544 results about "Geologic modelling" patented technology

The invention discloses an underground construction decision-making method based on three-dimensional geological modeling and risk hot area identification, and relates to the field of fusion of artificial intelligence and geological engineering. The method comprises the following steps: firstly, acquiring drilling data, geological radar images and seismic reflecting layer information, constructing a three-dimensional geological voxel model with spatial topology constraints, and accurately describing a geological unit structure by adopting an irregular grid mode; and then, extracting a time sequence characteristic index under construction disturbance, forming a continuous time sequence characteristic vector, inputting the continuous time sequence characteristic vector into a convolutional recurrent neural network model with a space attention aggregation mechanism and a deep memory unit, and predicting a risk heat value of each space position. And on the basis, through heat gradient clustering and neighborhood consistency analysis, a dynamic high-risk hot area is identified, and a risk hot area map is constructed. And finally, in combination with the construction stage, the equipment plan and the sensor feedback information, constructing a multi-target auxiliary decision function, and generating a construction decision result including operation path reconstruction, rhythm adjustment and power limit and control suggestions.

The invention discloses a mine safety risk prevention and control method and system based on multi-source data fusion, and particularly relates to the technical field of mine safety monitoring, and the method comprises the steps: obtaining surface topography, an underground geologic structure and real-time monitoring parameters through remote sensing images, drilling data and dynamic monitoring equipment, and constructing a mining area geologic database with consistent time and space; fusing geologic feature data, integrating earth surface and underground feature data by using a three-dimensional geologic modeling technology, and mapping dynamic monitoring parameters into a model to generate a dynamic geologic feature field; performing clustering analysis on the abnormal feature points based on a spatial clustering algorithm, and calibrating a potential safety hazard region; calculating a regional risk comprehensive index by combining the risk values of the dynamic features, the geological features and the spatial features; early warning is triggered in a graded mode according to the comprehensive index, prevention and control measures are put forward, and the evaluation model is dynamically updated; comprehensive support is provided for mine potential safety hazard area monitoring and safety management decision making, and the method is suitable for risk management scenes of complex mining areas.

The invention discloses a prospecting target area prediction method and system based on geological three-dimensional modeling, and relates to the technical field of mineral resource exploration, and the method comprises the steps: obtaining geological, geophysical, geochemical and remote sensing data of a target area, carrying out the preprocessing, generating a modeling data set, and carrying out the geological modeling; constructing a lithology classification model by combining the three-dimensional geologic model with deep learning, and extracting shallow lithology features to predict the deep lithology of the target area; screening metallogenic factors according to the prediction result of the deep lithology of the target area, the deep geophysical data and the three-dimensional geologic model, and generating a metallogenic prediction factor set; and establishing a prospecting prediction model based on the graph convolutional network, importing the metallogenic prediction factor set to obtain a metallogenic distribution prediction result, and carrying out three-dimensional prospecting target area delineation. According to the method, deep lithologic stratum prediction is carried out through multi-source geological data and geological three-dimensional modeling, and target region delineation is carried out by using the graph convolutional neural network, so that the efficiency and precision of prospecting target region prediction are improved, and the exploration cost is reduced.

The invention relates to the technical field of oil field databases, and discloses a dynamic data management method, device, equipment and medium for an oil and gas field database, and the method comprises the steps: docking multi-source data of the oil and gas field database, the multi-source data comprising a shaft sensor real-time monitoring data flow, geologic modeling gridding structure data and an equipment management tree coding table; the method comprises the following steps: performing abnormal value cleaning and timestamp alignment on real-time monitoring data flow of a shaft sensor, converting geologic modeling gridding structure data into a reservoir unit set with a coordinate system label, extracting a set membership chain of well IDs and equipment IDs in an equipment management tree-shaped coding table, generating an identifier system with a unified coding format, and storing the identifier system in a database; the identifier system comprises a well identifier, a reservoir unit identifier and a device identifier; generating a structured data pool based on the identifier system; and when the data pool is updated, sending a change instruction to a plurality of subsystems of the oil and gas field database, and updating each subsystem based on the change instruction.

The present invention belongs to the technical field of fracture network optimization in oilfield exploitation. Specifically disclosed are a method and system for optimizing complex fracture networks in shale reservoirs. The method comprises: S1, on the basis of geological-engineering bimodal data fusion, constructing a three-dimensional digital twin of heterogeneous reservoirs; S2, synchronously calculating the interactions among fluid flow, rock fracturing and proppant transport during a hydraulic fracturing process; and S3, automatically and iteratively optimizing a combination of fracturing operation parameters. By means of constructing a closed-loop system consisting of geological modeling, multi-field coupling simulation, intelligent optimization and dynamic correction, efficient design and real-time optimization of complex fracture networks in shale reservoirs are realized.

The invention discloses a fracture structure multi-scale modeling method based on multi-source data fusion, and belongs to the field of geological modeling, and the method comprises the following steps: S1, collecting and preprocessing multi-source data; s13, aligning the data, and integrating the data from different sources together; s2, three-dimensional geologic modeling: S21, generating an initial three-dimensional grid by using geologic modeling software to obtain an initial three-dimensional geologic body model; s22, dynamically adjusting the density of the initial three-dimensional grid by using a self-adaptive grid division technology; s23, using a machine learning algorithm to identify and classify faults; s3, expanding the three-dimensional geologic body model macroscopically and microcosmically; and S4, performing dynamic simulation and prediction by using the three-dimensional geologic body model. By adopting the fracture structure multi-scale modeling method based on multi-source data fusion, the accuracy and reliability of the fracture structure model are improved by integrating multiple data sources and multi-scale analysis.

The invention belongs to the technical field of three-dimensional geologic modeling, and particularly relates to a three-dimensional geologic model construction method based on multi-source data fusion, and the method comprises the steps: 1, extracting drilling data, and constructing a drilling database; 2, constructing a topographic and geomorphic surface model, and completing the fusion of topographic and geomorphic data and drilling data; 3, coupling information of strata, rock mass, fracture, ore body and the like, and constructing a geologic body comprehensive model; 4, extracting geophysical and geochemical data, and constructing a geophysical model and a geochemical model; and 5, coupling the borehole database, the landform surface model, the geologic body comprehensive model and the geophysical model, and constructing a multi-source data fused three-dimensional geologic model. The method improves the accuracy and precision of the three-dimensional geologic model, improves the data processing and analysis speed, improves the data analysis capability and depth, provides technical support for uranium resource potential analysis and prediction exploration, and guides uranium exploration.

The invention discloses a blasting design-oriented multi-source data fusion preprocessing method, and particularly relates to the technical field of blasting data scientific processing. Comprising the following steps: acquiring multi-source heterogeneous data of a blasting area through a multi-source sensor array and a geological modeling system, establishing a multi-modal data unified representation framework based on ontology, constructing a depth feature fusion network with physical constraints, developing a blasting parameter optimization-oriented mixed integer programming model, and establishing a blasting parameter optimization-oriented mixed integer programming model; integrating a multi-target genetic algorithm and an expert experience knowledge base to perform parameter optimization; according to the method, a multi-mode unified representation framework based on the ontology is constructed, millimeter-level space alignment and millisecond-level time synchronization of multi-source data are achieved through a space-time reference coordinate system and an improved DTW-B spline composite algorithm, the spatial resolution of blasting design is improved to the centimeter level, the time synchronization precision reaches the millisecond level, and the time synchronization efficiency is improved. Compared with a traditional method, the data utilization rate is increased by more than 40%, and a solid foundation is laid for fine blasting design.

The embodiment of the invention provides a BIM-GIS three-dimensional twin geological modeling method and system based on cognitive enhancement. The method is applied to the technical field of geological modeling, and comprises the following steps: acquiring different data sources to carry out geological data acquisition, and carrying out preprocessing to obtain preprocessed geological data; converting the geologic body into a voxel three-dimensional model according to the preprocessed geologic data; performing multi-level optimization processing on the voxel three-dimensional model, constructing an optimized model, and performing three-dimensional display; and performing mineral resource space distribution prediction according to the voxel three-dimensional model, predicting the position and the number of mineral resources in combination with historical exploration data and a convolutional neural network, and performing underground water flow simulation analysis in combination with an underground water flow model. In this way, by combining the BIM and GIS technologies, the three-dimensional geological data can be efficiently and accurately managed and displayed, and the method can be widely applied to the fields of geological exploration, mining development, urban construction and the like.

The invention relates to the technical field of geological exploration and three-dimensional modeling, in particular to a mining unmanned aerial vehicle high-precision three-dimensional geological modeling system which comprises a multispectral imaging acquisition module, a point cloud-image high-precision registration module, a geological feature fusion extraction module, a three-dimensional geological model construction module and a geological attribute visualization output module. Wherein the multispectral imaging acquisition module is used for acquiring registration image data and original point cloud data; the point cloud-image high-precision registration module is used for carrying out consistency matching and outputting a registration point cloud-image data set; the geological feature fusion extraction module is used for identifying geological boundaries and outputting geological feature vector data; and the three-dimensional geologic model construction module is used for generating a three-dimensional grid model with attribute topology. According to the method, through accurate three-dimensional modeling and lithology visualization, geological features and lithology information are efficiently combined, and reliable data support is provided for rock mass stability analysis.

The deep water port steel pipe pile foundation construction method comprises the steps that three-dimensional geological modeling and pile position positioning are conducted, specifically, a construction area is scanned through an unmanned aerial vehicle carrying a multispectral radar, geological data are obtained, a dynamic three-dimensional geological model is constructed based on a random forest algorithm, and the pile position layout and the pile sinking path of steel pipe piles are planned; multi-parameter data real-time collection and transmission: collecting perpendicularity, pile body stress and hammering vibration data in real time, uploading encrypted data to a cloud platform through a 5G / Beidou dual channel, and storing the encrypted data; the cloud platform calculates the optimal hammering energy, the vibration frequency and the hammer stopping standard by using a reinforcement learning algorithm in combination with the dynamic three-dimensional geological model and the real-time data; and pile sinking is conducted, specifically, the posture of a pile body is monitored through a laser radar and an inertial measurement unit, a PID control algorithm is adopted to drive a walking type pile driver hydraulic system, and pile sinking is conducted. According to the method, the scientificity of pile position layout and the reasonability of a pile sinking path are improved; the pile sinking efficiency is improved; the energy consumption is reduced; the pile foundation stability is guaranteed.

The invention provides a geophysical gravity and magnetic anomaly source model construction and rapid forward and reverse modeling method, and relates to the technical field of intelligent three-dimensional geological modeling and simulation. According to geological information of a research area, source body modeling parameters of a gravity and magnetic anomalous field are set for the research area, and a three-dimensional model matrix M capable of describing a plurality of underground anomalous bodies is obtained; constructing a fast forward modeling network, establishing nonlinear mapping from the three-dimensional model matrix to the simulated abnormal data through the fast forward modeling network, and calculating forward modeling response of the three-dimensional model matrix; and constructing an inversion network based on a concurrent module CFTBlock and combining a CNN and a Transform, and establishing nonlinear mapping from the gravity and magnetic abnormal data to a three-dimensional model matrix. The method has the advantages of fast and accurate forward modeling, high-resolution inversion and the like, and is suitable for better interpretation of actually measured gravity and magnetic data.

The invention provides a geological BIM modeling and engineering quantity calculation method based on point cloud sparse optimization, and relates to the technical field of geological engineering, and the method comprises the steps: obtaining high-resolution point cloud data through an unmanned aerial vehicle oblique photography technology, combining the high-resolution point cloud data with drilling exploration data, and carrying out the denoising, classification, segmentation, lithology discrimination and registration, thereby obtaining a point cloud point cloud model; a geological BIM model before excavation is constructed; area point cloud data are obtained again after excavation, the point cloud precision of the slope toe area is optimized through an inverse distance weighted interpolation algorithm, and a geological BIM model after excavation is generated; and in combination with a classified and optimized digital elevation model, detecting the elevation difference of the model before and after excavation pixel by pixel by adopting a robust elevation difference calculation method based on a neighborhood window, and accurately calculating the volume change of each lithologic region to obtain the engineering quantity. Through the point cloud sparse optimization and elevation change detection technology, the precision of the geological BIM model and the reliability of volume calculation are improved, and the method is widely suitable for geological engineering and earth volume calculation scenes.

The invention provides an urban groundwater inrush risk assessment method based on a three-dimensional grid model and an XGBoost algorithm, and belongs to the technical field of geological disaster early warning. The method comprises the following steps: acquiring geological, environmental and historical disaster data in real time through a multi-source heterogeneous data interface; constructing a heterogeneous grid unit based on three-dimensional geological modeling, and dynamically binding parameters such as underground water level, fault activity and lithologic permeability coefficient; an XGBoost algorithm is combined with second-order Taylor expansion to optimize gradient calculation, and a nonlinear risk assessment model is constructed through Bayesian hyper-parameter tuning and SHAP value feature interpretive analysis; identifying contiguous dangerous areas based on spatial autocorrelation analysis and an adaptive threshold segmentation algorithm; and a risk thermodynamic diagram, geological section superposition and real-time early warning are realized through a 3D GIS platform. According to the method, the problems that a traditional method depends on a linear model, data is single and local risk description is insufficient are solved, and the accuracy, efficiency and engineering practicability of risk assessment are remarkably improved.

The invention discloses a geological modeling, crack propagation and fluid-solid coupling production prediction integrated evaluation method, and relates to the field of multiple technologies, and the method comprises the steps: constructing a three-dimensional geological model of a deep shale gas reservoir; according to the construction model, the attribute model, the three-dimensional ground stress model and the rock mechanical parameter model, a hydraulic fracture model is constructed; based on the hydraulic fracture model and the three-dimensional geological model of the deep shale gas reservoir, establishing a fluid-solid coupling productivity simulation mathematical model of the deep shale gas reservoir; according to the fluid-solid coupling productivity simulation mathematical model of the deep shale gas reservoir, the fractured horizontal well yield of the shale gas reservoir is predicted, and a prediction result is comprehensively evaluated and optimized. According to the method, multiple links of geological modeling, fracture propagation simulation, fluid-solid coupling production prediction and the like are integrated, and the geological characteristics of the gas reservoir, the fracture propagation rule and the interaction between fluid flow and solid deformation are comprehensively considered, so that comprehensive evaluation and optimal development of the deep shale gas reservoir are realized.

The invention discloses a three-dimensional geological modeling method based on multi-source data, and particularly relates to the technical field of geological modeling. The method comprises the following steps: firstly, acquiring and preprocessing multi-source heterogeneous data including geological exploration, geophysics, remote sensing and drilling data, and carrying out cleaning, format unification and coordinate registration; performing semantic association, topological integration and uncertainty quantization processing on the data through a fusion rule to generate unified multi-source fusion data; then, an implicit or explicit modeling algorithm is adopted to automatically construct an initial three-dimensional geologic model, the model is optimized based on geologic law constraints such as geologic stack overlay and structural continuity, and a final model with reasonable geologic significance is generated; and finally, dynamically updating and maintaining the model through a version management and increment fusion technology. According to the method, efficient fusion of multi-source data and automatic model construction are realized, and the precision, reliability and updating efficiency of the three-dimensional geologic model are improved.

The invention relates to the technical field of hydraulic ring surveying and mapping, in particular to a hydraulic ring surveying and mapping data acquisition method and system based on geographic space information, and the method comprises the following steps: S1, data acquisition and preliminary data set generation: generating an initial geographic space data set; s2, space-time alignment and coupling feature extraction: constructing a preliminary geographic space model; s3, dynamic verification and cross verification: generating a dynamic verification parameter set; s4, three-dimensional geologic modeling and parameter fusion: generating a comprehensive three-dimensional geologic model; s5, environment interference correction and data optimization: analyzing the offset of an environment interference factor to sensor data through an adaptive learning algorithm, and outputting corrected hydraulic ring surveying and mapping data; and S6, safety threshold comparison and early warning map generation: generating a visual early warning map. According to the method, deep support is provided for underground structure analysis, and the comprehensive capability of hydraulic ring surveying and mapping is improved.

The invention belongs to the technical field of three-dimensional geological modeling, and discloses a real-time three-dimensional geological modeling system and method based on groundwater dynamics. The system comprises a geological data acquisition module, a complex geological structure modeling module, a geological body internal attribute simulation module, an underground water monitoring module, an underground water simulation module, a geological evolution simulation module, an underground water-geological body simulation module and a visual interaction module. By integrating multi-source data and applying advanced data cleaning and quality control technologies, the accuracy and consistency of the data are ensured, then by utilizing advanced geologic structure modeling and geologic body internal attribute simulation technologies, a high-precision three-dimensional geologic body model is constructed, and the accuracy and consistency of the geologic body model are improved. A reliable space frame is provided for dynamic simulation and analysis of underground water, and timely and accurate information support can be provided for water resource management and environmental protection. The method has a wide application prospect and an important practical value in the fields of dynamic monitoring, analysis and simulation of underground water.

The invention provides a coal mine digital twin geologic model construction method and system based on precise exploration, and relates to the technical field of coal mine geologic modeling, and the method comprises the steps: respectively obtaining ground static data, roadway dynamic data and coal mining real-time data; preprocessing the ground static data, the roadway dynamic data and the coal mining real-time data to obtain preprocessed data; integrating the preprocessed data, and constructing a three-dimensional dynamic geologic model according to the integrated data; dynamically updating the three-dimensional dynamic geologic model according to the coal mining real-time data so as to ensure the real-time performance and the accuracy of the model; according to the method, the three-dimensional dynamic geologic model is displayed through a three-dimensional visualization technology. Through multi-source data fusion and dynamic updating, transparent management of coal mine geological information is realized, and a powerful guarantee is provided for safe and efficient mining of a coal mine.

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 multi-source data fusion, in particular to a multi-source geological data processing method and system of a three-dimensional geological model.The method comprises the following steps that mountain landform and river valley images are obtained, gray frequency characteristics are extracted, a frequency energy gradient layer is constructed, a frequency continuous response area is screened to generate a structure boundary set, and a structure boundary set is constructed; the method comprises the following steps of: extracting a boundary normal vector by utilizing principal component analysis, identifying boundary sections with consistent directions, estimating a physical property parameter gradient direction, judging an included angle screening blocking region, generating a space attribute limiting layer, carrying out space alignment analysis on an overlapping region vector included angle, updating a boundary label, and generating an available attribute path structure set in three-dimensional geological modeling through a Dijkstra algorithm. According to the method, a conduction model is constructed through frequency domain decomposition and logarithmic transformation enhanced recognition, frequency window analysis noise reduction, principal component extraction vector analysis direction and center difference estimation, dynamic matching is promoted through alignment, a Dijkstra algorithm optimizes a path, and the geological model bedding characterization and conduction simulation precision is improved through cooperation of a multi-dimensional technology.

The invention relates to a landslide motion analysis method based on unmanned aerial vehicle remote sensing aerial survey and three-dimensional geological modeling, which comprises the following steps: acquiring high-resolution topographic data of a landslide hidden danger area by utilizing a laser scanner technology carried by an unmanned aerial vehicle, and calculating landslide instability failure ranges and stability coefficients under different scenes by utilizing finite element Geostudio software; and taking the stability coefficient as a reduction coefficient of a rock-soil body strength parameter, then determining the rock-soil body strength parameter under different scenes in discrete element PFC software, and realizing three-dimensional failure motion process analysis of the landslide under different scenes by using discrete elements. According to the invention, through PFC software, landslide occurrence scales under different rainfall and earthquake scenes and motion characteristics of landslides of different scales after instability can be compared; large deformation under the fluid-solid coupling condition can be effectively simulated, rock-soil body strength parameters under different rainfall (or earthquake) scenes can be determined, and the landslide three-dimensional motion process under different scenes can be carried out.

The invention relates to the technical field of underground water monitoring, in particular to an underground water dynamic monitoring multi-element early warning system based on data analysis, which comprises a data fusion acquisition module, a dynamic geological modeling module, a deep learning prediction module, a multi-level intelligent early warning module and an intelligent response decision module. Wherein the data fusion acquisition module is used for acquiring multi-dimensional data; the dynamic geologic modeling module is used for constructing a three-dimensional dynamic model of an underground water aquifer; the deep learning prediction module predicts the future change trend of the underground water level and the water quality; the multilevel intelligent early warning module is used for establishing a multilevel early warning mechanism; and the intelligent response decision module formulates corresponding underground water management and emergency response strategies. According to the invention, through real-time integration of multi-source data and combination of intelligent early warning and automatic management, the accuracy and response speed of underground water monitoring are significantly improved, and sustainable management and protection of underground water resources are effectively supported.

The invention relates to the technical field of accurate calculation of mining quantity, in particular to an intelligent accurate calculation system of mining quantity based on a three-dimensional geologic model, which comprises a multi-source heterogeneous data acquisition module used for acquiring and preprocessing various data such as geologic structure and mineral distribution; the dynamic three-dimensional geologic modeling module constructs a digital geologic model; the precise reserve calculation module calculates exploitable reserves; the intelligent mining planning module is used for generating a mining path optimal solution set by adopting a hybrid taboo genetic optimization algorithm and evaluating the mining efficiency and the safety risk; the resource collaborative scheduling module is used for establishing a multi-objective optimization model of the equipment-personnel-transportation system by using a space-time constraint particle swarm optimization algorithm; and the visual decision support module supports real-time simulation and adjustment of the mining scheme through a WebGL three-dimensional visual engine and an AR interactive interface. According to the intelligent mining method, accurate calculation of the mining quantity and intelligent mining are achieved, the mining efficiency is improved, safety is guaranteed, resource allocation is optimized, and economic benefits are improved.

The invention provides a coal mine high-precision three-dimensional geological modeling method and system based on multi-source heterogeneous data fusion, and relates to the technical field of coal mine geological modeling. The method comprises the following steps: establishing a unified semantic reference system and a time-space coordinate reference, and generating an alignment anchor point set; mapping the multi-source observation data to form an alignment feature set and calculating a source weight; according to a multi-evidence consistency rule and geomechanical prior inversion, a discontinuous geological structure is obtained; constructing an implicit stratigraphic function and applying a boundary jump condition to solve a stratigraphic boundary set; and taking the stratum boundary as a framework, and executing anisotropic joint estimation to obtain a property distribution model and an uncertainty result. According to the method, integrated modeling of the geological structure and the property of the complex structure area is achieved, and the precision, the stability and the credibility of the three-dimensional geological model are remarkably improved.

The invention discloses a cast-in-situ bored pile digital construction control method which comprises the following steps: S1, collecting historical data, and establishing a cast-in-situ bored pile construction information database; s2, geological modeling is established, and a pile hole area three-dimensional stratum and soil layer distribution corresponding to all pile holes are generated in a fitting mode; s3, according to the cast-in-situ bored pile construction information database, finding out average construction efficiency and cost data under various hole forming processes of similar stratums in various stratums of a pile hole area, and calculating the construction period and cost of different hole forming processes of a single pile for construction management personnel to select the hole forming processes and equipment specifications; s4, monitoring early warning and auxiliary decision making in construction; and S5, post evaluation analysis. According to the system and the method, key construction parameters of the bored pile are automatically monitored by relying on core construction equipment and devices, the production dynamic state of the bored pile is visually displayed through online monitoring and early warning of the key parameters by the system and the platform, a friendly interactive interface is provided for operators, and construction parameter selection is assisted.

The invention provides a sedimentary body lithology identification system and method for oil-gas exploration, and the system comprises a data collection module which is used for collecting seismic data and logging data; the data processing module is used for preprocessing the seismic data and the logging data; the data fusion module is used for fusing the preprocessed seismic data, logging data and a geologic model to generate a comprehensive data set; the lithology identification module is used for analyzing the comprehensive data set by using a machine learning algorithm and identifying the lithology type of the sedimentary body; the result verification module is used for performing comparison verification on the identification result and actual core analysis data; and the display module is used for visualizing the recognition result. The system provided by the invention not only can identify the lithology of the sedimentary body, but also can generate a visual three-dimensional lithology distribution diagram through three-dimensional geological modeling and a visualization technology. The visualization results enable geologists and engineers to clearly understand the underground structure and lithologic distribution so as to make more accurate exploration decisions and development plans.

The invention discloses a refined fourth-century three-dimensional geological modeling integration method which comprises the steps that basic geological data and drilling data of a research area are acquired, and the basic geological data comprise bedrock geological data and fourth-century geological data; the drilling data is modeled by a triangulated irregular network, and the basic unit of the triangulated irregular network is GTP; performing standardization processing on the drilling data; carrying out fourth stratigraphic division on the research area according to the basic geological data; dEMs of stratum interfaces are sequentially established from the earth surface to the underground according to the drilling data, sewing processing is conducted on the adjacent DEMs belonging to the same stratum, and a three-dimensional stratum model based on the multiple layers of DEMs is formed; dividing the GTP into TEN, and according to the three-dimensional stratum model based on the multilayer DEM, taking the TEN as a basic voxel, and constructing a fourth-century three-dimensional geologic model based on MD-GTP-TEN; the model constructed by the invention can express the geologic body more accurately and perform spatial analysis more efficiently.

The invention relates to a large-scale offshore engineering geologic model modeling system and method, and relates to the technical field of offshore engineering geologic investigation and modeling. According to the method, through the steps of multi-source data acquisition, preprocessing, fusion, three-dimensional geological modeling, model optimization, dynamic updating, visual analysis and the like, large-scale geological survey data can be efficiently processed, a high-precision three-dimensional geological model is generated, and dynamic updating and visual analysis are supported. The method has the advantages of high efficiency, high precision, real-time performance, engineering applicability and the like, and is suitable for geological modeling and geological condition analysis of engineering such as offshore wind power, submarine pipelines, ocean platforms and the like.

The invention relates to the technical field of data processing, and provides an unmanned aerial vehicle-mounted LiDAR geological modeling and intelligent blasting parameter optimization system, which is characterized in that a laser point cloud and a multispectral image are deeply correlated through a data acquisition module based on a tight coupling algorithm, the sampling quality of a point cloud data set is evaluated, and a supplementary flight instruction is judged and generated; a complete data source is provided for subsequent geological modeling; the geological modeling module divides the point cloud data set through an adaptive threshold algorithm to identify rock mass structural surfaces, analyzes a spatial topological relation of the rock mass structural surfaces based on a graph neural network, performs clustering to form a control structural surface group, and associates the control structural surface group with spectral features through a convolutional neural network to cooperatively discriminate rock mass properties; geological indexes of the three-dimensional geological model are extracted through a parameter optimization module, blasting parameters are generated after genetic algorithm processing, the blasting effect is judged through laser point cloud obtained again after blasting and change characteristics are extracted, the parameters of the genetic algorithm are reversely adjusted, and the three-dimensional geological model is updated.