Three-dimensional geologic body spatial interpolation system and method

Abstract

The invention discloses a three-dimensional geologic body spatial interpolation system and method, and belongs to the field of three-dimensional geologic body spatial interpolation, and the system comprises a data collection and judgment module, an interpolation calculation module, a modeling analysis module, a drilling geological point recommendation module, a geological data search and supplement module, and a result output module. The data acquisition and judgment module is used for acquiring drilling geological data, geological profile data, topographic data and geological interface data, setting a matching rule and matching an optimal interpolation algorithm combination; according to the method, accurate matching of geological data and an optimal algorithm, effective processing of abnormal data, rapid positioning of an abnormal area and continuous supplement of key geological information are realized, the accuracy and reliability of three-dimensional geologic body spatial interpolation are remarkably improved, and a powerful technical support is provided for geological exploration and research work.

Description

Technical Field

[0001] The invention belongs to the field of three-dimensional geological body space interpolation, and in particular relates to a three-dimensional geological body space interpolation system and method. Background Art

[0002] In the field of geological exploration and research, accurate acquisition of three-dimensional geological spatial information is crucial for in-depth understanding of underground geological structure, resource distribution, and geological disaster assessment. As a key technical means, three-dimensional geological spatial interpolation has the core goal of reasonably estimating the geological properties of unsampled areas through limited drilling data and geological data, and then constructing a high-precision three-dimensional geological model.

[0003] Traditional three-dimensional geological body spatial interpolation methods have many limitations when facing complex geological conditions. In the selection of interpolation algorithms, they often lack an intelligent matching mechanism and cannot quickly and accurately determine the best interpolation algorithm combination based on known borehole data and geological data. This not only makes it difficult for the interpolation calculation results to be highly consistent with the actual geological conditions, but also reduces the calculation efficiency. In addition, when performing interpolation calculations and modeling, there is often a lack of specific analysis and processing of anomalies, and there is no function of recommending borehole geological points and searching and supplementing related geological data, which hinders the further optimization and improvement of geological models. Therefore, a three-dimensional geological body spatial interpolation system and method are proposed. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art. To this end, the present invention proposes a three-dimensional geological body spatial interpolation system and method, so that relevant personnel can quickly obtain geological attribute data.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions: A three-dimensional geological body spatial interpolation system, including a data acquisition and judgment module, an interpolation calculation module, a modeling and analysis module, a drilling geological point recommendation module, a geological data search and supplement module, and a result output module; The data acquisition and judgment module is used to collect borehole geological data, geological profile data, terrain data and geological interface data, and set matching rules to match the best interpolation algorithm combination; The interpolation calculation module calculates the attribute value of the unknown position in the three-dimensional space according to the known geological data, and transmits the result to the modeling and analysis module when the calculation result is normal, and transmits the abnormality to the geological data search and supplement module when the result is abnormal; The modeling and analysis module constructs a three-dimensional geological body model based on the results obtained by interpolation calculation. When the geological model is abnormal, the abnormality is transmitted to the drilling geological point recommendation module; The drilling geological point recommendation module recommends the best drilling geological point according to the anomaly and collects the geological data of the point. If the data cannot be collected, other drilling geological points are recommended. If the data of other drilling geological points still cannot be collected, the data is transmitted to the geological data search supplement module. The geological data search and supplement module queries the relevant data of the interpolation calculation anomaly and the modeling anomaly, and transmits the data to the data acquisition and matching module; The result output module outputs the results of processing and analysis.

[0006] Furthermore, the data acquisition and judgment module is used to collect borehole geological data, geological profile data, terrain data and geological interface data, and set matching rules to match the best interpolation algorithm combination processing process as follows: Collect borehole geological data including lithology information, stratigraphic layers and physical property parameters, geological profile data including stratigraphic interfaces and structural information, topographic data including terrain elevation information, and geological interface data including stratigraphic boundaries and rock mass boundaries. The data are collected into a unified data set and verified and cleaned. First, the spatial coverage density of the borehole data is calculated. If the number of boreholes per square kilometer is less than 5, it is sparse; if the number of boreholes per square kilometer is greater than or equal to 5 and less than 15, it is medium; and if the number of boreholes per square kilometer is greater than 15, it is dense. Then, the principal axis direction of the data distribution is determined by principal component analysis, and the segmentation status of the borehole distribution area is determined by geological interface data. Finally, according to the formation code or physical property parameter mutation, the vertical layered structure is identified, the consistency between the borehole elevation and the terrain is compared, and the areas with violent terrain fluctuations are marked. When there are faults or discontinuous interfaces in the data, the segmented kriging and natural neighbor method are matched, and the interpolation area is forced to be split, and the two sides of the fault are processed independently; when the boreholes are sparse but the profile data are abundant, the co-kriging and random forest regression are matched, and the profile data are used as auxiliary variables; when the terrain is undulating and is a key constraint, the DEM is used as the interpolation base, and the TIN terrain-driven triangulation and Kriging attribute interpolation are matched; when the vertical stratification is clear, the stratified IDW and stratum thickness constraints are matched, and interpolation is performed according to the stratum layer, and each layer is processed separately; The weights of each algorithm combination are dynamically adjusted based on the drilling data density.

[0007] Furthermore, the process of dynamically adjusting the weights of various algorithm combinations based on the drilling data density is as follows: When the borehole data density of the matching segmented kriging and natural neighbor method is high, segmented kriging is assigned 80% weight and natural neighbor method is assigned 20% weight. When the borehole data density is medium, segmented kriging is assigned 30% to 80% weight and natural neighbor method is assigned 20% to 70% weight according to the borehole density data, and the sum of the two weights is 100%. When the borehole data density is low, segmented kriging is assigned 30% weight and natural neighbor method is assigned 70% weight. When the borehole data density of matching co-kriging and random forest regression is high, co-kriging is assigned 80% weight and random forest regression is assigned 20% weight. When the borehole data density is medium, co-kriging is assigned 40% to 80% weight and random forest regression is assigned 20% to 60% weight according to the borehole density data, and the sum of the two weights is 100%. When the borehole data density is low, co-kriging is assigned 40% weight and random forest regression is assigned 60% weight. When the borehole data density is high, Kerry metal interpolation is assigned a 70% weight and TIN terrain driven triangulation is assigned a 30% weight. When the borehole data density is medium, Kerry metal interpolation is assigned a 45% to 70% weight and TIN terrain driven triangulation is assigned a 30% weight based on the borehole density data, and the sum of the two weights is 100%. When the borehole data density is low, Kerry metal interpolation is assigned a 45% weight and TIN terrain driven triangulation is assigned a 55% weight. When the density of drilling data matching the layered IDW and terrain thickness constraints is high, the layered IDW is assigned a weight of 75% and the terrain thickness constraint is assigned a weight of 25%. When the density of drilling data is medium, the layered IDW is assigned a weight of 35% to 75% and the terrain thickness constraint is assigned a weight of 25% to 65% according to the drilling density data, and the sum of the two weights is 100%. When the density of drilling data is low, the layered IDW is assigned a weight of 35% and the terrain thickness constraint is assigned a weight of 65%.

[0008] When using interpolation algorithm combination calculations, the contribution ratio of different algorithms in the final result is dynamically adjusted according to the density of drilling data, so as to achieve the local optimal interpolation effect.

[0009] Furthermore, the interpolation calculation module calculates the attribute value of the unknown position in the three-dimensional space according to the known geological data. When the calculation result is normal, the result is transmitted to the modeling and analysis module. When the result is abnormal, the abnormality is transmitted to the geological data search and supplement module. The processing process is as follows: Use the matching interpolation algorithm to perform calculations, and preset the interpolation result range threshold and the attribute value change rate threshold between adjacent interpolation points; When the interpolation result exceeds the preset range threshold, it is judged as abnormal; when the interpolation result does not exceed the preset range threshold, the attribute value change rate between adjacent interpolation points is calculated. When the change rate exceeds the preset attribute value change rate threshold between adjacent interpolation points, it is judged as abnormal and the abnormality is transmitted to the geological data search supplement module; when the change rate does not exceed the preset attribute value change rate threshold between adjacent interpolation points, it is judged as normal and the calculation result is transmitted to the modeling analysis module.

[0010] Furthermore, the modeling and analysis module constructs a three-dimensional geological body model based on the results obtained by interpolation calculation. When the geological model is abnormal, the abnormality is transmitted to the drilling geological point recommendation module for processing as follows: First, the interpolation calculation data is input, the interpolation data is converted into a voxel model, and the spatial coordinates and attribute values ​​are stored for each voxel unit; then the isosurface is extracted to construct the continuous boundary surface of the geological body; finally, the extracted isosurface is smoothed and denoised to finally output a three-dimensional solid model that conforms to geological laws; Set anomaly determination rules to automatically determine anomalies. The specific rules are as follows: if the rock layer sequence is inconsistent and the dislocation direction of the layers on both sides of the fault is inconsistent with the geological map, it will be determined as an anomaly; if the attribute value exceeds the preset geological constraint range, it will be determined as an anomaly; if there are isolated fragments and discontinuous structures in the morphology, it will be determined as an anomaly; The abnormal area is determined according to the rules. When there is no abnormality, the data is transmitted to the result output module. When an abnormality is found, the abnormal area is marked, and the centroid coordinates of the abnormal area, the maximum value of the interpolation standard deviation in the abnormal area, and the influence radius are calculated, and the data is output to the drilling geological point recommendation module.

[0011] Furthermore, the borehole geological point recommendation module recommends the best borehole geological point according to the anomaly, and collects the geological data of the point. When the data cannot be collected, other borehole geological points are recommended. When the data of other borehole geological points still cannot be collected, the data is transmitted to the geological data search supplement module. The processing process is as follows: Receive data from the abnormal area. When the abnormality is that the rock layer sequence is inconsistent and the dislocation direction of the strata on both sides of the fault is inconsistent with the geological map, take the coordinates of the fault turning point as the reference, extend 50 meters along the strike direction of the fault before and after the turning, and set the intersection as the best drilling point; when the abnormality is that the attribute value exceeds the preset geological constraint range, take the abnormal extreme point as the starting point, advance 30 meters along the gradient direction, and set this point as the best drilling point; when the abnormality is that there are isolated fragments and discontinuous structures in the morphology, take the boundary point of the fragment as the reference, move toward the center, and the moving distance is ΔX=10⋅cosθ,ΔY=10⋅sinθ, where ΔX and ΔY are the projection components along the X-axis and Y-axis, and θ is the tangent direction angle of the boundary point; Among them, the number of meters advanced can be 10 meters for every 10% change in gradient; After the optimal drilling point is set, the drilling depth safety margin is preset, and the bottom depth of the abnormal body plus the safety margin is set as the drilling depth; The best drilling geological point is output, and it is manually determined whether drilling can be implemented. If drilling can be implemented, the drilling point data is collected for secondary interpolation calculation; if drilling cannot be implemented, other drilling geological points are recommended, and the data of these drilling points are collected for secondary interpolation calculation; When drilling is not possible at all drilling points, the data of the abnormal area will be transmitted to the geological data search supplement module.

[0012] After receiving the data of the abnormal area, the surface projection point of the centroid coordinates of the abnormal area is directly selected as the optimal geological point for drilling, and the safety margin of the drilling depth is preset. The drilling depth is determined by adding the bottom depth of the abnormal body to the margin. This method can accurately locate the key drilling position and ensure that the drilling touches the abnormal body while taking safety into account.

[0013] Furthermore, when drilling cannot be implemented, other drilling geological points are recommended, and the data of these drilling points are collected and processed by secondary interpolation calculation as follows: Taking the centroid of the original recommended point as the center, expand the circular buffer outward and generate candidate points in the buffer according to the polar coordinate grid; Calculate the interpolation variance reduction of the candidate points , the maximum variance reduction among all candidate points , the Euclidean distance from the candidate point to the centroid of the original abnormal area and the maximum allowed offset distance , and calculate the scores of candidate points based on these data , the specific formula is: ; in, They are the weight coefficients of distance priority and variance optimization priority, and need to satisfy ; Sort the calculated scoring results, output the top three scoring data points as recommended drilling points, and output the recommended drilling points; It is manually determined whether drilling can be carried out at the drilling point. If drilling can be carried out, the data of the drilling point is collected for secondary interpolation calculation.

[0014] Furthermore, the geological data search and supplement module queries the relevant data of the interpolation calculation anomaly and the modeling anomaly, and transmits the data to the data acquisition and matching module for processing as follows: Receive interpolation calculation anomalies and search for historical exploration data, geophysical data, remote sensing topographic data, geological maps and engineering disclosure data. Historical exploration data include descriptions of unused drill cores, logging curves and test data within a 500-meter radius with the anomaly as the center; geophysical data include magnetic method, gravity anomaly map and ground electrical profile with a grid accuracy of 50 meters; remote sensing and topographic data include 1-meter resolution LiDAR point cloud, hyperspectral image and InSAR deformation data; geological maps and engineering disclosure data include extraction of faults, lithology boundaries, adjacent tunnels, rock mass structural surface statistics of mine catalogs and logging parameters of engineering boreholes in 1:10,000 geological maps; Receive modeling anomaly data. When the anomaly is the inconsistency of the rock layer sequence and the inconsistency between the dislocation direction of the strata on both sides of the fault and the geological map, search and obtain fault kinematic data, stratigraphic marker layer data and tectonic stress field data. Fault kinematic data include fault scratch direction and step structure photos extracted from geological literature or structural analysis reports. Stratigraphic marker layer data include drilling column charts within a radius of 500 meters in the anomaly area, and the depth and lithology description of the key marker layer are extracted from the column chart. Tectonic stress field data include regional tectonic stress field analysis results; When the anomaly is an attribute value that exceeds the preset geological constraint range, the core geochemical data, alteration-mineralization zoning map, and dynamic monitoring data are searched and obtained. The core geochemical data include the core test results of the boreholes adjacent to the anomaly area extracted from the historical exploration database. The alteration-mineralization zoning map includes the alteration mineral mapping data and geochemical element contour map of the mining area. The dynamic monitoring data includes the monitoring records of groundwater level, ground temperature or gas concentration. When the anomaly is in the form of isolated fragments or discontinuous structures, high-resolution remote sensing data, engineering disclosure data, and geophysical anomaly verification data are searched and obtained. High-resolution remote sensing data include LiDAR point clouds and multispectral images. Engineering disclosure data include geological catalogs of tunnels and mines within 1 km, and extract rock mass structural surface statistics and lithologic contact zone locations. Geophysical anomaly verification data include ground high-density electrical or magnetic profile data. The queried data is transferred to the data collection and matching module.

[0015] A three-dimensional geological body spatial interpolation method, the specific steps are: S1. Collect existing drilling data and geological data, and determine the best interpolation algorithm combination based on the drilling data density and geological data, and dynamically adjust the interpolation algorithm weight; S2. Calculate the interpolation results according to the algorithm combination and analyze the interpolation results. When the interpolation results are abnormal, search for abnormal related data and perform secondary interpolation calculations to optimize the interpolation results. When the interpolation results are normal, use the calculation results for modeling. S3, analyzing the modeling, outputting the results when there is no abnormality in the modeling, locating the abnormal area when there is an abnormality in the modeling, generating the best drilling geological point based on the abnormal area, and collecting data of the point for secondary calculation modeling. When the best geological point cannot be used, recommending other geological points and performing data collection and calculation modeling; S4. When drilling is not possible, search for relevant data in the abnormal area and perform secondary calculation modeling based on the relevant data Compared with the prior art, the present invention has the following beneficial effects: The present invention sets a data acquisition and matching module, which can firstly quickly and accurately match the best interpolation algorithm combination according to the known drilling data and geological data, so that the interpolation calculation is highly consistent with the actual geological conditions, greatly improving the accuracy of the interpolation result. Secondly, the module can also dynamically allocate weights to the interpolation algorithm according to the coverage density of the drilling data, and adjust the contribution ratio of different algorithms in the final result, which can not only avoid errors caused by uneven data distribution, but also achieve a locally optimal interpolation effect. The present invention sets an interpolation calculation module, which can quickly identify interpolation results that obviously deviate from the normal range by presetting the range threshold, and timely screen out abnormal situations to avoid interference with subsequent analysis due to abnormal data, thereby ensuring the reliability of data. When the interpolation result does not exceed the range threshold, the attribute value change rate is further calculated and compared with the preset change rate threshold, which can dig out potential abnormal changes, thereby effectively identifying subtle but key abnormal features in the data; The present invention sets a modeling and analysis module, which can automatically identify anomalies comprehensively and accurately through the set anomaly judgment rules. When an anomaly is found, the abnormal area can also be quickly located; by calculating the centroid coordinates, the maximum value of the interpolation standard deviation and the influence radius, it can also provide a strong basis for subsequent steps; The present invention sets a borehole geological point recommendation module, which can accurately recommend the best borehole geological point according to the modeled abnormal area. When the geological data of the point can be collected, the purpose of further optimizing the geological model is achieved. When the data of the best borehole geological point cannot be collected, other borehole geological points will be recommended to ensure that key geological information can be continuously supplemented and the continuity of exploration work is maintained; when the data of other recommended borehole geological points still cannot be collected, the data can also be timely transmitted to the geological data search and supplement module, and the key data can be supplemented by searching for relevant data of the abnormal area; The present invention can supplement the analysis of the anomalies of the interpolation calculation module and the modeling analysis module by setting a geological data search and supplement module. When an anomaly occurs in the interpolation calculation module, data search and data supplement will be performed according to the interpolation calculation anomaly, effectively ensuring the integrity and continuity of the data. This not only improves the accuracy of the interpolation calculation results, but also avoids erroneous analysis caused by data missing or anomalies, and also ensures that subsequent modeling analysis is based on reliable data. When anomalies occur in the modeling analysis module, data will be supplemented according to the modeling anomalies. When the anomalies are manifested as inconsistent rock layer sequences and inconsistent stratum dislocation directions on both sides of the fault with the geological map, by obtaining fault kinematic data, stratigraphic marker layer data, and tectonic stress field data, the geological tectonic movement process can be analyzed more accurately, the real tectonic scenes of the geological history period can be restored, and modeling deviations can be corrected. When the anomaly is an attribute value that exceeds the preset geological constraint range, the core geochemical data, alteration-mineralization zoning map, and dynamic monitoring data are searched and obtained, which can deeply understand the material composition, chemical property changes, and dynamic evolution process of the geological body, provide key basis for correcting the model attribute parameters, and make the model more in line with the actual geological conditions; when the anomaly is an isolated fragment or discontinuous structure, high-resolution remote sensing data, engineering exposure data, and geophysical anomaly verification data are searched and obtained, which can fully characterize the geological body morphology from macro to micro, fill the gaps in the model's structural morphology description, and build a more complete and realistic geological model; In summary, the present invention first collects geological data, can quickly match the corresponding interpolation algorithm combination according to the geological data, and can realize dynamic adjustment of the algorithm weight according to the drilling data, so as to realize the matching of geological data with the optimal algorithm; when an abnormality occurs in the interpolation calculation, the relevant geological data can be searched for supplement according to the specific abnormality to realize the optimization of the interpolation calculation steps; when an abnormality occurs in the modeling, the abnormal area can be located, and the best drilling geological point can be recommended according to the abnormal area. When the best drilling geological point cannot collect data, other drilling geological points will be recommended. When other geological points still cannot collect data, the geological point data will be searched and supplemented, so as to achieve the effect of further improving the geological information. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A block diagram of a three-dimensional geological body spatial interpolation system of the present invention; Figure 2 This is a result output diagram of a three-dimensional geological body spatial interpolation system of the present invention. DETAILED DESCRIPTION

[0017] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. 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 creative work are within the scope of protection of the present invention.

[0018] like Figure 1As shown, a three-dimensional geological body space interpolation system includes a data acquisition and judgment module, an interpolation calculation module, a modeling and analysis module, a drilling geological point recommendation module, a geological data search and supplement module, and a result output module; The data acquisition and judgment module is used to collect borehole geological data, geological profile data, terrain data and geological interface data, and set matching rules to match the best interpolation algorithm combination; In this embodiment, the data acquisition and judgment module is used to collect borehole geological data, geological profile data, terrain data and geological interface data, and set matching rules. The matching best interpolation algorithm combination processing process is as follows: Collect borehole geological data including lithology information, stratigraphic layers and physical property parameters, geological profile data including stratigraphic interfaces and structural information, topographic data including terrain elevation information, and geological interface data including stratigraphic boundaries and rock mass boundaries. The data are collected into a unified data set and verified and cleaned. First, the spatial coverage density of the borehole data is calculated. If the number of boreholes per square kilometer is less than 5, it is sparse; if the number of boreholes per square kilometer is greater than or equal to 5 and less than 15, it is medium; and if the number of boreholes per square kilometer is greater than 15, it is dense. Then, the principal axis direction of the data distribution is determined by principal component analysis, and the segmentation status of the borehole distribution area is determined by geological interface data. Finally, according to the formation code or physical property parameter mutation, the vertical layered structure is identified, the consistency between the borehole elevation and the terrain is compared, and the areas with violent terrain fluctuations are marked. When there are faults or discontinuous interfaces in the data, the segmented kriging and natural neighbor method are matched, and the interpolation area is forced to be split, and the two sides of the fault are processed independently; when the boreholes are sparse but the profile data are abundant, the co-kriging and random forest regression are matched, and the profile data are used as auxiliary variables; when the terrain is undulating and is a key constraint, the DEM is used as the interpolation base, and the TIN terrain-driven triangulation and Kriging attribute interpolation are matched; when the vertical stratification is clear, the stratified IDW and stratum thickness constraints are matched, and interpolation is performed according to the stratum layer, and each layer is processed separately; The weights of each algorithm combination are dynamically adjusted based on the drilling data density.

[0019] In this embodiment, the process of dynamically adjusting the weights of various algorithm combinations based on the drilling data density is as follows: When the borehole data density of the matching segmented kriging and natural neighbor method is high, segmented kriging is assigned 80% weight and natural neighbor method is assigned 20% weight. When the borehole data density is medium, segmented kriging is assigned 30% to 80% weight and natural neighbor method is assigned 20% to 70% weight according to the borehole density data, and the sum of the two weights is 100%. When the borehole data density is low, segmented kriging is assigned 30% weight and natural neighbor method is assigned 70% weight. When the borehole data density of matching co-kriging and random forest regression is high, co-kriging is assigned 80% weight and random forest regression is assigned 20% weight. When the borehole data density is medium, co-kriging is assigned 40% to 80% weight and random forest regression is assigned 20% to 60% weight according to the borehole density data, and the sum of the two weights is 100%. When the borehole data density is low, co-kriging is assigned 40% weight and random forest regression is assigned 60% weight. When the borehole data density is high, Kerry metal interpolation is assigned a 70% weight and TIN terrain driven triangulation is assigned a 30% weight. When the borehole data density is medium, Kerry metal interpolation is assigned a 45% to 70% weight and TIN terrain driven triangulation is assigned a 30% weight based on the borehole density data, and the sum of the two weights is 100%. When the borehole data density is low, Kerry metal interpolation is assigned a 45% weight and TIN terrain driven triangulation is assigned a 55% weight. When the density of drilling data matching the layered IDW and terrain thickness constraints is high, the layered IDW is assigned a weight of 75% and the terrain thickness constraint is assigned a weight of 25%. When the density of drilling data is medium, the layered IDW is assigned a weight of 35% to 75% and the terrain thickness constraint is assigned a weight of 25% to 65% according to the drilling density data, and the sum of the two weights is 100%. When the density of drilling data is low, the layered IDW is assigned a weight of 35% and the terrain thickness constraint is assigned a weight of 65%.

[0020] It should be noted that the contribution ratio of different algorithms in the final result is dynamically adjusted according to the density of drilling data, so that the interpolation result is more in line with the actual situation and the accuracy is improved; in data sparse areas, by reasonably adjusting the algorithm contribution and using the advantages of other algorithms to supplement information, large errors and unreasonable interpolation results can be avoided, thereby enhancing the stability and reliability of interpolation.

[0021] The interpolation calculation module calculates the attribute value of the unknown position in the three-dimensional space according to the known geological data. When the calculation result is normal, the result is transmitted to the modeling and analysis module. When the result is abnormal, the abnormality is transmitted to the geological data search and supplement module. In this embodiment, the interpolation calculation module calculates the attribute value of the unknown position in the three-dimensional space according to the known geological data. When the calculation result is normal, the result is transmitted to the modeling and analysis module. When the result is abnormal, the abnormality is transmitted to the geological data search and supplement module. The processing process is as follows: Use the matching interpolation algorithm to perform calculations, and preset the interpolation result range threshold and the attribute value change rate threshold between adjacent interpolation points; When the interpolation result exceeds the preset range threshold, it is judged as abnormal; when the interpolation result does not exceed the preset range threshold, the attribute value change rate between adjacent interpolation points is calculated. When the change rate exceeds the preset attribute value change rate threshold between adjacent interpolation points, it is judged as abnormal and the abnormality is transmitted to the geological data search supplement module; when the change rate does not exceed the preset attribute value change rate threshold between adjacent interpolation points, it is judged as normal and the calculation result is transmitted to the modeling analysis module.

[0022] The modeling and analysis module constructs a three-dimensional geological model based on the results of interpolation calculation. When the geological model is abnormal, the abnormality is transmitted to the drilling geological point recommendation module; In this embodiment, the modeling and analysis module constructs a three-dimensional geological body model based on the results obtained by interpolation calculation. When the geological model is abnormal, the abnormality is transmitted to the drilling geological point recommendation module for processing as follows: First, the interpolation calculation data is input, the interpolation data is converted into a voxel model, and the spatial coordinates and attribute values ​​are stored for each voxel unit; then the isosurface is extracted to construct the continuous boundary surface of the geological body; finally, the extracted isosurface is smoothed and denoised to finally output a three-dimensional solid model that conforms to geological laws; Set anomaly determination rules to automatically determine anomalies. The specific rules are as follows: if the rock layer sequence is inconsistent and the dislocation direction of the layers on both sides of the fault is inconsistent with the geological map, it will be determined as an anomaly; if the attribute value exceeds the preset geological constraint range, it will be determined as an anomaly; if there are isolated fragments and discontinuous structures in the morphology, it will be determined as an anomaly; The abnormal area is determined according to the rules. When there is no abnormality, the data is transmitted to the result output module. When an abnormality is found, the abnormal area is marked, and the centroid coordinates of the abnormal area, the maximum value of the interpolation standard deviation in the abnormal area, and the influence radius are calculated, and the data is output to the drilling geological point recommendation module.

[0023] It should be noted that the phenomenon of normal interpolation calculation data and modeling anomalies is particularly common in geological modeling. Therefore, it is necessary to judge modeling anomalies. Judging modeling anomalies can more intuitively understand the problems in the model. And the abnormal position can be quickly located through the existing problems, which is also convenient for targeted optimization and improvement, so as to achieve the purpose of improving the quality and accuracy of three-dimensional modeling.

[0024] The drilling geological point recommendation module recommends the best drilling geological point according to the anomaly and collects the geological data of the point. If the data cannot be collected, other drilling geological points are recommended. If the data of other drilling geological points still cannot be collected, the data is transmitted to the geological data search supplement module; In this embodiment, the borehole geological point recommendation module recommends the best borehole geological point according to the anomaly and collects the geological data of the point. When the data cannot be collected, other borehole geological points are recommended. When the data of other borehole geological points still cannot be collected, the data is transmitted to the geological data search supplement module. The processing process is as follows: Receive data from the abnormal area. When the abnormality is that the rock layer sequence is inconsistent and the dislocation direction of the strata on both sides of the fault is inconsistent with the geological map, take the coordinates of the fault turning point as the reference, extend 50 meters along the strike direction of the fault before and after the turning, and set the intersection as the best drilling point; when the abnormality is that the attribute value exceeds the preset geological constraint range, take the abnormal extreme point as the starting point, advance 30 meters along the gradient direction, and set this point as the best drilling point; when the abnormality is that there are isolated fragments and discontinuous structures in the morphology, take the boundary point of the fragment as the reference, move toward the center, and the moving distance is ΔX=10⋅cosθ,ΔY=10⋅sinθ, where ΔX and ΔY are the projection components along the X-axis and Y-axis, and θ is the tangent direction angle of the boundary point; After the optimal drilling point is set, the drilling depth safety margin is preset, and the bottom depth of the abnormal body plus the safety margin is set as the drilling depth; The best drilling geological point is output, and it is manually determined whether drilling can be implemented. If drilling can be implemented, the drilling point data is collected for secondary interpolation calculation; if drilling cannot be implemented, other drilling geological points are recommended, and the data of these drilling points are collected for secondary interpolation calculation; When drilling is not possible at all drilling points, the data of the abnormal area will be transmitted to the geological data search supplement module.

[0025] It should be noted that by collecting the best drilling geological points and performing secondary interpolation calculations based on the collected data, the geological model can be effectively optimized and the interpolation accuracy can be improved. When the best drilling geological points cannot be drilled, other drilling points will be recommended and data will be collected at these drilling points. This method can ensure the continuity of geological exploration work, thereby facilitating the provision of sufficient and complete information for the optimization of the geological model.

[0026] In this embodiment, when drilling cannot be implemented, other drilling geological points are recommended, and the data of these drilling points are collected and the secondary interpolation calculation process is as follows: Taking the centroid of the original recommended point as the center, expand the circular buffer outward and generate candidate points in the buffer according to the polar coordinate grid; Calculate the interpolation variance reduction of the candidate points , the maximum variance reduction among all candidate points , the Euclidean distance from the candidate point to the centroid of the original abnormal area and the maximum allowed offset distance , and calculate the scores of candidate points based on these data , the specific formula is: ; in, They are the weight coefficients of distance priority and variance optimization priority, and need to satisfy ; Sort the calculated scoring results, output the top three scoring data points as recommended drilling points, and output the recommended drilling points; It is manually determined whether drilling can be carried out at the drilling point. If drilling can be carried out, the data of the drilling point is collected for secondary interpolation calculation.

[0027] The geological data search and supplement module queries the relevant data of interpolation calculation anomalies and modeling anomalies, and transmits the data to the data acquisition and matching module; In this embodiment, the geological data search supplement module queries the relevant data of interpolation calculation anomalies and modeling anomalies, and transmits the data to the data acquisition and matching module for processing as follows: Receive interpolation calculation anomalies and search for historical exploration data, geophysical data, remote sensing topographic data, geological maps and engineering disclosure data. Historical exploration data include descriptions of unused drill cores, logging curves and test data within a 500-meter radius with the anomaly as the center; geophysical data include magnetic method, gravity anomaly map and ground electrical profile with a grid accuracy of 50 meters; remote sensing and topographic data include 1-meter resolution LiDAR point cloud, hyperspectral image and InSAR deformation data; geological maps and engineering disclosure data include extraction of faults, lithology boundaries, adjacent tunnels, rock mass structural surface statistics of mine catalogs and logging parameters of engineering boreholes in 1:10,000 geological maps; Receive modeling anomaly data. When the anomaly is the inconsistency of the rock layer sequence and the inconsistency between the dislocation direction of the strata on both sides of the fault and the geological map, search and obtain fault kinematic data, stratigraphic marker layer data and tectonic stress field data. Fault kinematic data include fault scratch direction and step structure photos extracted from geological literature or structural analysis reports. Stratigraphic marker layer data include drilling column charts within a radius of 500 meters in the anomaly area, and the depth and lithology description of the key marker layer are extracted from the column chart. Tectonic stress field data include regional tectonic stress field analysis results; When the anomaly is an attribute value that exceeds the preset geological constraint range, the core geochemical data, alteration-mineralization zoning map, and dynamic monitoring data are searched and obtained. The core geochemical data include the core test results of the boreholes adjacent to the anomaly area extracted from the historical exploration database. The alteration-mineralization zoning map includes the alteration mineral mapping data and geochemical element contour map of the mining area. The dynamic monitoring data includes the monitoring records of groundwater level, ground temperature or gas concentration. When the anomaly is in the form of isolated fragments or discontinuous structures, high-resolution remote sensing data, engineering disclosure data, and geophysical anomaly verification data are searched and obtained. High-resolution remote sensing data include LiDAR point clouds and multispectral images. Engineering disclosure data include geological catalogs of tunnels and mines within 1 km, and extract rock mass structural surface statistics and lithologic contact zone locations. Geophysical anomaly verification data include ground high-density electrical or magnetic profile data. The queried data is transferred to the data collection and matching module.

[0028] It should be noted that after the query data is transmitted to the data collection and matching module, it will be transmitted again to the interpolation calculation module for secondary calculation. This process can supplement more complete and relevant data based on anomalies, thereby providing a more reliable input basis for secondary interpolation.

[0029] The result output module outputs the results of processing and analysis.

[0030] A three-dimensional geological body spatial interpolation method, the specific steps are: S1. Collect existing drilling data and geological data, and determine the best interpolation algorithm combination based on the drilling data density and geological data, and dynamically adjust the interpolation algorithm weight; S2. Calculate the interpolation results according to the algorithm combination and analyze the interpolation results. When the interpolation results are abnormal, search for abnormal related data and perform secondary interpolation calculations to optimize the interpolation results. When the interpolation results are normal, use the calculation results for modeling. S3, analyzing the modeling, outputting the results when there is no abnormality in the modeling, locating the abnormal area when there is an abnormality in the modeling, generating the best drilling geological point based on the abnormal area, and collecting data of the point for secondary calculation modeling. When the best geological point cannot be used, recommending other geological points and performing data collection and calculation modeling; S4. When drilling is not possible, search for relevant data in the abnormal area and perform secondary calculation modeling based on the relevant data.

[0031] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A three-dimensional geological body spatial interpolation system, characterized in that: It includes data collection and judgment module, interpolation calculation module, modeling analysis module, drilling geological point recommendation module, geological data search and supplement module, and result output module; The data acquisition and judgment module is used to collect borehole geological data, geological profile data, terrain data and geological interface data, and set matching rules to match the best interpolation algorithm combination; The interpolation calculation module calculates the attribute value of the unknown position in the three-dimensional space according to the known geological data, and transmits the result to the modeling and analysis module when the calculation result is normal, and transmits the abnormality to the geological data search and supplement module when the result is abnormal; The modeling and analysis module constructs a three-dimensional geological body model based on the results obtained by interpolation calculation. When the geological model is abnormal, the abnormality is transmitted to the drilling geological point recommendation module; The drilling geological point recommendation module recommends the best drilling geological point according to the anomaly and collects the geological data of the point. If the data cannot be collected, other drilling geological points are recommended. If the data of other drilling geological points still cannot be collected, the data is transmitted to the geological data search supplement module. The geological data search and supplement module queries the relevant data of the interpolation calculation anomaly and the modeling anomaly, and transmits the data to the data acquisition and matching module; The result output module outputs the results of processing and analysis.

2. A three-dimensional geological body spatial interpolation system according to claim 1, characterized in that: The data acquisition and judgment module is used to collect borehole geological data, geological profile data, terrain data and geological interface data, and set matching rules. The matching best interpolation algorithm combination processing process is as follows: Collect borehole geological data including lithology information, stratigraphic layers and physical property parameters, geological profile data including stratigraphic interfaces and structural information, topographic data including terrain elevation information, and geological interface data including stratigraphic boundaries and rock mass boundaries. The data are collected into a unified data set and verified and cleaned. First, the spatial coverage density of the borehole data is calculated. If the number of boreholes per square kilometer is less than 5, it is sparse; if the number of boreholes per square kilometer is greater than or equal to 5 and less than 15, it is medium; and if the number of boreholes per square kilometer is greater than 15, it is dense. Then, the principal axis direction of the data distribution is determined by principal component analysis, and the segmentation status of the borehole distribution area is determined by geological interface data. Finally, according to the formation code or physical property parameter mutation, the vertical layered structure is identified, the consistency between the borehole elevation and the terrain is compared, and the areas with violent terrain fluctuations are marked. When there are faults or discontinuous interfaces in the data, the segmented kriging and natural neighbor method are matched, and the interpolation area is forced to be split, and the two sides of the fault are processed independently; when the boreholes are sparse but the profile data are abundant, the co-kriging and random forest regression are matched, and the profile data are used as auxiliary variables; when the terrain is undulating and is a key constraint, the DEM is used as the interpolation base, and the TIN terrain-driven triangulation and Kriging attribute interpolation are matched; when the vertical stratification is clear, the stratified IDW and stratum thickness constraints are matched, and interpolation is performed according to the stratum layer, and each layer is processed separately; The weights of each algorithm combination are dynamically adjusted based on the drilling data density.

3. A three-dimensional geological body spatial interpolation system according to claim 2, characterized in that: The process of dynamically adjusting the weights of various algorithm combinations based on drilling data density is as follows: When the borehole data density of the matching segmented kriging and natural neighbor method is high, segmented kriging is assigned 80% weight and natural neighbor method is assigned 20% weight. When the borehole data density is medium, segmented kriging is assigned 30% to 80% weight and natural neighbor method is assigned 20% to 70% weight according to the borehole density data, and the sum of the two weights is 100%. When the borehole data density is low, segmented kriging is assigned 30% weight and natural neighbor method is assigned 70% weight. When the borehole data density of matching co-kriging and random forest regression is high, co-kriging is assigned 80% weight and random forest regression is assigned 20% weight. When the borehole data density is medium, co-kriging is assigned 40% to 80% weight and random forest regression is assigned 20% to 60% weight according to the borehole density data, and the sum of the two weights is 100%. When the borehole data density is low, co-kriging is assigned 40% weight and random forest regression is assigned 60% weight. When the borehole data density is high, Kerry metal interpolation is assigned a 70% weight and TIN terrain driven triangulation is assigned a 30% weight. When the borehole data density is medium, Kerry metal interpolation is assigned a 45% to 70% weight and TIN terrain driven triangulation is assigned a 30% weight based on the borehole density data, and the sum of the two weights is 100%. When the borehole data density is low, Kerry metal interpolation is assigned a 45% weight and TIN terrain driven triangulation is assigned a 55% weight. When the density of drilling data matching the layered IDW and terrain thickness constraints is high, the layered IDW is assigned a weight of 75% and the terrain thickness constraint is assigned a weight of 25%. When the density of drilling data is medium, the layered IDW is assigned a weight of 35% to 75% and the terrain thickness constraint is assigned a weight of 25% to 65% according to the drilling density data, and the sum of the two weights is 100%. When the density of drilling data is low, the layered IDW is assigned a weight of 35% and the terrain thickness constraint is assigned a weight of 65%.

4. A three-dimensional geological body spatial interpolation system according to claim 1, characterized in that: The interpolation calculation module calculates the attribute value of the unknown position in the three-dimensional space according to the known geological data. When the calculation result is normal, the result is transmitted to the modeling and analysis module. When the result is abnormal, the abnormality is transmitted to the geological data search and supplement module. The processing process is as follows: Use the matching interpolation algorithm to perform calculations, and preset the interpolation result range threshold and the attribute value change rate threshold between adjacent interpolation points; When the interpolation result exceeds the preset range threshold, it is judged as abnormal; when the interpolation result does not exceed the preset range threshold, the attribute value change rate between adjacent interpolation points is calculated. When the change rate exceeds the preset attribute value change rate threshold between adjacent interpolation points, it is judged as abnormal and the abnormality is transmitted to the geological data search supplement module; when the change rate does not exceed the preset attribute value change rate threshold between adjacent interpolation points, it is judged as normal and the calculation result is transmitted to the modeling analysis module.

5. A three-dimensional geological body spatial interpolation system according to claim 1, characterized in that: The modeling and analysis module constructs a three-dimensional geological body model based on the results obtained by interpolation calculation. When the geological model is abnormal, the abnormality is transmitted to the drilling geological point recommendation module for processing as follows: First, the interpolation calculation data is input, the interpolation data is converted into a voxel model, and the spatial coordinates and attribute values ​​are stored for each voxel unit; then the isosurface is extracted to construct the continuous boundary surface of the geological body; finally, the extracted isosurface is smoothed and denoised to finally output a three-dimensional solid model that conforms to geological laws; Set anomaly determination rules to automatically determine anomalies. The specific rules are: if the rock layer sequence is inconsistent and the dislocation direction of the layers on both sides of the fault is inconsistent with the geological map, it will be determined as an anomaly; Attribute values ​​that exceed the preset geological constraints are judged as abnormal; The morphology contains isolated fragments and discontinuous structures, which are considered abnormal; The abnormal area is determined according to the rules. When there is no abnormality, the data is transmitted to the result output module. When an abnormality is found, the abnormal area is marked, and the centroid coordinates of the abnormal area, the maximum value of the interpolation standard deviation in the abnormal area, and the influence radius are calculated, and the data is output to the drilling geological point recommendation module.

6. A three-dimensional geological body spatial interpolation system according to claim 1, characterized in that: The drilling geological point recommendation module recommends the best drilling geological point according to the anomaly and collects the geological data of the point. If the data cannot be collected, other drilling geological points are recommended. If the data of other drilling geological points still cannot be collected, the data is transmitted to the geological data search supplement module. The processing process is as follows: Receive data from the abnormal area. When the abnormality is that the rock layer sequence is inconsistent and the dislocation direction of the strata on both sides of the fault is inconsistent with the geological map, take the coordinates of the fault turning point as the reference, extend 50 meters along the strike direction of the fault before and after the turning, and set the intersection as the best drilling point; when the abnormality is that the attribute value exceeds the preset geological constraint range, take the abnormal extreme point as the starting point, advance 30 meters along the gradient direction, and set this point as the best drilling point; when the abnormality is that there are isolated fragments and discontinuous structures in the morphology, take the boundary point of the fragment as the reference, move toward the center, and the moving distance is ΔX=10⋅cosθ,ΔY=10⋅sinθ, where ΔX and ΔY are the projection components along the X-axis and Y-axis, and θ is the tangent direction angle of the boundary point; After the optimal drilling point is set, the drilling depth safety margin is preset, and the bottom depth of the abnormal body plus the safety margin is set as the drilling depth; The best drilling geological point is output, and it is manually determined whether drilling can be implemented. If drilling can be implemented, the drilling point data is collected for secondary interpolation calculation; if drilling cannot be implemented, other drilling geological points are recommended, and the data of these drilling points are collected for secondary interpolation calculation; When drilling is not possible at all drilling points, the data of the abnormal area will be transmitted to the geological data search supplement module.

7. A three-dimensional geological body spatial interpolation system according to claim 6, characterized in that: When drilling cannot be implemented, other drilling geological points are recommended, and the data of these drilling points are collected for secondary interpolation calculation and processing as follows: Taking the centroid of the original recommended point as the center, expand the circular buffer outward and generate candidate points in the buffer according to the polar coordinate grid; Calculate the interpolation variance reduction of the candidate points , the maximum variance reduction among all candidate points , the Euclidean distance from the candidate point to the centroid of the original abnormal area and the maximum allowed offset distance , and calculate the scores of candidate points based on these data , the specific formula is: ； in, They are the weight coefficients of distance priority and variance optimization priority, and need to satisfy ; Sort the calculated scoring results, output the top three scoring data points as recommended drilling points, and output the recommended drilling points; It is manually determined whether drilling can be carried out at the drilling point. If drilling can be carried out, the data of the drilling point is collected for secondary interpolation calculation.

8. A three-dimensional geological body spatial interpolation system according to claim 1, characterized in that: The geological data search and supplement module queries the relevant data of interpolation calculation anomalies and modeling anomalies, and transmits the data to the data acquisition and matching module for processing as follows: Receive interpolation calculation anomalies and search for historical exploration data, geophysical data, remote sensing topographic data, geological maps and engineering exposure data. Historical exploration data include descriptions of unused drill cores, logging curves and test data within a 500-meter radius centered on the anomaly point; geophysical data include magnetic method, gravity anomaly map and ground electrical profile with a 50-meter grid accuracy; remote sensing and topographic data include 1-meter resolution LiDAR point cloud, hyperspectral imagery and InSAR deformation data; Geological maps and engineering exposure data include extraction of faults, lithology boundaries, adjacent tunnels, rock mass structural surface statistics and logging parameters of engineering boreholes from 1:10,000 geological maps; Receive modeling anomaly data. When the anomaly is the inconsistency of the rock layer sequence and the inconsistency between the dislocation direction of the strata on both sides of the fault and the geological map, search and obtain fault kinematic data, stratigraphic marker layer data and tectonic stress field data. Fault kinematic data include fault scratch direction and step structure photos extracted from geological literature or structural analysis reports. Stratigraphic marker layer data include drilling column charts within a radius of 500 meters in the anomaly area, and the depth and lithology description of the key marker layer are extracted from the column chart. Tectonic stress field data include regional tectonic stress field analysis results; When the anomaly is an attribute value that exceeds the preset geological constraint range, the core geochemical data, alteration-mineralization zoning map, and dynamic monitoring data are searched and obtained. The core geochemical data include the core test results of the boreholes adjacent to the anomaly area extracted from the historical exploration database. The alteration-mineralization zoning map includes the alteration mineral mapping data and geochemical element contour map of the mining area. The dynamic monitoring data includes the monitoring records of groundwater level, ground temperature or gas concentration. When the anomaly is in the form of isolated fragments or discontinuous structures, high-resolution remote sensing data, engineering disclosure data, and geophysical anomaly verification data are searched and obtained. High-resolution remote sensing data include LiDAR point clouds and multispectral images. Engineering disclosure data include geological catalogs of tunnels and mines within 1 km, and extract rock mass structural surface statistics and lithologic contact zone locations. Geophysical anomaly verification data include ground high-density electrical or magnetic profile data. The queried data is transferred to the data collection and matching module.

9. A three-dimensional geological body spatial interpolation method, characterized in that: The method adopts a three-dimensional geological body spatial interpolation system as described in any one of claims 1 to 8, and the specific steps are: S1. Collect existing drilling data and geological data, and determine the best interpolation algorithm combination based on the drilling data density and geological data, and dynamically adjust the interpolation algorithm weight; S2. Calculate the interpolation results according to the algorithm combination and analyze the interpolation results. When the interpolation results are abnormal, search for abnormal related data and perform secondary interpolation calculations to optimize the interpolation results. When the interpolation results are normal, use the calculation results for modeling. S3, analyzing the modeling, outputting the results when there is no abnormality in the modeling, locating the abnormal area when there is an abnormality in the modeling, generating the best drilling geological point based on the abnormal area, and collecting data of the point for secondary calculation modeling. When the best geological point cannot be used, recommending other geological points and performing data collection and calculation modeling; S4. When drilling is not possible, search for relevant data in the abnormal area and perform secondary calculation modeling based on the relevant data.

Images