157 results about "Geological analysis" patented technology

The invention provides a rock image classification method based on edge enhancement and multi-scale feature fusion. By combining the edge enhancement and multi-scale feature fusion technology, the accuracy of mineral classification in the rock slice image is remarkably improved. According to the method, rock slice image interference is eliminated through filtering and denoising, and mineral particle edges are enhanced by fusing morphological top-hat transformation and a Laplace operator; and performing multi-scale pyramid decomposition on the enhanced image to extract high-frequency information, performing multi-direction response enhancement to generate a direction feature map, and performing channel-level fusion on the original image, the edge enhanced image and the direction feature map. And finally, inputting the fused image into a convolutional neural network to complete rock type classification. According to the method, mineral boundary expression is effectively enhanced, the classification accuracy is improved, and a reliable technical scheme is provided for geological analysis and lithology identification.

The invention relates to the technical field of geological analysis, in particular to a weathering crust reservoir fracture distribution intelligent identification system which comprises a fracture trend path construction module, a shielding extension fracture interpolation module, a cross-layer fracture directional connection module, a structural fracture space collection module and a fracture trend joint density analysis module. According to the method, directional connection of cross-layer cracks is achieved through joint judgment of three-dimensional space coordinates of the crack end point, the direction vector included angle and the ground plane normal included angle, the precision and reliability of a crack through structure are effectively improved, space distribution clustering of the cracks is achieved through statistics of the number of times of intersection of the structural unit cracks, concentration degree calculation and comparison of the concentration reference value, and the reliability of the crack through structure is improved. And combined with fracture path length, azimuth angle data and fracture quantity density statistics, combined density value calculation and integration of fracture trend and length weighting are constructed, so that reservoir fracture structure prediction precision and spatial positioning definiteness are greatly improved.

The invention relates to the technical field of geological analysis, and discloses a method for fusing a three-dimensional geological model and a WebGIS (Web Geographic Information System), aiming at solving the problems of poor data intercommunity, limited spatial analysis capability, difficulty in real-time updating and low model loading efficiency of the existing method, and the scheme mainly comprises the following steps: extracting geological model data, and carrying out standardized format processing; lightweight processing is carried out, and geological attributes and model nodes are bound one by one; the format is converted into a binary format embedded with a metadata label, and data integrity verification and automatic error correction are carried out in the conversion process; constructing a non-uniform adaptive octree spatial index, a multi-level attribute data architecture and a real-time updating mechanism of attribute data; after the geological model and the terrain are precisely registered and fused, a dynamic loading mechanism, a high-performance rendering mechanism and a geological model real-time updating mechanism are constructed, and a three-dimensional geological analysis tool is integrated. According to the method, efficient loading, real-time rendering, dynamic updating and spatial analysis of the three-dimensional geologic model in the WebGIS are realized.

The invention relates to a geological analysis technology, and discloses a multi-head attention model training method fused with geological rules, which is used for improving the scientificity and accuracy of geological body model prediction and improving the interpretability of a geological analysis process. According to the scheme, firstly, feature vectors of geological attribute data and geological coordinate data are spliced to obtain a fusion feature vector, then spatial locality and directivity are considered at the same time, geomorphic multi-head attention calculation is conducted on the fusion feature vector, and an attention feature sequence is obtained; then extracting multi-scale features from the input geological map, constructing a cross-fault weight mask matrix based on fault constraints, and obtaining comprehensive features through fusion; calculating a loss value by adopting a joint loss function containing prediction loss and fault non-penetrability constraint terms, and updating model parameters through a back propagation algorithm to complete model training; and finally, drawing an attention thermodynamic diagram for visual display, and superposing the attention thermodynamic diagram with the three-dimensional geologic model.

The invention relates to the technical field of wind power road geological analysis, in particular to a three-dimensional geological modeling and section visualization method and system for wind power road construction. The method comprises the following steps: establishing a geological drilling data matrix through geological drilling data; extracting geological attribute data through lithology analysis, calibrating the relationship of each stratum through sequence analysis, constructing a standardized geological drilling data set, constructing a spatial continuous geological attribute scalar value distribution model through a Gaussian process interpolation algorithm, and constructing an implicit function by taking the geological attribute scalar value distribution model as the implicit function. And generating a three-dimensional geologic model through a contour surface extraction algorithm, carrying out geologic attribute scalar value extraction on the three-dimensional geologic model based on the road route data, generating wind power road profile data, and visualizing a data result. An efficient and low-cost solution is provided for geological judgment and optimization in wind power plant road design, the requirements for accuracy and high efficiency of engineering projects are met, and reliable guarantee is provided for wind power road construction.

The invention discloses a method and a system for constructing a multi-level geologic structure model based on electromagnetic detection, and the method comprises the steps: transmitting electromagnetic signals with different frequencies at all measurement points through an electromagnetic detector, carrying out the resistivity inversion through apparent resistance and impedance phase, obtaining a geologic electrical structure, dividing non-uniform and uniform electrical geology based on electromagnetic static displacement, and obtaining a multi-level geologic structure model. Analyzing an orthogonal component magnetic field to obtain an electromagnetic response parameter and a polarization ellipse parameter; determining an electric field diffusion curve; obtaining an electric field distribution model through finite difference method inversion; deducing underground geological spatial form and distribution law; and finally, calculating an electromagnetic response curved surface to obtain a two-dimensional profile curve, and performing three-dimensional reconstruction to obtain a multi-level geologic structure model. The method not only can improve the precision and reliability of the structure model, but also has good interpretability, and can be directly applied to a construction system of a multilevel geological structure model based on electromagnetic detection.

The invention belongs to the technical field of coal bed gas mining, and particularly discloses a multi-coal-bed mining optimization control method based on crossheading position stability, and the method comprises the steps: comprehensively obtaining parameters such as coal bed spacing, thickness, inclination angle, roof and floor lithology and fault distribution, and generating an accurate three-dimensional geologic model through three-dimensional modeling software; and the condition of incomplete geological analysis of a traditional method is changed. And on the aspect of crossheading arrangement, empirical operation is replaced with finite element analysis, the anchor rod distance and the support density are accurately determined, and safety and economical efficiency are improved. The mining sequence planning is changed from dependence on a fixed rule to establishment of an identification model combined with a genetic algorithm, and dynamic optimization is realized. The mining height, the mining width and the advancing speed are flexibly regulated and controlled according to the mapping relation table in the mining process, and real-time dynamic adjustment is achieved. Meanwhile, the early warning mechanism calculates scores based on crossheading stress data, is more accurate and sensitive, and has higher pertinence and effectiveness.

The invention discloses a seismic first arrival wave pickup method and device based on a multi-input attention mechanism network, multi-domain data and multiple network advantages are fused to realize first arrival automatic pickup, and compared with manual pickup, the efficiency is greatly improved, and the result is more objective; compared with a traditional automatic pickup method, the method is higher in precision and stability under different signal-to-noise ratios. Meanwhile, through hyper-parameter optimization, the generalization ability is high, reliable data can be provided for subsequent seismic processing, the advantages are outstanding under complex geological conditions, and the method is of great significance to geological analysis and resource exploration.

A geological analysis system, device, and method using x-ray fluorescence and spectroscopy are provided. The geological analysis system includes a sample tray which holds the geological sample materials, and sensors including an X-ray fluorescence (XRF) unit and spectrometer. The sample tray includes chambers formed in an upper surface, ports, and passages, each providing communication between an interior of a chamber and an interior of a port. The ports are configured to be attachable to vials. The system positions the sample tray with respect to the sensors for sensing one or more properties of geological sample materials in the sample tray.

The invention discloses a mine geologic structure analysis and safety assessment method based on image processing, relates to the technical field of mine geologic analysis and assessment, and provides the following scheme: obtaining analysis image information of a mine slope, including confidence coefficients of crack probability, non-crack probability, regional deformation probability and internal damage probability; dividing the image into fixed-size areas and carrying out smoothing processing, and obtaining candidate areas after removing low-confidence areas; taking a confidence coefficient difference value between the crack and the non-crack as an evaluation index, and screening a target area; determining low, medium and high risk levels according to comparison results of the deformation and damage probabilities and corresponding threshold values; and generating and executing a reinforcement scheme for the high-risk area, obtaining an image calculation evaluation index again, and iteratively adjusting the scheme until conditions are met. According to the method, comprehensive risk layering evaluation of surface and internal damage is realized, and the safety and long-term stability of the slope are improved through dynamic optimization processing.

The invention belongs to the technical field of geological analysis, and discloses a ground subsidence analysis method and device, and the method comprises the steps: matching a sensor layout strategy corresponding to a foundation subsidence risk and meteorological data of a monitoring region; acquiring land subsidence data of the monitoring area according to a sensor; performing time-frequency analysis on the land subsidence data to obtain a geoacoustic spectrogram corresponding to the land subsidence data; inputting the geoacoustic spectrogram into a preset neural network, and outputting a settlement semantic vector corresponding to the geoacoustic spectrogram; acquiring and analyzing historical land subsidence data, and constructing a subsidence rule corresponding to the historical land subsidence data; and inputting the settlement semantic vector and the settlement rule into a preset space-time analysis model, and predicting to obtain a future settlement trend of the monitored area. By using the method disclosed by the invention, the problem that all risks in a certain area cannot be checked when geological data is monitored based on local monitoring points can be solved, and the problem that the geological risk analysis efficiency is relatively low can be solved.

The invention discloses an intelligent ore mining control method and system based on machine learning, and relates to the technical field of mining intelligentization, and the method comprises the steps: building a mining area geologic model based on a convolutional neural network model and a support vector machine model, inputting an ore body geologic feature map into the mining area geologic model, and generating a geologic analysis report; fusing the ore body geologic feature map and the geologic analysis report through a Bayesian updating method to obtain a geomechanical map; through a data fusion technology and a real-time analysis algorithm, a geomechanical map and mining area real-time monitoring data are combined, ore mining risk factors are analyzed, and an ore mining strategy is dynamically adjusted to generate an optimized ore mining instruction. The mining area geological environment data is converted into high-quality graph database nodes and edges, and key geological features are identified by using a complex network analysis technology, so that the ore extraction efficiency, safety and scientific decision-making capability are remarkably improved.

The invention provides a comprehensive advanced geological forecasting method for an ultra-deep vertical shaft of a metal mine, and belongs to the technical field of water prevention and control in construction of the ultra-deep vertical shaft of the metal mine. The conditions that a tectonic fracture zone, a high confined aquifer and the like possibly exist in the deep stratum, have construction hidden dangers and are prone to causing water burst disasters are accurately recognized, and the advanced detection precision of the deep stratum of the shaft is improved; meanwhile, a feedback forecasting process of geological analysis-geological modeling-geophysical prospecting circle target-drilling verification is formed, a multi-level verification system is constructed, the specific geological condition of an abnormal area is clearly detected, and the advanced positioning and judgment accuracy of a geological abnormal body in a deep stratum is remarkably improved; and by integrating and fusing multi-source geological information, the geological abnormal body information is comprehensively analyzed and judged, so that the requirements of deep rock mass mechanical property analysis and water inrush disaster prevention and control are met.

The invention discloses a mine water sealing layer stability evaluation method based on micro-seismic monitoring, and belongs to the field of mine water sealing layers. The invention discloses a mine water sealing layer stability evaluation method based on micro-seismic monitoring. The method comprises the following steps: S1, identifying a mine water sealing layer area; s2, monitoring the mine water storage area in real time; s3, determining the spatial distribution density and the energy accumulation trend of the micro-seismic events; s4, analyzing the micro-seismic event clustering characteristic and the evolution law of water seal reservoir rock mass fracture; and S5, obtaining a stability evaluation result of the mine water sealing layer. The problem that cross-regional environmental disasters such as water inrush or surface collapse are easily caused in the prior art is solved, the accuracy and reliability of data are ensured, geological analysis and prediction can be more deeply carried out, damage to the environment and cost input are reduced, the activation rule of a hidden structure and the fracture depth of a bottom plate are effectively monitored, and the monitoring accuracy and reliability of the hidden structure are improved. Therefore, the water inrush risk can be predicted and forecasted.

The invention provides a rock slice detail identification and slice text description generation method, and relates to the technical field of geological analysis. On the basis of constructing a picture and corresponding text description database under the rock polarizing microscope, matching the image under the rock polarizing microscope with a rock name, a mineral composition and a polarizing microscope type by utilizing a fine-tuned CNCLIP contrast learning network; and a text generation model is combined to directly generate slice description from the picture under the rock polarizing microscope. By adopting the method disclosed by the invention, the organization, classification and identification of the rock picture data under the polarizing microscope can be effectively realized, the rock slice image under the microscope can be directly read by the method constructed by the invention, and the content in the picture is matched with the rock name, the mineral and the polarizing microscope type; and on the basis, a text generation model is combined, and finally, the function of automatically carrying out text description on the image under the rock polarizing microscope is realized.

The invention discloses a three-dimensional geologic modeling level exploration system, belongs to the technical field of three-dimensional modeling, and aims to solve the problem that accurate evaluation of mineral resource reserves is affected due to the fact that fine morphological changes of an ore body are difficult to accurately present by a traditional method. Mesh subdivision adopts an improved algorithm, grid adaptive adjustment is realized according to physical properties of a geologic body, the expression ability of a model to a complex geologic structure is greatly improved, an attribute assignment unit accurately connects and fuses data and a grid unit and endows the data and the grid unit with real physical attributes, so that the model is more practical, and a dynamic updating unit analyzes by means of a time sequence, so that the dynamic updating efficiency is improved. Time dimension is fused, a model is updated in real time, geological dynamic changes are reflected, the problem of traditional updating lag is solved, the geological analysis unit utilizes multiple methods, volume, trend, inclination angle and resource distribution prediction quantitative data are output for geological research, deep analysis of geological conditions is assisted, and the dilemma that a traditional analysis function is single is overcome.

The invention relates to the technical field of tunnel monitoring, and discloses an advanced monitoring method and system based on an existing tunnel, and the method comprises the steps: obtaining a proper hole measurement position, depth and direction according to an analysis result; monitoring the displacement and stress change of the surrounding rock in real time, and analyzing according to the monitored surrounding rock data to obtain surrounding rock parameters such as elastic modulus, Poisson's ratio, friction angle and cohesive force of the surrounding rock; and the geological analysis system analyzes the unfavorable geologic body, and starts the advanced horizontal equipment for detection and verification. The system comprises an existing tunnel data acquisition module, an existing tunnel data calculation module and a geological forecast scheme module. Through the combination of the geological analysis system and the detection equipment, the state of the unfavorable geologic body can be more accurately judged, and the reliability of geological forecast is improved; early warning is given out in time, the construction scheme is adjusted, collapse, water burst and other disasters caused by unfavorable geologic bodies are effectively avoided, and construction safety is ensured.

The utility model provides a sample storage box for geological analysis of a deep-buried rock mass. The sample storage box comprises a shell cover; the storage bin is formed in the shell cover; the bin cover is rotationally connected to the top end of the shell cover; the storage mechanism is arranged in the shell cover; and the reset clamping mechanism is mounted on the side wall of each storage unit and is used for enabling the movable plate to automatically reset after the movable plate is opened and keeping the sealed connection between the movable plate and the storage groove. According to the sample storage box, the sealing cover can be used for shading and preventing dust, the sealing cover can be stretched so that samples can be stored and taken out conveniently, the samples can be stored and taken out more easily through rotation opening of the movable plate, the use convenience of the storage box is improved, and meanwhile the protection performance on the samples is improved. By arranging a reset clamping mechanism, the safety and the shading and dustproof performance of the sample storage box in the transportation process are further improved; and through the arrangement of the heat preservation mechanism, the device has a heat preservation transportation function, and the use functionality of the sample storage box can be greatly improved.

The invention discloses a time sequence sparse and dynamic feedback multi-modal large model reasoning method, which improves model analysis precision and processing efficiency through a sparse sampling strategy and a dynamic feedback reasoning mechanism, and effectively solves key challenges in deep sea geology video analysis. The method comprises the following steps: constructing a structured image-text data set by integrating multi-source ocean data, and constructing a three-level labeling system; the method comprises the following steps: based on a multi-modal large model architecture, performing parameter optimization on a Transform core module by adopting an LoRA technology; a time sequence sparse sampling and dynamic feedback reasoning mechanism is designed, context frame management is realized through a sliding window and a bidirectional queue, the calculation complexity is reduced in combination with a sparse sampling strategy, and the time sequence reasoning consistency is enhanced by using a historical prediction result. Through collaborative innovation of multi-modal data processing, efficient model optimization and an intelligent reasoning mechanism, synchronous improvement of deep sea geology analysis precision and efficiency is realized, and a reliable intelligent scheme is provided for marine geology research.

The invention discloses a muck intelligent processing method combined with tunnel advanced geological prediction. The muck intelligent processing method comprises the following steps: acquiring a seismic wave training set; carrying out geological analysis on muck categories in the seismic wave training set, obtaining dynamic calculation parameters and physical data corresponding to each muck category, and enabling the seismic wave features to correspond to the dynamic calculation parameters and the physical data to obtain an updated seismic wave training set; training a neural network by using the seismic wave training set to obtain a muck prediction processing model; acquiring real-time geological forecast data, preprocessing the real-time geological forecast data, inputting the preprocessed real-time geological forecast data into the muck prediction processing model, and outputting a muck type through the muck prediction processing model; and in combination with the working state of the shield tunneling machine and the geological forecast, a muck treatment suggestion is generated so as to treat muck generated in the shield tunneling construction process. According to the method, the type of the muck generated during tunnel excavation can be predicted in time, and the prediction timeliness is improved.

The invention discloses an automatic geological rock coring device, which relates to the technical field of geological rock sampling and comprises a coring base part, a plurality of self-adaptive core clamping devices, a telescopic coring drill bit device and an automatic controller based on a chip. According to the automatic coring device for the geological rock, multi-degree-of-freedom movement of a coring tool in space is achieved through the structure of the multiple self-adaptive core clamping devices and the telescopic coring drill bit device. The coring device can flexibly adjust the coring position, meets coring requirements under different stratum conditions, and particularly has remarkable advantages in complex geological structure areas. The self-adaptive core clamping device can carry out self-adaptive clamping according to the size and shape of the rock core, mechanical damage to the rock core is avoided, the integrity of the rock core is improved, and a more reliable sample is provided for subsequent rock physical property testing and geological analysis. Due to the design of the three-stage insertion type clamping jaw part, self-adaptive adjustment can be carried out according to the actual size and shape of a rock core.

The invention discloses a weak texture scene image and point cloud data fusion method based on a DMF-Net, and the method proposes that the DMF-Net guided by a single-view image is combined, is used for the deep fusion of an image and point cloud data, enhances the feature expression in a weak texture scene, and completes a cross-modal point cloud completion task through a DMF-Net frame. Two stages of rough point cloud generation and upsampling from rough to fine are realized, a 3D encoder and a 2D encoder are utilized to extract point cloud and image features respectively, features of two modes are integrated through a dual-channel mode fusion module, global feature vectors are generated and are interpreted into initial rough point cloud, and complete three-dimensional point cloud can be obtained after optimization. Therefore, the fusion of the weak texture scene image and the point cloud data is realized, the limitation of the weak texture scene is effectively overcome, and the precision and robustness of downstream tasks such as three-dimensional reconstruction and geological analysis are remarkably improved.

The invention discloses a quarry slope radar monitoring system, relates to the technical field of quarry radar monitoring and processing, and aims to solve the problem of influence of dust and vibration on slope radar detection images by collecting dust information in air, dynamically adjusting radar transmitting power and enabling pre-corrected signals to enter an imaging algorithm. The method is advantaged in that image definition and identifiability are substantially improved, accurate image data are provided for subsequent geological analysis, safety monitoring and other work, vibration acceleration data are acquired, a piezoelectric ceramic micro-actuator is driven to cooperatively offset instant vibration, and the radar equipment can be effectively protected even under the condition that the radar equipment is influenced by vibration. And the generated slope radar image can still maintain relatively high geometric accuracy and phase accuracy, so that the image truthfully reflects the real form of the slope, and a reliable basis is provided for slope stability evaluation.

The invention discloses a rock slice image component identification method based on deep learning. According to the method, a data set is constructed through PCA dimension reduction and normalization, segmentation parameters are generated by utilizing ResNet50 and a self-attention mechanism, automatic classification of quartz, rock debris, kaolinite, pores and matrixes is realized by combining a VGG16 model, two-stage segmentation is performed by adopting AGLFIF and Otsu algorithms, and high-precision identification and geological analysis automation of rock slice images are realized. According to the method, real-time component identification of the rock slice image can be realized, and automation and reliability of geological analysis are improved.

The invention discloses a generalized finite difference scalar wave unfavorable geology frequency dispersion analysis method and related equipment, relates to the field of unfavorable geology analysis, and mainly aims to solve the problem that the conventional unfavorable geology analysis is relatively low in flexibility and accuracy. The method comprises the following steps: generating field nodes of a target area; performing field variable approximation on the field nodes to determine a discretized wave equation; and performing frequency dispersion analysis and wave field simulation based on the discretized wave equation to obtain an output result of unfavorable geology. The method is used for the unfavorable geological frequency dispersion analysis process of the generalized finite difference scalar waves.

The present invention discloses a method and device for geological analysis of water terrain based on remote sensing technology. The method comprises: collecting a water image set consisting of multiple water images detected by a remote sensing detection terminal, the water image set being used to prepare a training set for a water analysis model; extracting the target water image from the multiple water images when it is determined that a target water image has a water area occupancy rate higher than an occupancy rate threshold among the multiple water images; reducing the occupancy rate of the water area of ​​the target water image according to a preset rule so that the occupancy rate of the water area of ​​the target water image is no higher than the occupancy rate threshold; inputting the water image set after the rate reduction process into a preset neural network for training to obtain a water analysis model, and analyzing the geology of the water terrain using the water analysis model. The present invention solves the problem of low accuracy in geological analysis of water terrain in the prior art.

This invention provides a method for characterizing sedimentary microfacies distribution based on comprehensive geological and seismic analysis. By studying the sedimentary environment and surrounding tectonic background of the entire block, this invention calculates the cumulative percentage of channel and shoal body types based on sedimentary microfacies and grain size analysis. Based on a comprehensive analysis of the lithofacies of drill cores and corresponding well logging curves and seismic response characteristics, it establishes a comprehensive response model of the main sedimentary facies-well logging facies of the target stratigraphic group in the study area. Furthermore, based on the fusion of seismic attributes, it characterizes sand bodies in seismic profiles. By integrating the sand body characterization results, the comprehensive response model of sedimentary facies-well logging facies, and the sedimentary microfacies types, a method for characterizing sedimentary microfacies distribution in tight sandstone reservoirs using comprehensive seismic and geological analysis is established.

This invention relates to the field of geophysical exploration and oil and gas geological analysis technology, and discloses a method for predicting fractured reservoirs in carbonate buried hills based on geological guidance and multi-scale fusion. The method includes: constructing a three-dimensional geological guidance constraint body using paleogeography and fault systems as geological priors; characterizing the fracture response mechanism using Gabor wavelet frequency division and structural tensor; constructing sensitive attributes and predicting the fracture body using a multi-branch convolutional neural network that fuses multi-source seismic attributes; and calculating the fracture complexity index based on the predicted fracture body to classify and zone the buried hill fractures. This invention introduces geological guidance constraints to improve the geological consistency of the prediction results; utilizes multi-scale Gabor frequency division and structural tensor analysis to achieve multi-scale fracture characterization; enhances model interpretability and prediction accuracy by fusing multi-source attributes through a multi-branch convolutional neural network; and achieves quantitative reservoir classification through the fracture complexity index, effectively guiding well location deployment and drilling decisions.

The invention provides an underground cavern group geological analysis method based on a TGS technology and a CT technology, and the method comprises the steps: scanning the geological conditions of an underground cavern group in the horizontal direction through the TGS technology, and obtaining first geological data in the horizontal direction; forecasting the geological conditions of the underground cavern group in the vertical direction through a CT technology to obtain second geological data in the vertical direction; fusing the first geological data and the second geological data to generate a three-dimensional geological model; based on the three-dimensional geologic model, identifying the position and the distribution range of unfavorable geologic bodies in the underground cavern group, and analyzing the geological characteristics of the surrounding rock to obtain an analysis result; according to the analysis result, the spatial distribution information of the unfavorable geologic body and the corresponding geological phenomenon description are output, the misjudgment risk caused by data discontinuity of a traditional method is overcome, and the recognition capacity for complex geological phenomena such as inclined strata and cross fractures is improved.

The application discloses a kind of based on microseismic crack face construction and seepage evaluation method, belong to geological analysis technical field.Use hydraulic fracturing to the detection area, the microseismic source position identification generated by rock mass rupture;Determine the best fitting crack plane from the clustered microseismic source position, extract the spatial orientation information of hydraulic fracturing induced crack;Reconstruct the spatial distribution range of hydraulic fracturing induced crack in the plane, obtain the induced crack geometry of limited scale;Discretize the geometry of induced crack face, construct a simplified hydraulic fracture plane at the perforation location and discretize, form the crack geometry set containing induced crack and hydraulic fracture;Embed the crack geometry set containing induced crack and hydraulic fracture into the rock geometry model, carry out reservoir seepage simulation under real working conditions, quantitative evaluation.It is simple in steps, convenient to use, and has good imaging effect.