ore porosity detection. The method comprises the following steps: taking an ore body on site, preparing a filling agent, performing vacuum gradient impregnation, curing, dissolving and separating the ore to obtain a pore model; melting and softening the pore model to obtain the pore volume in the ore, and finally obtaining the porosity of the ore; wherein nano SiO2 is added into the filler resin, and permeation of tiny pores is guaranteed based on the size effect and the interface optimization effect of a nano material; and through vacuum gradient impregnation, sufficient permeation of tiny pores is further ensured. According to the detection method, the limitation of a drainage method on ore pores containing water-soluble minerals is avoided; the problems that ore samples need to be collected and taken back to a laboratory to be detected in a mercury injection method, a gas adsorption method and the like, the ore body structure is damaged, and consumed time is long are solved. Detection can be carried out on site, ore permeability parameters are provided for the in-situ dump leaching process, and a real-time basis is provided for flow selection.

The invention provides an ore leaching property analysis method, and belongs to the field of process mineralogy, and the method comprises the following steps: taking a to-be-detected sample, carrying out ore grinding treatment, and carrying out ore washing and desliming to obtain a pretreated sample; mixing the pretreated sample with graphite to prepare an automatic mineralogical analysis sample, measuring the content of a target mineral and the content of a target element through automatic mineralogical analysis, and calculating the average content of the target mineral; adding an agent into the pretreated sample to carry out leaching reaction, carrying out solid-liquid separation to obtain mineral residues, and calculating the mass ratio of the mineral residues to the pretreated sample before reaction; mixing mineral residues with graphite to prepare an automatic mineralogical analysis sample, analyzing the sample, measuring the content of residual target minerals and the content of residual target elements, and calculating the average content of the residual target minerals; and calculating a mineral leaching coefficient and an ore leaching coefficient based on the obtained data. The in-situ leaching recovery rate prediction method based on mineralogical analysis is suitable for development and evaluation of low-grade and complex ore bodies.

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 relates to the technical field of oil exploration, and discloses a rock mechanical parameter logging intelligent evaluation method considering continental facies shale fabric characteristics. The method comprises the following steps: 1, dividing shale lithofacies, identifying and determining the bedding development thickness of a sample through an optical microscope, determining a granularity experiment of the sample through granularity analysis, and forming mineral composition and bedding factor lithofacies division; 2, constructing a typical logging facies based on a rock electricity response relationship, and dividing the imaging logging facies of the research area according to natural gamma curves of conventional logging and imaging logging, core deposition structure characteristics and imaging logging image characteristics; 3, testing the longitudinal and transverse wave velocities and the porosity of different shale lithofacies, and calculating the dynamic elastic modulus and the Poisson's ratio. Through fine division and description, the method for accurately evaluating the bedding development condition, the particle size characteristics and the mineral components of the shale sample is provided, the testing time is short, the cost is low, and accurate evaluation of shale can be achieved.

The invention discloses an orthotropic rock physical modeling method. The method comprises the following steps: S1, obtaining tight reservoir parameters; s2, estimating the elastic modulus of the mixed minerals; s3, enabling the mixed mineral to be equivalent to a VTI background rock matrix caused by a thin layer; s4, matrix pores are added into a VTI background rock matrix; s5, embedding the vertical crack into the VTI background'dry 'rock skeleton to obtain an OA medium'dry' rock skeleton; s6, calculating the bulk modulus and saturated rock density of the mixed fluid; s7, adding the mixed fluid into the OA medium'dry 'rock skeleton to obtain OA medium saturated rock; s8, calculating longitudinal and transverse wave velocities and anisotropy parameters of OA medium saturated rocks; and S9, calculating OA medium saturated rock. According to the method, the tight reservoir with the orthotropic characteristic can be simulated, the Thomsen parameter and the fracture weakness parameter of the tight reservoir can be obtained, and data support is provided for fracture evaluation, anisotropic parameter inversion, permeability prediction and the like of the tight reservoir.

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 nuclear magnetic T2 spectrum correction method for a shale reservoir, and relates to the field of object detection, and the nuclear magnetic T2 spectrum correction method for the shale reservoir comprises the following steps: 1, determining the gas logging porosity, saturated water porosity and main mineral components of the shale reservoir; compared with the prior art, the method disclosed by the invention has the beneficial effects that a drying-saturated water-centrifugal two-dimensional nuclear magnetic resonance experiment is carried out, and signals of crystal water, clay bound water and hydroxyl in a sample are preliminarily identified; through inversion of organic matter signals in the dry sample, signals of movable water are further determined; the relation between the difference value among the gas logging porosity, the saturated water porosity and the nuclear magnetic porosity and different mineral contents is discussed, and particularly the remarkable influence of iron-containing minerals on the porosity difference value is discussed; by eliminating the influence of diffusion relaxation caused by the magnetic susceptibility difference, the T2 spectrum correction method based on the mineral magnetic susceptibility is established, and the T2 spectrum accuracy obtained through nuclear magnetic resonance measurement is improved.

The invention relates to the technical field of oil and gas geological exploration, in particular to an over-mature hydrocarbon source rock parent material type distinguishing method and system.The method comprises the following steps that regional deposition characteristics are studied, an over-mature hydrocarbon source rock deposition environment is recognized, principal elements and microelements are extracted in combination with a geological background, and component relevance is judged; and sorting representative sedimentary environment elements, and establishing a sedimentary environment associated element set. According to the method, accurate recognition of the sedimentary environment is achieved by extracting major elements and trace elements, representative elements are screened, proportional analysis is combined with the macerals, distribution characteristics of saprolite groups, exinite groups and the like are determined, the ratio relation between the macerals and inorganic elements is recognized, a ratio operation set is constructed, and the relation between the macerals and the elements is analyzed in a multi-dimensional mode. The relationship between parent material types and maceral characteristics is disclosed, a maceral type index model is constructed, hydrocarbon source rock parent material type division precision and sedimentary environment analysis systematicness are improved, and a scientific basis is provided for oil and gas resource exploration.

The invention provides an altered mineral recognition model construction method and system and a storage medium, and relates to the technical field of geological exploration, and the method comprises the steps: obtaining remote sensing data of a geological resource environment hyperspectral microsatellite for a target region; performing feature enhancement on the remote sensing data through a band ratio method to obtain band ratio features of the remote sensing data; performing principal component analysis on the remote sensing data to obtain principal component characteristics of the remote sensing data; splicing the waveband ratio feature, the principal component feature and the remote sensing data to obtain a high-dimensional feature matrix, and allocating an actual target mineral proportion to each pixel in the high-dimensional feature matrix according to preset mineral sample data; and training the initial recognition model according to the high-dimensional feature matrix and the actual target mineral proportion, and taking the trained initial recognition model as an altered mineral recognition model. According to the method, through multi-dimensional feature extraction and an advanced machine learning algorithm, the recognition effect on altered minerals is remarkably improved.

The invention provides a method for measuring a structure coefficient, and belongs to the field of process mineralogy, and the method comprises the following steps: selecting a representative ore sample, and preparing an automatic mineralogy analysis sample; performing automatic mineralogical analysis on the automatic mineralogical analysis sample, measuring the area of a target mineral and the content of a target element, and calculating a structural distribution coefficient, an edge structural distribution coefficient and a far-end structural content of the target mineral in combination with the density of the target mineral; and based on the target mineral structure content, the edge structure content and the far-end structure content, a target mineral structure coefficient, an edge structure coefficient and a far-end structure coefficient are calculated respectively, and an ore structure coefficient is obtained through weighted summation. According to the method, a special calculation method is set, the structural characteristics of the ore are comprehensively represented by the target mineral structure, the edge structure and the far-end structure, and the structural characteristics of the ore can be measured; through analysis of ore characteristic structures, structure coefficients are calculated so as to represent the influence of the structures on the permeability of the ore.

The invention discloses a hyperspectral satellite target rock and mineral identification method and system based on spectral characteristic parameters. The method comprises the following steps: S1, collecting and preprocessing a standard rock and mineral reflection spectrum curve; s2, collecting a regional hyperspectral satellite image and carrying out image preprocessing; s3, identifying diagnostic spectral reflection and absorption characteristics of the target rock mine based on the standard curve; s4, screening and extracting a diagnostic spectral range of the hyperspectral satellite image; s5, calculating diagnostic spectral characteristic parameters of the hyperspectral image target rock mine; and S6, on the basis of the S5, processing the spectral characteristic parameters obtained by calculation, and realizing target rock and mine identification based on multi-dimensional diagnosis spectral characteristics. According to the method, the application potential of the hyperspectral satellite image in the field of remote sensing geology is effectively improved and the scientificity and the accuracy of the hyperspectral satellite image in large-range rock and ore recognition drawing application are improved through the target rock and ore standard spectral curve characteristic analysis, hyperspectral satellite image processing and spectral characteristic parameter estimation methods.

The invention belongs to the technical field of magnetite beneficiation, and particularly relates to a method for removing iron impurities in minerals through manual and automatic three-stage combination in magnet beneficiation, a three-stage iron removal system is arranged, the iron impurities and ferromanganese are detected step by step according to the size of the iron impurities and the property of magnets or ferromanganese, and a detected magnetic field is cooperatively calibrated step by step; and iron impurities in the ores are removed in a classified manner. Compared with the prior art, the system has the beneficial effects that a manual and automatic three-stage combined iron removal solution is adopted, large magnetic iron impurities, small magnetic iron impurities and ferromanganese impurities in the process are efficiently classified and removed in a targeted manner, damage of the iron impurities to equipment such as an ore crusher and a belt conveyor is avoided, the operation efficiency of the process is improved, and the production cost is reduced. And the problem of removing iron impurities in magnet beneficiation is solved.

A rock breaking efficiency prediction method based on image recognition and machine learning comprises the following steps: acquiring a rock surface image, performing graying processing by applying an image processing technology, and then performing pixel classification and image segmentation so as to clearly divide different minerals into a plurality of independent structure diagrams; modeling a rock material according to mineral components, importing boundary information of the plurality of structure diagrams into a model, generating a plurality of large-particle filled rock blocks with the same size as the plurality of structure diagrams, and calibrating mesoscopic parameter values according to rock mechanical characteristics; establishing a hob rock breaking discrete element calculation model, and performing multiple intrusion rock breaking simulation tests on rock samples with different mineral contents; collecting simulation results to construct a rock breaking efficiency data set; a prediction model is established based on a PSO-BPNN algorithm, and a rock breaking efficiency prediction model is obtained after training; and carrying out real-time prediction on the rock breaking efficiency by utilizing the established model. According to the method, the influence of rock mineral components on the rock breaking effect of the hob is considered, and efficient and accurate prediction of the rock breaking efficiency of the hob is realized by utilizing a method of combining rock microscopic components and macroscopic rock breaking behaviors.

The invention discloses a method and a system for estimating the content of key metal elements of a crusting based on a hyperspectrum, and belongs to the technical field of deep sea mineral detection. The method comprises the following steps: selecting a crusting sample, obtaining hyperspectral data and chemical data of the crusting sample, establishing a point selection data set at a corresponding position, deleting abnormal sample points, and calculating the content of the key metal elements of the crusting sample; the method comprises the following steps: selecting a characteristic wave band of a crusting sample through preprocessing and CARS to obtain a characteristic wave band data set; and based on an MLP neural network model, performing model training through the data set, and constructing an estimation model for estimating the grade of the crusting sample. Compared with the prior art, the method has high accuracy and high predictive capacity, by inverting chemical data of the whole crusting section and applying the scheme for estimating the content of the key metal elements of the crusting, nondestructive grade and abundance analysis of the crusting sample can be achieved, and a reliable scientific basis is provided for seabed detection and multi-metal mineral exploitation.

The invention provides a multivariate numerical analysis method and system based on a TEHB test system, and the method comprises a multidirectional synchronous impact test numerical simulation step: building a rock numerical model with a real mineral structure and breakable mineral crystals, and constructing a single-axis bidirectional synchronous impact test simulation frame, the multi-directional synchronous impact test simulation module is used for implementing multi-directional synchronous impact test numerical simulation on the rock numerical model; a dynamic response index calculation step: separating and recombining the incident wave signal and the reflected wave signal obtained by monitoring, and obtaining a dynamic response index of the rock numerical model in the impact process; and a multi-element parameter intelligent analysis step: during numerical simulation of the multidirectional synchronous impact test, displaying spatial distribution characteristics of different types of cracks in real time, and realizing intelligent microscopic analysis of crack evolution, rock damage and energy characteristics. According to the invention, the dynamic mechanical behavior of the rock under the impact load can be simulated, and the real-time fracture information in the rock can be displayed more visually.

The embodiment of the invention relates to the technical field of pile foundation construction, and particularly discloses a karst pile foundation slurry leakage prevention early warning method and system. According to the embodiment of the invention, the pile foundation construction area is determined, and geological radar detection, electrical exploration and drilling exploration are carried out on the pile foundation construction area to obtain geological detection data; monitoring deployment is carried out, real-time monitoring data is acquired, a three-dimensional monitoring model is established, and visual monitoring display is carried out; extracting a plurality of key feature data in the real-time monitoring data, and importing the key feature data into a preset slurry leakage model to obtain a slurry leakage prediction probability; and according to the slurry leakage prediction probability, determining a slurry leakage early warning grade, and according to the slurry leakage early warning grade, carrying out early warning alarm and emergency treatment. According to the method, a synergistic leaking stoppage mechanism of the pH sensitive pneumatic capsule and the geological bonding agent is innovatively designed, directional enrichment of nano materials is driven through the instantaneous negative pressure field effect, in-situ strengthening reaction based on rock mass mineral characteristics is triggered, and dependence of a traditional grouting process on the fracture form is broken through.

The invention discloses a quantitative evaluation method for complexity of shale oil and gas horizontal well reservoir reconstruction cracks, which comprises the following steps: determining a crack development strength factor representing reservoir inherent crack development potential by calculating a mineral heterogeneous coefficient based on rock sample mineral component data at each perforation cluster position in a target fracturing section; determining the optimal fracture length by combining reservoir numerical simulation, determining the total fracturing fluid amount, performing non-uniform distribution according to the heterogeneity of each cluster, and determining a fracture propagation complexity factor representing the dynamic propagation complexity of the hydraulic fracture; weighting the two factors to obtain a crack complexity index for comprehensively evaluating the reservoir transformation effect, and performing grading; according to the method, static geological evaluation and dynamic engineering evaluation are combined, quantification of inter-cluster transformation differences is achieved, the defects that a traditional method is one-sided in evaluation and low in precision are overcome, and a reliable quantitative basis is provided for optimal design of a shale oil and gas reservoir fracturing scheme and accurate evaluation of the transformation effect.

The invention provides a metal ore artificial intelligence sorting method based on lithofacies analysis, and relates to the technical field of data processing, and the method comprises the steps: obtaining a unified image of an ore sample, extracting a crystal structure contour, and calculating texture direction consistency, particle distribution density and color concentration degree in each region; constructing a lithofacies analysis model based on a two-channel neural network; training the lithofacies analysis model according to the training data set to obtain a fusion recognition model; obtaining an ore image to be sorted, and inputting the ore image to be sorted into the fusion recognition model to obtain predicted mineral distribution data; and extracting a boundary confidence factor and a region type probability, carrying out re-calibration on predicted mineral distribution data, generating a sorting control instruction, and driving sorting equipment to carry out physical sorting operation. The rock facies analysis is carried out on the ore image sample through artificial intelligence, and the types of symbiotic minerals can be accurately distinguished.

The invention relates to the technical field of big data processing, and discloses a data extraction method and system for geological mineral exploration, and the method comprises the steps: carrying out the standardization preprocessing of original data containing space coordinates, lithology texts, mineral components, logging curves and mineralization labels; spatial, semantic, concentration and time sequence deep representations are extracted in parallel through a multi-modal geologic feature encoder and fused into high-dimensional vectors; applying structured sparse constraint to the features by using a graph attention mechanism guided by an expert knowledge graph, and strengthening a mineralization association dimension; a dynamic incremental learning engine is combined with an elastic weight solidification mechanism to realize local fine tuning of model parameters and historical knowledge retention; and finally outputting a mineralization potential score, a mineralization factor sequence and an abnormal element combination. According to the method, through triple mechanisms of multi-modal fusion, knowledge embedding and incremental evolution, the accuracy, interpretability and timeliness of data extraction are improved, and the real-time analysis requirement of large-scale mineral exploration is met.

The invention relates to the technical field of grading gangue selection of coal gangue, in particular to a grading gangue selection method of coal gangue, which comprises the following steps: acquiring mineral texture data through a multispectral imaging device, analyzing the spatial distribution of aluminum and silicon elements in combination with an X-ray diffractometer, and generating a three-dimensional component map through spatial registration and fusion with infrared heat value data; impurities are dynamically removed through sulfur element spectrum detection, and the air pressure and the material flow of winnowing equipment are adjusted by matching roasting process parameters; components of the sorted waste are analyzed through an X-ray fluorescence spectrometer, particle size data are obtained through a laser particle analyzer, a genetic algorithm is input to iteratively optimize detection channel combination and sampling density, a resource distribution instruction is generated, and equipment parameter correction is fed back. According to the method, aluminum-silicon ratio critical value accurate identification, sorting parameter dynamic adaptation and waste recycling path optimization are realized, and the problem of overburning caused by insufficient quantitative analysis of element distribution in the prior art is solved.

The invention relates to the technical field of mineral exploration, and discloses a method for determining a heat source center of a gold and copper ore area containing alunite minerals, which comprises the following steps of: determining a to-be-detected area of a target mining area, sampling surface rocks according to a preset grid or section, and acquiring a plurality of rock samples and corresponding original acquisition points; carrying out mineral component analysis on the plurality of rock samples, screening the alunite-containing samples to obtain a plurality of alunite-containing samples, and screening effective samples; performing elemental component analysis on the effective sample, and extracting elements and contents related to gold mineralization or copper mineralization in the effective sample; setting a potential heat source center, calculating the distance between each effective sample and the potential heat source center, introducing a distance attenuation index, establishing an objective function of the element content and the distance, and adopting a gradient descent method to perform inversion solution by minimizing the objective function to obtain coordinates of the potential heat source center, namely the determined heat source center of the gold ore or the copper ore; the method improves the accuracy of gold and copper ore area heat source center exploration.

The invention provides a method for measuring and calculating the article position of continuous silver ore with the particle size of 0.037 mm or above, and belongs to the technical field of mineral grade detection. The silver grade in the sample is measured and calculated through screening; leaching and measuring the content of silver monomers and continuous silver minerals, and reselecting to obtain a heavy sand product; carrying out fluorescent dyeing on the heavy sand product, and selecting monomer silver minerals; analyzing the color of the silver mineral through point scanning data of a scanning electron microscope, melting the monomer silver mineral to obtain the volume of the monomer silver mineral, and calculating the content of the monomer silver mineral; and carrying out conversion to obtain the continuous silver ore article position with the size of more than 0.037 mm. According to the method, the target mineral is rapidly and accurately obtained by adopting density medium reselection and fluorescent dye tracing; introducing a scanning electron microscope to measure and calculate the actual density of the silver mineral to replace the theoretical density, smelting the silver mineral in a mold, and carrying out volume measurement and calculation to obtain the actual metal amount closer to the actual silver mineral; measuring and calculating errors caused by impurities and irregular shapes of mineral particles are reduced; and the calculated grade of the silver mineral is more accurate.

The invention belongs to the field of tunnel construction and the field of deep engineering disaster prevention and control, and provides a hydraulic and microwave combined insensitive hard rock burst prevention and control device which comprises a vehicle-mounted system, a hydraulic fracturing system and a microwave emission system. The hydraulic fracturing system is used for injecting water into the insensitive hard rock drill hole, forming a hydraulic fracturing crack on the circumferential wall surface of the insensitive hard rock drill hole, and then injecting a sensitive mineral proppant to fill the hydraulic fracturing crack; the microwave emission system is used for moving into the insensitive hard rock drill hole for microwave irradiation after the sensitive mineral proppant is injected; according to the method, hydraulic fracturing, microwave fracturing and sensitive mineral filling are combined and applied to fracturing and pressure relief of the insensitive hard rock of the deep tunnel, and due to the fact that sensitive minerals have high dielectric constants and dielectric loss factors, a good temperature rise effect can be shown under microwave irradiation.