118 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 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.

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 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 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 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 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.

The invention relates to the technical field of granite sampling, in particular to a granite sampling device convenient to discharge and a sampling method. Comprising a sampling pipe and a rock core inner pipe, the sampling pipe is formed by splicing a first splicing pipe and a second splicing pipe, the sampling pipe is provided with the rock core inner pipe used for collecting a rock core, and one end of the rock core inner pipe is provided with a discharging port used for discharging of the rock core. The sampling pipe is formed by splicing the first splicing pipe and the second splicing pipe, the stability of the sampling pipe is ensured through cooperation of the clamping rod and the arc-shaped groove, in the discharging process, the rock core inner pipe extends into the sampling pipe for discharging, then the rock core inner pipe is driven by the vibration motor to vibrate, rock cores can sequentially fall into the sampling pipe, and the sampling efficiency is improved. Therefore, an operator can conveniently unload the rock core, the working efficiency is improved, the problems of mixing and sample omission during traditional rock core unloading can be avoided, the integrity and the original sequence of rock core samples are effectively guaranteed, and a reliable basis is provided for subsequent geological analysis.

The invention relates to a geological data acquisition and analysis method based on an urban geological database, and the method comprises the steps: obtaining an urban geological database which stores the geological data of a plurality of stratums and the characteristics of the stratums; according to the geological data of the plurality of stratums of a pre-constructed geological database and a preset stratigraphic division standard, obtaining standard layers corresponding to the plurality of stratums of the geological database; performing prediction model training according to the geological data of each standard layer to obtain a bearing capacity prediction model corresponding to each standard layer; collecting target geological data of the target stratum; and performing geological analysis on the target stratum according to the target geological data, geological data stored in the geological database and the bearing capacity prediction model to obtain stratum characteristics and predicted bearing capacity of a standard stratum corresponding to the target stratum, the accuracy and efficiency of characteristic analysis and bearing capacity analysis of geological data can be improved.

The invention relates to the technical field of detonation control, in particular to an electronic detonator network synchronous detonation control system and method based on topological optimization. The method comprises the steps that information of a to-be-blasted area where electronic detonator network topological nodes are located is collected, and inter-hole delay of the to-be-blasted area and the optimal explosive loading amount of blast holes are determined based on blasting vibration prior data; geological analysis calculation is conducted on the geological parameter data to obtain a stability index of the to-be-blasted area, and an explosion performance index is obtained through calculation based on the optimal explosive loading amount of the blast hole and the initial explosion source depth of the to-be-blasted area; whether the number of topological nodes of the to-be-blasted area is adjusted or not is judged based on the explosion performance index and the stability index, so that a detonation control scheme is generated; and the detonation control scheme is executed to execute synchronous detonation control of the electronic detonator, the detonation effect can be optimized, the synchronous detonation accuracy of the electronic detonator can be improved, it is ensured that the detonation effect meets the expectation, and meanwhile construction safety is guaranteed.

This invention relates to the field of tunnel construction technology, and more particularly to a system and method for dynamically optimizing tunnel construction parameters based on geological information from point cloud data. At multiple monitoring time points, point cloud data is collected from the tunnel segment to be constructed, obtaining multiple point cloud datasets. The tunnel segment is divided into multiple construction areas, and multiple regional point cloud datasets are obtained from these datasets. Point cloud change analysis is performed on each regional dataset to obtain multiple point cloud change rates. Based on these regional point cloud datasets, reflection intensity analysis is conducted to obtain multiple reflection intensity coefficients. Combined with the multiple point cloud change rates, geological analysis is performed to obtain the distribution of concealed geological information. Based on this distribution, tunnel construction parameters are dynamically optimized to obtain optimized tunnel construction parameters for tunnel construction. This achieves the technical effect of improving the efficiency and safety of tunnel construction while reducing construction risks and costs.

The invention belongs to the technical field of foundation pit engineering construction monitoring, and provides a model training method and a rock slag feature extraction method and device for solving the problems that rock slag feature extraction precision is low and rock slag color features are not considered. According to the method, based on a YOLO11n-seg improved model fusing MSFEM and a TripleGD-Neck mechanism, through multi-scale space-frequency feature joint enhancement and cross-layer information interaction, the segmentation precision of rock slag particles is improved, and automatic and high-precision analysis of particle size distribution is realized. According to the method, a rock slag area is extracted by using a mask obtained after segmentation of a YOLO11n-seg improved model, geometric particle size parameters of the rock slag are calculated, and color features of the rock slag are obtained, so that richer surrounding rock information is provided, and powerful data support can be provided for further geological analysis.

The invention relates to the technical field of three-dimensional modeling, in particular to a VTK-based three-dimensional geological section model generation method, system and device and a medium. The method comprises the following steps: firstly, acquiring original drilling data, performing nested storage according to the position of the original drilling data on an exploration line, and performing cleaning and multi-dimensional sorting to obtain structured drilling data; extracting ore bed boundary points from the structured data, constructing a local adjacency graph, and calculating a comprehensive regularity score of each quadrilateral patch in the local adjacency graph based on regularity quantitative indexes; setting a threshold value, if the comprehensive regularity score is lower than the threshold value, adopting vtkQuad for modeling, otherwise, adopting vtkTriangle for modeling, and generating primitive data; performing topology check on the primitive data, storing the primitive data into vtkCell Array, converting polygonal primitives into triangular primitives, and smoothing the triangular primitives to generate a three-dimensional geological section model; performing visualization and rendering processing to obtain a final three-dimensional geological section model; according to the invention, accurate data visualization support is provided for geological analysis, and the intelligent and precise level of geological work is improved.

The invention provides a rock image classification method based on super-resolution and texture feature fusion. According to the method, the accuracy of mineral classification in the rock slice image is remarkably improved by combining a super-resolution model and a texture feature analysis technology, the enhanced image texture features are extracted by utilizing a Gabor filter, and classification is carried out by adopting a support vector machine. By comparing the performance of various SR models, the optimal model is selected to enhance the image resolution, so that the recognition effect of minerals and pores is improved. In addition, the system further optimizes the classification result through multi-color space feature fusion, finer mineral distribution data is provided for geological analysis, the mineral classification efficiency and precision are improved, and reliable technical support is provided for geological evaluation of oil and gas reservoirs.

This invention provides a method and system for automatic vertex picking of DAS-based microseismic events, relating to the field of microseismic location technology. The method includes acquiring multi-channel data corresponding to microseismic events and performing demodulation analysis to form multi-channel waveform data; performing correlation analysis on the waveform data from different channels to establish an automatic picking correlation model; performing image transformation based on the automatic picking correlation model to form corresponding grayscale images; and performing location discrimination analysis based on the grayscale images to determine the event vertex channel. This method improves the interpretation accuracy and reliability of geological analysis of seismic images by removing noise while preserving geological structural features such as faults and strata.

The present application relates to a shallow-water delta sand body configuration method based on a sequence stratigraphic sedimentary pattern, and belongs to the technical field of geological analysis, comprising the following steps: establishing a shallow-water braided river delta plane sedimentary pattern of a study area; determining a three-level base level cycle sedimentary system domain; analyzing the scale and pattern of the sediment plane and profile according to the change of the base level, establishing a longitudinal and lateral sequence stratigraphic sedimentary pattern of the shallow-water delta; controlling the sand body resolution, realizing different precision sand body configuration identification and division; applying the sand body configuration combination relationship to carry out sand body classification research, and establishing a reservoir comprehensive classification chart. The present application also relates to a shallow-water delta sand body configuration system based on a sequence stratigraphic sedimentary pattern, and solves the problems of how to accurately and efficiently predict the spatial distribution form and scale of the sand body in the strong heterogeneous reservoir, and the diversification of the sand body configuration prediction results caused by personal subjective experience, guides the high-precision sand body configuration identification and division, and finally determines the longitudinal and lateral remaining oil distribution range.

The utility model belongs to the field of hydraulic ring geological detection, and particularly relates to a hydraulic ring geological crack measuring device which comprises a device body, the front face and the back face of the device body are both fixedly connected with supporting legs, and the front face of the other supporting leg is fixedly connected with a control unit. The device is started through the touch panel, the laser leveling instrument is observed at the same time, and the measuring probe can be in a horizontal state and is aligned with the geological crack by adjusting the transverse angle adjusting seat and the longitudinal angle adjusting seat, so that data deviation caused by inaccurate position of the measuring probe can be avoided; a more accurate basis is provided for subsequent geological analysis and engineering design, the electric sliding frame is operated to slide in the electric sliding groove through the control unit, the horizontal position of the measuring probe can be adjusted, finally, the measuring probe is used for measuring the geological crack, the edge, the center and the specific key area of the crack can be easily reached, and the measurement accuracy is improved. And the comprehensiveness and the accuracy of measured data are ensured.

The invention provides a geological analysis parameter protection method and system based on logarithm mapping, and relates to the technical field of geological exploration data protection, and the method comprises the steps: obtaining an original R parameter, building a linear mapping relation g = aR + b, building logarithm transformation mapping based on the linear mapping relation, converting the original parameter into a transformed parameter value, and obtaining a parameter value; and the transformed parameter values are provided for the data processing party for geological exploration operation, and the data owner recovers the original parameters through an inverse transformation formula after receiving the data obtained by exploration of the data processing party. According to the method, through logarithm transformation, an exploration company cannot identify the stratum type through conventional linear fitting, and sensitive geological information is effectively protected; meanwhile, irreversibility of the transformation process is ensured by adopting random parameters, and a data owner can completely recover original geological parameters through an inverse transformation formula; on the premise of protecting the data security, the normal exploration operation flow and the data processing precision are not influenced.

This invention relates to the field of petroleum exploration and development technology, and discloses a method and device for high-precision identification of low-order faults in tight sandstone channels. The invention first simulates the river channel based on geological analysis results of the study area, integrating the simulated channel into a horizontal reflectivity model. Then, based on this, fault and fold simulations are performed according to the geological analysis results. Finally, the reflectivity model is convolved with Ricker wavelets to generate a 3D seismic data volume through forward modeling. An improved Unet network model is constructed, and the network model is trained using the 3D seismic data volume obtained through forward modeling. After training, the 3D seismic data volume to be predicted is fed into the trained model to achieve automatic identification of low-order faults in tight sandstone channels. This invention, through deep learning algorithms, fully explores the potential features of seismic data, greatly improving the identification capability of low-order faults and effectively distinguishing lithological boundaries and fault boundaries, thus improving the accuracy of geological interpretation.

The invention relates to a method and device for recovering the uplift denudation amount of a petroliferous basin, equipment and a medium, and relates to the technical field of geological analys.The method comprises the steps that a reference well is selected in a research area, and the uplift denudation amount delta H0 and the time-depth conversion relation of a target layer of the reference well are obtained; a standard layer is selected, and the marker bed three-dimensional structure top interface depth Tn is reconstructed according to the time-depth conversion relation of the reference well; and calculating the uplift denudation amount Xn of the target stratum based on the uplift denudation amount delta H0 of the reference well and the marker bed paleostructural plane. According to the recovery method provided by the invention, the three-dimensional continuous space of the petroliferous basin scale is modeled by virtue of the matching of the reference well and the standard layer, so that the accurate recovery of the multi-curtain uplift denudation thickness three-dimensional space is realized, and a scientific basis is provided for the exploration and development of oil and gas.