A city built-up area geological survey whole-process control method, system, device and medium

Abstract

The application discloses a kind of urban built-up area geological survey whole-process control method, system, equipment and medium, mainly related to geological survey technical field, to solve the problem that existing scheme is difficult to rely on underground structure data to realize collaborative collection dimension design and investigation area accurate division, stratum feature analysis lacks multidimensional environment acquisition data system support, lack of model dynamic replacement mechanism based on real-time environmental data. Including: based on the value range of underground structure data and stratum feature data, generate corresponding constraint condition;According to underground structure data, stratum feature data and constraint condition, construct geological three-dimensional model;When the threshold value comparison result of real-time environmental acquisition data corresponding to collaborative collection dimension triggers the preset replacement condition, project the latest real-time environmental acquisition data corresponding to collaborative collection dimension into geological three-dimensional model.

Description

Technical Field

[0001] This application relates to the field of geological survey technology, and in particular to a method, system, equipment and medium for the whole process control of geological surveys in urban built-up areas. Background Technology

[0002] With the acceleration of urbanization in my country, the intensity of underground space development in urban built-up areas continues to increase, raising the requirements for the refinement and full-process control of geological surveys. Existing urban geological survey technologies mostly focus on independent links such as single drilling and conventional data modeling, and generally adopt traditional static survey models. For scenarios such as collaborative surveys of dense underground structures in urban built-up areas, multi-source data fusion, and dynamic updates of 3D models, a suitable full-process technical system has not yet been formed.

[0003] Existing technologies struggle to leverage underground structure data for collaborative data collection, dimensional design, and precise regional delineation, failing to meet the survey needs of complex underground spaces in built-up areas. Stratigraphic feature analysis lacks systematic support from multi-dimensional environmental data collection, and geological modeling fails to adequately construct constraints on underground structures and stratigraphic features, limiting model accuracy. Furthermore, the lack of a dynamic model update mechanism based on real-time environmental data results in mostly static and fixed survey findings, making it difficult to meet the refined geological support requirements of high-density urban development. Summary of the Invention

[0004] This application provides a method, system, equipment, and medium for the whole-process control of geological surveys in urban built-up areas, in order to solve the problems of existing schemes, such as difficulty in achieving collaborative data acquisition dimensional design and accurate division of survey areas based on underground structure data, lack of system support for stratigraphic feature analysis based on multi-dimensional environmental data acquisition, and lack of a dynamic model update mechanism based on real-time environmental data.

[0005] Firstly, this application provides a method for controlling the entire process of geological surveys in urban built-up areas, the method including: Acquire underground structure data for the area to be investigated; based on the underground structure data, determine the collaborative acquisition dimensions and underground subdivision areas corresponding to the area to be investigated; Obtain environmental data for the subsurface division within a preset time period, and determine the stratigraphic characteristics of the area to be investigated based on the environmental data. Based on the value ranges of underground structure data and stratigraphic feature data, corresponding constraints are generated; based on the underground structure data, stratigraphic feature data, and constraints, a three-dimensional geological model is constructed. When the threshold comparison result of the real-time environmental data corresponding to the collaborative acquisition dimension triggers the preset iteration condition, the latest real-time environmental data corresponding to the collaborative acquisition dimension is projected into the geological 3D model.

[0006] In one implementation of this application, data on underground structures in the area to be investigated are acquired; based on the underground structure data, the collaborative acquisition dimension and underground subdivision area corresponding to the area to be investigated are determined, specifically including: Collect data on the percentage of the projected area of ​​underground structures within the unit survey grid in the area to be investigated, the density of underground pipelines, and the foundation depth, structural form, spatial coordinates, and distribution direction of underground garages, integrated pipe corridors, and underground pipelines within a preset threshold range outside the centerline of the preset main roads. Based on the proportion of the projected area of ​​underground structures and the density of underground pipelines within the unit's survey grid, the underground area to be surveyed is divided into the core area of ​​underground structures, the auxiliary area of ​​underground structures, and the area without underground structures. The collaborative data collection dimensions for the core area of ​​underground structures are determined to be the foundation depth, structural form, spatial coordinates, and distribution direction of underground parking garages, integrated utility tunnels, and pipelines. The collaborative data collection dimensions for the underground structure auxiliary area were determined to be pipeline linear density and the projection ratio of major structures. The collaborative data collection dimension for determining the underground unstructured area is whether there are underground pipelines or structures within a preset threshold range outside the centerline of the main road.

[0007] In one implementation of this application, environmental data of the subsurface subdivision area within a preset time period is acquired, and stratigraphic characteristic data of the area to be investigated are determined based on the environmental data, specifically including: In the core area of ​​the underground construction, using the spatial coordinates of pipelines and underground parking garages as anchor points, the lithological stratification data of boreholes within a 5m radius are extracted, the thickness variation coefficient of each rock layer and the dip angle distribution of the interlayer contact surface are calculated, and the cumulative probability distribution of CPT cone tip resistance and sidewall friction is combined to obtain the compaction gradient model of the disturbed soil layer. In the underground construction auxiliary area, based on the statistical values ​​of pipeline linear density and projection ratio, a linear interpolation weighting function is constructed to extend sparse borehole data to the full grid, and the spatial continuity field of soil permeability coefficient is fitted by Gaussian process regression. In the unstructured underground area, by combining surface feature records and soil moisture data retrieved from remote sensing, and using a stratigraphic timescale, the Quaternary sedimentary sequence in the region was matched to determine the vertical superposition relationship of the clay, silt, and gravel layers.

[0008] In one implementation of this application, corresponding constraints are generated based on the value ranges of underground structure data and stratigraphic feature data; a geological three-dimensional model is constructed based on the underground structure data, stratigraphic feature data, and constraints, specifically including: Based on a three-dimensional spatial coordinate system of underground structure data and stratigraphic feature data, a unified geographic reference framework is established. Using the survey grid as the basic unit, the spatial coordinates and burial depth data of underground structures are used as bottom constraints to form an initial geometric topological boundary layer. The vertical stacking relationship of rock strata, thickness variation coefficient, and permeability coefficient field in the stratigraphic feature data are discretized into attribute values ​​of grid nodes. Spatial continuity is filled through a trilinear interpolation algorithm to construct the foundation of the initial voxel model. Based on the initial voxel model, constraints generated from the value range are introduced to apply rigid boundary constraints to the structural information of the building core area. For the pipeline linear density and projection ratio in the underground auxiliary area, a density-weighted porosity correction function is used to dynamically adjust the porosity distribution of soil voxels, so that the permeability field and the spatial distribution of the pipeline network are nonlinearly coupled. In the unconstructed area, based on the vertical stratification results of the Quaternary sedimentary sequence, combined with the particle size distribution thresholds of clay, silt and gravel layers, a membership function for lithological classification is set to realize fuzzy boundary modeling of the stratigraphic interface.

[0009] In one implementation of this application, when the threshold comparison result of the real-time environmental data corresponding to the collaborative acquisition dimension triggers a preset iteration condition, the latest real-time environmental data corresponding to the collaborative acquisition dimension is projected into the geological 3D model, specifically including: When the real-time environmental data collected in the collaborative collection dimension triggers the preset iteration conditions... In the core area of ​​the underground structure, the latest borehole lithological stratification data and CPT cone tip resistance-sidewall friction sequence are used as inputs to calculate the thickness variation coefficient deviation and interlayer dip angle residuals of the corresponding voxel nodes in the model. If any index exceeds the preset threshold, the voxel set within a 5m radius around the corresponding anchor point is locked, and a local voxel replacement mechanism is adopted to reconstruct the vertical discrete properties of the lithological sequence with new data. In the underground auxiliary construction zone, when the Mahalanobis distance between the real-time monitored value of pipeline linear density or projected proportion and the mean of the Gaussian process regression prediction in the model exceeds the 95% confidence interval of the χ² distribution, the permeability coefficient field of all voxel nodes in the region is extracted. Based on the density-weighted porosity correction function, the porosity-permeability coupling relationship of each node is recalculated, and the updated formula is: , in, For the updated porosity-permeability coupling relationship, This indicates the previous porosity-permeability coupling relationship. The linear density sensitivity coefficient, For nonlinear coupling exponent, This represents the real-time pipeline projection percentage. These are the model's predicted values. The model is preset with a maximum value, and after updating, it is repropagated to neighboring voxels via trilinear interpolation. In areas without underground structures, when the vertical stratification results of the Quaternary sedimentary sequence jointly inferred from remote sensing inversion of soil moisture content and surface feature records show a spatial offset from the clay-silt-gravel layer boundary defined by the membership function in the model by a preset distance, or when the grain size distribution threshold exceeds a preset range, the stratigraphic age-stratigraphic scale matching module is invoked to recalculate the lithological membership vector of all voxels in the area and update the membership function as follows: , in, Represents the lithological membership vector. For boundary steepness parameters, Z represents the new positioning depth of the top interface of the clay layer, where Z indicates the previous positioning depth above the top interface of the clay layer. To show the deviation between the measured particle size and the threshold, This represents the maximum preset deviation value, which is then used to reconstruct the formation interface using a fuzzy boundary modeling algorithm after the update.

[0010] Secondly, this application provides a whole-process control system for geological surveys in urban built-up areas, the system comprising: The area determination module is used to acquire underground structure data of the area to be investigated; based on the underground structure data, it determines the collaborative acquisition dimension and underground subdivision area corresponding to the area to be investigated. The stratigraphic determination module is used to acquire environmental data corresponding to the underground subsurface division area within a preset time period, and to determine the stratigraphic characteristic data of the area to be investigated based on the environmental data. A geological module is constructed to generate corresponding constraints based on the value ranges of underground structure data and stratigraphic feature data; a three-dimensional geological model is constructed based on the underground structure data, stratigraphic feature data, and constraints. The real-time module is used to project the latest real-time environmental data corresponding to the collaborative acquisition dimension into the geological 3D model when the threshold comparison result of the real-time environmental data corresponding to the collaborative acquisition dimension triggers the preset iteration condition.

[0011] In one implementation of this application, the region determination module includes a dimension determination unit. This is used to collect data on the percentage of the projected area of ​​underground structures within the unit survey grid in the area to be investigated, the density of underground pipelines, and the foundation depth, structural form, spatial coordinates, and distribution direction of underground garages, integrated pipe corridors, and underground pipelines within a preset threshold range outside the center line of the preset main road. Based on the proportion of the projected area of ​​underground structures and the density of underground pipelines within the unit's survey grid, the underground area to be surveyed is divided into the core area of ​​underground structures, the auxiliary area of ​​underground structures, and the area without underground structures. The collaborative data collection dimensions for the core area of ​​underground structures are determined to be the foundation depth, structural form, spatial coordinates, and distribution direction of underground parking garages, integrated utility tunnels, and pipelines. The collaborative data collection dimensions for the underground structure auxiliary area were determined to be pipeline linear density and the projection ratio of major structures. The collaborative data collection dimension for determining the underground unstructured area is whether there are underground pipelines or structures within a preset threshold range outside the centerline of the main road.

[0012] In one implementation of this application, constructing a geological module includes constructing geological units. Used to construct the core area underground, with the spatial coordinates of pipelines and underground garages as anchor points, extract the lithological layering data of boreholes within a 5m radius, calculate the thickness variation coefficient of each rock layer and the dip angle distribution of the interlayer contact surface, and combine the cumulative probability distribution of CPT cone tip resistance and sidewall friction resistance to obtain the compaction gradient model of the disturbed soil layer. In the underground construction auxiliary area, based on the statistical values ​​of pipeline linear density and projection ratio, a linear interpolation weighting function is constructed to extend sparse borehole data to the full grid, and the spatial continuity field of soil permeability coefficient is fitted by Gaussian process regression. In the unstructured underground area, by combining surface feature records and soil moisture data retrieved from remote sensing, and using a stratigraphic timescale, the Quaternary sedimentary sequence in the region was matched to determine the vertical superposition relationship of the clay, silt, and gravel layers.

[0013] Thirdly, this application provides a whole-process control device for geological surveys in urban built-up areas, the device including: processor; And a memory, on which executable code is stored, which, when executed, causes the processor to execute a whole-process control method for geological surveys in urban built-up areas, as described above.

[0014] Fourthly, this application provides a non-volatile computer storage medium storing computer instructions, which, when executed, implement a full-process control method for geological surveys in urban built-up areas as described above.

[0015] As can be seen from the above technical solutions, this application has the following advantages: By acquiring data on underground structures in the area to be investigated and determining collaborative data collection dimensions and underground zoning areas accordingly, a dynamic generation of investigation strategies based on the spatial distribution of underground structures was achieved. This overcomes the limitations of traditional investigations that rely on experience-based zoning or fixed grids, enabling data collection dimensions and regional boundaries to accurately adapt to the complex and heterogeneous underground structural characteristics of urban built-up areas, thereby improving the targeting and coverage effectiveness of investigation resources.

[0016] In the stratigraphic feature analysis stage, data on underground structures are integrated with multi-dimensional environmental data collected within a preset time period. Constraints are automatically generated based on the range of values ​​for both, and a three-dimensional geological model is constructed accordingly. By introducing the geometric shape, material properties, and spatial relationships of underground structures as hard constraints into the geological modeling process, the misjudgment of stratigraphic interfaces and parameter distortion caused by ignoring the interference of artificial structures in traditional models are suppressed, thereby improving the model's accuracy and physical consistency in representing the real geological environment.

[0017] By setting a threshold comparison mechanism for real-time environmental data collection, the latest data is directly projected into the existing 3D geological model when preset update conditions are triggered, achieving automated, closed-loop dynamic updates of the model. This mechanism changes the problem of static and delayed updates in traditional geological survey results, enabling the model to continuously evolve with real-time changes in the urban underground environment (such as construction disturbances and groundwater level fluctuations), ensuring that the survey results always reflect the latest geological conditions and providing continuous and reliable dynamic geological support for high-density urban development. Attached Figure Description

[0018] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart of a method for controlling the entire process of geological surveys in urban built-up areas, provided in an embodiment of this application.

[0020] Figure 2 This is a schematic diagram of the internal structure of a whole-process control system for geological surveys in urban built-up areas, provided in an embodiment of this application.

[0021] Figure 3 This is a schematic diagram of the internal structure of a whole-process control device for geological surveys in urban built-up areas, provided in an embodiment of this application. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] Those skilled in the art should understand that the embodiments described below are merely preferred embodiments of this disclosure and do not imply that this disclosure can only be implemented through these preferred embodiments. These preferred embodiments are merely used to explain the technical principles of this disclosure and are not intended to limit the scope of protection of this disclosure. Based on the preferred embodiments provided by this disclosure, all other embodiments obtained by those skilled in the art without creative effort should still fall within the scope of protection of this disclosure.

[0024] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0025] The technical solutions proposed in the embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0026] The embodiment provides a method for full-process control of geological surveys in urban built-up areas, such as... Figure 1 As shown in the embodiments of this application, the method mainly includes the following steps: Step 110: Obtain underground structure data for the area to be investigated; based on the underground structure data, determine the collaborative acquisition dimension and underground subdivision area corresponding to the area to be investigated.

[0027] In some embodiments, it can specifically be: Collect data on the percentage of the projected area of ​​underground structures within the unit survey grid in the area to be investigated, the density of underground pipelines, and the foundation depth, structural form, spatial coordinates, and distribution direction of underground garages, integrated pipe corridors, and underground pipelines within a preset threshold range outside the centerline of the preset main roads. Based on the proportion of the projected area of ​​underground structures and the density of underground pipelines within the unit's survey grid, the underground area to be surveyed is divided into the core area of ​​underground structures, the auxiliary area of ​​underground structures, and the area without underground structures. The collaborative data collection dimensions for the core area of ​​underground structures are determined to be the foundation depth, structural form, spatial coordinates, and distribution direction of underground parking garages, integrated utility tunnels, and pipelines. The collaborative data collection dimensions for the underground structure auxiliary area were determined to be pipeline linear density and the projection ratio of major structures. The collaborative data collection dimension for determining the underground unstructured area is whether there are underground pipelines or structures within a preset threshold range outside the centerline of the main road.

[0028] It should be further explained that, within each unit survey grid, the proportion of the projected area occupied by underground structures is obtained by overlaying remote sensing image interpretation with underground pipeline survey maps. The ratio of the projected area of ​​structures within the grid to the total area of ​​the grid is calculated using a pixel counting method, with an accuracy of no less than 0.5%. The linear density of underground pipelines is measured by the total length of the pipeline centerline per square meter of the grid (unit: m / m²), and the data comes from the urban underground pipeline integrated management information system, covering five main types of pipelines: water supply, drainage, gas, electricity, and communication, excluding duplicated and abandoned pipelines. A 30m control zone outside the road red line is set with a preset threshold range outside the centerline of the main roads. Within this range, the foundation depth, structural form, spatial coordinates, and distribution direction data of underground parking garages, integrated utility tunnels, and pipelines are derived from existing engineering as-built drawings and real estate registration information, and converted to the CGCS2000 geographic reference system through coordinate system one. In the zoning determination, the core area of ​​underground structures is defined as a grid with a projection ratio ≥ 15% and a pipeline linear density ≥ 0.8 m / m². The auxiliary area is a grid with a projection ratio ≤ 5% and a pipeline linear density < 15% or a pipeline linear density ≤ 0.3 m / m² and a pipeline-free area. The no-structure area is a grid where both are below the lower limit. The collaborative acquisition dimensions strictly correspond to the zoning characteristics: all six parameters are collected in the core area to ensure the integrity of key structures; only two quantifiable indicators, pipeline linear density and projection ratio, are retained in the auxiliary area to avoid redundant acquisition; the no-structure area only detects the presence of pipelines or structures within the threshold range, simplifying the data acquisition logic through binary judgment (yes / no).

[0029] Step 120: Obtain environmental data for the underground subdivision area within a preset time period, and determine the stratigraphic characteristics of the area to be investigated based on the environmental data.

[0030] In some embodiments, it can specifically be: In the core area of ​​the underground construction, using the spatial coordinates of pipelines and underground parking garages as anchor points, the lithological stratification data of boreholes within a 5m radius are extracted, the thickness variation coefficient of each rock layer and the dip angle distribution of the interlayer contact surface are calculated, and the cumulative probability distribution of CPT cone tip resistance and sidewall friction is combined to obtain the compaction gradient model of the disturbed soil layer. In the underground construction auxiliary area, based on the statistical values ​​of pipeline linear density and projection ratio, a linear interpolation weighting function is constructed to extend sparse borehole data to the full grid, and the spatial continuity field of soil permeability coefficient is fitted by Gaussian process regression. In the unstructured underground area, by combining surface feature records and soil moisture data retrieved from remote sensing, and using a stratigraphic timescale, the Quaternary sedimentary sequence in the region was matched to determine the vertical superposition relationship of the clay, silt, and gravel layers.

[0031] It should be further explained that in the core area of ​​underground structures, using the spatial coordinates of pipelines and underground parking garages as anchor points, lithological stratification data of boreholes within a 5m radius are extracted. Combined with the cumulative probability distribution of CPT cone tip resistance and sidewall friction, a compaction gradient model of disturbed soil layers is constructed. This ensures that the stratigraphic characteristic data reflects the local impact of human activities on the physical state of the soil, avoiding misjudgments of soil bearing capacity due to neglecting disturbance. In the auxiliary area of ​​underground structures, a linear interpolation weighting function is constructed based on the statistical values ​​of pipeline linear density and projection ratio. Combined with Gaussian process regression, the spatial continuity field of soil permeability coefficients is fitted, enabling reasonable extrapolation of sparse borehole data and improving the spatial integrity of permeability parameters under conditions of no new drilling. In the unstructured underground area, soil moisture content data obtained from surface feature records and remote sensing inversion is matched with the stratigraphic age scale of the regional Quaternary sedimentary sequence. This establishes the vertical superposition relationship of clay, silt, and gravel layers based on geological evolution laws, reducing the subjectivity of stratigraphic division due to a lack of borehole control.

[0032] In the core area of ​​the underground structure, using the spatial coordinates of pipelines and underground parking garages as anchor points, lithological stratification data from boreholes within a 5m radius were extracted. The coefficient of variation of each stratum thickness and the dip angle distribution of the interlayer contact surface were calculated to identify soil structural anomalies caused by artificial disturbance. Combined with the measured sequences of CPT cone tip resistance and sidewall friction, an empirical cumulative distribution function (ECDF) was constructed to characterize the spatial variability of compaction in a non-parametric manner, avoiding reliance on theoretical distribution assumptions and ensuring that the model reflects the actual in-situ soil response. In the auxiliary area of ​​the underground structure, based on the grid statistics of pipeline linear density and projection proportion, an interpolation weighting function was constructed using the inverse distance weighting method (IDW). The weights are positively correlated with pipeline density. Sparse borehole data were weighted by this function and expanded to the entire grid. Then, a Gaussian process regression was used to fit the permeability coefficient field, ensuring that the spatial interpolation results are consistent with the local hydraulic connectivity trend of the pipeline network distribution. In areas without underground structures, based on surface vegetation type, topographic slope, and soil moisture content data retrieved from remote sensing, and combined with Quaternary stratigraphic classification standards, the vertical superposition relationship of clay, silt, and gravel layers is anchored to the geomagnetic polarity chronology and oxygen isotope stage of the loess-paleosol sequence (such as Malan Loess and Lishi Loess). Remote sensing moisture content is only used to assist in determining the water content of the clay layer and is not used as a direct basis for stratigraphic classification, ensuring that stratigraphic correlation has a logical support for geological evolution.

[0033] Step 130: Generate corresponding constraints based on the value ranges of underground structure data and stratigraphic feature data; construct a three-dimensional geological model based on the underground structure data, stratigraphic feature data, and constraints.

[0034] In some embodiments, it can specifically be: Based on a three-dimensional spatial coordinate system of underground structure data and stratigraphic feature data, a unified geographic reference framework is established. Using the survey grid as the basic unit, the spatial coordinates and burial depth data of underground structures are used as bottom constraints to form an initial geometric topological boundary layer. The vertical stacking relationship of rock strata, thickness variation coefficient, and permeability coefficient field in the stratigraphic feature data are discretized into attribute values ​​of grid nodes. Spatial continuity is filled through a trilinear interpolation algorithm to construct the foundation of the initial voxel model. Based on the initial voxel model, constraints generated from the value range are introduced to apply rigid boundary constraints to the structural information of the building core area. For the pipeline linear density and projection ratio in the underground auxiliary area, a density-weighted porosity correction function is used to dynamically adjust the porosity distribution of soil voxels, so that the permeability field and the spatial distribution of the pipeline network are nonlinearly coupled. In the unconstructed area, based on the vertical stratification results of the Quaternary sedimentary sequence, combined with the particle size distribution thresholds of clay, silt and gravel layers, a membership function for lithological classification is set to realize fuzzy boundary modeling of the stratigraphic interface.

[0035] It should be further clarified that the range of constraint values ​​is derived from the statistical distribution range of measured engineering data and industry standard limits, and is not subjectively set. In the core area of ​​the underground structure, the structural boundary coordinates of the underground parking garage and integrated utility tunnel are used as rigid constraints, forcing the voxel model to completely coincide with the measured structure outline in this area, ensuring the geometric fidelity of the model to the artificial structure. In the auxiliary area of ​​the underground structure, a density-weighted porosity correction function is used based on the statistical values ​​of pipeline linear density and projection ratio. ,in, The background soil porosity, The pipeline projection density per unit area is given by k, an empirical coefficient (ranging from 0.05 to 0.15), which causes the permeability field to increase nonlinearly with pipeline network density, consistent with the measured trend of increased permeability in pipeline disturbance zones during engineering projects. In the unstructured underground zone, based on the particle size distribution thresholds of clay, silt, and gravel in the Quaternary sedimentary sequence (clay < 0.005 mm, silt 0.005–0.05 mm, gravel > 2 mm), a triangular membership function is constructed: , Where c is the typical grain size median and a is the half-width parameter, which is determined based on the statistical analysis of regional stratigraphic samples to achieve fuzzy boundary modeling of lithological transition zones and avoid geological continuity distortion caused by hard segmentation.

[0036] Step 140: When the threshold comparison result of the real-time environmental data corresponding to the collaborative acquisition dimension triggers the preset iteration condition, the latest real-time environmental data corresponding to the collaborative acquisition dimension is projected into the geological 3D model.

[0037] In some embodiments, this step may specifically be: When the real-time environmental data collected in the collaborative collection dimension triggers the preset iteration conditions... In the core area of ​​the underground structure, the latest borehole lithological stratification data and CPT cone tip resistance-sidewall friction sequence are used as inputs to calculate the thickness variation coefficient deviation and interlayer dip angle residuals of the corresponding voxel nodes in the model. If any index exceeds the preset threshold, the voxel set within a 5m radius around the corresponding anchor point is locked, and a local voxel replacement mechanism is adopted to reconstruct the vertical discrete properties of the lithological sequence with new data. In the underground auxiliary construction zone, when the Mahalanobis distance between the real-time monitored value of pipeline linear density or projected proportion and the mean of the Gaussian process regression prediction in the model exceeds the 95% confidence interval of the χ² distribution, the permeability coefficient field of all voxel nodes in the region is extracted. Based on the density-weighted porosity correction function, the porosity-permeability coupling relationship of each node is recalculated, and the updated formula is: , in, For the updated porosity-permeability coupling relationship, This indicates the previous porosity-permeability coupling relationship. The linear density sensitivity coefficient, For nonlinear coupling exponent, This represents the real-time pipeline projection percentage. These are the model's predicted values. The model is preset with a maximum value, and after updating, it is repropagated to neighboring voxels via trilinear interpolation. In areas without underground structures, when the vertical stratification results of the Quaternary sedimentary sequence jointly inferred from remote sensing inversion of soil moisture content and surface feature records show a spatial offset from the clay-silt-gravel layer boundary defined by the membership function in the model by a preset distance, or when the grain size distribution threshold exceeds a preset range, the stratigraphic age-stratigraphic scale matching module is invoked to recalculate the lithological membership vector of all voxels in the area and update the membership function as follows: , in, Represents the lithological membership vector. For boundary steepness parameters, Z represents the new positioning depth of the top interface of the clay layer, where Z indicates the previous positioning depth above the top interface of the clay layer. To show the deviation between the measured particle size and the threshold, This represents the maximum preset deviation value, which is then used to reconstruct the formation interface using a fuzzy boundary modeling algorithm after the update.

[0038] In addition, this application Figure 2 This application provides a full-process control system for geological surveys in urban built-up areas. For example... Figure 2 As shown in the embodiments of this application, the system mainly includes: The area determination module 210 is used to acquire underground structure data of the area to be investigated; based on the underground structure data, it determines the collaborative acquisition dimension and underground subdivision area corresponding to the area to be investigated.

[0039] The region determination module 210 includes a dimension determination unit. This is used to collect data on the percentage of the projected area of ​​underground structures within the unit survey grid in the area to be investigated, the density of underground pipelines, and the foundation depth, structural form, spatial coordinates, and distribution direction of underground garages, integrated pipe corridors, and underground pipelines within a preset threshold range outside the center line of the preset main road. Based on the proportion of the projected area of ​​underground structures and the density of underground pipelines within the unit's survey grid, the underground area to be surveyed is divided into the core area of ​​underground structures, the auxiliary area of ​​underground structures, and the area without underground structures. The collaborative data collection dimensions for the core area of ​​underground structures are determined to be the foundation depth, structural form, spatial coordinates, and distribution direction of underground parking garages, integrated utility tunnels, and pipelines. The collaborative data collection dimensions for the underground structure auxiliary area were determined to be pipeline linear density and the projection ratio of major structures. The collaborative data collection dimension for determining the underground unstructured area is whether there are underground pipelines or structures within a preset threshold range outside the centerline of the main road.

[0040] The stratigraphic determination module 220 is used to acquire environmental data corresponding to the underground subdivision area within a preset time period, and to determine the stratigraphic characteristic data of the area to be investigated based on the environmental data.

[0041] A geological module 230 is constructed to generate corresponding constraints based on the value ranges of underground structure data and stratigraphic feature data; a three-dimensional geological model is constructed based on the underground structure data, stratigraphic feature data, and constraints.

[0042] Constructing geological module 230 includes constructing geological units. Used to construct the core area underground, with the spatial coordinates of pipelines and underground garages as anchor points, extract the lithological layering data of boreholes within a 5m radius, calculate the thickness variation coefficient of each rock layer and the dip angle distribution of the interlayer contact surface, and combine the cumulative probability distribution of CPT cone tip resistance and sidewall friction resistance to obtain the compaction gradient model of the disturbed soil layer. In the underground construction auxiliary area, based on the statistical values ​​of pipeline linear density and projection ratio, a linear interpolation weighting function is constructed to extend sparse borehole data to the full grid, and the spatial continuity field of soil permeability coefficient is fitted by Gaussian process regression. In the unstructured underground area, by combining surface feature records and soil moisture data retrieved from remote sensing, and using a stratigraphic timescale, the Quaternary sedimentary sequence in the region was matched to determine the vertical superposition relationship of the clay, silt, and gravel layers.

[0043] The real-time module 240 is used to project the latest real-time environmental data corresponding to the collaborative acquisition dimension into the geological 3D model when the threshold comparison result of the real-time environmental data corresponding to the collaborative acquisition dimension triggers the preset iteration condition.

[0044] The above are method embodiments of this application. Based on the same inventive concept, this application also provides a device for controlling the entire process of geological surveys in urban built-up areas. Figure 3 As shown, the device includes: a processor; and a memory storing executable code, which, when executed, causes the processor to perform a full-process control method for geological surveys in urban built-up areas as described in the above embodiment.

[0045] Specifically, the server acquires underground structure data of the area to be investigated; based on the underground structure data, it determines the collaborative acquisition dimension and underground subdivision area corresponding to the area to be investigated; it acquires the environmental acquisition data corresponding to the underground subdivision area within a preset time period, and determines the stratigraphic feature data of the area to be investigated based on the environmental acquisition data; it generates corresponding constraints based on the value range of the underground structure data and stratigraphic feature data; it constructs a geological 3D model based on the underground structure data, stratigraphic feature data, and constraints; when the threshold comparison result of the real-time environmental acquisition data corresponding to the collaborative acquisition dimension triggers the preset iteration condition, the latest real-time environmental acquisition data corresponding to the collaborative acquisition dimension is projected into the geological 3D model.

[0046] In addition, this application embodiment also provides a non-volatile computer storage medium storing executable instructions, which, when executed, implement the above-described method for full-process control of geological surveys in urban built-up areas.

[0047] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for controlling the entire process of geological surveys in urban built-up areas, characterized in that, The method includes: Acquire underground structure data for the area to be investigated; based on the underground structure data, determine the collaborative acquisition dimensions and underground subdivision areas corresponding to the area to be investigated; Obtain environmental data for the subsurface division within a preset time period, and determine the stratigraphic characteristics of the area to be investigated based on the environmental data. Based on the value ranges of underground structure data and stratigraphic feature data, corresponding constraints are generated; based on the underground structure data, stratigraphic feature data, and constraints, a three-dimensional geological model is constructed. When the threshold comparison result of the real-time environmental data corresponding to the collaborative acquisition dimension triggers the preset iteration condition, the latest real-time environmental data corresponding to the collaborative acquisition dimension is projected into the geological 3D model.

2. The method for full-process control of geological surveys in urban built-up areas according to claim 1, characterized in that, Obtain data on underground structures in the area to be investigated; Based on underground structure data, the collaborative data collection dimensions and underground subdivision zones corresponding to the area to be investigated are determined, specifically including: Collect data on the percentage of the projected area of ​​underground structures within the unit survey grid in the area to be investigated, the density of underground pipelines, and the foundation depth, structural form, spatial coordinates, and distribution direction of underground garages, integrated pipe corridors, and underground pipelines within a preset threshold range outside the centerline of the preset main roads. Based on the proportion of the projected area of ​​underground structures and the density of underground pipelines within the unit's survey grid, the underground area to be surveyed is divided into the core area of ​​underground structures, the auxiliary area of ​​underground structures, and the area without underground structures. The collaborative data collection dimensions for the core area of ​​underground structures are determined to be the foundation depth, structural form, spatial coordinates, and distribution direction of underground parking garages, integrated utility tunnels, and pipelines. The collaborative data collection dimensions for the underground structure auxiliary area were determined to be pipeline linear density and the projection ratio of major structures. The collaborative data collection dimension for determining the underground unstructured area is whether there are underground pipelines or structures within a preset threshold range outside the centerline of the main road.

3. The method for full-process control of geological surveys in urban built-up areas according to claim 1, characterized in that, Obtain environmental data for the subsurface subdivisions within a preset time period. Based on this data, determine the stratigraphic characteristics of the area to be investigated, specifically including: In the core area of ​​the underground construction, using the spatial coordinates of pipelines and underground parking garages as anchor points, the lithological stratification data of boreholes within a 5m radius are extracted, the thickness variation coefficient of each rock layer and the dip angle distribution of the interlayer contact surface are calculated, and the cumulative probability distribution of CPT cone tip resistance and sidewall friction is combined to obtain the compaction gradient model of the disturbed soil layer. In the underground construction auxiliary area, based on the statistical values ​​of pipeline linear density and projection ratio, a linear interpolation weighting function is constructed to extend sparse borehole data to the full grid, and the spatial continuity field of soil permeability coefficient is fitted by Gaussian process regression. In the unstructured underground area, by combining surface feature records and soil moisture data retrieved from remote sensing, and using a stratigraphic timescale, the Quaternary sedimentary sequence in the region was matched to determine the vertical superposition relationship of the clay, silt, and gravel layers.

4. The method for full-process control of geological surveys in urban built-up areas according to claim 1, characterized in that, Based on the value ranges of underground structure data and stratigraphic feature data, corresponding constraints are generated. Based on data on underground structures, stratigraphic characteristics, and constraints, a three-dimensional geological model is constructed, specifically including: Based on a three-dimensional spatial coordinate system of underground structure data and stratigraphic feature data, a unified geographic reference framework is established. Using the survey grid as the basic unit, the spatial coordinates and burial depth data of underground structures are used as bottom constraints to form an initial geometric topological boundary layer. The vertical stacking relationship of rock strata, thickness variation coefficient, and permeability coefficient field in the stratigraphic feature data are discretized into attribute values ​​of grid nodes. Spatial continuity is filled through a trilinear interpolation algorithm to construct the foundation of the initial voxel model. Based on the initial voxel model, constraints generated from the value range are introduced to apply rigid boundary constraints to the structural information of the building core area. For the pipeline linear density and projection ratio in the underground auxiliary area, a density-weighted porosity correction function is used to dynamically adjust the porosity distribution of soil voxels, so that the permeability field and the spatial distribution of the pipeline network are nonlinearly coupled. In the unconstructed area, based on the vertical stratification results of the Quaternary sedimentary sequence, combined with the particle size distribution thresholds of clay, silt and gravel layers, a membership function for lithological classification is set to realize fuzzy boundary modeling of the stratigraphic interface.

5. The method for full-process control of geological surveys in urban built-up areas according to claim 1, characterized in that, When the threshold comparison result of the real-time environmental data corresponding to the collaborative acquisition dimension triggers the preset iteration condition, the latest real-time environmental data corresponding to the collaborative acquisition dimension is projected onto the geological 3D model, specifically including: When the real-time environmental data collected in the collaborative collection dimension triggers the preset iteration conditions... In the core area of ​​the underground structure, the latest borehole lithological stratification data and CPT cone tip resistance-sidewall friction sequence are used as inputs to calculate the thickness variation coefficient deviation and interlayer dip angle residuals of the corresponding voxel nodes in the model. If any index exceeds the preset threshold, the voxel set within a 5m radius around the corresponding anchor point is locked, and a local voxel replacement mechanism is adopted to reconstruct the vertical discrete properties of the lithological sequence with new data. In the underground auxiliary construction zone, when the Mahalanobis distance between the real-time monitored value of pipeline linear density or projected proportion and the mean of the Gaussian process regression prediction in the model exceeds the 95% confidence interval of the χ² distribution, the permeability coefficient field of all voxel nodes in the region is extracted. Based on the density-weighted porosity correction function, the porosity-permeability coupling relationship of each node is recalculated, and the updated formula is: ， in, For the updated porosity-permeability coupling relationship, This indicates the previous porosity-permeability coupling relationship. The linear density sensitivity coefficient, For nonlinear coupling exponent, This represents the real-time pipeline projection percentage. These are the model's predicted values. The model is preset with a maximum value, and after updating, it is repropagated to neighboring voxels via trilinear interpolation. In areas without underground structures, when the vertical stratification results of the Quaternary sedimentary sequence jointly inferred from remote sensing inversion of soil moisture content and surface feature records show a spatial offset from the clay-silt-gravel layer boundary defined by the membership function in the model by a preset distance, or when the grain size distribution threshold exceeds a preset range, the stratigraphic age-stratigraphic scale matching module is invoked to recalculate the lithological membership vector of all voxels in the area and update the membership function as follows: ， in, Represents the lithological membership vector. For boundary steepness parameters, Z represents the new positioning depth of the top interface of the clay layer, where Z indicates the previous positioning depth above the top interface of the clay layer. To show the deviation between the measured particle size and the threshold, This represents the maximum preset deviation value, which is then used to reconstruct the formation interface using a fuzzy boundary modeling algorithm after the update.

6. A whole-process control system for geological surveys in urban built-up areas, characterized in that, The system includes: The area determination module is used to acquire underground structure data of the area to be investigated; based on the underground structure data, it determines the collaborative acquisition dimension and underground subdivision area corresponding to the area to be investigated. The stratigraphic determination module is used to acquire environmental data corresponding to the underground subsurface division area within a preset time period, and to determine the stratigraphic characteristic data of the area to be investigated based on the environmental data. A geological module is constructed to generate corresponding constraints based on the value ranges of underground structure data and stratigraphic feature data; a three-dimensional geological model is constructed based on the underground structure data, stratigraphic feature data, and constraints. The real-time module is used to project the latest real-time environmental data corresponding to the collaborative acquisition dimension into the geological 3D model when the threshold comparison result of the real-time environmental data corresponding to the collaborative acquisition dimension triggers the preset iteration condition.

7. The whole-process control system for geological surveys in urban built-up areas according to claim 6, characterized in that, The region determination module includes a dimension determination unit. This is used to collect data on the percentage of the projected area of ​​underground structures within the unit survey grid in the area to be investigated, the density of underground pipelines, and the foundation depth, structural form, spatial coordinates, and distribution direction of underground garages, integrated pipe corridors, and underground pipelines within a preset threshold range outside the center line of the preset main road. Based on the proportion of the projected area of ​​underground structures and the density of underground pipelines within the unit's survey grid, the underground area to be surveyed is divided into the core area of ​​underground structures, the auxiliary area of ​​underground structures, and the area without underground structures. The collaborative data collection dimensions for the core area of ​​underground structures are determined to be the foundation depth, structural form, spatial coordinates, and distribution direction of underground parking garages, integrated utility tunnels, and pipelines. The collaborative data collection dimensions for the underground structure auxiliary area were determined to be pipeline linear density and the projection ratio of major structures. The collaborative data collection dimension for determining the underground unstructured area is whether there are underground pipelines or structures within a preset threshold range outside the centerline of the main road.

8. The whole-process control system for geological surveys in urban built-up areas according to claim 6, characterized in that, Constructing a geological module includes constructing geological units. Used to construct the core area underground, with the spatial coordinates of pipelines and underground garages as anchor points, extract the lithological layering data of boreholes within a 5m radius, calculate the thickness variation coefficient of each rock layer and the dip angle distribution of the interlayer contact surface, and combine the cumulative probability distribution of CPT cone tip resistance and sidewall friction resistance to obtain the compaction gradient model of the disturbed soil layer. In the underground construction auxiliary area, based on the statistical values ​​of pipeline linear density and projection ratio, a linear interpolation weighting function is constructed to extend sparse borehole data to the full grid, and the spatial continuity field of soil permeability coefficient is fitted by Gaussian process regression. In the unstructured underground area, by combining surface feature records and soil moisture data retrieved from remote sensing, and using a stratigraphic timescale, the Quaternary sedimentary sequence in the region was matched to determine the vertical superposition relationship of the clay, silt, and gravel layers.

9. A control device for the entire process of geological surveys in urban built-up areas, characterized in that, The device includes: processor; And a memory storing executable code, which, when executed, causes the processor to perform a whole-process control method for geological surveys in urban built-up areas as described in any one of claims 1-5.

10. A non-volatile computer storage medium, characterized in that, It stores computer instructions, which, when executed, implement a full-process control method for geological surveys in urban built-up areas as described in any one of claims 1-5.

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