345 results about "Prospecting" 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 provides a prospecting prediction method based on a multi-agent technology. The method specifically comprises the steps that S11, keyword extraction is conducted on mineral problems input by a user; s12, establishing a vector database of the mineral knowledge text and a graph database of the mineral knowledge graph, and optimizing the extracted keywords to generate cue words; s13, constructing a large prospecting model to think the cue words, expanding the cue words, and obtaining a complete statement for professional expression of the user question again; s14, performing multi-task decomposition on the complete statement to obtain a plurality of sub-tasks, and scheduling the plurality of sub-tasks to corresponding agents based on a graph database of the mineral knowledge graph to perform step-by-step prediction; and S15, integrating prediction results of the intelligent agents and feeding back the integrated prediction results to a user. According to the method, prospecting prediction is promoted to be converted from manual driving to intelligent driving, and emerging technical support is provided for prospecting breakthrough.

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 geological prospecting, in particular to a prospecting target area resource decision-making method and system based on minimization of influence of an environment sensitive area, and the method comprises the steps: obtaining geological data and environment data of each prospecting target area in a target exploration area, and carrying out the preprocessing; constructing a space-time coupled environment sensitivity dynamic quantification model based on the preprocessed environment data, and extracting environment sensitivity quantification results of the prospecting target areas; constructing a geological potential quantification model based on the preprocessed geological data set, and extracting a geological potential quantification result of each prospecting target area; constructing a prospecting target region difference matrix based on the environmental sensitivity and the geological potential result, and extracting a typical prospecting target region through fuzzy support vector machine classification and density peak clustering; and constructing a three-dimensional decision-making space, and solving a decision-making result of the prospecting target area by adopting a multi-objective optimization algorithm. The objective of the invention is to improve the efficiency and accuracy of large-scale prospecting target area resource decision.

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 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 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 boundary-preserving seismic wave impedance inversion method, device, equipment and medium, and relates to the technical field of geological prospecting. Historical seismic data of a target area and logging curve data including logging impedance parameters are acquired, and seismic wavelet data are extracted from the historical seismic data; carrying out data processing on the seismic wavelet data to obtain target seismic wavelet data, constructing an initial impedance parameter model according to the logging curve data, carrying out forward modeling on the initial impedance parameter model, constructing a composite objective function comprising a boundary preserving constraint term and a prior information constraint term, and carrying out the forward modeling on the initial impedance parameter model based on the composite objective function. And the initial impedance parameter model is updated to obtain the target impedance parameter model, and the output impedance parameter inversion curve is obtained through the target impedance parameter model, so that the inversion precision and efficiency are improved, and the inversion stability and the geological reduction capability are improved.

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 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.

The invention belongs to the technical field of geological prospecting, and particularly discloses an exploration method for constructing an altered rock type gold mine in a shallow coverage area, which comprises the following steps of: firstly, optimizing a working area by using regional geochemical prospecting abnormity, and gradually reducing a prospecting target area by using 1: 25,000 geochemical measurement, 1: 10,000 soil profile measurement and 1: 10,000 geological grass survey; identifying a linear negative topographic development section by using an unmanned aerial vehicle, quickly positioning a gold-bearing structure alteration zone by using a manner of stripping soil and adopting a detection sample, and performing ground surface control by using a groove exploration project; and a target position is predicted by combining the ore body grade, the ore body thickness and the product contour map of the ore body grade thickness by utilizing a structure superposition halo method, drilling engineering deep verification is carried out, and finally the topography and the landform are recovered to find out the shape, the occurrence, the scale and the resource potential condition of the gold mineralized body. The method is simple and convenient, small in environmental disturbance, low in cost investment and good in coverage area effect, the purpose of rapid prospecting is achieved, and an excellent gold ore prospecting effect is achieved in the Heidong region of the Qieemun Tagean, the cliff and the Qieemun Tagean.

The invention belongs to the technical field of tunnel engineering geophysical prospecting, and particularly relates to a full-wave-field tunnel advanced prospecting method based on rock physical constraint, which comprises the following steps of: constructing an initial geologic model, sampling on an upper interface of a layer section where a tunnel is located and carrying out longitudinal and transverse wave velocity measurement to obtain a longitudinal wave velocity Vp and a transverse wave velocity Vs; combining all sampled longitudinal wave velocities Vp and transverse wave velocities Vs, calculating longitudinal wave velocities and transverse wave velocities of a target layer section, obtaining elastic parameters of the target layer section, importing the obtained elastic parameters into an initial geologic model, obtaining a parameter inversion initial model, constructing a forward wave field and a simulated seismic record, and making a difference between an actual observation record and a simulation record, so as to obtain an initial geologic model; and conjugate gradient inversion is carried out. According to the method, all wave field information excited by the shield tunneling machine is fully utilized, and high-precision parameter inversion is carried out under rock physical constraints, so that more accurate tunnel front geological prediction can be provided, and a scientific basis is provided for safe and efficient construction of the shield tunneling machine.

The invention provides a diffracted wave separation method and device under non-uniform space-time sampling, and relates to the technical field of seismic prospecting, the method comprises the following steps: obtaining common offset seismic data of a target area, the common offset seismic data comprising fluctuation signals of a plurality of sampling points, the position intervals among the sampling points of different seismic traces are non-uniform, and / or the time intervals among different sampling points of the same seismic trace are non-uniform; calculating the plane wave slope of each sampling point of the common offset seismic data through a finite difference method to obtain plane wave slope data; determining a reflected wave travel time curve of each sampling point according to the plane wave slope data; and diffracted wave separation of the common offset seismic data is carried out according to the reflected wave travel time curve of each sampling point. According to the method, accurate diffracted wave separation under non-uniform space-time sampling is realized, and the seismic data analysis accuracy is improved.

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 belongs to the field of mineral resource exploration, and particularly relates to an oil-gas hydrocarbon micro-leakage alteration information identification and uranium mineralization association-based prospecting method, which comprises the following steps of: 1, selecting a research area and collecting basic data; 2, oil gas hydrocarbon micro-leakage alteration information is extracted; step 3, establishing an alteration information and uranium mineralization association model; 4, delineating a favorable uranium mineralization area; and 5, drilling verification and model optimization. According to the method, alteration information caused by oil gas micro-leakage is accurately extracted through multi-source data fusion, dynamic monitoring and intelligent modeling technologies, a correlation model of the alteration information and uranium mineralization is established, the exploration efficiency of the sandstone type uranium mine is effectively improved, and the exploration cost of the sandstone type uranium mine is reduced. The problems that deep alteration information is difficult to effectively recognize in a thick covering layer basin, oil gas micro-leakage and uranium mineralization mineralization are not clear in association, the utilization rate of multi-source data is low, the prospecting period is long, cost is high and the like in a traditional prospecting technology are solved.

The invention provides a crack pore medium multi-domain seismic inversion method and device, and relates to the technical field of geological prospecting, and the method employs a reflection coefficient calculation mode based on an accurate Graebner equation, and employs a Cauchy prior constraint to combine a target function constructed by a time domain and a frequency domain. The method realizes simultaneous inversion of three parameter profiles of porosity, crack weakness and water saturation, an accurate Graebner equation can accurately describe reflection coefficient characteristics of a crack medium, time domain inversion can enhance noise immunity, and frequency domain inversion can improve resolution, so that the accuracy, the noise immunity and the resolution of an inversion result are considered, and the method is suitable for large-scale popularization and application. And high-precision and high-resolution estimation of the porosity, the crack weakness and the water saturation is realized.

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 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 gold mine rapid prospecting method suitable for a plateau desert region, and belongs to the field of gold mine prospecting, and the method comprises the steps: obtaining geological and chemical prospecting data, and selecting a prospecting region based on the geological and chemical prospecting data; acquiring a high-resolution satellite image of the prospecting area, and acquiring geological, construction and mineralization alteration characteristics of an abnormal area of the prospecting area based on the high-resolution satellite image to construct a geological data set; a gold ore metallogenic area prediction model is constructed based on the long and short term memory network and the convolutional neural network; and inputting the geological data set into the gold ore metallogenic area prediction model for calculation, and generating a gold ore metallogenic area delineation result. Compared with a traditional geological prospecting method, the method has the advantage that the prospecting cost can be remarkably reduced by utilizing the high-resolution satellite image and the deep learning model to perform gold ore metallogenic prediction. Meanwhile, due to the fact that the accuracy of the prediction result is higher, unnecessary drilling and sampling work can be reduced, and resources and time are further saved.

The invention relates to an alkaline miscellaneous rock type niobium ore prospecting method, which belongs to the technical field of geological prospecting, and comprises the following steps: systematically carding regional geological structure evolution and stratum lithology distribution, and mastering the distribution range, rock type and geological age of alkaline miscellaneous rocks; a gravimeter is adopted for measurement, and gravity abnormal data are obtained; the method comprises the following steps: collecting sediment samples in a water system in a target area, analyzing the content of niobium in the sediment, collecting surface and deep soil samples in a niobium element enrichment area, analyzing the content of the niobium element, collecting remote sensing image data in the target area, highlighting geological information related to alkaline miscellaneous rocks, and calculating the content of the niobium element in the target area. Comprehensively analyzing the remote sensing image, and delineating a possible mineralization alteration area; establishing a comprehensive database, and delineating a target region with the highest prospecting potential; sampling is conducted in the delineated target area, and the ore body position, scale and grade of the alkaline miscellaneous rock type niobium ore are determined. By comprehensively applying various technical means, the prospecting accuracy and efficiency are improved.

The invention relates to the technical field of geological prospecting, in particular to a cube prediction model prospecting method and system based on three-dimensional modeling, and the method comprises the following steps: based on the position information of a prospecting point, employing an electromagnetic imaging device, adjusting scanning parameters, collecting reflection electromagnetic waves at a plurality of positions of a target area, and calculating the position information of the prospecting point; and recording electromagnetic response data under various frequencies and intensities, and generating electromagnetic characteristic data. According to the method, by integrating electromagnetic imaging and geological data interpolation technologies, the underground structure is accurately evaluated and mapped, construction of a geological model is optimized, the utilization rate of data is improved, uncertainty and risks in mining are reduced, and by analyzing geometric morphology and texture features of an ore body, underground minerals are detected and distribution features are identified, so that the mining efficiency is improved. The method effectively guides the mineral exploitation strategy, optimizes the resource allocation, reduces the environmental damage and exploration cost, and enhances the scientificity and economic benefits of geological exploration through the deep analysis and model optimization of geological data.

The invention belongs to the technical field of geological prospecting evaluation, and discloses an ore body positioning method and a rapid sampling device for niobium-tantalum ore target region prediction and evaluation. According to the method, based on existing geological data, various geologic bodies in a 1: 250,000-1: 10,000 geological map are analyzed, distribution, form, invasion contact relation, formation times and other characteristics of alkaline rock masses are found out, and a favorable metallogenic area is delineated; a linear structure, an annular structure and alteration information are recognized through satellites and aerial images, and target area positioning is assisted; the method comprises the following steps: exploring and detecting ore-bearing rock mass and fracture structures through a magnetic method, delineating potential positions of ore bodies, and inferring geological attributes of abnormal sources in combination with geological data; measuring the total amount of gamma at different positions in the niobium-tantalum prediction target area by using radioactive detection equipment, and preliminarily judging the position of the niobium-tantalum ore according to a gamma abnormal result; and carrying out systematic sampling and assay analysis on the target area by using the rapid sampling device. By means of the method and device, the metallogenic geological condition and the prospecting prospect can be evaluated, and the exploration network degree is optimized.

The invention discloses a deep prospecting method and system based on ground-air electromagnetic detection, and relates to the technical field of geological mineral exploration. The method comprises the following specific steps: obtaining geological background data of a research area, carrying out field survey, determining transmitting and receiving positions, and carrying out ground-air transient electromagnetic measurement at different flight height positions to obtain ground-air electromagnetic detection data; preprocessing the ground-air electromagnetic detection data to obtain preprocessed data; performing inversion on the preprocessed data by using an inversion algorithm to obtain an electrical structure model of the underground medium; and according to the electrical structure model, predicting distribution and characteristics of an underground geologic body, and determining a mineral product position. According to the method, ground-air transient electromagnetic measurement is adopted for deep prospecting, denoising operation is carried out on the obtained data, and the exploration precision of deep mineral resources in the complex terrain area is improved.

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 provides a carbonate pore structure inversion method and related equipment, and relates to the technical field of geological prospecting, and the method comprises the steps: obtaining test data, employing a trained deep learning prediction model to carry out pore structure inversion through employing a Bayesian estimation algorithm for the test data, so as to obtain a pore structure prediction result, the deep learning prediction model comprises a Bayesian convolutional neural network layer. According to the technical scheme, the test data are input into the trained deep learning prediction model, and the Bayesian estimation algorithm is adopted to perform pore structure inversion so as to obtain the pore structure prediction result including the confidence interval of the pore structure parameters. Therefore, the uncertainty quantification of the prediction result can be realized, the uncertainty is further expressed, the confidence interval is obtained, and the prediction precision can be effectively improved, namely the accuracy of the pore structure prediction result is improved. The method has great application potential in the field of data-driven pore structure prediction, and better decision support is facilitated.

The embodiment of the present application relates to the pile foundation construction technical field, specifically discloses a kind of karst pile foundation leak slurry early warning method and system.The embodiment of the present application is determined by pile foundation construction area, carries out geological radar detection, electrical prospecting and borehole exploration to pile foundation construction area, obtains geological detection data;Monitoring deployment is carried out, and real-time monitoring data is obtained, and three-dimensional monitoring model is established, and visual monitoring display is carried out;Extract multiple key feature data in real-time monitoring data, import into the preset slurry leakage preset model, obtain slurry leakage prediction probability;According to slurry leakage prediction probability, determine slurry leakage early warning level, according to slurry leakage early warning level, early warning and emergency treatment are carried out.The present application breaks through the dependence of traditional grouting process on crack morphology by innovative design of the synergistic plugging mechanism of pH-sensitive pneumatic capsules and geological bonding agents, using the instantaneous negative pressure field effect to drive the directional enrichment of nanomaterials, triggering in-situ strengthening reactions based on the mineral characteristics of rock mass.

A portable drilling device for geological prospecting. The device comprises a first support frame (1), wherein a second support frame (2) is slidably connected to the interior of the left side of the first support frame; a storage box (6) is fixedly connected to the top of the first support frame; and a sampling groove (26) is embedded in the right side of a drill pipe (22). In the device, firstly, the second support frame is inserted into the first support frame, then a connection sleeve (14) is detached from a support column (9), a sleeve (21) is detached from a fixing device (18), the provided storage box is used for storage, and a limiting block (27) is driven by means of the rotation of a rotating electric motor (19) so as to open and close the sampling groove, thereby performing sampling.

The utility model belongs to the technical field of geological exploration, and particularly relates to a rock debris sampler for geological exploration, which comprises a sampler, guide strips are welded on the outer walls of two sides of the sampler, and a sleeve column is movably sleeved at the bottom of the sampler; four mounting parts are welded on the outer wall of the sleeve column at equal intervals, a bracket is fixedly mounted in an opening of each mounting part, an included angle between each bracket and each mounting part is 45 degrees, and the internal diameter of the sleeve column is larger than that of the sampler. Then the guide strips on the two sides of the sampler are in butt joint with the corresponding group of inner strips, the sampler is started, the spiral blades on the sampler can work on the rock, the sampler is pressed downwards, the sampler can move downwards along the tracks of the two groups of inner strips and the inner strips, and the inner strips and the inner strips are separated from each other. Meanwhile, under the cooperation of the sleeve column and the bracket, the stability of the sampler during movement can be effectively guaranteed, so that the whole rock debris collection work is more convenient and faster.

The invention provides an intelligent prospecting method and device, electronic equipment and a storage medium. The problem that a satellite-borne platform or an airborne platform is not high in prospecting precision is effectively solved. The method comprises the steps of performing continuous imaging on a target to-be-measured mining area to obtain multi-frame remote sensing data, and preprocessing the multi-frame remote sensing data to obtain a target hyperspectral image sequence; selecting a reference frame and a to-be-registered sequence frame for registration, and superposing all registered images to intercept a public overlapping region image; carrying out collaborative quality enhancement reconstruction on the public overlapping region image to obtain a hyperspectral image, and respectively carrying out altered mineral and structural element identification on the hyperspectral image to obtain a mineral distribution map and a classification structural map; and fusing the mineral distribution map, the classification structure map and a preset geological metallogenic rule to obtain a prospecting distant view map with a prospecting mark, so as to complete intelligent prospecting of the target to-be-detected mining area based on the prospecting distant view map.