256 results about "Geological formation" patented technology

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

The invention discloses a geological structure three-dimensional reconstruction and analysis system based on multi-modal data fusion, and relates to the technical field of geological exploration information. The method comprises the following steps: acquiring and normalizing multi-source heterogeneous geological observation data through a preprocessing module, and generating basic data and a data coverage density map; the adaptive fusion module performs analysis to generate a dynamic adaptive weight field, and performs weighted fusion on the data to obtain a primary three-dimensional geological data volume; the construction and optimization module constructs a three-dimensional space residual field in a vector form based on the difference between the fusion body and the original data, and deduces the geometric morphology of the geological interface; the reconstruction module ensures the consistency between model layers through hierarchical bidirectional belief propagation processing; the quantification module calculates an uncertainty index; and the visualization module finally generates a three-dimensional geological scene. According to the method, the problems of conflict resolution and reliability evaluation in multi-source geological data fusion are effectively solved, and the precision of the three-dimensional geological model and the engineering decision support capability are improved.

The embodiment of the invention discloses a mineral resource exploration data analysis method and device based on three-dimensional space modeling. The method comprises the steps that back-flushing pushing-covering structure feature information is extracted through structure interface occurrence measurement, lithology combination analysis and structure movement trace recognition and converted into geologic structure feature parameters; stratigraphic age data and lithology distribution information are integrated, and a three-dimensional stratigraphic model is constructed with a stratigraphic superposition relation as a constraint; geophysical data are imported to extract geophysical response characteristics of stratums with different depths, and lithologic boundary correction is combined to obtain deep fracture characteristic parameters; sedimentary system division is carried out on lithofacies paleogeographic information, and deep fracture characteristic parameters are fused to establish a fracture system three-dimensional model; the multi-feature association relationship is identified, the ore body prediction model is established, the spatial data is input to obtain the three-dimensional visual prediction result of the hidden ore body spatial distribution, and the exploration efficiency and accuracy in the deep phosphorite exploration process are improved.

Provided is a method for judging geology of a time-delayed extremely intense rockburst as to deep tunnel engineering. Information about geological structures is recorded according to methods such as geological mapping and advanced geological prediction of the tunnel face. Geometric characteristics of burst craters formed during the rockburst are recorded by utilizing advanced geological drilling and profile scanning technologies in a rockburst-damaged zone. 3D geostress in the rockburst-damaged zone is measured by using a stress relief method or a hydraulic fracturing method to determine the orientation of the maximum principal stress. A 3D numerical calculation model is established based on initial geostress testing results and physical and mechanical parameters of rock and structural discontinuities obtained through on-site geological investigations. By conducting excavation simulations under different combinations of structural discontinuities and performing numerical calculation, the risk of time-delayed extremely intense rockburst disasters at current locations after tunnel excavation is judged.

The invention belongs to the technical field of seismic exploration, and discloses a pre-stack gather optimization method based on multi-dimensional constraint dynamic time warping, which remarkably improves the space continuity and stability of a time shift field. According to the method, the time shift field which is smoother and more continuous in a three-dimensional space can be generated, and the common abnormal jump and unreasonable jitter of the time shift field in a conventional DTW method are effectively inhibited. This better conforms to the gradient characteristics of the geologic structure. Mismatching and processing illusion are effectively avoided, the adaptability of a complex structure area is improved, the global optimization capacity of the DTW algorithm is enhanced through multi-dimensional constraint, and the phenomenon that different horizons or effective waves are wrongly matched with interference waves due to local waveform complexity or noise interference is reduced. Therefore, common processing illusions such as event dislocation and local distortion in a conventional DTW method can be remarkably reduced.

The invention relates to the technical field of three-dimensional modeling, in particular to a dynamic modeling method for a geological structure three-dimensional model. The method comprises the steps that multi-source data are acquired and preprocessed, a voxel semantic fusion algorithm based on variational optimization is introduced, after semantic information is extracted from the preprocessed multi-source data, the preprocessed multi-source data are mapped to a target three-dimensional space grid, and an optimal semantic fusion vector is obtained; based on the optimal semantic fusion vector, generating a standard voxel data pool, and constructing a geological structure three-dimensional model; monitoring data change, calculating the position of a newly added data point, combining the standard voxel data pool to obtain a space updating area, and modeling the space updating area to realize model updating; and after the modeling of the space updating region is completed, optimizing the boundary continuity. The problems that multi-source geological data cannot be directly used for structure construction and semantic fusion of a three-dimensional model, dynamic response to newly-added data is lacked, and geometric discontinuity and structural logic discontinuity exist at the boundary are solved.

The invention provides a three-dimensional geological structure modeling method, device and system based on drilling information. The method comprises the following steps: S1, collecting drilling data, seismic exploration data and remote sensing image data of a target area; s2, constructing a neural network model composed of a simple full-connection module, a complex convolution residual module and a hierarchical integration module which are connected in sequence; s3, training the initial three-dimensional geologic model by adopting a joint loss function; and S4, in the network training process, a plurality of geological scene models are generated, and each scene model corresponds to a group of different network parameter combinations. According to the three-dimensional geologic structure modeling method, device and system based on drilling information, a spatial receptive field for feature extraction is expanded through a three-dimensional cavity convolution residual block of a complex convolution residual module according to a symmetric expansion rate, input features and deep convolution features are added, processing is carried out through a hierarchical integration module, and the three-dimensional geologic structure modeling method, device and system based on drilling information are obtained. And geologic structure correlation characteristics across drill holes can be effectively captured.

The invention discloses a multi-source information real-time identification and positioning method for a coal mine rock burst risk area. The method comprises the following steps: integrating a micro-seismic system, a rock noise system, a stress system and a geological system to construct an acquisition network; extracting multi-source characteristic indexes and carrying out space-time unification; establishing a dynamic weighted risk fusion model to calculate a comprehensive risk index RI of a three-dimensional grid unit, wherein the weight of the comprehensive risk index RI is dynamically and adaptively adjusted along with mining; based on the RI value, a high-risk area is identified and positioned through three-dimensional visualization, and graded early warning information is generated; according to the invention, a time-space synchronous multi-source information acquisition network is constructed, and uniform preprocessing and feature extraction are carried out on four types of data of microseism, rock noise, stress and geologic structure, so that deep fusion and collaborative analysis of multi-source information are realized, and an information island phenomenon existing in traditional monitoring is overcome; and the judgment on the rock burst risk is more comprehensive.

The invention provides a mineral resource overburden risk assessment method and system, and the method comprises the steps: obtaining multi-source heterogeneous geological data, carrying out the deep fusion of the multi-source heterogeneous geological data through employing a game theory gradient control robust neural network training method, and obtaining a fusion data set; performing deep mining and reasoning on high-dimensional geological data by utilizing the pattern recognition and correlation analysis capability of a large model and combining a manifold perception regularization technology, and recognizing geological structure features; establishing a dynamic safety mining depth evaluation model by using a fractional peak differential equation neural network with efficient accompanying parameter training, and calculating safety mining depth intervals and risk probabilities under different confidence degrees by integrating geological structure risks, mining disturbance effects and engineering safety thresholds; and constructing an assessment report generation module including core risk point analysis, key technology demonstration and prospective risk early warning, and generating an intelligent overburden risk assessment report. According to the invention, the accuracy and reliability of the pressing and covering risk assessment can be improved.

The invention relates to the technical field of tunnel construction geological disaster early warning, and discloses a tunnel construction geological disaster early warning method and system. According to the method, multi-source geological monitoring data and environment dynamic parameters of a tunnel construction area are collected; and then through data fusion and feature engineering processing, data contradiction and redundancy are eliminated, and a standardized training data set is formed. And then training and verifying a disaster risk prediction model by using the data set and adopting a machine learning algorithm so as to obtain an optimized model to accurately predict the disaster risk. And performing risk value prediction on different geological structure units by applying the optimization model, generating a risk distribution map, and determining an optimal geological structure unit through a search algorithm. Based on this, numerical simulation of geological disaster triggering and propagation is executed, a disaster evolution rule is analyzed, and a path simulation data set is output. And finally, performing multi-objective optimization on the data set according to a safety early warning objective, generating a geological disaster early warning scheme, and performing iterative calibration.

The invention discloses a geological structure recognition method based on deep learning, and relates to the technical field of geological recognition, and the method comprises the steps: inputting enhanced multi-modal data into a multi-scale visual Transform network to generate a depth feature map, extracting a local structure feature map through a geological prior function and a pyramid structure, and obtaining a local structure feature map; fusing the local construction feature map with the depth feature map to generate a multi-modal feature map, establishing a spatial attention weight map, calculating the regional correlation between the multi-modal feature map and the spatial attention weight map, and performing regional adaptive weighting on the multi-modal feature map according to the regional correlation to obtain a weighted feature map; according to the method, global feature modeling is realized through the multi-scale visual Transform network, the cross-regional continuity and the wrinkle macroform of the fault are captured, and the processing capability of high-resolution geological data is improved.

The invention relates to a tunneling action generation method and system based on time-space depth fusion multi-task prediction in the technical field of shield engineering data processing, and the method and system integrate local and global time sequence information through a dynamic depth fusion network, achieve the fusion of multiple time-space scales, improve the perception capability of complex working conditions, and improve the efficiency of shield engineering data processing. Meanwhile, future state prediction and control candidates are output, action fusion is carried out on a strategy layer, performance loss caused by prediction-control splitting is reduced, prediction-control integration is achieved, an uncertainty head is introduced, explicit constraint is carried out on a loss function and strategy fusion layer, the risk under stratum sudden change or sensing noise is effectively restrained, and the prediction-control performance is improved. Uncertainty constraint security is realized; on the basis of experience playback, weight self-adaption and noise removal, online self-adaption updating requirements of different stratums and tunneling stages are met, online self-adaption updating can be achieved, and the action generation capacity of tunneling stability control under the complex stratums and noise conditions is remarkably improved.

The invention discloses a karst region land degradation degree evaluation method. The method comprises the steps of collecting karst multi-source data; constructing a soil quality index, a climate quality index, a vegetation quality index, a terrain quality index, a human activity index and an underground leakage index as a karst region MEDALUS-Karst index system; carrying out standardization and comprehensive score calculation on each index to realize comparability among indexes of different dimensions, and reflecting the land degradation degree of the karst region through a land degradation comprehensive index; the method solves the problems that an MEDALUS model is adopted for land degradation evaluation of the karst region, due to the fact that unique geological structures, hydrological processes and degradation characteristics of the karst region conflict with core assumptions and index systems of the MEDALUS model, key driving factors and spatial distribution characteristics of land degradation are difficult to accurately recognize, and the evaluation accuracy of the land degradation is affected. And thus, the technical problems of lack of pertinence of ecological management measures are solved.

The present application relates to the technical field of geological model, especially to a three-dimensional geological model dynamic visualization method, system, equipment and storage medium for underground engineering. The technical scheme comprises the following steps: data acquisition and integration: obtaining geological data through various exploration methods, and performing standardized and fusion processing to obtain unified three-dimensional coordinate geological data; three-dimensional geological model initialization construction: constructing a stratigraphic framework based on the integrated data, and accurately embedding geological structures therein to form a complete three-dimensional geological model framework; model dynamic visualization rendering: setting specific lighting and material properties for the constructed three-dimensional geological model. The present application constructs a high-precision model through multi-source data fusion, optimizes the visualization effect and interactivity, realizes real-time monitoring and continuous optimization of the model, provides accurate geological basis for underground engineering, enhances decision accuracy, ensures safety, improves construction quality and economic benefits.

The invention discloses a mineral resource reserve estimation method and system based on satellite data, and the method comprises the steps: S1, obtaining multispectral satellite remote sensing data, extracting surface mineral alteration information and geological structure features through a spectral feature recognition algorithm, and generating a surface feature data set; s2, based on the earth surface feature data set, establishing a spatial correlation model of earth surface anomaly and deep mineralization by adopting a geostatistics method, and obtaining a three-dimensional probability distribution matrix of deep mineralization intensity based on the spatial correlation model; s3, dividing a to-be-estimated region into three-dimensional grid units based on the three-dimensional probability distribution matrix; and S4, calculating an in-mineral resource reserve estimation value of each grid unit in the three-dimensional grid units, and completing mineral resource reserve estimation based on satellite data based on the in-mineral resource reserve estimation value.

The invention relates to the technical field of geological exploration, in particular to an X-ray fluorescence spectrometer and geological radar combined gold vein rapid positioning method, which comprises the following steps: S1, arranging an exploration survey line in a pre-selected exploration area; s2, along the same measuring line, measuring the content of the gold mineralization indication element in the earth surface or the shallow medium by using an X-ray fluorescence spectrometer, synchronously recording the position information of a measuring point, and generating element content spatial distribution data; the gold mineralization indicating element comprises at least one of arsenic As, antimony Sb and mercury Hg; s3, carrying out detection by using a geological radar along the same measuring line, obtaining a reflected wave signal of an underground medium, synchronously recording position information of a detection point, identifying fault zone and joint zone geological structure anomalous bodies through data processing, and generating geological radar space distribution data; through XRF and GPR data fusion, a CAI quantitative model is established to precisely delineate an ore prospecting target area, a hidden ore body is effectively identified, the exploration precision and efficiency are greatly improved, and the exploration cost is reduced.

The invention relates to the technical field of geological exploration and three-dimensional modeling, and discloses a geological structure three-dimensional measurement system based on inertial navigation. According to the system, an inertial measurement data flow is processed through a resolving module, the instantaneous space attitude and the relative displacement vector of a measurement carrier are obtained, and a basic three-dimensional geologic structure model is constructed. The quantization module calculates the confidence coefficient of a resolving result in real time and generates a space-time uncertainty distribution field; and the model correction module performs error propagation analysis by using the distribution field, and performs iterative optimization of geometric morphology on a low-confidence region in the model. The system imports lithology, formation and structure interpretation data from the outside, and associates the data as attributes to the model. And the result packaging module packages the optimized model, the association attribute and the uncertainty distribution field into a composite three-dimensional geological survey result file. According to the method, dynamic quantification and visualization of measurement uncertainty are realized, the model can be autonomously optimized, and the reliability and precision of inertial navigation three-dimensional geological modeling are improved.

The invention discloses a coal seam gas content dynamic prediction method based on Bayesian optimization XGBoost, and belongs to the field of coal mine gas control, and the method comprises the steps: collecting a sample set U composed of influence factors of coal seam gas occurrence, preprocessing the sample set to obtain a sample set, and dividing the sample set in proportion to obtain a training set, a verification set and a test set; dividing the training set into a plurality of sample sets; an XGBoost model is constructed, the nth sample set serves as input, the actual coal seam gas content serves as output, the XGBoost model is trained, and an nth coal seam gas content prediction model is obtained; the influence factors of coal seam gas occurrence are calculated through a three-dimensional geologic model, geologic structure characteristics and coal seam roof and floor lithologic characteristics are comprehensively considered, and a Bayesian optimization algorithm is adopted to carry out adaptive search on hyper-parameters of an XGBoost model. The technical problem that a traditional gas content prediction method mostly depends on static geological parameters and cannot achieve real-time prediction of the gas occurrence state under the complex geological condition is solved.

The invention relates to the technical field of underground engineering monitoring, in particular to an underground cavern monitoring and early warning method and system based on machine learning. The method comprises the following steps: acquiring stratum rock mass parameters and geological structure labels of a target cavern; generating a virtual geological disaster scene data set by using the generative adversarial network; a combined feature tensor of InSAR point cloud phase fluctuation, anchor rod stress meter reading and composite electrode potential gradient is extracted through a time sequence convolution layer; the fusion weight is optimized, and a pre-training strategy network is output; a model independent element learning adapter is adopted, and actual cavern monitoring data are utilized to carry out fine tuning on the pre-training network to obtain a disaster response model; and finally, the potential gradient of the composite electrode is monitored in real time, a displacement and stress cooperative control instruction is generated through the model, and a rockburst risk grade instruction and a target reinforcement area coordinate are issued. According to the method, the physical rationality of the virtual data and the geological adaptation capability and interpretability of the model are effectively improved.

The invention relates to the technical field of geological disaster-causing identification, and discloses a big data-based limestone cave hidden disaster-causing factor identification method. The method comprises the following steps: acquiring geological structure data, hydrological monitoring data and earth surface deformation data of a limestone area to form a multi-source geological monitoring data set; performing space-time alignment processing on the multi-source geological monitoring data set to generate standardized geological data with a unified space-time reference; geologic structure features, hydrologic dynamic features and earth surface displacement features are extracted from the standardized geologic data, and a three-dimensional geologic feature space is constructed; based on the three-dimensional geologic feature space, calculating a combined anomaly index of a geologic structure anomaly degree, a hydrologic dynamic anomaly degree and a surface displacement anomaly degree; establishing a geological anomaly event detection model according to the joint anomaly index, and identifying a potential hidden disaster-causing area; performing multi-scale feature fusion on the hidden disaster-causing area to generate a disaster-causing risk level map; and outputting a lime karst cave hidden disaster-causing factor identification result based on the disaster-causing risk grade map.

A method for passively producing hydrogen from a geological formation includes drilling a plurality of lateral wellbores into an iron-rich geological formation from a mother wellbore extending from a surface location. Each of the plurality of lateral wellbores has an inclination along its length of less than 90 degrees. A biocide configured to inactivate hydrogen-consuming microbes is placed into the plurality of lateral wellbores and thereby into formation water that is flowed from the geological formation into the plurality of wellbores. Hydrogen gas effervesced from the formation water in the plurality of lateral wellbores is collected via the mother wellbore. The hydrogen gas is generated at least in part from a water reduction reaction of minerals of the geological formation with the formation water and risen through the plurality of lateral wellbores passively by buoyancy effects without pumping.

The invention relates to the technical field of coal mine hydrogeology and environmental engineering, and discloses a coal mine groundwater flow-water quality coupling simulation method under mining disturbance condition, which comprises the following steps: step 1, mining disturbance area hydrogeology basic data acquisition: field investigation, drilling sampling, field test and long-term monitoring are carried out to obtain mining disturbance area hydrogeology basic data; the method comprises the following steps: acquiring landform, stratum lithology, geological structure, initial hydraulic gradient, porosity, initial permeability, initial pollutant concentration and hydrogeochemical parameters of a research area, and collecting a coal mining scheme, rock stratum movement observation data and fracture development characteristic parameters; according to the method, the dynamic hydrogeological parameter model is constructed, the water flow-water quality coupling control equation is established, numerical solution and accurate calibration are combined, and accurate simulation of the underground water flow field and the water quality migration process under the mining disturbance condition can be achieved.

The invention provides a sedimentary strata three-dimensional geology construction method and system integrating carbon footprint evaluation and intelligent block modeling, and relates to the field of energy and geology. According to the method, carbon footprint evaluation and sedimentary stratum three-dimensional geological construction are organically fused, so that full-process integration of data acquisition, dynamic partitioning, spatial reconstruction and low-carbon scheduling is realized, and the bottlenecks that data and carbon emission information are separated and model precision and energy consumption control are difficult to balance in the traditional technology are broken through; the real-time performance of fine expression of geological structures and environmental risk assessment is greatly improved, and more quantitative and intelligent technical support is provided for carbon capture site selection and green exploration decision.

The invention relates to the technical field of mining, and discloses an open-air graphite mine mining method and system based on fine rock-ore separation, and the method comprises the following steps: analyzing the geological structure, the ore occurrence state and the surrounding rock property of a graphite mine, and judging whether the graphite mine is a mining area or not according to the analysis result; blasting the mining area by adopting an open-pit mining mode to obtain mixed ore; fine rock-ore separation is conducted on the mixed ore through gravity separation, magnetic separation and flotation, and graphite ore and surrounding rock are obtained through separation; wherein the geological structure comprises fractures, wrinkles and lithology changes; the ore occurrence state comprises the form and continuity of graphite; the surrounding rock property comprises a rock stratum dip angle and a fault zone. According to the method, the mining process of the graphite mine is finely managed and controlled, so that the mining efficiency is improved, the cost is reduced, the safety guarantee is enhanced, the resource waste is reduced, and remarkable benefits are brought to the mining industry of the graphite mine.

This invention provides a method for expanding the functionality of directional boreholes for grouting in Ordos limestone aquifers. The method includes acquiring and analyzing mine hydrogeological data, determining the lithological structure characteristics, sedimentary characteristics, geological structural distribution parameters, and hydrogeological parameters of the coal seam floor, constructing a stratigraphic structure model, analyzing the hydrogeological parameters based on the stratigraphic structure model to determine the treatment strata in the Ordos limestone aquifer, analyzing the geological structural distribution parameters based on the stratigraphic structure model to determine the trajectory design parameters for the directional borehole, determining the function of the directional borehole according to the project objective and pre-defined directional borehole function classification information, and designing the directional borehole corresponding to the treatment strata and / or the borehole trajectory design parameters. This method refines the functional classification of directional boreholes, provides design methods for directional boreholes with different functions, expands the functionality of directional boreholes, and makes the surface area treatment technology for Ordos limestone water hazards more comprehensive, applicable, and targeted.

The utility model relates to the technical field of geology pre-alarm, in particular to an advanced geology forecasting device based on tunnel water gushing, which comprises a fixed plate, a rotating shaft is movably connected to one side of the fixed plate, rotating fan blades are fixedly connected to the side surface of the rotating shaft, a transmission plate is fixedly connected to one side of the rotating fan blades, and the transmission plate is fixedly connected to the other side of the rotating fan blades. And one side of the fixing plate is movably connected with a rotating shaft, the side surface of the rotating shaft is movably connected with a transmission part through a hinge, the transmission part is matched with the rotating fan blades, and one side of the fixing plate is fixedly connected with a connecting plate. According to the advanced geological forecasting device based on the tunnel water inrush, the geological structure and the water body distribution condition in front of the tunnel can be accurately detected, enough early warning time is gained for constructors, the constructors can make corresponding preparations in advance, the threat of the water inrush to personnel safety is reduced, the construction period delay cost caused by the water inrush is reduced, and the construction efficiency is improved. The project can be completed on time, and the total construction cost is saved.

The invention relates to the field of geological recognition, in particular to an axial chain type rockburst disaster-pregnant geological recognition method and device, and the method comprises the steps: obtaining micro-seismic monitoring data in the excavation process of a deeply-buried hard rock tunnel; according to the micro-seismic monitoring data, identifying the axial chain type rockburst disaster-pregnancy area to obtain a disaster-pregnancy area range; calculating the normal vector of the fracture surface according to the disaster-pregnant area range and the micro-seismic monitoring data; establishing a parameter system and constraint conditions required by ST-DBSCAN clustering according to the normal vector of the fracture surface and the micro-seismic monitoring data; sT-DBSCAN clustering processing is carried out according to the required parameter system and constraint conditions, and a micro-seismic event cluster reflecting a potential rock mass structural plane is obtained; and performing three-dimensional reconstruction processing on a rock mass structure network according to the micro-seismic event clustering cluster to obtain a reconstructed three-dimensional geometric model of the axial chain type rockburst disaster-pregnant geology. According to the axial chain type rockburst disaster-pregnant geology three-dimensional geometric model and the construction method thereof, accurate description of a hidden rock mass structure and effective advanced early warning of a rockburst risk are realized.

The invention discloses a two-dimensional inversion operation method, system and device for a magnetotelluric sounding profile, a medium and a product, relates to the technical field of magnetotelluric sounding exploration, and aims to solve the problem that existing inversion based on nonlinear conjugate gradients is highly dependent on an initial model. The method comprises the following steps: firstly, acquiring measured data including measured point measured kilometer network coordinates, apparent resistivity and phase data; a two-dimensional inversion profile with complete data of each measuring point is constructed according to linear projection, and data interference and distortion are eliminated through preprocessing; the method comprises the following steps: firstly, constructing a uniform half-space model, and carrying out two-dimensional nonlinear conjugate gradient TE mode inversion to obtain a rough two-dimensional resistivity model; and taking the rough model as an initial model, carrying out TM mode inversion to obtain a target two-dimensional resistivity model, and finally carrying out geological interpretation by combining rock physical property, geology and drilling geophysical prospecting data. According to the method, through a strategy of first TE and then TM, dependence of an initial model is reduced by means of a TE mode, resolution capability is improved by means of a TM mode, false anomalies are reduced, reliability of a target model can be improved, and accurate data support is provided for mineral exploration and deep geologic structure research.

The invention relates to the field of image recognition, in particular to a geological structure recognition method based on deep learning. The method comprises the following steps: firstly, carrying out image preprocessing on an acquired original geological image, and carrying out feature extraction based on the preprocessed geological image to generate a feature map; calculating gradient vectors and gradient norms of the pixel points based on the feature map; calculating a local connectivity factor based on the gradient norm of the pixel point; then, on the basis of the gradient norm and the local connectivity factor of the pixel points, a dynamic boundary feature reconstruction algorithm is used for processing to obtain a reconstructed feature map; and finally, based on the reconstructed feature map, classifying the geological structure through a geological structure probability classification algorithm, and generating a classification probability vector. The technical problems that the precision of automatic geological structure recognition is insufficient, boundary feature extraction is limited, feature enhancement and noise suppression are unbalanced, and the generalization ability of geological structure classification is insufficient are solved.

The present application relates to the technical field of three-dimensional geological visualization modeling, and discloses a mine geological structure intelligent analysis method and system based on three-dimensional visualization modeling, which comprises the following steps: acquiring continuous drilling process parameters along a drill hole, establishing a parameter fingerprint library to identify the causes of parameter changes, identifying effective physical beacon points capable of representing real geological discontinuity, and then generating a geological reality guide field in three-dimensional space using the beacon points as a source, and imposing constraints on the weight across potential geological boundaries when performing spatial interpolation. The present application converts long-neglected drilling process data into effective geometric constraints for the three-dimensional modeling kernel, changes the model construction from pure mathematical filling to a form closer to the engineering reality guided by the physical process, and ensures the reliability of the constraint source through an internal anti-fake mechanism, thereby improving the structural reality of the final geological model.