507 results about "Mineral exploration" patented technology

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

The invention belongs to the technical field of mineral exploration, and particularly discloses a copper ore prospecting method based on three-dimensional geological modeling. The method comprises the following steps: acquiring geological data of a target area; after extreme values in the geological data are recognized and removed through a box plot, the geological data are mapped to an interval of [0, 1], and the geological data are divided into terrain data, stratum data and mineral resource data; adopting Kalman filtering to enable the data to form fusion data, and generating a thematic map comprising a geological map, a mineralization anomaly map and a topographic slope map; based on the data and the thematic map, constructing a three-dimensional geologic model by a finite element method, and performing mining path planning by adopting a specific path planning algorithm formula; exploring by the mining equipment according to the planned path, acquiring geological data, comparing the geological data with the predicted data, re-planning the path and continuing exploring if the path is blocked, the resource recovery is out of tolerance and new mineralization is abnormal, otherwise continuing exploring according to the planned path. The method has the advantages of being high in exploration efficiency and data precision, low in comprehensive cost and high in adaptability.

The invention relates to the technical field of unmanned aerial vehicle geological survey, and discloses a path planning method and system for unmanned aerial vehicle geological survey, and the method comprises the steps: obtaining the image, spectrum and topographic data of a remote mountainous area through a multispectral sensor and a laser radar, and recognizing potential vein abnormal points through data fusion and geological feature analysis; and constructing a geological interestingness weight map and planning a flight path. Dense sampling flights are performed in a high interestingness region, high resolution data are processed in real-time to identify key reconnaissance targets, a weight map is updated, and a flight trajectory is dynamically adjusted. Through the closed-loop self-adaptive exploration process, accurate positioning and feature description of the hidden vein are realized, the mineral exploration efficiency is improved, the labor cost and the safety risk are reduced, and an innovative solution is provided for mineral resource exploration in remote areas.

The invention provides a multi-source geophysical prospecting data fused Zenzenite rock mass contact zone anomaly method and system, and relates to the technical field of geophysical prospecting, the method comprises the following steps: executing joint denoising processing and time-frequency feature enhancement processing on a TFEM data set in a three-dimensional fused data volume, and outputting the optimized three-dimensional fused data volume; and based on the optimized three-dimensional fusion data body, by establishing a mapping relationship between magnetic, electric and polarization anomalies and a geologic body, quantifying the correlation between a multi-parameter combination and a mineralization index and screening an up-to-standard abnormal region, and finally delineating a magnetic anomaly gradient zone, a low-resistance region and a high-polarization anomaly co-occurrence ore prospecting target region three-dimensional distribution diagram. Through multi-source geophysical prospecting method collaboration, data deep fusion, quality optimization and accurate mapping, full-chain technology upgrading from data acquisition to target area delineation is realized, and the high efficiency of mineral exploration is improved.

The invention discloses a dust raising prevention sampling device and method for geological mineral exploration, and particularly relates to the technical field of geological exploration, the device comprises a drilling assembly, a drilling pipe assembly, a sampling inner pipe and an extraction rod, the drilling assembly comprises a drilling machine and a feeding driving frame, the drilling pipe assembly comprises a section of primary drilling pipe and a plurality of sections of secondary drilling pipes, the sampling inner pipe is arranged in the primary drill pipe, a plurality of groups of elastic pressing strips are arranged at the bottom end of the sampling inner pipe, and a tightening controller is further arranged on the outer side of the bottom of the sampling inner pipe. When the sampling inner pipe is lifted, the tightening controller extrudes the bottom end areas of the elastic pressing strips, so that all the elastic pressing strips are bent and deformed inwards, a soil sample entering the sampling inner pipe is extruded to a certain extent, and the carrying capacity of the soil sample is improved; furthermore, the soil sample in the sampling inner pipe can be effectively taken out when the sampling inner pipe ascends, and the sampling integrity and accuracy are greatly improved.

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

The invention discloses a grooving method sampling device for geological mineral exploration surveying and mapping, which comprises a shell, a cutting device, a water spraying device, a vertical pressing device and a collecting device, the cutting device is installed at the front end of the shell, a water spraying assembly is installed at the top of the cutting device, the vertical pressing device is installed in the middle of the shell, and the collecting device is located at the rear end of the shell. The cutting device adjusts the width of a sample, the water spraying device cools a cutting area through water flow, reduces friction heat, reduces dust raising and improves the cleanliness of the working environment, the pressure relieving device adjusts the length and thickness of the sample and ensures the cutting precision, and the collecting device shovels the cut sample out of a mineral product and delivers the cut sample to the top of the shell through the conveying belt. And all the devices operate in a coordinated mode, an efficient cutting process is formed, the working efficiency is improved, and operation safety is guaranteed. The whole design is compact, operation is easy and convenient, various mineral cutting requirements are met, energy consumption is reduced, and the service life of equipment is prolonged.

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 discloses a mineral resource metallogenic law simulation and target prediction system based on big data, and relates to the technical field of geological exploration. The multi-source data acquisition and standardization module supports acquisition of five types of data, and the data are preprocessed and then transmitted to the distributed database; mining key elements by using an improved Apriori algorithm, and constructing a correlation graph; building a model based on Unity 3D, and integrating three types of dynamic simulation; performing three-level prediction by using a CNN-LSTM model; three-dimensional rendering and multifunctional display are supported; and automatically updating data, models and rules to form an optimized closed loop. According to the method, multi-source data is integrated to improve ore-forming element recognition comprehensiveness, dynamic simulation fits geological reality, AI prediction is accurate, uncertainty analysis is included, visual interaction is practical, iterative optimization continuously improves efficiency, invalid exploration cost is reduced, and mineral exploration is efficiently guided.

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 relates to the technical field of mineral exploration, and discloses a method for estimating the mineralization probability of residual slope product type anatase based on multi-source parameters, and the method comprises the steps: determining a geographic region, collecting geological data, sampling a geological sample, and collecting the characteristics of the sample; extracting the first characteristic index set to judge the region classification of the geographic region, wherein the region classification comprises a conventional exploration region, a main mineralization mode region and a secondary mineralization mode region; extracting a second characteristic index set from the geological data to calculate a standard mineralization probability; calculating a weathering correction coefficient and a maturity correction coefficient; and correcting the standard mineralization probability to generate a mineralization probability, and judging whether the geographic region is a high-potential target region or not according to the mineralization probability. According to the technical scheme, the metallogenic probability judgment standard can be determined and corrected under different conditions, and judgment of a high-potential target region is achieved.

The invention relates to a lithium ore prospecting prediction method and system, and relates to the technical field of mineral exploration. According to the lithium ore prospecting prediction method and system, the prediction accuracy of ore body identification is high, the exploration period can be shortened, and the exploration cost can be reduced. According to the method, the multi-dimensional data fusion is combined with the intelligent algorithm, the three-dimensional mineralization probability is output through the prediction neural network model, the prediction accuracy of ore body recognition is high, the exploration period can be shortened, and the exploration cost can be reduced.

The invention relates to the technical field of mineral exploration, and discloses a mineral resource intelligent identification method based on multi-source remote sensing data, and the method constructs an intelligent identification model based on a deviation analysis and correction mechanism through integrating the multi-source remote sensing data, geological data and mineral reaction characteristic signals, can dynamically adapt to different environmental conditions, and improves the identification efficiency. According to the method, the mineral resource exploration precision and reliability are remarkably improved, through dynamic correction and multi-coefficient integration, the misjudgment rate is effectively reduced, the recognition accuracy and precision ratio of the mineral target area are improved, potential mining areas can be rapidly screened out in a large-range area, manual intervention is reduced, the exploration efficiency is remarkably improved, and the method is suitable for popularization and application. By generating a plurality of mineral marker guidance coefficients KWX, the mineral resource potential is comprehensively evaluated from multiple angles, and the accuracy and stability of mineral recognition are remarkably improved.

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 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 discloses a deep niobium phosphate ore positioning physical and chemical exploration method based on multi-method cooperation, and belongs to the technical field of geological mineral exploration. According to the method, a three-stage exploration system of region optimization, target region delineation and fine verification is constructed, multi-parameter cooperation of a magnetic method, an electromagnetic method, an induced polarization method, a three-component magnetic logging method and a geochemical method is combined, and each step is constrained by a basic rock-niobium phosphorite metallogenic model. An ore prospecting mark is determined through regional geological background analysis and metallogenic model construction, a metallogenic prospective region is delineated through regional optimization, a specific target region is delineated and locked, engineering verification is carried out through fine verification, and finally, a result is integrated to estimate the resource quantity. According to the method, the multiplicity of solutions of a single method is effectively reduced, the positioning precision of the deep niobium phosphorite is improved, the exploration efficiency and the target area ore finding rate are improved, and the method is suitable for accurate exploration of the deep niobium phosphorite.

The invention relates to the technical field of deep mineral exploration, and discloses a deep metal mine multi-source geophysical data real-time fusion system. The system comprises a data access module which divides detection dimensions according to physical field types so as to receive original data; the space-time registration module is used for establishing mapping between original data and a unified space-time reference system through timestamps and space coordinates; the feature extraction module is used for extracting key features from the registration data, determining weights according to physical meanings and constructing a feature association network; the fusion decision module identifies an abnormal value and adjusts a network topology structure based on the credibility of the network evaluation data; and the real-time updating module is used for optimizing the fusion priority and algorithm parameters and generating a real-time fusion result library. According to the system, real-time fusion of multi-source geophysical data is realized, and systematicness and timeliness of data processing are improved.

The invention discloses a geophysical prospecting signal denoising method based on VMD (variational mode decomposition) combined with an improved wavelet threshold function, and belongs to the technical field of mineral exploration geophysical prospecting signal process.The method includes the steps that firstly, a decomposition mode number K of a signal is determined through VMD in a self-adaptive mode, a plurality of IMFs (intrinsic mode components) are obtained, and then according to the frequency characteristic and noise distribution of each IMF component, a wavelet threshold function is obtained; and carrying out targeted noise suppression by adopting an improved wavelet threshold function containing an adjustment parameter alpha, and finally, carrying out linear superposition reconstruction on all the processed IMF components to obtain a de-noised geophysical prospecting signal. Experimental verification shows that compared with a traditional method, the method has the advantages that the signal-to-noise ratio and the correlation coefficient of the noisy geophysical prospecting signals can be effectively increased, the root-mean-square error can be effectively reduced, the inherent defects of the traditional method are overcome, the geologic features of the geophysical prospecting signals can be effectively reserved, the method is suitable for various mineral exploration scenes, and reliable data support is provided for anomaly recognition in mineral exploration.

The invention relates to the field of mineral resource exploration, and discloses a mineral prediction method based on multivariate geoscience information superposition recognition, which comprises the following steps: collecting multivariate three-dimensional geoscience information through multiple modes such as unmanned aerial vehicle remote sensing and ground survey, classifying and sorting, and carrying out deep preprocessing and feature extraction such as denoising and correction to obtain a multi-element three-dimensional geoscience information model; a fusion layer is generated by adopting an adaptive fusion algorithm, a mineralization prediction model is constructed in combination with machine learning, and after training optimization, prediction regions of different grades are delineated and the resource quantity is estimated. And a verification feedback mechanism is also set, and each link is optimized and improved according to a field exploration result. The method improves the mineral product prediction accuracy and adaptability, improves the exploration efficiency, reduces the cost, promotes the technical development of the mineral exploration field, and has an important application value.

The invention discloses geological mineral exploration sampling equipment, relates to the technical field of exploration sampling, and aims to solve the technical problems that the quality of a soil sample is affected and the service life of a drill bit is shortened due to heat generated by friction between the drill bit and a stratum during drilling of existing soil sampling equipment, soil at different depths is easy to mix when discharged, and the accuracy of detection data is reduced. Comprising a driver, a first grip, a second grip and a water pump, liquid can be discharged according to the punching depth in the punching process, on one hand, the temperature of the punching assembly and the inner cylinder assembly during operation can be reduced, damage caused by overheating is avoided, and therefore the use safety of the device is ensured; on the other hand, the sampling difficulty can be reduced by humidifying the soil, after sampling is completed, the sample can be discharged only by reversely operating the driver, and through the design of the spiral blade, the situation that the sample is crossed and mixed can be avoided, and the accuracy of soil sample data detected and collected by the device is guaranteed.

The invention discloses a mineral exploration sampling method for mineral geology, and belongs to the technical field of geological exploration. Comprising the following steps: generating a standardized alteration anomaly spatial distribution map; accurate prediction of the mineralization probability is realized, and a mineralization probability distribution diagram is generated; the sampling depth is intelligently determined by combining the alteration-mineralization space relation of the mineralization type, and an initial sampling grid scheme is formed; establishing a digital file including a coordinate position, a sampling depth and geological features for each sampling point; the on-site detection module is controlled to implement on-site sampling according to the optimized sampling grid, and an on-site detection result is obtained in real time; whenever significant deviation exists between the field detection result and remote sensing alteration prediction, the sampling point generating deviation is marked as an abnormal deviation point; if the sampling integrity does not reach the preset exploration standard, dynamically adjusting a subsequent sampling scheme and continuing sampling; and if the sampling integrity reaches the preset exploration standard, generating a final mineralization probability distribution diagram and an exploration sampling report.

The invention provides a prospecting system and method based on software defined radio, and belongs to the technical field of mineral detection, and the system comprises a software defined radio transmitting device which is used for generating transmitting parameters based on the geological structure and detection requirements of a to-be-detected area, an electromagnetic wave emission signal emitted to the to-be-detected area is generated based on the emission parameter; the software-defined radio receiving equipment is used for receiving electromagnetic wave receiving signals propagated in the to-be-detected area; and the mineral analysis module is used for determining a distortion mode based on the electromagnetic wave transmitting signal and the electromagnetic wave receiving signal, and determining the type and grade of minerals based on the distortion mode. According to the invention, the high flexibility of the software defined radio technology is utilized, rapid adjustment of emission parameters is realized to adapt to different geological structures and detection requirements, and the prospecting efficiency of the system is improved. Meanwhile, mineral detection is achieved based on the distortion mode, manual work is not needed, and the mineral detection accuracy is improved.

The invention discloses an uncertainty perception deep learning mineral product prediction method, and relates to the technical field of mineral product exploration, and the uncertainty perception deep learning mineral product prediction method mainly comprises the steps: carrying out the preprocessing and feature processing of a multi-source geological data set, and obtaining a training set and a test set; constructing an uncertainty perception deep learning model and a loss function, training the uncertainty perception deep learning model by using the loss function and the training set to obtain a trained uncertainty perception deep learning model, predicting Dirichlet parameters of the training set and the test set, and calculating a prediction probability and uncertainty of each sample; and a prediction probability graph and an uncertainty graph are obtained. By implementing the uncertainty perception deep learning mineral product prediction method provided by the invention, the uncertainty of the mineral product prediction result can be measured and simulated, and the robustness of mineral product prediction is improved.

The invention is applicable to the technical field of mineral exploration, and provides a multi-layer soil sampling device for prospecting, comprising: a bearing plate used as a mounting carrier of a support frame, a stabilizing assembly and a dust collection assembly; the support frame is mounted on the bearing plate and is used as a mounting carrier of the drilling assembly; and the drilling barrel is connected with the drilling assembly through the disassembly and assembly assembly and used for loosening the multiple layers of soil. By arranging the sampling assembly, sampling operation can be conveniently conducted on multiple layers of soil in one-time operation, it is avoided that multiple times of sampling operation are needed by workers, the working time is shortened, the soil sampling efficiency is improved, the mineral exploration efficiency is further improved, the applicability of equipment is improved, and actual application and operation are facilitated; through the soil blocking assembly, the sampled soil in the sampling box is blocked, the soil in the sampling box is prevented from being thrown out when the drilling barrel rotates upwards, and the sampled soil is further protected.

The invention belongs to the technical field of rock core cutting, and particularly relates to a solid mineral exploration rock core automatic cutting device which comprises a box body, and a fixing frame is fixed to the upper portion of the box body; the fixing assembly is used for fixing a rock core, the fixing assembly comprises a mounting plate arranged in the box body, a pair of U-shaped frames are arranged on the mounting plate, a supporting rod is arranged in the middle of each U-shaped frame, the two ends of each supporting rod are fixedly connected with the side wall of the corresponding U-shaped frame through connecting rods, and pressing rods are slidably arranged on the connecting rods on the two sides respectively; the hydraulic cylinder is arranged below the mounting plate and used for controlling the mounting plate to ascend or descend; the hydraulic cylinder is arranged to sink a rock core into water before cutting and after cutting, on one hand, floating dust on the surface of the rock core can be removed before cutting, and fly ash generated in the cutting process is reduced; on the other hand, mud attached to the fixing assembly and the rock core in the cutting process can be effectively removed, and the cleaning effect is improved.

The invention discloses a prospecting exploration method for ion adsorption type heavy rare earth ore in middle and low mountainous areas, and belongs to the technical field of geological mineral exploration. According to Y, Dy and Nb abnormity and Y-Nb combination abnormity areas such as water chemical exploration and soil chemical exploration of a working area, high-silicon, potassium-rich, alkali-rich and sphene-rich heavy rare earth secondary mineral mineralization mother rocks are preferably selected, and a favorable mineralization area of the ion adsorption type heavy rare earth ore is delineated by combining characteristic parameters that Y / Ce is greater than 0.9 and Dy / Ce is greater than 0.2; screening south and east-south-east abrupt slope (gradient of about 30 degrees) areas by utilizing a GIS spatial analysis technology, overlapping favorable mineralization areas of the ion adsorption type heavy rare earth ore, and comparing and determining an ion adsorption type heavy rare earth ore prospecting target area in a working area; whether mineralization abnormity exists in the heavy rare earth ore prospecting target area or not is verified by using a manual impact sampling drill and a rare earth ion leaching-titration qualitative analysis method; chemical samples are preliminarily collected, 15 components of ion phases are analyzed, whether heavy rare earth ore bodies exist or not is judged and evaluated, the prospecting exploration range of the ion adsorption type heavy rare earth ore is determined, and the prospecting efficiency of the ion adsorption type heavy rare earth ore is improved. According to the method, the mineralization prospective area of the ion adsorption type heavy rare earth ore can be rapidly delineated in a large range, the prospecting target area is narrowed, and the prospecting efficiency of the ion adsorption type heavy rare earth ore is improved.

The invention discloses a mineral sample acquisition optimization method based on stratum change identification, and particularly relates to the technical field of mineral exploration sampling, comprising the following steps: acquiring lithologic characteristics, fault distribution, underground stress information and historical sampling data, fusing to form spatial reference data and generating a stratum change level distribution map, then constructing a sample collection candidate area map; generating a sampling path group and adjusting path layout according to the candidate area map, matching a sampling mode for each path, recording multiple types of data in real time in the sampling process and comparing the data with spatial reference data, and dynamically adjusting the sampling path or mode according to a comparison result; spatial reference data are generated through multi-source geological information fusion, and high-precision stratum change recognition is achieved; the sampling path layout is optimized in combination with disturbance distribution and operation constraint, so that the operation safety and the coverage integrity are improved; in the sampling process, response data are compared in real time, a sampling strategy is dynamically adjusted, and the geological consistency and reliability of a sampling result are ensured.

The invention relates to a refined three-dimensional geological modeling method based on a geophysical prospecting three-dimensional inversion algorithm, and belongs to the field of geological exploration, and the method comprises the steps: obtaining multi-source data, constructing an initial model, and obtaining a three-dimensional physical property model through the combined constraint of the three-dimensional inversion algorithm; creating a lithology classifier, generating a three-dimensional lithology probability body according to the three-dimensional physical property model, performing geological structure boundary enhancement, and performing geological classification based on the probability body; and extracting a contour surface from the three-dimensional lithologic probability body, generating a preliminary geological interface, performing construction processing, performing attribute model coupling, and outputting a model. According to the method, the spatial continuous model is directly constructed through three-dimensional joint inversion, and interpolation errors between measuring lines are avoided; drilling data forced matching and geophysical prospecting data trend control consider both local precision and global rationality; the whole process algorithm is driven from inversion to lithology classification, and manual intervention is reduced; the method is suitable for high-precision scenes such as urban underground space, mineral exploration and geological disaster assessment.