Three-dimensional geological model construction method and device, equipment and storage medium

Abstract

The invention relates to the technical field of artificial intelligence, in particular to a method, a device and equipment for constructing a three-dimensional geologic model of a goaf of a steeply inclined coal seam under a repeated mining condition and a computer storage medium. According to the method for constructing the three-dimensional geologic model of the goaf of the steeply inclined coal seam under the repeated mining condition, provided by the invention, multi-source geologic data are subjected to integrated processing, useful information data are extracted, a geologic structure digital model with certain precision is established, and a space structure of a geologic body is simulated to the greatest extent; a visual three-dimensional geological model is established through multi-source geological data, information such as underground geological conditions, geological structures and coal seam occurrence laws is displayed in detail, and a basis can be provided for goaf site stability calculation and evaluation, goaf treatment scheme determination, computer numerical simulation and project display.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to a method, device, equipment and computer storage medium for constructing a three-dimensional geological model of a steeply inclined coal seam goaf under repeated mining conditions. Background Art

[0002] In recent years, with the rapid development of artificial intelligence technology, the fields of intelligent mines, transparent geology and three-dimensional geological modeling have received more and more attention. In particular, three-dimensional geological models play a fundamental role in guiding the safe, efficient and intelligent mining of coal mines. The storage and expression of geological survey data and geological results data are facing major changes. Traditional point, line and surface two-dimensional data results can no longer meet the expression of geological big data. Three-dimensional point, line, surface and entity data are the core data for enriching geological big data. In addition, a visual three-dimensional geological model is established through multi-source geological data to show detailed information such as underground geological conditions, geological structure and coal seam occurrence laws, which can provide a basis for the calculation and evaluation of the stability of the goaf area, the determination of the goaf area governance plan, computer numerical simulation and project display.

[0003] The mining method of steeply inclined coal seams is closely related to the geological conditions of the coal seam burial. The selected drilling layout method is not only related to the inclination and thickness of the coal seam, but also to many geological factors such as the burial depth of the coal seam, the number of coal seams, the properties of the surrounding rock, the geological structure, and the spontaneous combustion properties of the coal seam, the gas content, and the hydrological conditions.

[0004] The prior art discloses a method and system for surveying and arranging drilling holes based on steeply inclined coal seam goafs, including: obtaining exploration lines, initial values ​​of roof movement angles, and initial values ​​of floor movement angles according to a three-dimensional geological model; drawing an exploration profile through the exploration lines, and then obtaining initial values ​​of drilling positions and drilling depths; performing signal integrity analysis on the initial values ​​of drilling positions and drilling depths, obtaining correction values ​​of drilling positions and drilling depths, and finally realizing the drilling arrangement operation for steeply inclined coal seams. The exploration accuracy of drilling positions and drilling depths is greatly improved, and it can be widely used in drilling arrangements in small kiln room pillar goafs, storage goafs, pseudo-inclined flexible shielding support blasting goafs, top and bottom plate fracture surfaces, etc., and timely obtaining safety risks such as cracks and cavities in the goaf strata, providing an accurate and reliable basis for construction. However, the three-dimensional geological model established in this scheme is not accurate enough and cannot simulate the spatial structure of the geological body with maximum authenticity. Summary of the invention

[0005] Therefore, the technical problem to be solved by the present invention is to overcome the problem that the three-dimensional geological model in the prior art is not accurate enough.

[0006] In order to solve the above technical problems, the present invention provides a method for constructing a three-dimensional geological model, comprising:

[0007] Collect and pre-process the above-ground drone measurement data and underground geological information data of the steeply inclined coal seam goaf;

[0008] A three-dimensional geological structure model is established based on the preprocessed data, and corresponding constraint conditions are established to obtain a three-dimensional geological model network;

[0009] Establish a mapping relationship between the preprocessed data and the real-time three-dimensional geological network model to obtain a simulated network;

[0010] Perform multi-point statistical random simulation based on the simulation network to obtain multiple simulation output models;

[0011] The multiple simulation output models are embedded into the three-dimensional geological model network to obtain a target three-dimensional geological model.

[0012] Preferably, the collecting of ground drone measurement data and underground geological information data of steeply inclined coal seam goaf and preprocessing includes:

[0013] Using three-dimensional oblique photography technology, a preset scale topographic map measurement is performed on the steeply inclined coal seam goaf to obtain drone measurement data;

[0014] Orthophotos, digital elevation models and digital line drawings are generated based on the drone measurement data.

[0015] Preferably, the collecting of ground drone measurement data and underground geological information data of steeply inclined coal seam goaf and preprocessing also includes:

[0016] The transient electromagnetic method is used to measure the transient induced voltage of each measuring point in each time window of the goaf area of ​​the steeply inclined coal seam, and the resistivity and apparent depth are calculated according to the transient induced voltage, and filtering and one-dimensional forward and inverse processing are performed to obtain the goaf area range analysis result data;

[0017] After completing the seismic exploration field test, the seismic cross-hole elastic wave CT was used to detect the wave velocity range and characteristics of various rock and soil layers in the goaf of steeply inclined coal seams. The inter-hole seismic wave velocity image map was drawn based on the detection results and comprehensive geological interpretation data was obtained;

[0018] Use geophysical logging to detect the goaf of steeply inclined coal seams, interpret and divide the rock formations according to their geophysical characteristics, and perform qualitative and quantitative interpretation of logging curve characteristics according to the laws of physical property changes of rock and coal seams;

[0019] Using high-definition cameras, the borehole wall is peeked and recorded in an upward and downward manner to fully observe and collect the morphology of the goaf of the steeply inclined coal seam, the degree of crack development in the rock in the hole, the integrity and collapse state of the goaf roof, and the water accumulation in the goaf.

[0020] Preferably, the seismic exploration field test includes noise analysis, determination of spark source excitation parameters and determination of receiving parameters.

[0021] Preferably, the method of using cross-hole seismic elastic wave CT to detect the wave velocity range and characteristics of various rock and soil layers in the goaf of steeply inclined coal seams, drawing inter-hole seismic wave velocity images and obtaining comprehensive geological interpretation data according to the detection results includes:

[0022] Obtain the electronic waveform files of each pair of cross-hole CT, rearrange them into common excitation point gathers, and perform quality checks;

[0023] After the quality inspection is passed, the observation system is established and the first arrival time is picked;

[0024] Pick the correct gather for the first arrival time and calculate the average wave velocity of the ray for each shot-detection pair;

[0025] Establishing an initial velocity model between holes according to the average wave velocity of the rays;

[0026] According to the initial velocity model and the first arrival time, iterative calculation is performed according to the preset node interval, the wave velocity image of the cross-hole profile is inverted, and the analysis is performed in combination with the drilling data to obtain the position and range of the geological anomaly.

[0027] Preferably, the qualitative and thickness determination interpretation of the logging curve characteristics according to the physical property change law of the rock and coal seams includes:

[0028] Qualitative interpretation of well logging curve characteristics is made using preset proportional curves of three lateral resistivity or potential resistivity, long-source-distance gamma-ray, short-source-distance gamma-ray and natural gamma;

[0029] On the basis of qualitative analysis, three-lateral resistivity or potential resistivity and long-source-distance gamma-gamma curve or natural gamma curve are used to interpret the thickness of the logging curve characteristics.

[0030] Preferably, the thickness interpretation point of the three lateral resistivities or potential resistivities is set to the inflection point of the abnormal amplitude segment;

[0031] The fixed thickness interpretation point of the long source distance gamma-gamma curve is set to 1 / 3 of the abnormal amplitude. When the thickness of the coal seam intercalated with rocks is less than the source distance, the fixed thickness interpretation point of the coal seam intercalated with rocks is set to 1 / 3 of the abnormal amplitude. When the thickness of the coal seam intercalated with rocks is greater than the source distance, the fixed thickness interpretation point of the coal seam intercalated with rocks is set to 1 / 2 of the abnormal amplitude.

[0032] The thickness interpretation point of the natural gamma curve is set to 1 / 2 of the abnormal amplitude, and the thickness interpretation point of the coal seam with rock is set to 1 / 2 of the abnormal amplitude of the coal seam with rock.

[0033] The present invention also provides a three-dimensional geological model construction device, comprising:

[0034] The data acquisition module is used to collect ground drone measurement data and underground geological information data of steeply inclined coal seam goafs and perform preprocessing;

[0035] The initial model construction module is used to establish a three-dimensional geological structure model based on the preprocessed data and establish corresponding constraint conditions to obtain a three-dimensional geological model network;

[0036] A simulation network construction module is used to establish a mapping relationship between the preprocessed data and the real-time three-dimensional geological network model to obtain a simulation network;

[0037] A simulation result acquisition module, used for performing multi-point statistical random simulation based on the simulation network to obtain multiple simulation output models;

[0038] The target model acquisition module is used to embed the multiple simulation output models into the three-dimensional geological model network to obtain a target three-dimensional geological model.

[0039] The present invention also provides a three-dimensional geological model construction device, comprising:

[0040] Memory for storing computer programs;

[0041] The processor is used to implement the above-mentioned three-dimensional geological model construction method steps when executing the computer program.

[0042] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned three-dimensional geological model construction method are implemented.

[0043] The above technical solution of the present invention has the following advantages compared with the prior art:

[0044] The method for constructing a three-dimensional geological model of a steeply inclined coal seam goaf under repeated mining conditions provided by the present invention integrates multi-source geological data, extracts useful information data, and establishes a digital model of geological structure with a certain accuracy, simulates the spatial structure of the geological body with maximum realism, and establishes a visual three-dimensional geological model through multi-source geological data, which displays information such as underground geological conditions, geological structure and coal seam occurrence laws in detail, and can provide a basis for calculating and evaluating the stability of the goaf site, determining the goaf management plan, computer numerical simulation and project display. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to make the content of the present invention more clearly understood, the present invention is further described in detail below according to specific embodiments of the present invention in conjunction with the accompanying drawings, wherein:

[0046] Figure 1 It is a flow chart for realizing a method for constructing a three-dimensional geological model of a goaf area of ​​a steeply inclined coal seam under repeated mining conditions provided by the present invention;

[0047] Figure 2 It is a flow chart of a method for constructing a three-dimensional geological model provided by an embodiment of the present invention;

[0048] Figure 3 It is a transient electromagnetic method detection data processing flow chart of the method for constructing a three-dimensional geological model of a goaf area of ​​a steeply inclined coal seam under repeated mining conditions provided by the present invention;

[0049] Figure 4 A flow chart of cross-hole elastic wave CT data processing and interpretation for a method for constructing a three-dimensional geological model of a goaf area of ​​a steeply inclined coal seam under repeated mining conditions provided by the present invention. DETAILED DESCRIPTION

[0050] The core of the present invention is to provide a method, device, equipment and computer storage medium for constructing a three-dimensional geological model of a steeply inclined coal seam goaf under repeated mining conditions, which effectively improves the accuracy of the three-dimensional geological model.

[0051] In order to enable those skilled in the art to better understand the scheme of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0052] Please refer to Figure 1 and Figure 2 , Figure 1 This is a flow chart of a method for constructing a three-dimensional geological model of a goaf area of ​​a steeply inclined coal seam under repeated mining conditions provided by the present invention. Figure 2 A flowchart of a method for constructing a three-dimensional geological model provided by an embodiment of the present invention; the specific operation steps are as follows:

[0053] S101: Collecting ground drone measurement data and underground geological information data of steeply inclined coal seam goaf areas and performing preprocessing;

[0054] S102: Establishing a three-dimensional geological structure model based on the preprocessed data and establishing corresponding constraint conditions to obtain a three-dimensional geological model network;

[0055] S103: Establishing a mapping relationship between the preprocessed data and the real-time three-dimensional geological network model to obtain a simulated network;

[0056] S104: performing multi-point statistical random simulation based on the simulation network to obtain multiple simulation output models;

[0057] S105: Embed the multiple simulation output models into the three-dimensional geological model network to obtain a target three-dimensional geological model.

[0058] Based on the above embodiments, this embodiment describes step S101 in detail:

[0059] ·Use 3D oblique photography technology to measure the topographic map of the steeply inclined coal seam goaf in a preset scale and obtain drone measurement data;

[0060] 3D oblique photography is an advanced remote sensing technology that takes photos of the ground or structure from multiple angles (usually five directions: front, back, left, right and bottom) and then uses these photos to create a 3D model. This technology is very useful in topographic mapping of steeply inclined coal seam goafs because it can provide high-precision 3D terrain data:

[0061] First, the flight route and shooting angle of the drone are planned based on the geographical location and scope of the goaf to ensure that the entire area can be covered; then the drone equipped with a high-resolution camera flies along the planned route and takes photos at predetermined angles; since the photos taken by the drone will contain rich texture and geometric information, this data will be used for subsequent 3D modeling.

[0062] Generate orthophotos, digital elevation models and digital line drawings based on the drone measurement data.

[0063] Generating orthophotos (DOM), digital elevation models (DEM) and digital line graphs (DLG) based on drone measurement data is a common data processing process in the field of geographic information systems (GIS) and remote sensing. The following are the general steps for generating these maps:

[0064] Orthophoto (DOM) generation: An orthophoto is a map derived from oblique aerial photography or satellite imagery that corrects distortion so that the image looks like it was taken from a perpendicular angle to the surface. Use photogrammetry software (such as Pix4Dmapper, Agisoft Photoscan, ArcGIS, etc.) to correct the oblique images taken by drones to eliminate the distortion caused by terrain undulations; stitch the corrected images to create a continuous, seamless image coverage area; perform color correction and enhancement on the stitched images to improve the visual effect and quality of the images; output the processed images as orthophotos, usually in GeoTIFF format, containing geographic reference information.

[0065] Digital Elevation Model (DEM) Generation:

[0066] A digital elevation model is a digital representation of surface elevation data, either as a regularly spaced grid (raster DEM) or irregularly spaced points (vector DEM). Generate a 3D point cloud from drone imagery, usually automatically through photogrammetry software. Filter the point cloud data to remove noise and non-ground points. Generate a DEM from the filtered point cloud. This can be done by gridding the point cloud data in the case of a raster DEM or by extracting contour lines or constructing an irregular triangulated network (TIN) in the case of a vector DEM. Verify the generated DEM for accuracy to ensure the accuracy of the elevation data.

[0067] Digital Line Map (DLG) generation: A digital line map is a vector map that contains linear and planar geographic features on the surface, such as rivers, roads, buildings, etc. Extract geographic features such as rivers, roads, and building boundaries from orthophotos or DEMs. Digitize the extracted features manually or automatically and convert them into vector data. Edit the digitized features, build topological relationships, and ensure the logical consistency of the data. Assign attribute information to vector features, such as feature type, name, etc. Output the edited vector data as DLG, usually in Shapefile or GeoJSON format.

[0068] ·Use transient electromagnetic method to measure the transient induced voltage of each measuring point in each time window of the goaf area of ​​steeply inclined coal seams, calculate the resistivity and apparent depth according to the transient induced voltage, and perform filtering and one-dimensional forward and inverse processing to obtain the goaf area range analysis result data;

[0069] Transient Electromagnetic Method (TEM) is a geophysical exploration method that infers the resistivity distribution of underground rocks by stimulating transient currents on the surface or underground and measuring the resulting transient electromagnetic fields. This method is particularly suitable for detecting goafs in steeply inclined coal seams because it can provide detailed information about underground structures. Figure 2 , the following are the general steps for measurement and data processing using transient electromagnetic method:

[0070] Select appropriate transient electromagnetic equipment and arrange transmitting coils and receiving coils at the measuring points. Arrange measuring points in and around the goaf to ensure full coverage of the target area. Excite transient current in the transmitting coil. Measure the transient induced voltage generated by the excited current in the receiving coil. Select multiple different time windows (time intervals) to measure the transient induced voltage to obtain information at different depths. Filter the measured transient induced voltage data to remove noise and interference and improve data quality. Calculate the resistivity under different time windows based on the transient induced voltage and the known excited current. -Apparent depth refers to the underground depth reflected by the resistivity data in transient electromagnetic measurement, which is related to the measurement time window.

[0071] A one-dimensional geoelectric model is established to simulate the effect of different resistivity layers on transient electromagnetic response. The measured resistivity data is used to estimate the underground resistivity distribution through inversion algorithms (such as least squares method, genetic algorithm, etc.). According to the inversion results, the geoelectric model parameters are adjusted until the model predictions match the actual measured data. According to the resistivity distribution obtained by inversion, the spatial range, morphology and scale of the goaf are analyzed. Combined with the geological background and other geophysical data, the geological structure of the goaf is interpreted.

[0072] After completing the seismic exploration field test, use the seismic cross-hole elastic wave CT to detect the wave velocity range and characteristics of various rock and soil layers in the goaf of steeply inclined coal seams, draw inter-hole seismic wave velocity images and obtain comprehensive geological interpretation data based on the detection results;

[0073] like Figure 3 , Seismic cross-hole elastic wave CT (Computed Tomography) is a geophysical exploration technology that detects the wave velocity distribution of underground rock and soil layers by exciting and receiving elastic waves in a borehole. The following is a detailed process of data processing after seismic exploration field tests:

[0074] Field test preparation: Before exciting elastic waves, perform noise analysis to determine the background noise level so that noise can be removed in subsequent data processing. Select appropriate spark source excitation parameters, such as current size, duration, etc., to ensure effective excitation of elastic waves. Set appropriate receiving parameters, such as gain, filter settings, etc., to optimize signal reception.

[0075] Field data acquisition: Excite elastic waves in the predetermined boreholes and receive elastic wave signals in other boreholes. Record the time when the elastic waves reach the receiver and other relevant parameters.

[0076] Data processing: Select representative gathers from the raw data for preliminary analysis. Obtain the electronic waveform files of each pair of cross-hole CT, rearrange them into common excitation point gathers, and check the data of all receiving points generated at the same excitation point to ensure the consistency and reliability of the data.

[0077] Data analysis: Identifying and picking up the first arrival time of elastic waves from seismic traces is a key step in seismic data processing. Pick up the correct trace set for the first arrival time, and calculate the average wave velocity of the ray based on the first arrival time and the known distance between holes.

[0078] Velocity model establishment: Use the average wave velocity of the ray and other geological information to establish the initial velocity model of the underground medium.

[0079] CT inversion: According to the initial velocity model and the first arrival time, iterative calculation is performed according to the preset node interval to invert the wave velocity image of the cross-hole section, and the wave velocity image and geological knowledge are combined to perform comprehensive geological interpretation, including the identification of rock and soil layers, the location of faults and folds, etc. Based on the results of geological interpretation, geological maps such as structural maps, stratigraphic distribution maps, fault maps, etc. are drawn, which are crucial for geological exploration and resource assessment.

[0080] Use geophysical logging to detect the goaf of steeply inclined coal seams, interpret and divide the rock formations according to their geophysical characteristics, and perform qualitative and quantitative interpretation of the logging curve characteristics according to the laws of physical property changes of rock and coal seams;

[0081] Geophysical logging, usually referred to as logging, is a technique for detecting underground rock formation characteristics in boreholes using geophysical methods. It obtains information about underground rock formations by measuring the physical properties of rocks, such as resistivity, radioactivity, acoustic velocity, density, etc. The following are the general steps for detecting and interpreting the goaf of steeply inclined coal seams using geophysical logging:

[0082] Logging preparation: Select appropriate logging instruments according to the detection target and geological conditions, such as resistivity logging, gamma logging, sonic logging, etc. Design logging plans, including logging depth, measurement parameters, logging speed, etc.

[0083] Well logging data acquisition: The well logging instrument is lowered into the borehole and measured at a predetermined depth. The geophysical parameters at different depths are recorded to generate well logging curves.

[0084] Data preprocessing: Remove outliers and noise from logging curves. Perform environmental correction and instrument correction on logging data to ensure data accuracy.

[0085] Rock formation interpretation and classification: According to the shape and amplitude change of the logging curve, the rock formation is qualitatively interpreted to identify the type and nature of the rock formation. The marker layer or special layer in the logging curve is identified to determine the rock formation interface.

[0086] Analysis of physical property change rules: Analyze the physical property change rules of coal seams and rock strata, such as resistivity, density, porosity, etc. Identify coal seams based on the physical property change rules and determine the purity and maturity of coal seams.

[0087] Qualitative interpretation: Qualitative interpretation of rock and coal seams is carried out based on the geological background and logging curve characteristics.

[0088] Parameter selection: The 1:200 curves of four parameters, namely, three-lateral resistivity (LL3) (or potential resistivity NR), long source distance gamma-gamma (GGL), short source distance gamma-gamma (GGS), and natural gamma (GR), were used, and qualitative interpretation was made with reference to the characteristics of the logging curves.

[0089] Thickness interpretation: Estimate the thickness of rock and coal seams by comparing the characteristics of different logging curves.

[0090] On the basis of qualitative analysis, two curves, namely, three-lateral resistivity (LL3) (or potential resistivity NR) and long source distance gamma-gamma (GGL) (or natural gamma (GR)), are used for thickness determination interpretation.

[0091] Interpretation principles:

[0092] ① Three-dimensional resistivity or potential resistivity (NR): The thickness interpretation point is determined as the inflection point of the abnormal amplitude segment.

[0093] ② Gamma-Gamma curve (GGL): The fixed thickness interpretation point is usually 1 / 3 of the abnormal amplitude. The fixed thickness interpretation point of coal seam intercalation is: when the thickness of coal seam intercalation is less than the source distance, it is 1 / 3 of the abnormal amplitude, and when it is greater than the source distance, it is 1 / 2 of the abnormal amplitude.

[0094] ③ Natural gamma curve (GR): The thickness interpretation point is usually the half-amplitude point of the abnormal amplitude, and the thickness interpretation point of the stone inclusion is 1 / 2 of the abnormal amplitude of the stone inclusion.

[0095] Well logging curve comparison: Compare the well logging curves of different boreholes to identify regional geological characteristics and change trends. In the same borehole, compare the well logging curves of different depths to identify small-scale geological changes.

[0096] ·Use high-definition cameras to peek and record the borehole wall in an upward and downward manner, and comprehensively observe and collect the morphology of the goaf area of ​​the steeply inclined coal seam, the degree of development of cracks in the rock in the hole, the integrity and collapse of the roof of the goaf area, and the water accumulation in the goaf area.

[0097] Using high-definition cameras to peer into and record the goaf of steeply inclined coal seams is a direct and effective exploration method that can provide intuitive information inside the goaf. The following are the general steps for exploration using this method:

[0098] Preparation stage: Select a high-definition camera suitable for underground operations, and ensure that it has sufficient brightness, resolution, and temperature resistance. Install the camera on a controllable downhole equipment, such as a drill pipe or a specialized camera device.

[0099] Downhole observation: The camera is lowered along the borehole to the predetermined depth to start recording the condition of the borehole wall. The real-time transmission function of the camera is used to monitor the shape of the borehole wall and the development of rock fractures.

[0100] Upstream video recording: Record video while the camera is upstream to capture detailed features of the borehole wall. Ensure that the camera can cover all angles of the borehole wall to obtain comprehensive observation data.

[0101] Data recording: Record the morphological characteristics of the goaf, including the irregularity of the hole wall, changes in hole diameter, etc. Record the development, direction and distribution of rock fissures in detail. Observe and record the integrity, collapse state and stability of the goaf roof. Check and record whether there is water accumulation in the goaf, the location, range and possible depth of the water accumulation.

[0102] Data analysis: Analyze the recorded video in detail to extract key information. Enhance the captured images to improve the recognition accuracy of features such as cracks and water bodies.

[0103] Based on the above embodiments, this embodiment describes step S102 in detail:

[0104] Establishing a 3D geological structure model based on preprocessed data and establishing corresponding constraints to obtain a 3D geological model network is a key step in geological modeling. This process involves multiple stages, including data integration, model construction, constraint setting, and model network generation. The following are the detailed steps of this process:

[0105] Data integration: Integrate all relevant geological data, including but not limited to drilling data, geophysical exploration data (such as seismic, electromagnetic, gravity and magnetic data), surface geological maps, remote sensing images, etc. Clean, format and standardize the collected data to ensure data quality and consistency.

[0106] Build a 3D geological structure model: Based on the stratigraphic data, build a 3D model of the stratigraphic structure, including the stratigraphic shape, thickness, and contact relationship. Identify and simulate the location, direction, and displacement of faults to ensure that the faults are accurately represented in the model. Simulate the shape and axis of folds, including the tightness and direction of folds. Identify and simulate unconformities, which are usually important events in geological history.

[0107] Establish constraints: Based on geological knowledge, establish geological constraints, such as continuity of strata, closure of faults, etc. Convert geophysical data into constraints for geological models, such as resistivity anomalies, seismic wave velocity changes, etc. Consider geochemical data, such as element distribution, as constraints for the model. If available, incorporate hydrogeological data (such as groundwater flow, water quality) into model constraints.

[0108] Generation of 3D geological model network: Convert the 3D geological model into a gridded form, where each grid cell represents a small area underground. Assign geological attributes to each grid cell, such as rock type, porosity, permeability, etc. Build a model network to ensure that the connection between grid cells meets the geological structure and constraints.

[0109] Based on the above embodiments, this embodiment describes steps S103-S105 in detail:

[0110] Establishing a mapping relationship between the preprocessed data and the real-time 3D geological network model, and based on this, conducting multi-point statistical random simulation, and finally embedding the simulation results into the 3D geological model network is the key process for achieving model refinement and uncertainty quantification in geological modeling. The following are the detailed steps of this process:

[0111] Establish mapping relationship: Integrate preprocessed data (such as drilling data, geophysical exploration data, etc.) with the 3D geological network model. Define the mapping relationship between data and model to ensure that each data point can correspond to the corresponding position in the model. Apply geological, geophysical, geochemical and other constraints to ensure the geological rationality of the mapping relationship.

[0112] Construct simulation network: Based on the mapping relationship, construct a simulation network, which will be used for multi-point statistical random simulation. Set necessary parameters for the simulation network, such as variation function, correlation length, probability distribution, etc.

[0113] Multi-point statistical random simulation: Select appropriate multi-point statistical simulation methods, such as sequential Gaussian simulation, escape sequence simulation, etc. Based on the simulation network and set parameters, perform multi-point statistical random simulation to generate multiple possible geological models. Evaluate the statistical characteristics of the simulation results, such as variability, correlation, etc., to ensure the rationality of the simulation results.

[0114] Embed simulation output models: Select the best model from multiple simulation output models or integrate models to reduce uncertainty. Embed the selected simulation output model into the 3D geological model network to update the model's attributes and structure. Refine the model after embedding the simulation results to improve the model's resolution and local details.

[0115] Obtain the target 3D geological model: Verify the accuracy and reliability of the target 3D geological model by comparing it with the measured data. According to the verification results, adjust the model parameters, optimize the model structure, and improve the geological rationality and prediction ability of the model.

[0116] The embodiment of the present invention also provides a device for constructing a three-dimensional geological model of a goaf area of ​​a steeply inclined coal seam under repeated mining conditions; the specific device may include:

[0117] The data acquisition module is used to collect ground drone measurement data and underground geological information data of steeply inclined coal seam goafs and perform preprocessing;

[0118] The initial model construction module is used to establish a three-dimensional geological structure model based on the preprocessed data and establish corresponding constraint conditions to obtain a three-dimensional geological model network;

[0119] A simulation network construction module is used to establish a mapping relationship between the preprocessed data and the real-time three-dimensional geological network model to obtain a simulation network;

[0120] A simulation result acquisition module, used for performing multi-point statistical random simulation based on the simulation network to obtain multiple simulation output models;

[0121] The target model acquisition module is used to embed the multiple simulation output models into the three-dimensional geological model network to obtain a target three-dimensional geological model.

[0122] The three-dimensional geological model construction device of this embodiment is used to implement the aforementioned three-dimensional geological model construction method. Therefore, the specific implementation method of the three-dimensional geological model construction device can be seen in the embodiment part of the three-dimensional geological model construction method mentioned above. For example, the data acquisition module, the initial model construction module, the simulation network construction module, the simulation result acquisition module, and the target model acquisition module are respectively used to implement steps S101, S102, S103, S104 and S105 in the above-mentioned three-dimensional geological model construction method. Therefore, its specific implementation method can refer to the description of the corresponding embodiments of each part, which will not be repeated here.

[0123] A specific embodiment of the present invention further provides a three-dimensional geological model construction device, comprising: a memory for storing a computer program; a processor for implementing the steps of the above-mentioned three-dimensional geological model construction method when executing the computer program.

[0124] A specific embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned three-dimensional geological model construction method are implemented.

[0125] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0126] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0127] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0128] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0129] Obviously, the above embodiments are merely examples for the purpose of clear explanation and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the present invention.

Claims

1. A method for constructing a three-dimensional geological model, characterized in that: include: Collect and pre-process the above-ground drone measurement data and underground geological information data of the steeply inclined coal seam goaf; A three-dimensional geological structure model is established based on the preprocessed data, and corresponding constraint conditions are established to obtain a three-dimensional geological model network; Establish a mapping relationship between the preprocessed data and the real-time three-dimensional geological network model to obtain a simulated network; Perform multi-point statistical random simulation based on the simulation network to obtain multiple simulation output models; The multiple simulation output models are embedded into the three-dimensional geological model network to obtain a target three-dimensional geological model.

2. The three-dimensional geological model construction method according to claim 1, characterized in that: The collecting of ground drone measurement data and underground geological information data in the steeply inclined coal seam goaf and preprocessing includes: Using three-dimensional oblique photography technology, a preset scale topographic map measurement is performed on the steeply inclined coal seam goaf to obtain drone measurement data; Orthophotos, digital elevation models and digital line drawings are generated based on the drone measurement data.

3. The three-dimensional geological model construction method according to claim 1, characterized in that: The collecting of ground drone measurement data and underground geological information data of steeply inclined coal seam goaf areas and preprocessing also includes: The transient electromagnetic method is used to measure the transient induced voltage of each measuring point in each time window of the goaf area of ​​the steeply inclined coal seam, and the resistivity and apparent depth are calculated according to the transient induced voltage, and filtering and one-dimensional forward and inverse processing are performed to obtain the goaf area range analysis result data; After completing the seismic exploration field test, the seismic cross-hole elastic wave CT was used to detect the wave velocity range and characteristics of various rock and soil layers in the goaf of steeply inclined coal seams. The inter-hole seismic wave velocity image map was drawn based on the detection results and comprehensive geological interpretation data was obtained; Use geophysical logging to detect the goaf of steeply inclined coal seams, interpret and divide the rock formations according to their geophysical characteristics, and perform qualitative and quantitative interpretation of logging curve characteristics according to the laws of physical property changes of rock and coal seams; Using high-definition cameras, the borehole wall is peeked and recorded in an upward and downward manner to fully observe and collect the morphology of the goaf of the steeply inclined coal seam, the degree of crack development in the rock in the hole, the integrity and collapse state of the goaf roof, and the water accumulation in the goaf.

4. The method for constructing a three-dimensional geological model according to claim 3, characterized in that: The seismic exploration field test includes noise analysis, determination of electric spark source excitation parameters and determination of receiving parameters.

5. The three-dimensional geological model construction method according to claim 3, characterized in that: The method of using cross-hole seismic elastic wave CT to detect the wave velocity range and characteristics of various rock and soil layers in the goaf of steeply inclined coal seams, drawing inter-hole seismic wave velocity images and obtaining comprehensive geological interpretation data based on the detection results includes: Obtain the electronic waveform files of each pair of cross-hole CT, rearrange them into common excitation point gathers, and perform quality checks; After the quality inspection is passed, the observation system is established and the first arrival time is picked; Pick the correct gather for the first arrival time and calculate the average wave velocity of the ray for each shot-detection pair; Establishing an initial velocity model between holes according to the average wave velocity of the rays; According to the initial velocity model and the first arrival time, iterative calculation is performed according to the preset node interval, the wave velocity image of the cross-hole profile is inverted, and the analysis is performed in combination with the drilling data to obtain the position and range of the geological anomaly.

6. The method for constructing a three-dimensional geological model according to claim 3, characterized in that: The qualitative and thickness interpretation of the logging curve characteristics according to the physical property change law of the rock and coal seams includes: Qualitative interpretation of well logging curve characteristics is made using preset proportional curves of three lateral resistivity or potential resistivity, long-source-distance gamma-ray, short-source-distance gamma-ray and natural gamma; On the basis of qualitative analysis, three-lateral resistivity or potential resistivity and long-source-distance gamma-gamma curve or natural gamma curve are used to interpret the thickness of the logging curve characteristics.

7. The method for constructing a three-dimensional geological model according to claim 6, characterized in that: Setting the thickness interpretation point of the three lateral resistivities or potential resistivities to the inflection point of the abnormal amplitude segment; The fixed thickness interpretation point of the long source distance gamma-gamma curve is set to 1 / 3 of the abnormal amplitude. When the thickness of the coal seam intercalated with rocks is less than the source distance, the fixed thickness interpretation point of the coal seam intercalated with rocks is set to 1 / 3 of the abnormal amplitude. When the thickness of the coal seam intercalated with rocks is greater than the source distance, the fixed thickness interpretation point of the coal seam intercalated with rocks is set to 1 / 2 of the abnormal amplitude. The thickness interpretation point of the natural gamma curve is set to 1 / 2 of the abnormal amplitude, and the thickness interpretation point of the coal seam with rock is set to 1 / 2 of the abnormal amplitude of the coal seam with rock.

8. A three-dimensional geological model construction device, characterized in that: include: The data acquisition module is used to collect ground drone measurement data and underground geological information data of steeply inclined coal seam goafs and perform preprocessing; The initial model construction module is used to build a three-dimensional geological structure model based on the preprocessed data. And establish corresponding constraints to obtain a three-dimensional geological model network; A simulation network construction module is used to establish a mapping relationship between the preprocessed data and the real-time three-dimensional geological network model to obtain a simulation network; A simulation result acquisition module, used for performing multi-point statistical random simulation based on the simulation network to obtain multiple simulation output models; The target model acquisition module is used to embed the multiple simulation output models into the three-dimensional geological model network to obtain a target three-dimensional geological model.

9. A three-dimensional geological model construction device, characterized in that: include: Memory for storing computer programs; A processor is used to implement the steps of a three-dimensional geological model construction method as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the three-dimensional geological model construction method according to any one of claims 1 to 7 are implemented.

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