404 results about "System" patented technology

The invention relates to the technical field of tunnel engineering, in particular to a tunnel surrounding rock grading method and system, comprising intelligent sensing and data acquisition, multi-source data fusion and modeling, hybrid model dynamic grading, real-time decision and support optimization, online learning and dynamic feedback, and risk early warning and emergency response. Compared with the prior art that a geological data acquisition mode combining manual drilling coring and low-resolution geophysical prospecting is adopted, efficiency is low, subjective errors are large, and a complex geological structure is difficult to cover, unmanned aerial vehicle LiDAR scanning, intelligent rock core image analysis and a high-density IoT sensor network work cooperatively, and the working efficiency is greatly improved. Real-time dynamic acquisition of full-section geological information is achieved, manual intervention errors are eliminated in combination with a multi-source data fusion algorithm, the automation level and three-dimensional space representation precision of data acquisition are remarkably improved, and a high-resolution holographic data base is provided for surrounding rock classification.

The invention discloses a tunnel blasting simulation method and system for a karst area, and relates to the field of tunnel blasting simulation, and the method comprises the steps: building a three-dimensional geologic model of the karst area, and generating an initial ground stress distribution rule through numerical simulation; generating refined initial crustal stress field data; calculating stress wave intensity and time sequence data generated by explosion; acquiring stress wave propagation data; calculating the surrounding rock damage degree and the crack initial position and direction; simulating the surrounding rock crack propagation process, and calculating the penetration probability and the propagation speed of the crack near the karst cave in combination with the karst cave characteristic parameters; analyzing the surrounding rock stability and damage evolution trend of the karst cave area; and optimizing explosive source item parameters and stress wave propagation boundary conditions, and generating a karst area tunnel blasting simulation result. According to the method, the influence of the karst cave on stress wave propagation is accurately simulated, powerful support is provided for optimizing a blasting scheme and improving construction safety and efficiency, and the method has important guiding significance on tunnel engineering under complex geological conditions.

The invention provides a tunnel disaster source multi-attribute joint inversion method and system based on physical property constraint, and relates to the technical field of tunnel engineering and joint inversion, and the method comprises the steps: constructing a tunnel face three-dimensional geologic model, applying controlled disturbance to surrounding rock physical property parameters, analyzing the change characteristics of earthquake and electromagnetic observation response, and obtaining a tunnel face three-dimensional geologic model; establishing a quantitative mapping relation between the surrounding rock physical property parameter disturbance quantity and the multi-field response signal variable quantity; constructing a multi-dimensional sensitivity evaluation index, and generating a joint sensitivity result; the surrounding rock units are identified and divided, differentiated partition rock physical relationship constraints are constructed, and a physical multi-attribute inversion target of joint inversion is determined based on the partition rock physical relationship constraints; and on the basis of a physical multi-attribute inversion target, a multi-source joint inversion target function is constructed in combination with the joint sensitivity result, joint solving and iterative updating are carried out, and a tunnel face advanced inversion result is output. According to the invention, calamity source fine identification and risk quantitative evaluation in front of the tunnel face during the tunnel construction period are realized.

The invention relates to the technical field of layered surrounding rock inversion analysis, and discloses a layered surrounding rock three-dimensional crustal stress field inversion intelligent analysis system and method, and the system comprises a dimensional geological value module, an intelligent inversion analysis module and an inversion result verification module. The method comprises the steps of collecting geological data in target layered surrounding rock; carrying out normalization processing on the geological data, and carrying out sensitivity analysis; constructing a three-dimensional geologic model, and performing numerical simulation; a crustal stress field inversion intelligent analysis model is generated based on the three-dimensional geologic model; training the crustal stress field inversion intelligent analysis model by using the training sample; inputting the real-time geological data into the crustal stress field inversion intelligent analysis model to obtain a crustal stress inversion analysis result; carrying out visual output on the ground stress analysis result; and adjusting the crustal stress field inversion intelligent analysis model according to the actually measured data. Scientific ground stress field analysis basis can be provided for complex projects such as tunnel engineering, underground engineering and hydropower stations.

The invention provides a tunnel surrounding rock grouting control method and system, and relates to the technical field of tunnel engineering.The tunnel surrounding rock grouting control method comprises the steps that grouting parameters are obtained, and the grouting parameters comprise grouting pressure and slurry viscosity; performing multi-dimensional real-time monitoring on the surrounding rock fracture, and constructing a dynamic three-dimensional geologic model through the multi-dimensional real-time monitored data; performing grout diffusion path prediction based on the three-dimensional geologic model, and generating an initial grouting scheme through the predicted grout diffusion path; the fractal dimension is optimized according to a genetic algorithm, the grouting parameters are dynamically corrected through the optimized fractal dimension, and a grout diffusion result is obtained; establishing a multi-field coupling equation based on the slurry diffusion result, and optimizing the initial grouting scheme through the multi-field coupling equation to obtain an optimal grouting scheme; and according to the optimal grouting scheme, power pressure compensation is conducted, and grouting control is conducted. The problem that slurry diffusion is difficult to accurately control is solved.

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.

The invention relates to the technical field of rock mass earthquake dynamic response, and discloses a layered rock mass earthquake dynamic response multi-scale monitoring system and method, and the system comprises a rock mass three-dimensional geological module, a simulation setting module and an earthquake simulation module. The method comprises the following steps: establishing a layered rock mass three-dimensional geologic model; the method comprises the following steps: identifying a dangerous rock mass structural surface, monitoring slope displacement, and installing sound emission monitoring equipment at a key position to form a three-dimensional monitoring network; a layered rock mass and a broken area in the layered rock mass three-dimensional geological model are divided into discrete element areas, and a continuous medium area is divided into finite difference areas; coupling the discrete element region and the finite difference region; inputting the seismic wave as a dynamic boundary condition into the finite difference region, transmitting a response to the discrete element region through a coupling interface, and simulating a rock stratum and rock mass dynamic fracture process; and the crack propagation particle size and the original stress propagation are transmitted to the cloud platform. The geometric morphology and the internal structure of the rock mass can be accurately reflected.

The invention relates to the technical field of data processing, in particular to an engineering geological survey data processing method and system, and the method comprises the following steps: obtaining hole site space positioning and lithologic boundary information, collecting a structure segment sequence, extracting resistance change direction classification disturbance behaviors, recognizing node sequence conflicts, and judging hydrological turning positions. Identifying the corresponding relation between the structural section and the water level track, and generating a structural section water level merging mapping table. According to the method, the spatial information, the lithology identification, the sampling level and the penetration resistance of the drilling structure sections are collected and serialized, disturbance identification and non-sampling section classification are performed based on the resistance change trend between the sections, and node conflicts are identified in combination with the numbering relation and the lithology combination; continuous modeling and classified merging of geological information on the spatial level are achieved, the linkage adaptability of data in a multi-dimensional analysis scene is enhanced, misjudgment interference caused by information isolation is avoided, and dynamic recognition and hydrological response analysis of a geological structure are supported.

Methods and systems are disclosed. The methods may include determining a first sequence of permeabilities by subjecting a rock sample to a first sequence of confining stress, axial stress, pore pressure (CSASPP) triplets and determining a first rock parameter using the first sequence of permeabilities, the first sequence of CSASPP triplets, and a first permeability model. The methods may further include determining a second sequence of permeabilities by subjecting the rock sample to a second sequence of CSASPP triplets and determining a second rock parameter using the second sequence of permeabilities, the second sequence of CSASPP triplets, and the first permeability model. The method may still further include determining an in situ permeability for an in situ rock based on an initial permeability, a second stress sensitivity parameter, a first stress sensitivity parameter, a confining stress value, axial stress values, a pore pressure value, and a second permeability model.

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 provides a quality evaluation method for a geological three-dimensional model, and the method comprises the steps: S11, carrying out the analysis of a historical geological project document, extracting evaluation indexes and data demands, and determining related modeling source data according to the type and target of a geological project; s12, learning an evaluation scheme of a historical successful geological project document, and generating a three-dimensional geological model evaluation scheme containing a verification data range and method; s13, monitoring and analyzing the modeling process of the three-dimensional geologic model based on the three-dimensional geologic model evaluation scheme; s14, determining the weight of each evaluation index in the three-dimensional geologic model evaluation scheme so as to determine the quality grade of the three-dimensional geologic model, and continuously adjusting the weight distribution of the evaluation indexes; and S15, according to the quality grade of the three-dimensional geologic model, determining whether the three-dimensional geologic model meets the acceptance requirement or not. The invention provides a systematic evaluation method for the quality evaluation of the three-dimensional geologic model, thereby promoting the application and development of the three-dimensional geologic model in various fields.

The invention discloses a three-dimensional geological model dynamic updating system and method based on multi-modal data fusion, and belongs to the technical field of geological engineering and information. According to the method, multi-source data of geological radar, earthquake, drilling, remote sensing and the like are integrated, and after unified formatting and quality optimization preprocessing, geological features of a stratum interface, a fault zone and the like are automatically extracted by using a deep learning network; multi-source feature data fusion is realized through space-time registration and attention; constructing a three-dimensional geologic model by adopting a TIN and Octree mixed structure based on a fusion result; dynamic updating of the model is realized through incremental detection and a local reconstruction mechanism, and the boundary of the model is optimized by adopting a radial basis function interpolation. According to the method, the problems of single data, updating lag and the like of a traditional method are solved, the modeling precision and efficiency are remarkably improved, and reliable support is provided for geological engineering decision making.

The invention belongs to the technical field of geological research, and discloses a multi-scale lithofacies identification and sedimentary microfacies reconstruction method and system, and the method comprises the steps: data collection and preprocessing: collecting core data, slice data, logging data and seismic data of a research region; multi-scale lithofacies feature extraction, wherein the multi-scale lithofacies feature extraction comprises micro-scale feature extraction, medium-scale feature extraction and macro-scale feature extraction; constructing and training a multi-scale lithofacies recognition model, constructing the multi-scale lithofacies recognition model by adopting a deep learning algorithm, and taking the extracted microscopic, mesoscopic and macroscopic lithofacies features as input data; multi-scale lithofacies identification: extracting multi-scale lithofacies features from the preprocessed multi-source data; and sedimentary microfacies reconstruction: establishing a lithofacies-sedimentary microfacies conversion relation in combination with a sedimentology principle and a geological knowledge base. According to the method, multi-source data such as rock cores, slices, logging and earthquakes are integrated, lithofacies features are extracted from microcosmic, mesoscopic and macroscopic multiple scales, the features and changes of lithofacies can be comprehensively and accurately reflected, and compared with a traditional single-scale method, the accuracy and reliability of lithofacies recognition are improved.

The invention provides a large-scale three-dimensional tunnel surrounding rock parameter random field model construction method and system, and relates to the technical field of tunnel surrounding rock modeling, and the method comprises the steps: carrying out the fitting construction of a probability distribution model reflecting surrounding rock parameters; selecting a plurality of surrounding rock parameters as clustering features, quantitatively classifying global geologic structures in tunnel surrounding rocks, and performing global decomposition on a tunnel model into continuous sub-domains containing overlapped buffer areas; for a first sub-domain from any direction of the whole domain of the tunnel model, performing covariance matrix spectral decomposition by adopting a KL decomposition method to generate a first sub-domain random field, and extracting random field values of overlapped regions among the sub-domains as boundary condition data of a recursive generation process; on the basis of the boundary condition data, conditional random fields of subsequent sub-domains are generated layer by layer; and seamlessly splicing the conditional random fields generated by recursion of the sub-fields into a global parameter random field, converting the global parameter random field into probability distribution by adopting a probability mapping method, and performing instruction encapsulation by developing a cross-platform data interface engine to realize a construction process of a parameter random field model.

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 method and a system for identifying a micro-seismic signal mode of a surrounding rock rockburst risk, particularly relates to the technical field of deep underground engineering rockburst monitoring, and is used for solving the problem that an existing micro-seismic early warning model lags in identifying a rock mass damage evolution critical state. The method comprises the following steps: collecting a surrounding rock micro-seismic event signal in real time, intercepting an event sequence based on a sliding time window, and calculating a space-time fractal dimension; extracting an event space density field in the window to calculate an energy gradient, and marking a strong interaction cluster of which the energy gradient exceeds a threshold value; storing the fractal dimension change sequence in real time; performing characteristic frequency band filtering on the signals in the window, calculating a ratio of an energy ratio entropy descent rate to a fractal dimension descent rate, and determining a damage acceleration state when the ratio is a supercritical coefficient; generating a rockburst high-risk instruction when the strong interaction cluster and the damage acceleration state coexist and the fractal dimension descent rate is supercritical threshold; the multi-dimensional collaborative identification of the rockburst precursor is realized, and the early warning accuracy and timeliness are remarkably improved.

The invention provides a potential safety hazard analysis method and system based on underground cavern three-dimensional geological intelligent modeling, and the method comprises the steps: firstly, based on underground cavern three-dimensional model data, cutting the underground cavern three-dimensional model data into a plurality of sub-models according to a geological condition segmentation rule, and enabling the geological condition segmentation rule to dynamically adjust the cutting spacing according to the gradient change characteristics of a rock stratum; performing gradient analysis on the longitudinal and axial rock stratum attributes of each sub-model to generate rock stratum transition characteristic data containing the adjacent rock stratum attribute change rate and the transition area space distribution, and dynamically identifying the surrounding rock type of the sub-model according to the rock stratum transition characteristic data; and mapping and matching the surrounding rock identification result with a preset protected object space coordinate, collecting a sub-model geological parameter set in real time, finally triggering a safety early warning signal according to a geological parameter set numerical value interval, and generating an emergency disposal scheme set associated with the safety early warning signal, so that the potential safety hazard of the underground cavern can be effectively analyzed.

The invention discloses a geological multi-scale data hierarchical retrieval method and electronic equipment, and belongs to the technical field of geological data management and retrieval, and the geological multi-scale data hierarchical retrieval method comprises the following steps: S1, constructing a multi-scale data system, namely a three-level data structure system of a digital outcrop model, a rock specimen and a rock sample; s2, establishing an association mechanism among the three-level data structure systems, digital outcrop model-rock specimen association and rock specimen-rock sample association are carried out; and S3, performing multi-scale data hierarchy retrieval by adopting bidirectional association retrieval and feature retrieval. The digital outcrop-rock sample-rock sample association retrieval method has the advantages that the digital outcrop-rock sample-rock sample association retrieval efficiency is improved, the multi-dimensional retrieval capability is achieved, multi-class feature combination query, lithology + era + components and the like are supported, and seamless connection of macroscopic-mesoscopic-microscopic data can be realized; a bidirectional traceable chain is established, and data traceability is complete.

The invention discloses a TBM surrounding rock geology sensing method and system based on multi-source heterogeneous information, and the method carries out the feature fusion based on the tunneling parameter statistical features and rock slag image analysis features, carries out the model prediction based on the fusion features, achieves the deep fusion of the multi-source heterogeneous information, and improves the precision of the TBM surrounding rock geology sensing. The prediction accuracy of the model is improved, the model output is the surrounding rock score, so that the model training is not limited by the sparsity of a single label, the training precision of the model is improved, and in addition, the surrounding rock grade quantitative score and the surrounding rock state qualitative evaluation are combined, so that the surrounding rock score and the surrounding rock grade are in discontinuous correspondence. Continuous evaluation of the surrounding rock state is achieved, and the problem that a surrounding rock grading mode of a traditional method is discrete is solved.

The invention provides a grouting path optimization method and system based on multi-field coupling constraint, and belongs to the technical field of geotechnical engineering grouting, and the method comprises the steps: collecting geological data, including rock stratum distribution and physical and mechanical parameters, and underground water data; establishing a three-dimensional multi-physics field coupling model based on the acquired geological data, including establishing a three-dimensional rock-soil body model, performing stress field analysis on the three-dimensional rock-soil body model, constructing a seepage field, simulating a temperature field, quantifying mutual influence among the stress field, the seepage field and the temperature field, and obtaining a coupling relationship among the physics fields; obtaining rheological property data of the slurry, and calibrating the established three-dimensional multi-physics field coupling model based on the obtained rheological property data of the slurry to obtain a calibrated three-dimensional multi-physics field coupling model; and aiming at the calibrated three-dimensional multi-physics field coupling model, optimizing the grouting path, the slurry pressure and the slurry proportioning parameter, and generating an optimal grouting path planning scheme.

The invention relates to the technical field of tunnel engineering, in particular to a method and a system for optimizing design parameters based on unsymmetrical pressure tunnel blasting excavation dynamic response. The method comprises the following steps of obtaining geological parameters and construction parameters of surrounding rock of the bias tunnel, constructing a discontinuous structure equivalent damage model, and obtaining initial stress field distribution of a rock mass in combination with the discontinuous structure equivalent damage model, the geological parameters and the construction parameters; analyzing the time-varying modified dynamic mechanical parameters, and calculating through a stress wave propagation path and an energy dissipation rule to obtain a time travel curve of dynamic stress and vibration speed of each point of the surrounding rock in the blasting process; correcting a dynamic response index by using a self-adaptive artificial boundary condition to obtain a dynamic response state characteristic; and on the basis of the initial stress field distribution of the rock mass, the time history curve and the dynamic response state characteristics, optimal design parameters are obtained according to optimal design indexes. According to the method, the balance between the blasting vibration strength and the construction efficiency is realized by optimizing and adjusting the design parameters.

The invention discloses a tunnel precise drilling and blasting design method integrating multi-source intelligence and closed-loop optimization. The method comprises the steps that geological parameters are collected through geological detection equipment; based on fracture mechanics and rock mass damage theories, constructing a quantitative relation model reflecting joint network distribution, stress wave propagation characteristics and a rock mass crushing effect coupling mechanism; inputting the geological parameters into a pre-constructed multi-dimensional knowledge base, integrating historical engineering data association rules by the multi-dimensional knowledge base by using a graph database, and extracting geological features; based on a deep learning model, analyzing the mapping relation between the geological features and the blasting parameters, and generating a preliminary blasting scheme including the blast hole distance, the charging structure and the detonating mode; according to the method, a closed-loop optimization system of geologic features-blasting parameters-effect evaluation is constructed, so that dynamic intelligent decision-making and construction self-adaptive regulation and control of tunnel drilling and blasting design are realized, and the contour forming precision and the blasting efficiency are remarkably improved.

The invention discloses a metamorphic rock P-T-t trajectory reconstruction method and system based on multi-source data fusion, and relates to the field of metamorphic rock P-T-t trajectory reconstruction.The method comprises the steps that electronic probe microcell map data and internal standard sample data of a metamorphic rock sample are obtained, and multi-stage data correction is conducted; carrying out mineral phase identification and chemical component quantitative interpretation to generate a mineral classification map, an element concentration distribution map and a total rock main component data set; thermodynamic phase equilibrium simulation is carried out, a P-T view profile map is generated, and a P-T track is extracted; performing microcell in-situ chronological analysis on selected minerals in the mineral classification map to obtain chronological data; and carrying out space-time coupling on the P-T trajectory and chronology data, constructing a P-T-t three-dimensional trajectory model of the metamorphic rock, and outputting a visual reconstruction report. According to the method, automation and standardization of the whole process of metamorphic rock P-T-t trajectory from data acquisition and processing to model reconstruction are realized, and the precision, efficiency and reliability of trajectory analysis are improved.

The invention discloses a foundation pit seepage-deformation space-time coupling early warning method and system based on a large geological model, and belongs to the technical field of geotechnical engineering intelligent monitoring, and the method comprises the steps: processing a regional geological survey report through the large geological model based on a Transform architecture, and generating a high-precision three-dimensional stratum parameter field; further, an improved particle finite element method is adopted to carry out dynamic coupling solution of a seepage field and a stress field, a displacement rate vector is obtained, a hybrid network space-time prediction model fused with LSTM-Transform is constructed, a composite early warning index is calculated in combination with the real-time displacement rate vector, and through multi-source data fusion and space-time coupling analysis, an early warning result is obtained. Accurate evaluation and advanced early warning of the seepage stability and the deformation state of the deep foundation pit project are achieved, the accuracy and reliability of early warning signals are remarkably improved, and the method is suitable for foundation pit safety control under complex geological conditions.

The invention provides a hydraulic ring geological environment detection method and system, and belongs to the technical field of geological detection.The method comprises the steps that original geological environment data and historical geological abnormal data of a target area are obtained, space-time alignment processing operation is conducted on the original geological environment data and the historical geological abnormal data, and a three-dimensional geological parameter grid is obtained; obtaining a standard geological parameter template and a geological anomaly mode based on the three-dimensional geological parameter grid and the historical geological anomaly data; obtaining geological instability probability parameters and an optimization monitoring strategy table based on the standard geological parameter template and the geological abnormal mode; according to the method, monitoring indexes and space deployment schemes can be adjusted according to distribution hot spots and risk levels of geological anomalies, waste of monitoring resources and insufficient monitoring of high-risk areas are avoided, a real-time geological environment data set is obtained according to an optimized monitoring strategy table, and the problem that a traditional geological environment detection method is prone to waste monitoring resources is solved.

The mineralogical, chemical, magnetic, and physical properties of a rock can be used to determine the amount of hydrogen that was generated during rock alteration and the remaining amount of hydrogen generation potential. The methodologies evaluate the hydrogen generation potential of geological samples and identify natural hydrogen source rocks. The mineralogy, elemental composition, iron content and oxidation state, and other properties of a geological sample may be determined. From the determined mineralogy and other properties of the geological sample, the amount of hydrogen which the geological sample may have generated may be quantified. This method can determine the maturity of hydrogen source rocks, the potential volume of hydrogen that can be generated in other parts of a given geologic province with higher degrees of hydrogen source rock maturity, and quantify the potential remaining volume of hydrogen that can be still be generated via secondary enhanced hydrogen stimulation processes.

The invention discloses a method for depicting the boundary of a sedimentary system through a heavy mineral combination based on an intelligent sensing system, and relates to the technical field of geological exploration, and the method comprises the steps: obtaining the heavy mineral content data of a sedimentary rock sample collected by a target layer section and a peripheral exposed section of the target layer section in a research area through the intelligent sensing system; carrying out statistics on the contents of various heavy minerals in the collected samples, calculating the percentage of each heavy mineral, and carrying out data arrangement to form a data table; and importing the heavy mineral content data into data analysis software, carrying out Q-type clustering analysis, and classifying according to the similarity between samples. According to the method, the heavy mineral content data of the sedimentary rock sample is obtained through the uniformly distributed sampling points, compared with traditional single-point sample analysis, the spatial distribution characteristics of a material source system in a research area can be more comprehensively reflected, the boundary of a sedimentary system can be accurately divided, the recognition precision of sedimentary facies distribution is improved, and the analysis accuracy of the sedimentary facies is improved. And more detailed basic data are provided for geological research and resource exploration.

The invention relates to the technical field of mineral resource prospecting exploration, in particular to a prospecting prediction method based on a compound rock mass anatomy porphyry-skarn composite mineralization system. The control factors and formation mechanism of the ore deposit are clarified, and the deep earth dynamics process of porphyry mineralization development is disclosed. Through typical ore deposit fine dissection, the space-time structure characteristics of mineralization in different structural evolution stages are discussed; according to the method, mineral in-situ micro-area surface scanning and sulfide isotope in-situ tracing technologies are utilized to determine occurrence forms of metallogenic elements, restrain activation migration behaviors of microelements, find out sources of metallogenic metal substances, reveal a superposition metallogenic development mechanism and provide theoretical basis and technical support for prospecting exploration.

The invention relates to a tunnel surrounding rock grading method and system based on multi-source data fusion, and the method comprises the following steps: obtaining image data and point cloud data of a tunnel face, carrying out the preprocessing and data enhancement, obtaining image features and point cloud features reflecting the shape, structure, texture and roughness of the tunnel face, and carrying out the classification of the image features and the point cloud features; carrying out fusion processing on the obtained features; during feature fusion, according to the joint density in the image, determining the image block granularity, and projecting the image block granularity to the image features; determining a geological weight according to geological information acquired in advance, and embedding the geological weight into the image features; fusing the surrounding rock roughness and the rock quality index in the point cloud features with the image features through a cross-modal attention mechanism to obtain fused features; and the fused features learn geological structure laws through a pre-trained main network and a pre-trained slave network to obtain a comprehensive score, and a surrounding rock grading result is determined in combination with a threshold value of a set geological parameter.

The invention relates to the technical field of underground geotechnical engineering and tunnel construction monitoring, in particular to a shield tunneling rock stratum real-time judgment method. The method comprises the steps that according to signals of neutron radiation characteristics released when different lithologic samples are fractured under a shield tunneling stress path simulated in a laboratory, a knowledge base of the neutron radiation characteristics of a rock stratum is constructed; deploying an on-site multi-source data acquisition system, and acquiring data of neutron radiation characteristics and shield tunneling parameters; jointly forming a fusion feature vector according to the data of the neutron radiation features and the shield tunneling parameters; the method has the advantages that signals of neutron radiation characteristics released in the rock fracture process are directly monitored, the signals are fused with shield tunneling parameters in a multi-source mode, a machine learning model is combined, and the lithology classification probability and the rock mass integrity index are obtained. Real-time and accurate discrimination of lithology and integrity of a front rock stratum is realized, physical characteristics of a rock mass are reflected, and a discrimination effect is continuously optimized.