A geotechnical engineering comprehensive evaluation method based on multi-source survey data

Abstract

The present application relates to the technical field of geotechnical engineering investigation, and more particularly to a geotechnical engineering comprehensive evaluation method based on multi-source investigation data. Based on the engineering properties and regional geological background data of the target investigation site, the priority level division standard of multi-source investigation data and the one-way constraint rule of high-level to low-level in the whole process are preset according to the data measurement accuracy, reliability and geological constraint effectiveness, and the investigation operation execution criteria are generated; the first-level reference investigation point is laid out according to the criteria to collect the first-level core constraint measured data, the site stratum reference constraint framework and the first-level core constraint reference data set are constructed, the low-level data is collected in a constrained manner and closed-loop verification is performed to generate the full-level multi-source investigation data set, the site three-dimensional stratum fusion model and the target full-parameter fusion data set are generated through hierarchical hard-constrained multi-source data space fusion interpolation, and the multi-dimensional comprehensive evaluation is completed in combination with the criteria to generate a report. The evaluation accuracy and authority are improved, and reliable geological basis is provided for engineering design and construction.

Description

Technical Field

[0001] This invention relates to the field of geotechnical engineering investigation technology, and in particular to a comprehensive evaluation method for geotechnical engineering based on multi-source investigation data. Background Technology

[0002] Currently, geotechnical engineering investigations commonly employ multiple methods, including drilling, in-situ testing, engineering geophysics, and laboratory geotechnical tests, to acquire multi-source investigation data for comprehensive site evaluation. Existing geotechnical engineering evaluation methods often adopt a fragmented approach: first, full data collection, then centralized fusion. This involves completing all data collection according to a standardized uniform borehole layout, followed by weighted calculations, conventional interpolation algorithms, or general data models to fuse the multi-source data. In this model, high-precision drilling and in-situ testing data, along with geophysical data exhibiting ambiguity, are input into the fusion model as equal data sources. All types of investigation data undergo centralized laboratory quality control only after the entire collection process is completed. The inherent errors of low-precision data are not effectively corrected during the collection phase and are directly carried over to subsequent fusion and evaluation stages.

[0003] However, due to the inherent spatial heterogeneity of soil and rock masses and the significant differences in the reliability of data from different sources, the aforementioned existing technologies, lacking pre-defined hierarchical constraints on multi-source data throughout the entire process, exhibit unsolvable systemic defects in practical engineering applications. Regarding site stability and suitability evaluation, the lack of hierarchical constraints on multi-source data makes it impossible to accurately identify the spatial distribution of adverse geological processes, hindering comprehensive prediction of engineering risks, and resulting in evaluation conclusions lacking reliable data support. In terms of site seismic effect evaluation, insufficient precision in stratigraphic data makes it impossible to accurately classify site categories, determine seismic-resistant zone types, and meet the mandatory requirements of seismic design. For foundation evaluation, the amplification of data errors makes it impossible to accurately evaluate foundation uniformity, leading to excessive deviations in core design parameter values ​​and a lack of specificity in foundation scheme applicability analysis, failing to meet actual engineering needs. Finally, in terms of specialized project evaluation, it is impossible to accurately complete stability and seepage analyses, making it difficult to predict engineering risks caused by flooding. Summary of the Invention

[0004] This invention provides a comprehensive evaluation method for geotechnical engineering based on multi-source exploration data, which solves the technical problem that existing geotechnical engineering evaluation methods lack pre-set hierarchical constraint rules for multi-source exploration data, resulting in insufficient reliability of multi-source data fusion evaluation results.

[0005] The first aspect of this invention provides a comprehensive geotechnical engineering evaluation method based on multi-source exploration data, comprising the following steps:

[0006] Based on the engineering attributes of the target exploration site and regional geological background data, and according to the measured accuracy, reliability and geological constraint effectiveness of the data, a priority hierarchy classification standard for multi-source exploration data and a one-way constraint rule from high-level to low-level data throughout the entire process are preset to generate exploration operation execution criteria.

[0007] According to the exploration operation execution guidelines, primary benchmark exploration points are set up in the target exploration site to construct a full-process constraint benchmark, and the primary core constraint measured data corresponding to the primary benchmark exploration points are collected to construct the site stratigraphic benchmark constraint framework and the primary core constraint benchmark dataset.

[0008] Using the site stratigraphic benchmark constraint framework and the first-level core constraint benchmark dataset as calibration benchmarks, constrained acquisition and closed-loop verification of low-level exploration data are carried out in accordance with the exploration operation execution criteria to generate a full-level multi-source exploration dataset that meets quality control requirements.

[0009] Using the first-level core constraint benchmark dataset as fixed hard control points and the full-level multi-source exploration dataset as input data source, multi-source data spatial fusion interpolation with hierarchical hard constraints is performed according to the exploration operation execution criteria to generate a site three-dimensional stratigraphic fusion model and a target full parameter fusion dataset.

[0010] Based on the site's three-dimensional stratigraphic fusion model and the target's full-parameter fusion dataset, and combined with the exploration operation execution criteria, a multi-dimensional comprehensive evaluation of geotechnical engineering is conducted to generate a comprehensive geotechnical engineering evaluation report corresponding to the target exploration site.

[0011] Optionally, the step of generating exploration operation execution criteria based on the engineering attributes and regional geological background data of the target exploration site, pre-setting priority hierarchy standards for multi-source exploration data and unidirectional constraint rules from high-level to low-level data throughout the entire process, includes:

[0012] Based on the engineering importance level, site category, and regional geological background data of the target exploration site, and in conjunction with the requirements of the current geotechnical engineering exploration specifications, an evaluation dimension matrix of multi-source exploration data is constructed with the data measurement accuracy, reliability, and geological constraint effectiveness as the core evaluation dimensions.

[0013] The evaluation dimension matrix is ​​used to prioritize and classify the various types of exploration data involved in the entire process of geotechnical engineering exploration corresponding to the target exploration site, and to generate the priority classification standard of the multi-source exploration data.

[0014] Based on the aforementioned priority hierarchy classification standard, for the four core stages of the entire exploration operation process—collection, quality control, fusion, and evaluation—one-way constraint execution rules for higher-level to lower-level stages are formulated respectively, generating one-way constraint rules for the entire process.

[0015] The priority level classification criteria and the full-process unidirectional constraint rules are integrated and verified for compliance to generate standardized exploration operation execution guidelines.

[0016] Optionally, the step of setting up primary benchmark exploration points within the target exploration site according to the exploration operation execution criteria to construct a full-process constraint benchmark, and collecting measured data of primary core constraints corresponding to the primary benchmark exploration points to construct a site stratigraphic benchmark constraint framework and a primary core constraint benchmark dataset includes:

[0017] Based on the priority hierarchy classification criteria and dynamic exploration point layout rules in the exploration operation execution guidelines, and combined with the preliminary regional geological assessment results of the target exploration site and the overall engineering control requirements, a primary benchmark exploration point layout scheme is constructed.

[0018] According to the above-mentioned primary benchmark exploration point layout plan, primary benchmark exploration points are laid out in the target exploration site, and drilling operations and in-situ tests are carried out at the primary benchmark exploration points to obtain the measured data of the primary core constraints corresponding to the primary benchmark exploration points.

[0019] Based on the measured data of the first-level core constraints, the standard stratigraphic sequence of the site is divided, and the lithological characteristics, layer interface depth, benchmark values ​​of physical and mechanical parameters and full-process constraint boundaries of each stratum are determined to construct the site stratigraphic benchmark constraint framework.

[0020] Based on the quality control rules in the exploration operation execution criteria, the measured data of the first-level core constraints are standardized, processed, and quality controlled, and outliers are removed to generate a first-level core constraint benchmark dataset.

[0021] Optionally, the step of using the site stratigraphic benchmark constraint framework and the first-level core constraint benchmark dataset as calibration benchmarks, and conducting constrained acquisition and closed-loop verification of low-level exploration data according to the exploration operation execution criteria to generate a quality-controlled full-level multi-source exploration dataset includes:

[0022] Based on the one-way constraint rules in the exploration operation execution guidelines, and using the site stratigraphic benchmark constraint framework as the calibration benchmark, combined with the layout of the first-level benchmark exploration points, a segmented acquisition scheme for low-level exploration data is constructed.

[0023] According to the segmented acquisition scheme, segmented collaborative acquisition of low-level exploration data is carried out. Using the first-level core constraint benchmark dataset as the correction benchmark, stratigraphic calibration, deviation correction and invalid data removal are performed on the acquired low-level exploration data to generate low-level exploration correction data.

[0024] Using the aforementioned low-level exploration and correction data, stratigraphic anomaly zones and suspected adverse geological processes within the target exploration site are identified, and a site anomaly zone distribution map is generated.

[0025] Based on the dynamic exploration point layout rules in the exploration operation execution guidelines, first-level verification exploration points are added to the abnormal areas in the site anomaly distribution map, and the first-level core constraint measured data of the first-level verification exploration points are collected as verification data.

[0026] The verification data is used to iteratively refine the low-level survey data of the corresponding anomaly areas, and the site anomaly distribution map is updated synchronously.

[0027] When there are no abnormal areas on the site anomaly distribution map, a full-level multi-source exploration dataset is constructed using all quality-controlled and qualified exploration data from each level.

[0028] Optionally, the step of using the first-level core constraint benchmark dataset as fixed hard control points and the full-level multi-source exploration dataset as input data source, and performing hierarchical hard constraint multi-source data spatial fusion interpolation according to the exploration operation execution criteria to generate a site three-dimensional stratigraphic fusion model and a target full-parameter fusion dataset includes:

[0029] Based on the fusion modeling constraint rules in the exploration operation execution criteria, the full-level multi-source exploration dataset is standardized and preprocessed, and then split into first-level core constraint data, second-level supplementary verification data and third-level regional reference data according to the preset hierarchical division standard.

[0030] Based on the point coordinates and measured values ​​of the first-level core constraint data, a hard constraint condition matrix that cannot be adjusted during the interpolation calculation process is constructed.

[0031] Based on the parameter value range of the secondary supplementary verification data, inequality constraint terms for interpolation calculation are constructed;

[0032] Based on the stratigraphic spatial distribution characteristics of the three-level regional reference data, a stratigraphic spatial variation trend term is constructed using interpolation calculation;

[0033] Based on the hard constraint condition matrix, inequality constraint terms, and stratigraphic spatial variation trend terms, spatial interpolation calculations with hierarchical hard constraints are performed to obtain the stratigraphic properties and physical and mechanical parameters of each node of the three-dimensional stratigraphic grid corresponding to the target exploration site.

[0034] Based on the calculated values ​​of the geological properties and physical and mechanical parameters, the original data source code and hierarchical constraint identifier are matched for each parameter, a full parameter fusion matrix with hard constraints is constructed and encapsulated to generate the initial full parameter fusion dataset;

[0035] Based on the three-dimensional stratigraphic grid, stratigraphic properties and physical and mechanical parameters, and the measured stratigraphic interface of the first-level core constraint data corresponding to the target exploration site, a three-dimensional stratigraphic structure model with the first-level core constraint data as fixed hard control points is constructed. After matching the corresponding parameters in the initial full-parameter fusion dataset, the initial three-dimensional stratigraphic fusion model of the site is generated.

[0036] In accordance with the quality control and verification rules of the exploration operation execution criteria, the initial full-parameter fusion dataset and the initial three-dimensional stratigraphic fusion model are subjected to hierarchical quality control and verification. After the verification is passed, the site three-dimensional stratigraphic fusion model and the target full-parameter fusion dataset are generated.

[0037] Optionally, the step of performing hierarchical hard-constrained spatial interpolation calculations based on the hard constraint matrix, inequality constraint terms, and stratigraphic spatial variation trend terms to obtain the calculated values ​​of stratigraphic properties and physical and mechanical parameters of each node of the three-dimensional stratigraphic grid corresponding to the target exploration site includes:

[0038] The input parameters for interpolation calculation are assigned using the hard constraint condition matrix as the equality constraint term, the inequality constraint term as the boundary constraint term, and the stratigraphic spatial variation trend term as the auxiliary trend term.

[0039] Based on the input parameter values, perform spatial interpolation calculations with hierarchical hard constraints to obtain initial interpolation parameter values;

[0040] Based on the planar coordinates and borehole elevation of the three-dimensional stratigraphic grid corresponding to the target exploration site, a corresponding stratigraphic sequence number is matched for each grid node to determine the stratigraphic properties and physical and mechanical parameter types of each stratum in the three-dimensional stratigraphic grid.

[0041] According to the fusion modeling constraint rules in the exploration operation execution criteria, the interpolation initial parameter values ​​are checked for hierarchical constraints to obtain the calculated values ​​of the stratigraphic properties and physical and mechanical parameters of each node of the three-dimensional stratigraphic grid corresponding to the target exploration site.

[0042] Optionally, the step of performing a multi-dimensional comprehensive geotechnical engineering evaluation based on the site's three-dimensional stratigraphic fusion model and the target full-parameter fusion dataset, combined with the exploration operation execution criteria, to generate a comprehensive geotechnical engineering evaluation report corresponding to the target exploration site includes:

[0043] Based on the evaluation output constraint rules in the exploration operation execution criteria, the measured data of the corresponding level are extracted from the target full parameter fusion dataset as the calculation input parameters of each evaluation dimension to obtain the input parameter set;

[0044] Based on the aforementioned three-dimensional geological fusion model, the site stability and suitability evaluation, site seismic effect evaluation, foundation evaluation, and special project evaluation are carried out using the aforementioned input parameter set, generating special evaluation data for each dimension.

[0045] For all core evaluation indicators and conclusions in the special evaluation data, match the corresponding data source level and original measured data in the target full parameter fusion dataset to construct a complete data traceability link;

[0046] Using all the aforementioned specialized evaluation data, all the aforementioned complete data traceability links, and the original exploration dataset corresponding to the target exploration site, a comprehensive geotechnical engineering evaluation report corresponding to the target exploration site is constructed in accordance with the exploration operation execution guidelines and current exploration specifications.

[0047] The second aspect of this invention provides a comprehensive geotechnical engineering evaluation system based on multi-source exploration data, comprising:

[0048] The criteria generation module is used to generate exploration operation execution criteria based on the engineering attributes of the target exploration site and regional geological background data, according to the measured accuracy, reliability and geological constraint effectiveness of the data, preset the priority level classification standard of multi-source exploration data and the one-way constraint rules of high level to low level throughout the process.

[0049] The benchmark construction module is used to set up primary benchmark exploration points in the target exploration site according to the exploration operation execution criteria, and to collect the primary core constraint measured data corresponding to the primary benchmark exploration points, thereby constructing the site stratigraphic benchmark constraint framework and the primary core constraint benchmark dataset.

[0050] The data quality control module is used to carry out constrained acquisition and closed-loop verification of low-level exploration data according to the exploration operation execution criteria, based on the site stratigraphic benchmark constraint framework and the first-level core constraint benchmark dataset as the calibration benchmark, and generate a full-level multi-source exploration dataset that has passed quality control.

[0051] The fusion modeling module is used to perform spatial fusion interpolation of multi-source data with hierarchical hard constraints, using the first-level core constraint benchmark dataset as fixed hard control points and the full-level multi-source exploration dataset as input data source, in accordance with the exploration operation execution criteria, to generate a three-dimensional stratigraphic fusion model of the site and a target full-parameter fusion dataset.

[0052] The comprehensive evaluation module is used to conduct a multi-dimensional comprehensive evaluation of geotechnical engineering based on the three-dimensional stratigraphic fusion model of the site and the target full-parameter fusion dataset, combined with the exploration operation execution criteria, and generate a comprehensive geotechnical engineering evaluation report corresponding to the target exploration site.

[0053] A third aspect of the present invention provides an electronic device, including a memory and a processor. The memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the geotechnical engineering comprehensive evaluation method based on multi-source exploration data as described above.

[0054] The fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed, it implements the geotechnical engineering comprehensive evaluation method based on multi-source exploration data as described above.

[0055] As can be seen from the above technical solutions, the present invention has the following advantages:

[0056] This invention specifically addresses the technical problem of insufficient reliability in multi-source data fusion evaluation results caused by the lack of pre-set hierarchical constraint rules for multi-source exploration data in existing geotechnical engineering evaluation methods. Its beneficial effects are derived as follows: Existing methods, due to the lack of clear priority division and constraint rules for multi-source exploration data, are prone to problems such as high-precision data being interfered with by low-precision data and the lack of a unified standard for data selection when data conflicts occur. This invention, by pre-setting hierarchical division standards and unidirectional constraint rules, clarifies the authority and application boundaries of different types of data from the source, ensuring the core constraint role of high-level, high-precision data and avoiding logical contradictions caused by low-level data correcting high-level data. The stratigraphic benchmark constraint framework and core dataset constructed from the first-level benchmark exploration points provide a unified and authoritative reference standard for the entire process of data acquisition and correction, solving the problems of chaotic stratigraphic division and large parameter deviations caused by the lack of a unified benchmark in traditional evaluations. The constraint-based acquisition and closed-loop verification mechanism of low-level data ensures that low-level data always conforms to the high-level benchmark, significantly improving the consistency and reliability of multi-source data across all levels. The hierarchical hard-constraint spatial fusion interpolation method locks in the hard constraints of primary core data, while secondary data defines parameter boundaries and tertiary data guides stratigraphic trends. This effectively avoids the deviation between the model and the actual stratigraphy caused by unconstrained interpolation, significantly improving the accuracy of the site's 3D stratigraphic fusion model and the target full-parameter fusion dataset. The multi-dimensional comprehensive evaluation stage, based on preset criteria and combined with a complete data source hierarchy and data traceability chain, ensures that evaluation conclusions can be traced back to the original measured data. This solves the problems of insufficient data support and credibility in traditional evaluation conclusions, ultimately achieving a comprehensive improvement in the reliability, accuracy, and authority of geotechnical engineering comprehensive evaluation results, providing more reliable geological basis for engineering design and construction decisions. Attached Figure Description

[0057] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the 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.

[0058] Figure 1 A flowchart illustrating the steps of a comprehensive geotechnical engineering evaluation method based on multi-source exploration data, provided in this embodiment of the invention;

[0059] Figure 2 A structural block diagram of a geotechnical engineering comprehensive evaluation system based on multi-source exploration data provided in an embodiment of the present invention;

[0060] Figure 3 This is a structural block diagram of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0061] This invention provides a comprehensive evaluation method for geotechnical engineering based on multi-source exploration data, which addresses the technical problem that existing geotechnical engineering evaluation methods lack pre-set hierarchical constraint rules for multi-source exploration data, resulting in insufficient reliability of multi-source data fusion evaluation results.

[0062] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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, 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. It should be noted that in the optional embodiments of the present invention, the object information and other related data involved require the permission or consent of the object when the embodiments of the present invention are applied to specific products or technologies, and the collection, use, and processing of related data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. That is to say, if the embodiments of the present invention involve data related to the object, it needs to be obtained with the authorization and consent of the object, the authorization and consent of the relevant departments, and in compliance with the relevant laws, regulations, and standards of the country and region. If personal information is involved in the embodiments, the acquisition of all personal information requires the consent of the individual. If sensitive information is involved, the separate consent of the information subject is required, and the embodiments also need to be implemented with the authorization and consent of the object.

[0063] Please see Figure 1 , Figure 1A flowchart illustrating the steps of a comprehensive evaluation method for geotechnical engineering based on multi-source exploration data, provided in this embodiment of the invention.

[0064] This invention provides a comprehensive geotechnical engineering evaluation method based on multi-source exploration data, comprising:

[0065] Step 101: Based on the engineering attributes and regional geological background data of the target exploration site, and according to the measured accuracy, reliability and geological constraint effectiveness of the data, preset the priority level classification standard of multi-source exploration data and the one-way constraint rule of high level to low level throughout the process, and generate the exploration operation execution criteria.

[0066] In this embodiment of the invention, multi-source exploration data refers to conventional geotechnical engineering exploration data (drilling, in-situ testing, geophysical exploration, regional geological background data, etc.). Engineering attributes include core information such as the engineering importance level and site category of the target exploration site. Regional geological background data covers basic data such as stratigraphic distribution, geological structure, and adverse geological development in the area to which the site belongs. Existing technologies mostly adopt a "non-discriminatory fusion" mode, resulting in high-precision data being interfered with by low-precision data. This invention solves this problem through "hierarchical division + unidirectional constraint". Among them: data measurement accuracy refers to the degree of consistency between measured values ​​and true values ​​during data acquisition; reliability refers to the credibility guarantee brought by data acquisition methods, instruments, and personnel qualifications; geological constraint effectiveness refers to the data's ability to support and guide stratigraphic division and engineering design. The priority hierarchy division standard is a three-level classification rule based on data measurement accuracy, reliability, and geological constraint effectiveness. The unidirectional constraint rule of high-level to low-level throughout the entire process refers to the constraint and correction rule of high-level data on low-level data in the entire exploration operation (low-level data cannot correct high-level data in reverse). The exploration operation execution guidelines are standardized operating procedures formed by integrating priority level classification standards and one-way constraint rules and after compliance verification.

[0067] Further, step 101 includes the following steps:

[0068] S11. Based on the engineering importance level, site category, and regional geological background data of the target exploration site, and in conjunction with the requirements of the current geotechnical engineering exploration specifications, an evaluation dimension matrix of multi-source exploration data is constructed with the data measurement accuracy, reliability, and geological constraint effectiveness as the core evaluation dimensions.

[0069] In this embodiment of the invention, the engineering attributes specifically include the engineering importance level (Level 1, Level 2, Level 3) and site category (Class I, Class II, Class III, Class IV) of the target exploration site. The regional geological background data includes information on outcrops of strata surrounding the site, regional geological survey reports, and geological hazard zoning data. Based on the "Code for Geotechnical Engineering Investigation" (GB50021-2001), three core evaluation dimensions and secondary indicators are determined: Measured data accuracy corresponding to measured error (e.g., drilling layer depth error ≤ 0.1m), data repeatability (deviation between two tests at the same point ≤ 5%); reliability corresponding to the accuracy of the acquisition instrument (e.g., static cone penetrometer range 0-50MPa, accuracy ±0.5MPa), and the qualifications of the acquisition personnel (requiring relevant professional technical certificates); geological constraint effectiveness corresponding to the stratigraphic support degree (e.g., drilling data can directly determine stratigraphic interfaces, support degree 100%), and engineering design guidance degree (e.g., foundation bearing capacity data directly guides foundation selection, guidance degree 100%). The weights were determined using the analytic hierarchy process (40% for measured data accuracy, 30% for reliability, and 30% for geological constraint effectiveness). The scores of each indicator were quantified in accordance with the specifications (e.g., full marks are given for meeting the accuracy standards of the data acquisition instruments, and points are deducted proportionally for failing to meet the standards). An evaluation dimension matrix of multi-source exploration data was constructed to provide a feasible quantitative basis for hierarchical division.

[0070] S12. Prioritize and classify various types of exploration data involved in the entire process of geotechnical engineering exploration corresponding to the target exploration site by using the evaluation dimension matrix, and generate priority classification standards for multi-source exploration data.

[0071] In this embodiment of the invention, the various types of exploration data involved in the entire geotechnical engineering investigation process include drilling data (core logging, indoor geotechnical test data), in-situ testing data (heavy dynamic penetration test, standard penetration test, static penetration test data), geophysical data (ground penetrating radar, high-density electrical resistivity tomography data), and regional geological background data (stratigraphic distribution map, geological hazard zoning map). Existing technologies do not clearly define data priorities, resulting in a lack of criteria for selecting data when drilling (high-precision) and geophysical (low-precision) data conflict. This invention quantifies and scores various types of data using an evaluation dimension matrix, dividing the data into three levels: Level 1 core constraint data (comprehensive score ≥ 90 points, including drilling and heavy dynamic penetration test data, with the highest measured accuracy and reliability), Level 2 supplementary verification data (70-89 points, including standard penetration test and static penetration test data, with moderate measured accuracy and reliability), and Level 3 regional reference data (< 70 points, including ground-penetrating radar, high-density electrical resistivity tomography, and regional geological background data, with relatively low measured accuracy and reliability). It clarifies the specific scope and judgment criteria of each level of data and generates a priority hierarchy classification standard for multi-source exploration data.

[0072] S13. Based on the priority hierarchy classification standard, for the four core links of the entire exploration operation process—collection, quality control, fusion, and evaluation—the corresponding high-level to low-level one-way constraint execution rules are formulated to generate one-way constraint rules for the entire process.

[0073] In this embodiment of the invention, the data acquisition stage of the entire exploration operation refers to the on-site acquisition process of various types of exploration data. The quality control stage refers to the data cleaning, outlier removal, and standardization process. The fusion stage refers to the spatial interpolation and parameter matching process of multi-source data. The evaluation stage refers to the multi-dimensional analysis process based on the data, including site stability and foundation analysis. Based on the routine operation process, the following four-stage one-way constraint execution rules were formulated: (1) The one-way constraint execution rules for the data acquisition stage are that the first-level core constraint data points should prioritize covering key areas such as the site stratigraphic boundary and suspected areas of adverse geology, and the data acquisition points of the lower-level data should not exceed the stratigraphic boundary determined by the higher-level data; (2) The one-way constraint execution rules for the quality control stage are that the judgment of outliers in the lower-level data should be based on the higher-level data. If the deviation between the second-level data and the first-level data exceeds ±10%, it is judged as an anomaly; The one-way constraint execution rules for the fusion stage are that the interpolation weight of the higher-level data is higher than that of the lower-level data. The weight of the first-level data is twice that of the second-level data and three times that of the third-level data; The one-way constraint execution rules for the evaluation stage are that the calculation of core indicators such as foundation bearing capacity and seismic motion parameters must be based on the higher-level data as the core input, and the lower-level data is only used as an auxiliary supplement. The rules of each stage are integrated to generate the one-way constraint rules of the higher-level to the lower-level for the entire process.

[0074] S14. Integrate and verify the priority level division standards and the one-way constraint rules of the whole process to generate standardized exploration operation execution guidelines.

[0075] In this embodiment of the invention, following the logic of "data classification - process constraints - execution requirements," the priority hierarchy of multi-source exploration data and the unidirectional constraint rules from high-level to low-level throughout the entire process are integrated to form a unified draft of operating guidelines. Compliance verification is performed against the "Code for Geotechnical Engineering Investigation" (GB50021-2001) to ensure that all rules do not violate the requirements of the code regarding point density, testing items, data accuracy, etc., and to eliminate conflicting or unreasonable content. Finally, standardized exploration operation execution guidelines are generated, clarifying the operational procedures, judgment criteria, and constraint requirements for each stage, providing a unified basis for subsequent exploration operations.

[0076] Step 102: In accordance with the exploration operation execution guidelines, set up primary benchmark exploration points within the target exploration site to construct the full-process constraint benchmark, and collect the primary core constraint measured data corresponding to the primary benchmark exploration points to construct the site stratigraphic benchmark constraint framework and the primary core constraint benchmark dataset.

[0077] In this embodiment of the invention, the primary benchmark survey points are the core data collection points used to construct the full-process constraint benchmark. They must meet the requirements of high measured data accuracy, uniform distribution, and coverage of key areas. Primary core constraint measured data refers to measured information collected through primary benchmark survey points, such as drilling data, in-situ test data, and indoor geotechnical test data, including parameters such as lithology, color, structure, density, water content, compression modulus, and shear strength. The site stratigraphic benchmark constraint framework is the site standard stratigraphic sequence, stratigraphic interface depth, physical and mechanical parameter benchmark values, and full-process constraint boundaries determined based on the primary core constraint measured data. The primary core constraint benchmark dataset is a collection of primary core constraint measured data after quality control verification, containing information such as point coordinates, measured parameter values, collection time, and traceability codes; it is a non-adjustable hard constraint data source.

[0078] Further, step 102 includes the following steps:

[0079] S21. Based on the priority level classification standard and dynamic exploration point layout rules in the exploration operation execution guidelines, and combined with the preliminary regional geological assessment results of the target exploration site and the overall control requirements of the project, a primary benchmark exploration point layout scheme is constructed.

[0080] In this embodiment of the invention, the dynamic survey point layout rule refers to the rule of dynamically adjusting the distribution of points according to regional geological conditions and engineering needs. The preliminary regional geological assessment results of the target survey site include the general distribution of strata, the location of suspected adverse geological areas, and the topographic relief, etc. The overall engineering control requirements include the project scale, design requirements, and safety level, etc. Referring to the point density requirements in the "Code for Geotechnical Engineering Investigation" (GB50021-2001), survey points should be arranged according to the perimeter line and corner points of buildings. For foundation complexity level I (complex), the spacing between survey points is 10-15m; for foundation complexity level II (medium complexity), the spacing between survey points is 15-30m; and for foundation complexity level III (simple), the spacing between survey points is 30-50m. Prioritize the placement of survey points at stratigraphic boundaries, areas with significant topographic relief, and areas suspected of having adverse geological conditions, ensuring uniform coverage of the entire target exploration site. Define the plane coordinates (X, Y), borehole elevation (Z), drilling depth (which must penetrate the main strata), and testing items (drilling + heavy dynamic penetration test + indoor geotechnical test) for each point, and construct a primary benchmark survey point layout plan. The plan can be drawn using AutoCAD.

[0081] S22. According to the primary benchmark exploration point layout plan, primary benchmark exploration points are laid out in the target exploration site, and drilling operations and in-situ tests are carried out at the primary benchmark exploration points to obtain the measured data of the primary core constraints corresponding to the primary benchmark exploration points.

[0082] In this embodiment of the invention, a conventional XY-100 drilling rig (drilling efficiency 5m / hour) is used to establish primary benchmark exploration points within the target exploration site according to the layout plan. Drilling is conducted at each point to a preset depth (the preset depth meets the requirements of the "Code for Geotechnical Engineering Investigation" (GB50021-2001) and the "General Code for Engineering Investigation" (GB 55017-2021)). Core logging is performed during drilling to record information such as lithology, color, structure, and degree of cementation. Simultaneously, in-situ testing (heavy dynamic penetration test, test hammer blow count N63.5) is conducted. Core samples are collected and sent to the laboratory for indoor geotechnical testing to measure physical and mechanical parameters such as density (natural density, dry density), moisture content, compression modulus (Es), and shear strength (cohesion c, internal friction angle φ). The core logging data, in-situ test data, and laboratory test data are integrated to obtain the measured primary core constraint data corresponding to each primary benchmark exploration point.

[0083] S23. Based on the measured data of the first-level core constraints, the standard stratigraphic sequence of the site is divided, and the benchmark values ​​of the lithological characteristics, layer interface depth, physical and mechanical parameters and the full-process constraint boundaries of each stratum are determined, so as to construct the site stratigraphic benchmark constraint framework.

[0084] In this embodiment of the invention, the measured data of all primary benchmark survey points are summarized and analyzed to divide the site into standard stratigraphic sequences (e.g., artificial fill - silty clay - silty clay - moderately weathered basalt). Referring to the parameter statistical requirements of the "Code for Design of Building Foundations" (GB50007-2011), the arithmetic mean method is used to calculate the benchmark values ​​of physical and mechanical parameters for each stratum (e.g., the benchmark value of the compression modulus of silty clay is 5 MPa). The constraint boundaries are set according to "benchmark value ± 3 standard deviations" (physical and mechanical parameters) or "±0.5m" (layer interface depth). For example, the benchmark value of the top interface depth for artificial fill is 0m, and the benchmark value of the bottom interface depth is 3m, with a constraint boundary of 3±0.5m; the benchmark value of the compression modulus of silty clay is 3MPa, with a constraint boundary of 3±0.6MPa. By clarifying the lithological characteristics, benchmark values ​​of layer interface depths, benchmark values ​​of physical and mechanical parameters, and the full-process constraint boundaries for each stratum, a complete site stratigraphic benchmark constraint framework is constructed.

[0085] S24. Based on the quality control rules in the exploration operation execution criteria, the measured data of the first-level core constraints are standardized and quality control verified, and outliers are removed to generate the first-level core constraint benchmark dataset.

[0086] In this embodiment of the invention, the quality control rules in the exploration operation execution criteria refer to the data quality control requirements determined in step 101, including data integrity, accuracy, and consistency verification standards. Outliers are eliminated using the industry-standard 3x standard deviation method: the mean (μ) and standard deviation (σ) of each physical and mechanical parameter are calculated, and data exceeding the range of μ ± 3σ are identified as outliers (e.g., the water content of silty soil at a certain point is 68%, exceeding the range of 32%-68% corresponding to μ=50% and σ=6%, and are therefore eliminated). The causes of the anomalies are analyzed in conjunction with drilling records and test logs, and after confirmation, the outliers are eliminated. The processed valid data were organized into a CSV (Comma-Separated Values) format according to the format "location number-stratum number-parameter name-measured value-collection time-collector-traceability code". Each data entry included the location number (e.g., ZK-001), coordinates (X, Y, Z), parameter value (e.g., compression modulus 10MPa), collection time, and traceability code (e.g., "ZK-001-T-05") for easy subsequent traceability.

[0087] Step 103: Using the site stratigraphic benchmark constraint framework and the first-level core constraint benchmark dataset as calibration benchmarks, conduct constraint-based acquisition and closed-loop verification of low-level exploration data in accordance with the exploration operation execution guidelines, and generate a qualified full-level multi-source exploration dataset.

[0088] In this embodiment of the invention, low-level exploration data refers to secondary supplementary verification data (standard penetration test, static cone penetration test data) and tertiary regional reference data (grounding radar, high-density electrical resistivity tomography data). Constrained acquisition refers to a low-level data acquisition method under the constraints of high-level data, and closed-loop verification refers to an iterative process of "anomaly identification - supplementary point placement - data correction - anomaly update". A full-level multi-source exploration dataset refers to a complete dataset formed by integrating qualified primary, secondary, and tertiary data.

[0089] Furthermore, step 103 includes the following steps:

[0090] S31. Based on the one-way constraint rules in the exploration operation execution guidelines, and taking the site stratigraphic benchmark constraint framework as the calibration benchmark, combined with the layout of the first-level benchmark exploration points, a segmented acquisition scheme for low-level exploration data is constructed.

[0091] In this embodiment of the invention, the target exploration site is divided into several acquisition units, with the location of the primary benchmark exploration points serving as the dividing point. The boundary of each acquisition unit is the line connecting two adjacent primary benchmark exploration points. For each acquisition unit, the acquisition density of low-level data is determined according to the stratigraphic complexity of the unit (based on the site stratigraphic benchmark constraint framework): for simple stratigraphic areas (such as homogeneous silty clay layers), the acquisition density of secondary supplementary verification data is 1 point / 625㎡, and the acquisition density of tertiary reference data is 1 point / 900㎡; for complex stratigraphic areas (such as silty soil distribution areas and suspected areas of adverse geology), the acquisition density of secondary supplementary verification data is 1 point / 225㎡, and the acquisition density of tertiary reference data is 1 point / 400㎡. The above acquisition densities correspond to an exploration point spacing controlled within 30m, which complies with the requirements of the "Code for Geotechnical Engineering Investigation" (GB50021-2001) and practical engineering application habits. Define the coordinates of the acquisition points, test items, and test depths for secondary data (standard penetration test, static cone penetration test) and tertiary data (grounding radar, high-density electrical resistivity tomography) within each acquisition unit, and construct a segmented acquisition scheme for low-level exploration data.

[0092] S32. Conduct segmented collaborative acquisition of low-level exploration data according to the segmented acquisition scheme. Using the first-level core constraint benchmark dataset as the correction benchmark, perform stratigraphic calibration, deviation correction and invalid data removal on the acquired low-level exploration data to generate low-level exploration correction data.

[0093] In this embodiment of the invention, following a segmented acquisition scheme, a conventional standard penetrometer (testing hammer blow count N63.5) and a static cone penetrometer (testing cone tip resistance and sidewall friction resistance) are used to acquire secondary supplementary verification data, while a ground-penetrating radar (detection depth 20m) and a high-density electrical resistivity tomography (detection depth 30m) are used to acquire tertiary regional reference data, thereby achieving segmented collaborative acquisition. Using the primary core constraint benchmark dataset as the calibration benchmark, the data is processed through the Lizheng exploration software: Stratigraphic calibration matches the stratigraphic division of the lower-level data with the standard stratigraphic sequence in the site's stratigraphic benchmark constraint framework (e.g., the "low-resistivity layer" identified by ground-penetrating radar is calibrated as silty soil); Deviation correction compares the lower-level data with the primary data of the corresponding area, and performs linear correction on data whose deviation exceeds the allowable range (parameter deviation ±15%, depth deviation ±0.8m) (e.g., a secondary data compression modulus of 8MPa, corresponding to the primary data benchmark value of 10MPa in the area, is proportionally corrected to 9.6MPa); Invalid data removal identifies and discards data with a deviation of more than 30% from the primary data without a reasonable cause (e.g., outliers caused by instrument malfunction). After processing, lower-level exploration calibration data is generated.

[0094] S33. Using low-level exploration and correction data, identify stratigraphic anomaly zones and suspected adverse geological processes within the target exploration site, and generate a site anomaly zone distribution map.

[0095] In this embodiment of the invention, the anomaly identification threshold is based on industry standards: Low-level exploration and correction data are compared with the site's stratigraphic benchmark constraint framework. When the deviation between the stratigraphic interface depth reflected by the low-level data and the benchmark framework exceeds ±1m, or the deviation between the physical and mechanical parameters and the benchmark values ​​exceeds ±10%, the area is marked as a stratigraphic anomaly zone. Combined with regional geological background data, when low-level data show abrupt changes in stratigraphic interfaces (e.g., depth changes exceeding 2m) or abnormal fluctuations in physical and mechanical parameters (fluctuation amplitude exceeding 30%), the area is marked as a suspected area of ​​adverse geological processes (e.g., karst development area, weak interlayer distribution area). Anomaly zone distribution maps are drawn using AutoCAD, clearly defining the boundary coordinates, anomaly types (stratigraphic thickness anomaly / parameter anomaly / suspected karst), and anomaly severity, providing a clear and intuitive understanding.

[0096] S34. Based on the dynamic exploration point layout rules in the exploration operation execution guidelines, supplement the abnormal areas in the site abnormal area distribution map with primary verification exploration points, and collect the primary core constraint measured data of the primary verification exploration points as verification data.

[0097] In this embodiment of the invention, according to the dynamic survey point layout rules, primary verification survey points are added to each anomalous area in the site anomaly distribution map, with a borehole spacing of 15-30m to ensure coverage of the entire anomalous area (e.g., for a suspected karst area of ​​2000㎡, 8 verification points are added). Drilling operations, in-situ testing (heavy dynamic penetration testing), and indoor geotechnical tests are conducted according to the same technical requirements as the primary benchmark survey points. Primary core constraint measured data are collected as verification data to verify the geological conditions of the anomalous area and the accuracy of lower-level data. The data collection methods are consistent with those for the primary benchmark points.

[0098] S35. Use the verification data to iteratively refine the low-level survey data of the corresponding anomaly areas, and update the site anomaly distribution map simultaneously.

[0099] In this embodiment of the invention, a weighted average method is used to correct low-level data. The weight of the verification data is set to 0.7, and the weight of the original low-level data is 0.3. For example, the original second-level data compression modulus of an anomaly area is 7 MPa, the measured value of the verification data is 9 MPa, and the corrected data is 7 × 0.3 + 9 × 0.7 = 8.4 MPa. The corrected low-level data is then compared again with the site stratigraphic benchmark constraint framework to re-identify anomaly areas: areas where the deviation has been eliminated (parameter deviation ≤ ±5%, depth deviation ≤ ±0.5m) are removed from the anomaly marker; areas where anomalies still exist are marked and the reasons are analyzed (e.g., whether there are undetected adverse geological conditions). The site anomaly distribution map is updated synchronously to reflect the changes in anomaly areas; anomalies can be eliminated after 2-3 iterations.

[0100] S36. When there are no abnormal areas on the site anomaly distribution map, construct a full-level multi-source exploration dataset using all quality-controlled and qualified exploration data from all levels.

[0101] In this embodiment of the invention, steps S33-S35 are repeated until there are no abnormal areas on the site anomaly distribution map, indicating that the low-level data has completely matched the first-level benchmark data and the data reliability meets the requirements. The data is categorized and stored according to the logic of "level-location-parameter-time," integrating all quality control qualified data (first-level core constraint benchmark dataset, first-level verification data, second-level supplementary verification and correction data, and third-level regional reference correction data). Each data entry includes a level identifier (first-level / second-level / third-level), location number, coordinates, parameter name, parameter value, collection time, and traceability code, stored in CSV format. The dataset contains complete level identifiers and traceability information, providing a reliable data source for subsequent fusion interpolation.

[0102] Step 104: Using the first-level core constraint benchmark dataset as fixed hard control points and the full-level multi-source exploration dataset as the input data source, perform spatial fusion interpolation of multi-source data with hierarchical hard constraints according to the exploration operation execution criteria to generate a three-dimensional stratigraphic fusion model of the site and a target full-parameter fusion dataset.

[0103] In this embodiment of the invention, fixed hard control points refer to first-level points whose parameter values ​​remain unchanged during the interpolation process; input data sources refer to all data used for interpolation calculations; multi-source data spatial fusion interpolation with hierarchical hard constraints refers to an interpolation method with first-level hard constraints, second-level boundary constraints, and third-level trend constraints; site three-dimensional stratigraphic fusion model refers to a three-dimensional stratigraphic visualization model containing parameter information; and target full-parameter fusion dataset refers to a dataset containing stratigraphic attributes and physical and mechanical parameters of all grid nodes.

[0104] Furthermore, step 104 includes the following steps:

[0105] S41. Based on the fusion modeling constraint rules in the exploration operation execution criteria, the multi-source exploration dataset at all levels is standardized and preprocessed, and then split into first-level core constraint data, second-level supplementary verification data, and third-level regional reference data according to the preset hierarchical division standard.

[0106] In this embodiment of the invention, the fusion modeling constraint rules in the exploration operation execution criteria are the multi-source data fusion requirements determined in step 101, and the preset hierarchical division standard is the three-level data division rule in step 101. The preprocessing process specifically includes: data cleaning (removing missing values, duplicate values, and obviously erroneous data, such as data with parameter values ​​of 0 without reasonable justification, and supplementing a small amount of reasonable missing data using linear interpolation); coordinate unification (converting the coordinates of all data to the national geodetic coordinate system to ensure data spatial consistency and avoid interpolation deviations caused by differences in coordinate systems); and format standardization (converting data obtained by different acquisition methods into a structured format, specifying data fields: point coordinates (X, Y, Z), acquisition time, parameter name, parameter value, and hierarchical identifier). After preprocessing, the data is split according to the preset hierarchical division standard to obtain first-level core constraint data (original first-level benchmark + verification data), second-level supplementary verification data (original second-level correction data), and third-level regional reference data (original third-level correction data). The split data retains the hierarchical identifier to facilitate subsequent constraint applications, and all are implemented using Excel or Lizheng Exploration Software.

[0107] S42. Based on the point coordinates and measured values ​​of the first-level core constraint data, construct a hard constraint condition matrix that cannot be adjusted during the interpolation calculation process.

[0108] In this embodiment of the invention, the planar coordinates (X, Y), orifice elevation (Z), and measured values ​​of core physical and mechanical parameters (such as natural density ρ=1.8g / cm³, compressive modulus Es=10MPa, cohesion c=25kPa, and internal friction angle φ=18°) of each point in the primary core constraint data are extracted. Using the point coordinates as row indices (X, Y, Z combination) and column indices (parameter type), and the measured parameter values ​​as matrix elements, a hard constraint condition matrix is ​​constructed (dimension = number of primary points × number of parameters, e.g., 100 points × 6 parameters, matrix dimension is 100 × 6). This matrix is ​​set to be non-adjustable; during subsequent interpolation calculations, the parameter values ​​of the primary core constraint data points remain consistent with the measured values ​​and do not participate in interpolation fitting adjustments, ensuring the hard constraint effect of the primary data. The matrix is ​​imported using the "hard constraint interpolation" function of Surfer software (a 3D data visualization and analysis software commonly used for interpolation and modeling in geology, geography, and other fields).

[0109] S43. Based on the parameter value range of the secondary supplementary verification data, construct the inequality constraint terms for interpolation calculation.

[0110] In this embodiment of the invention, statistical analysis is performed on each physical and mechanical parameter (density, moisture content, compression modulus, shear strength, etc.) in the secondary supplementary verification data to determine the value range (minimum and maximum value) of each parameter. For example, the natural density of artificial fill ranges from 1.6 to 1.8 g / cm³, the compression modulus of silty soil ranges from 2 to 4 MPa, the shear strength cohesion c of silty clay ranges from 20 to 30 kPa, and the internal friction angle φ ranges from 15 to 25°. Based on these value ranges, inequality constraints for interpolation calculations are constructed to clarify the allowable fluctuation range of each parameter during the interpolation process, such as 1.6 g / cm³ ≤ natural density of artificial fill ≤ 1.8 g / cm³, 2 MPa ≤ compression modulus of silty soil ≤ 4 MPa. These inequalities are set using the boundary constraint function of Surfer software to ensure that the parameter values ​​obtained by interpolation calculation do not exceed the reasonable range determined by the secondary data.

[0111] S44. Based on the stratigraphic spatial distribution characteristics of the three-level regional reference data, construct the stratigraphic spatial change trend term for interpolation calculation.

[0112] In this embodiment of the invention, the third-level regional reference data is analyzed. Using spatial analysis tools (such as trend surface analysis) of ArcGIS (ArcGeographic Information System, a geographic information system software used to create, manage, analyze, and share geospatial data), the spatial distribution characteristics of the site's strata are identified: for example, silty soil is distributed in strips along a certain direction, with its thickness increasing from 3m to 8m from west to east; the lithology of silty clay gradually changes from stiff plastic to plastic from north to south, with the compression modulus decreasing from 12MPa to 8MPa. These spatial distribution characteristics are transformed into linear trend terms (such as the thickness change trend term Z=0.005X+3, where X is the eastward coordinate) or exponential trend terms, constructing interpolated stratigraphic spatial change trend terms to guide the interpolation results to conform to the actual spatial distribution of the strata and avoid irregular fluctuations in the interpolation results.

[0113] S45. Based on the hard constraint condition matrix, inequality constraint terms and stratigraphic spatial variation trend terms, perform spatial interpolation calculations with hierarchical hard constraints to obtain the stratigraphic properties and physical and mechanical parameters of each node of the three-dimensional stratigraphic grid corresponding to the target exploration site.

[0114] In this embodiment of the invention, Kriging interpolation (a geostatistical interpolation method based on regionalized variable theory, which can consider the spatial correlation of data) is used to perform spatial interpolation calculations with hierarchical hard constraints. During the calculation process, hierarchical constraint rules are strictly followed: the calculated values ​​of the first-level core constraint data points are completely consistent with the measured values ​​(limited by the hard constraint condition matrix); the second-level supplementary verification data limits the boundaries of the calculated parameter values ​​through inequality constraint terms; and the third-level regional reference data guides the spatial variation trend of the stratigraphy through the stratigraphic spatial variation trend term. Before interpolation, a structured three-dimensional stratigraphic grid is constructed based on the boundary range and exploration accuracy requirements of the target exploration site. The grid size is set to 5m × 5m × 0.5m (standard accuracy, adjustable according to engineering needs), covering the entire target exploration site. Through interpolation calculations, the stratigraphic attributes (strata number, lithological name) and calculated physical and mechanical parameters (density, water content, compression modulus, shear strength, etc.) of each node of the three-dimensional stratigraphic grid corresponding to the target exploration site are obtained, which can be directly used for subsequent modeling.

[0115] Further, step S45 includes the following steps:

[0116] S451. Using the hard constraint condition matrix as the equality constraint term, the inequality constraint term as the boundary constraint term, and the stratigraphic spatial variation trend term as the auxiliary trend term for interpolation, the input parameters for interpolation calculation are assigned.

[0117] In this embodiment of the invention, according to the constraint parameter input requirements of the Surfer software, the hard constraint condition matrix is ​​imported into the "Equality Constraint" module to clarify the coordinates and fixed parameter values ​​of the first-level points; the inequality constraint terms are imported into the "Boundary Constraint" module to set the allowable fluctuation range of each parameter; the stratigraphic spatial change trend terms are imported into the "Trend Constraint" module to set the weight of the trend terms (accounting for 10%-20%), thus completing the assignment of input parameters for interpolation calculation.

[0118] S452. Based on the input parameter assignment, perform spatial interpolation calculation with hierarchical hard constraints to obtain the initial interpolation parameter values.

[0119] In this embodiment of the invention, the Kriging interpolation algorithm of the Surfer software is initiated to perform calculations. During the calculation process, the algorithm logic automatically locks the calculated values ​​of the primary core constraint data points, ensuring complete consistency with the measured values. These points do not participate in the interpolation fitting adjustment, ensuring the effect of hard constraints. Simultaneously, the algorithm verifies the calculated parameter values ​​of all three-dimensional stratigraphic grid nodes in real time, determining whether they exceed the allowable fluctuation range of the parameters corresponding to the secondary supplementary verification data. Calculation results exceeding the range are temporarily marked (e.g., the calculated value of the silty clay compression modulus of a certain node is 13 MPa, exceeding the constraint range of 8-12 MPa, and is therefore marked). After the calculation is completed, the initial interpolation parameter values ​​are output, including the stratigraphic properties (preliminary matching) and the calculated physical and mechanical parameters of all grid nodes (including marked out-of-range values).

[0120] S453. Based on the planar coordinates and borehole elevation of the three-dimensional stratigraphic grid corresponding to the target exploration site, match the corresponding stratigraphic sequence number for each grid node, and determine the stratigraphic properties and physical and mechanical parameter types of each stratum in the three-dimensional stratigraphic grid.

[0121] In this embodiment of the invention, based on the planar coordinates (X, Y) and orifice elevation (Z) of each node in the three-dimensional stratigraphic grid, combined with the stratigraphic interface depth reference value and constraint boundary in the site stratigraphic reference constraint framework, the stratigraphic sequence number corresponding to each node is matched using an Excel function (such as the IF function): for example, if the node depth Z = 2m, falling within the depth constraint boundary (3±0.5m) of the artificial fill bottom interface, stratigraphic sequence number 1 is matched; if the node depth Z = 5m, falling between the top interface (3m) and bottom interface (8m) of the silty soil, stratigraphic sequence number 2 is matched. Based on the stratigraphic sequence number, the stratigraphic properties (e.g., number 1 corresponds to artificial fill, grayish-brown, loose) and physical and mechanical parameter types (e.g., number 1 needs to include natural density, moisture content, density of silty clay, compression modulus, shear strength, etc.) corresponding to each grid node are determined.

[0122] S454. In accordance with the fusion modeling constraint rules in the exploration operation execution guidelines, perform hierarchical constraint verification on the interpolation initial parameter values ​​to obtain the calculated values ​​of the stratigraphic properties and physical and mechanical parameters of each node of the three-dimensional stratigraphic grid corresponding to the target exploration site.

[0123] In this embodiment of the invention, hierarchical verification is performed according to the fusion modeling constraint rules: Level 1 verification (checking the consistency between the calculated and measured values ​​of parameters at Level 1 data points, with a deviation ≤ 0); Level 2 verification (checking the deviation between the calculated and measured values ​​of parameters at Level 2 data points, with a deviation ≤ ±5%); Level 3 verification (checking whether the changing trend of the calculated parameters is consistent with the stratigraphic trend reflected by the Level 3 data). For parameter values ​​found to be outside the constraint range during verification (e.g., the calculated value of the compression modulus of silty clay at a certain node is 13 MPa, exceeding the constraint range of 8-12 MPa), the nearest Level 1 core constraint data point (e.g., point ZK-008, 50 m away from the node) is found through spatial distance calculation. The corresponding measured parameter value of this point (e.g., 10 MPa) is extracted, and the out-of-range parameter value is truncated and corrected using this measured value (13 MPa is corrected to 10 MPa). After calibration, the stratigraphic properties (stratigraphic number, lithology) and calculated physical and mechanical parameters (density, water content, compressibility modulus, etc.) of each node of the three-dimensional stratigraphic grid corresponding to the target exploration site are obtained.

[0124] S46. Based on the calculated values ​​of stratigraphic properties and physical and mechanical parameters, match the original data source code and hierarchical constraint identifier for each parameter, construct a full parameter fusion matrix with hard constraints, and encapsulate it to generate the initial full parameter fusion dataset.

[0125] In this embodiment of the invention, for each physical and mechanical parameter calculated value of each three-dimensional stratigraphic grid node, a corresponding original data source code (determined through spatial correlation analysis of which original measured data mainly generated the calculated value and associated with its source code) and a hierarchical constraint identifier (marking the constraint type followed by the parameter calculated value, such as "first-level hard constraint", "second-level boundary constraint", "third-level trend constraint") are matched. Using the coordinates (X, Y, Z) of the three-dimensional stratigraphic grid node as an index, and stratigraphic attributes (stratigraphic number, lithology), parameter calculated values ​​(density, water content, etc.), source codes, and hierarchical constraint identifiers as matrix elements, a full-parameter fusion matrix with hard constraints is constructed (dimension = number of grid nodes × (2 + number of parameters + 2), such as 200 × 200 × 60 nodes × (2 + 6 + 2) = 200 × 200 × 60 × 10). This matrix is ​​then encapsulated in the industry-standard HDF5 format (or Excel format) to generate an initial full-parameter fusion dataset.

[0126] S47. Based on the three-dimensional stratigraphic grid, stratigraphic properties and physical and mechanical parameters, and the measured stratigraphic interface of the first-level core constraint data corresponding to the target exploration site, a three-dimensional stratigraphic structure model with the first-level core constraint data as fixed hard control points is constructed. After matching the corresponding parameters in the initial full-parameter fusion dataset, the initial three-dimensional stratigraphic fusion model of the site is generated.

[0127] In this embodiment of the invention, a three-dimensional stratigraphic mesh is used as the basis. Combined with calculated stratigraphic properties and measured stratigraphic interfaces from primary core constraint data, a three-dimensional stratigraphic structure model is constructed using the three-dimensional modeling function of Surfer software. This model clarifies the spatial distribution range and layer interface morphology of each stratum (e.g., the strip-like distribution of silty soil). The calculated parameter values ​​from the initial full-parameter fusion dataset are matched one-to-one with the grid node coordinates into the three-dimensional stratigraphic structure model, ensuring that each grid node possesses complete stratigraphic properties and physical and mechanical parameters. Through model rendering (e.g., assigning different colors based on lithology and different transparency based on parameter values) and optimization, an initial three-dimensional stratigraphic fusion model of the site is generated. The model format is OBJ (Object File Format, a file format used to describe three-dimensional models, which can be imported by various 3D software). It can be imported into Civil 3D for engineering design, a process frequently used in conventional road and building survey projects.

[0128] S48. In accordance with the quality control and verification rules of the exploration operation execution guidelines, hierarchical quality control and verification are carried out on the initial full-parameter fusion dataset and the initial three-dimensional stratigraphic fusion model. After the verification is passed, the site three-dimensional stratigraphic fusion model and the target full-parameter fusion dataset are generated.

[0129] In this embodiment of the invention, hierarchical quality control verification is performed according to the quality control verification rules: Level 1 verification targets the primary core constraint data points, ensuring that the parameters of these points in the model are completely consistent with the measured values ​​(deviation ≤ 0); Level 2 verification targets the secondary supplementary verification data points, ensuring that the deviation of the parameters of these points in the model from the measured values ​​is ≤ ±5%; Level 3 verification targets the rationality of the entire model, checking the continuity of the stratigraphic interface (no obvious breaks or abrupt changes) and the logic of parameter distribution (such as smooth changes in parameters of the same stratigraphic layer without irregular fluctuations), ensuring no obvious unreasonable abrupt changes. For problems found during verification (such as stratigraphic interface breaks or parameter abrupt changes in a certain area), the process is traced back to the interpolation process to check whether there are problems with the constraint settings or data preprocessing, and targeted corrections are made until all verification items pass. Finally, a three-dimensional stratigraphic fusion model of the site (OBJ format, which can be directly used for engineering design visualization) and a target full parameter fusion dataset (HDF5 or CSV format, containing qualified parameters of all grid nodes) are generated, and a quality control verification report is output.

[0130] Step 105: Based on the site's three-dimensional stratigraphic fusion model and the target's full-parameter fusion dataset, and in conjunction with the exploration operation execution criteria, conduct a multi-dimensional comprehensive evaluation of geotechnical engineering, and generate a comprehensive geotechnical engineering evaluation report corresponding to the target exploration site.

[0131] In this embodiment of the invention, the multi-dimensional geotechnical engineering comprehensive evaluation refers to a comprehensive evaluation of site stability and suitability, site seismic effects, foundation, and special projects.

[0132] Furthermore, step 105 includes the following steps:

[0133] S51. Based on the evaluation output constraint rules in the exploration operation execution criteria, the measured data of the corresponding level are extracted from the target full parameter fusion dataset as the calculation input parameters of each evaluation dimension to obtain the input parameter set.

[0134] In this embodiment of the invention, the evaluation output constraint rule in the exploration operation execution criteria is the evaluation data usage requirement determined in step 101. According to this rule, the parameter extraction requirements for each evaluation dimension are clarified: core evaluation indicators (such as foundation bearing capacity, seismic motion parameters, and slope safety factor) only extract parameters corresponding to the first-level core constraint data and the second-level supplementary verification data; the third-level regional reference data is only used as an auxiliary reference and does not participate in the calculation of core indicators. From the target full parameter fusion dataset, measured data of the corresponding level are extracted according to the evaluation dimension: site stability and suitability evaluation extracts stratum bearing capacity, shear strength (c, φ), and permeability coefficient; site seismic effect evaluation extracts shear wave velocity, stratum damping ratio, and stratum thickness; foundation evaluation extracts foundation bearing capacity, compression modulus, layer thickness, and void ratio; special project evaluation (such as roads, buildings, and pipelines) extracts corresponding core parameters (such as subgrade bearing capacity, foundation pit support parameters, and pipeline laying stratum conditions). Unify the data format (e.g., bearing capacity unit kPa, thickness unit m) and units to obtain the input parameter set for each evaluation dimension. Each parameter is labeled with a hierarchical identifier (level 1 / level 2) and a traceability code (e.g., “ZK-005-T-10”).

[0135] S52. Based on the three-dimensional stratum fusion model of the site, the site stability and suitability evaluation, site seismic effect evaluation, foundation evaluation and special project evaluation are carried out using the input parameter set, and special evaluation data of each dimension are generated.

[0136] In this embodiment of the invention, the site's three-dimensional stratigraphic fusion model is used to evaluate the following aspects using the input parameter set, thereby constructing specialized evaluation data for each dimension.

[0137] (1) Site stability and suitability evaluation: Based on the Technical Specification for Building Slope Engineering (GB50330-2013), the limit equilibrium method (built into the Lizheng software) is used to calculate the slope safety factor (Fs≥1.3 is stable). Combined with the bearing capacity of the stratum (determined according to the Code for Design of Building Foundations GB50007-2011), the site suitability is judged (bearing capacity≥120kPa is suitable for buildings). The stability level (stable / basically stable / unstable), suitability level (suitable / basically suitable / unsuitable) and targeted suggestions are generated.

[0138] (2) Site seismic effect evaluation: According to the "Code for Seismic Design of Buildings" (GB50011-2010), the site category (Class I / Class II / Class III / Class IV) is determined based on the shear wave velocity and stratum thickness. Combined with the regional seismic ground motion parameter zoning data, the peak ground acceleration and response spectrum characteristic period of the site are calculated, and the seismic effect evaluation conclusion is generated (e.g., "The site is a Class II site with a peak ground acceleration of 0.15g, and seismic resistance measures need to be taken").

[0139] (3) Foundation evaluation: Based on the "Code for Design of Building Foundation" (GB50007-2011), the final settlement of the foundation is calculated using the layered summation method (Lizheng software) (allowable settlement ≤30cm). Combined with the stratum conditions (such as soil layer thickness and bearing capacity), suitable foundation types (natural foundation, composite foundation, pile foundation) and design parameters (such as pile length, pile diameter, bearing capacity characteristic value) are recommended, and a foundation selection suggestion and design parameter table are generated.

[0140] (4) Special project evaluation: For specific project types such as roads, buildings, and pipelines, select corresponding core parameters (such as the bearing capacity and settlement of roadbeds for road projects, the foundation pit support parameters for building projects, and the laying stratum conditions for pipeline projects), evaluate the feasibility and risks of project construction (such as "the roadbed needs to be replaced, otherwise uneven settlement is likely to occur"), and generate special project construction suggestions.

[0141] S53. For all core evaluation indicators and conclusions in the special evaluation data, match the corresponding data source level and original measured data in the target full parameter fusion dataset to construct a complete data traceability link.

[0142] In this embodiment of the invention, for the core evaluation indicators and conclusions in each special evaluation data, the corresponding calculation input parameters in the target full parameter fusion dataset are back-matched: for example, the input parameter corresponding to "site suitability level (suitable)" is "silty clay bearing capacity 180kPa"; then, through the traceability code of the input parameter, the original measured data "silty clay indoor geotechnical test bearing capacity data of primary point ZK-005 (traceability code ZK-005-T-10)" is matched. Clearly define the one-to-one correspondence between "evaluation conclusion → calculation input parameters → fusion dataset parameters → original measured data", record the data number, hierarchical identifier (level 1 / level 2) and source information (such as "drilling data at point ZK-005") for each link, and construct a complete data traceability link through an Excel spreadsheet. The link is clear and traceable (e.g., "site stability level (stable) → slope safety factor 1.6 → silty clay shear strength c=28kPa, φ=22° → measured data at level 1 point ZK-008 → traceability code ZK-008-T-12").

[0143] S54. Using all special evaluation data, all complete data traceability links, and the original exploration dataset corresponding to the target exploration site, construct a comprehensive geotechnical engineering evaluation report corresponding to the target exploration site in accordance with the exploration operation execution guidelines and current exploration specifications.

[0144] In this embodiment of the invention, the original survey dataset corresponding to the target survey site is the primary, secondary, and tertiary original data collected in steps 102 and 103. Following the survey operation execution guidelines and current survey specifications (such as the "Code for Geotechnical Engineering Investigation" GB50021-2001 and the "Code for Design of Building Foundations" GB50007-2011), all specialized evaluation data, complete data traceability links, and the original survey dataset are integrated to construct a comprehensive geotechnical engineering evaluation report. The report structure is in a standard format: Project Overview (project name, site location, project scale, etc.), Survey Methods and Technical Requirements (survey methods, test items, execution specifications), Site Engineering Geological Conditions (topography, stratigraphic distribution, adverse geological conditions, with screenshots of the site's three-dimensional stratigraphic fusion model), Multi-dimensional Specialized Evaluation Results (stability, seismic effects, foundation, specialized engineering evaluation results and calculation process), Data Traceability Explanation (with a complete data traceability link table), and Engineering Recommendations (construction, design, and protection recommendations based on the evaluation results). The report includes screenshots of the 3D model (visually showing the stratigraphy and parameter distribution), calculation process tables for each evaluation dimension, data traceability table, and a thumbnail of the original data (measured data at key points).

[0145] Please see Figure 2 , Figure 2 This is a structural block diagram of a geotechnical engineering comprehensive evaluation system based on multi-source exploration data, provided as an embodiment of the present invention.

[0146] This invention provides a comprehensive geotechnical engineering evaluation system based on multi-source exploration data, comprising:

[0147] The criteria generation module 201 is used to generate exploration operation execution criteria based on the engineering attributes and regional geological background data of the target exploration site, according to the measured accuracy, reliability and geological constraint effectiveness of the data, preset the priority level division standard of multi-source exploration data and the one-way constraint rules of high level to low level throughout the process.

[0148] The benchmark construction module 202 is used to set up first-level benchmark exploration points in the target exploration site to construct the full-process constraint benchmark in accordance with the exploration operation execution guidelines, and to collect the first-level core constraint measured data corresponding to the first-level benchmark exploration points, and construct the site stratigraphic benchmark constraint framework and the first-level core constraint benchmark dataset.

[0149] The data quality control module 203 is used to carry out constrained acquisition and closed-loop verification of low-level exploration data in accordance with the exploration operation execution guidelines, based on the site stratigraphic benchmark constraint framework and the first-level core constraint benchmark dataset as the calibration benchmark, and generate a full-level multi-source exploration dataset that has passed quality control.

[0150] The fusion modeling module 204 is used to perform spatial fusion interpolation of multi-source data with hierarchical hard constraints, using the first-level core constraint benchmark dataset as fixed hard control points and the full-level multi-source exploration dataset as input data source, in accordance with the exploration operation execution criteria, to generate a three-dimensional stratigraphic fusion model of the site and a target full-parameter fusion dataset.

[0151] The comprehensive evaluation module 205 is used to conduct a multi-dimensional comprehensive evaluation of geotechnical engineering based on the site's three-dimensional stratigraphic fusion model and the target's full-parameter fusion dataset, combined with the exploration operation execution criteria, and to generate a comprehensive geotechnical engineering evaluation report corresponding to the target exploration site.

[0152] The specific implementation of this geotechnical engineering comprehensive evaluation system based on multi-source exploration data is basically the same as the specific implementation of the geotechnical engineering comprehensive evaluation method based on multi-source exploration data described above, and will not be repeated here.

[0153] Please see Figure 3 , Figure 3 This is a structural block diagram of an electronic device provided in an embodiment of the present invention.

[0154] An electronic device according to an embodiment of the present invention includes: a memory 301 and a processor 302. The memory 301 stores a computer program. When the computer program is executed by the processor 302, the processor 302 executes the geotechnical engineering comprehensive evaluation method based on multi-source exploration data as described in any of the above embodiments.

[0155] Memory 301 may be an electronic memory such as flash memory, EEPROM (Electrically Erasable Programmable Read-Only Memory), EPROM, hard disk, or ROM. Memory 301 has storage space 303 for program code 313 for performing any of the method steps described above. For example, storage space 303 for program code may include various program codes 313 for implementing the various steps in the methods described above. These program codes may be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, CDs, memory cards, or floppy disks. The program code may be compressed, for example, in a suitable form. When run by a computing processing device, this code causes the computing processing device to perform the various steps in the methods described above. These program codes may be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, CDs, memory cards, or floppy disks. The program code may be compressed, for example, in a suitable form. When these codes are run by a computing device, the computing device causes the device to perform the various steps in the geotechnical engineering comprehensive evaluation method based on multi-source exploration data described above.

[0156] This invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the geotechnical engineering comprehensive evaluation method based on multi-source exploration data as described in any of the above embodiments.

[0157] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0158] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between apparatuses or units, and may be electrical, mechanical, or other forms.

[0159] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0160] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0161] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0162] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A comprehensive evaluation method for geotechnical engineering based on multi-source exploration data, characterized in that, Includes the following steps: Based on the engineering attributes of the target exploration site and regional geological background data, and according to the measured accuracy, reliability and geological constraint effectiveness of the data, a priority hierarchy classification standard for multi-source exploration data and a one-way constraint rule from high-level to low-level data throughout the entire process are preset to generate exploration operation execution criteria. According to the exploration operation execution guidelines, primary benchmark exploration points are set up in the target exploration site to construct a full-process constraint benchmark, and the primary core constraint measured data corresponding to the primary benchmark exploration points are collected to construct the site stratigraphic benchmark constraint framework and the primary core constraint benchmark dataset. Using the site stratigraphic benchmark constraint framework and the first-level core constraint benchmark dataset as calibration benchmarks, constrained acquisition and closed-loop verification of low-level exploration data are carried out in accordance with the exploration operation execution criteria to generate a full-level multi-source exploration dataset that meets quality control requirements. Using the first-level core constraint benchmark dataset as fixed hard control points and the full-level multi-source exploration dataset as input data source, multi-source data spatial fusion interpolation with hierarchical hard constraints is performed according to the exploration operation execution criteria to generate a site three-dimensional stratigraphic fusion model and a target full parameter fusion dataset. Based on the site's three-dimensional stratigraphic fusion model and the target's full-parameter fusion dataset, and combined with the exploration operation execution criteria, a multi-dimensional comprehensive evaluation of geotechnical engineering is conducted to generate a comprehensive geotechnical engineering evaluation report corresponding to the target exploration site.

2. The geotechnical engineering comprehensive evaluation method based on multi-source exploration data according to claim 1, characterized in that, The steps for generating exploration operation execution criteria based on the engineering attributes and regional geological background data of the target exploration site, pre-setting priority hierarchy standards for multi-source exploration data and unidirectional constraint rules from high-level to low-level data throughout the entire process, include: Based on the engineering importance level, site category, and regional geological background data of the target exploration site, and in conjunction with the requirements of the current geotechnical engineering exploration specifications, an evaluation dimension matrix of multi-source exploration data is constructed with the data measurement accuracy, reliability, and geological constraint effectiveness as the core evaluation dimensions. The evaluation dimension matrix is ​​used to prioritize and classify the various types of exploration data involved in the entire process of geotechnical engineering exploration corresponding to the target exploration site, and to generate the priority classification standard of the multi-source exploration data. Based on the aforementioned priority hierarchy classification standard, for the four core stages of the entire exploration operation process—collection, quality control, fusion, and evaluation—one-way constraint execution rules for higher-level to lower-level stages are formulated respectively, generating one-way constraint rules for the entire process. The priority level classification criteria and the full-process unidirectional constraint rules are integrated and verified for compliance to generate standardized exploration operation execution guidelines.

3. The geotechnical engineering comprehensive evaluation method based on multi-source exploration data according to claim 1, characterized in that, The steps of establishing primary benchmark exploration points within the target exploration site to construct a full-process constraint benchmark, in accordance with the exploration operation execution guidelines, and collecting measured data of primary core constraints corresponding to the primary benchmark exploration points, to construct the site stratigraphic benchmark constraint framework and the primary core constraint benchmark dataset, include: Based on the priority hierarchy classification criteria and dynamic exploration point layout rules in the exploration operation execution guidelines, and combined with the preliminary regional geological assessment results of the target exploration site and the overall engineering control requirements, a primary benchmark exploration point layout scheme is constructed. According to the above-mentioned primary benchmark exploration point layout plan, primary benchmark exploration points are laid out in the target exploration site, and drilling operations and in-situ tests are carried out at the primary benchmark exploration points to obtain the measured data of the primary core constraints corresponding to the primary benchmark exploration points. Based on the measured data of the first-level core constraints, the standard stratigraphic sequence of the site is divided, and the lithological characteristics, layer interface depth, benchmark values ​​of physical and mechanical parameters and full-process constraint boundaries of each stratum are determined to construct the site stratigraphic benchmark constraint framework. Based on the quality control rules in the exploration operation execution criteria, the measured data of the first-level core constraints are standardized, processed, and quality controlled, and outliers are removed to generate a first-level core constraint benchmark dataset.

4. The geotechnical engineering comprehensive evaluation method based on multi-source exploration data according to claim 1, characterized in that, The steps of using the site stratigraphic benchmark constraint framework and the first-level core constraint benchmark dataset as calibration benchmarks, and conducting constrained acquisition and closed-loop verification of low-level exploration data according to the exploration operation execution criteria to generate a quality-controlled, multi-source exploration dataset at all levels include: Based on the one-way constraint rules in the exploration operation execution guidelines, and using the site stratigraphic benchmark constraint framework as the calibration benchmark, combined with the layout of the first-level benchmark exploration points, a segmented acquisition scheme for low-level exploration data is constructed. According to the segmented acquisition scheme, segmented collaborative acquisition of low-level exploration data is carried out. Using the first-level core constraint benchmark dataset as the correction benchmark, stratigraphic calibration, deviation correction and invalid data removal are performed on the acquired low-level exploration data to generate low-level exploration correction data. Using the aforementioned low-level exploration and correction data, stratigraphic anomaly zones and suspected adverse geological processes within the target exploration site are identified, and a site anomaly zone distribution map is generated. Based on the dynamic exploration point layout rules in the exploration operation execution guidelines, first-level verification exploration points are added to the abnormal areas in the site anomaly distribution map, and the first-level core constraint measured data of the first-level verification exploration points are collected as verification data. The verification data is used to iteratively refine the low-level survey data of the corresponding anomaly areas, and the site anomaly distribution map is updated synchronously. When there are no abnormal areas on the site anomaly distribution map, a full-level multi-source exploration dataset is constructed using all quality-controlled and qualified exploration data from each level.

5. The geotechnical engineering comprehensive evaluation method based on multi-source exploration data according to claim 1, characterized in that, The steps of generating a site 3D stratigraphic fusion model and a target full-parameter fusion dataset by using the first-level core constraint benchmark dataset as fixed hard control points and the full-level multi-source exploration dataset as input data sources, and performing hierarchical hard constraint multi-source data spatial fusion interpolation according to the exploration operation execution criteria, include: Based on the fusion modeling constraint rules in the exploration operation execution criteria, the full-level multi-source exploration dataset is standardized and preprocessed, and then split into first-level core constraint data, second-level supplementary verification data and third-level regional reference data according to the preset hierarchical division standard. Based on the point coordinates and measured values ​​of the first-level core constraint data, a hard constraint condition matrix that cannot be adjusted during the interpolation calculation process is constructed. Based on the parameter value range of the secondary supplementary verification data, inequality constraint terms for interpolation calculation are constructed; Based on the stratigraphic spatial distribution characteristics of the three-level regional reference data, a stratigraphic spatial variation trend term is constructed using interpolation calculation; Based on the hard constraint condition matrix, inequality constraint terms, and stratigraphic spatial variation trend terms, spatial interpolation calculations with hierarchical hard constraints are performed to obtain the stratigraphic properties and physical and mechanical parameters of each node of the three-dimensional stratigraphic grid corresponding to the target exploration site. Based on the calculated values ​​of the geological properties and physical and mechanical parameters, the original data source code and hierarchical constraint identifier are matched for each parameter, a full parameter fusion matrix with hard constraints is constructed and encapsulated to generate the initial full parameter fusion dataset; Based on the three-dimensional stratigraphic grid, stratigraphic properties and physical and mechanical parameters, and the measured stratigraphic interface of the first-level core constraint data corresponding to the target exploration site, a three-dimensional stratigraphic structure model with the first-level core constraint data as fixed hard control points is constructed. After matching the corresponding parameters in the initial full-parameter fusion dataset, the initial three-dimensional stratigraphic fusion model of the site is generated. In accordance with the quality control and verification rules of the exploration operation execution criteria, the initial full-parameter fusion dataset and the initial three-dimensional stratigraphic fusion model are subjected to hierarchical quality control and verification. After the verification is passed, the site three-dimensional stratigraphic fusion model and the target full-parameter fusion dataset are generated.

6. The geotechnical engineering comprehensive evaluation method based on multi-source exploration data according to claim 5, characterized in that, The step of performing hierarchical hard-constrained spatial interpolation calculations based on the hard constraint matrix, inequality constraint terms, and stratigraphic spatial variation trend terms to obtain the calculated values ​​of stratigraphic properties and physical and mechanical parameters of each node of the three-dimensional stratigraphic grid corresponding to the target exploration site includes: The input parameters for interpolation calculation are assigned using the hard constraint condition matrix as the equality constraint term, the inequality constraint term as the boundary constraint term, and the stratigraphic spatial variation trend term as the auxiliary trend term. Based on the input parameter values, perform spatial interpolation calculations with hierarchical hard constraints to obtain initial interpolation parameter values; Based on the planar coordinates and borehole elevation of the three-dimensional stratigraphic grid corresponding to the target exploration site, a corresponding stratigraphic sequence number is matched for each grid node to determine the stratigraphic properties and physical and mechanical parameter types of each stratum in the three-dimensional stratigraphic grid. According to the fusion modeling constraint rules in the exploration operation execution criteria, the interpolation initial parameter values ​​are checked for hierarchical constraints to obtain the calculated values ​​of the stratigraphic properties and physical and mechanical parameters of each node of the three-dimensional stratigraphic grid corresponding to the target exploration site.

7. The geotechnical engineering comprehensive evaluation method based on multi-source exploration data according to claim 1, characterized in that, The steps of performing a multi-dimensional comprehensive geotechnical engineering evaluation based on the site's three-dimensional stratigraphic fusion model and the target full-parameter fusion dataset, combined with the exploration operation execution criteria, to generate a comprehensive geotechnical engineering evaluation report corresponding to the target exploration site include: Based on the evaluation output constraint rules in the exploration operation execution criteria, the measured data of the corresponding level are extracted from the target full parameter fusion dataset as the calculation input parameters of each evaluation dimension to obtain the input parameter set; Based on the aforementioned three-dimensional geological fusion model, the site stability and suitability evaluation, site seismic effect evaluation, foundation evaluation, and special project evaluation are carried out using the aforementioned input parameter set, generating special evaluation data for each dimension. For all core evaluation indicators and conclusions in the special evaluation data, match the corresponding data source level and original measured data in the target full parameter fusion dataset to construct a complete data traceability link; Using all the aforementioned specialized evaluation data, all the aforementioned complete data traceability links, and the original exploration dataset corresponding to the target exploration site, a comprehensive geotechnical engineering evaluation report corresponding to the target exploration site is constructed in accordance with the exploration operation execution guidelines and current exploration specifications.

8. A comprehensive geotechnical engineering evaluation system based on multi-source exploration data, characterized in that, include: The criteria generation module is used to generate exploration operation execution criteria based on the engineering attributes of the target exploration site and regional geological background data, according to the measured accuracy, reliability and geological constraint effectiveness of the data, preset the priority level classification standard of multi-source exploration data and the one-way constraint rules of high level to low level throughout the process. The benchmark construction module is used to set up primary benchmark exploration points in the target exploration site according to the exploration operation execution criteria, and to collect the primary core constraint measured data corresponding to the primary benchmark exploration points, thereby constructing the site stratigraphic benchmark constraint framework and the primary core constraint benchmark dataset. The data quality control module is used to carry out constrained acquisition and closed-loop verification of low-level exploration data according to the exploration operation execution criteria, based on the site stratigraphic benchmark constraint framework and the first-level core constraint benchmark dataset as the calibration benchmark, and generate a full-level multi-source exploration dataset that has passed quality control. The fusion modeling module is used to perform spatial fusion interpolation of multi-source data with hierarchical hard constraints, using the first-level core constraint benchmark dataset as fixed hard control points and the full-level multi-source exploration dataset as input data source, in accordance with the exploration operation execution criteria, to generate a three-dimensional stratigraphic fusion model of the site and a target full-parameter fusion dataset. The comprehensive evaluation module is used to conduct a multi-dimensional comprehensive evaluation of geotechnical engineering based on the three-dimensional stratigraphic fusion model of the site and the target full-parameter fusion dataset, combined with the exploration operation execution criteria, and generate a comprehensive geotechnical engineering evaluation report corresponding to the target exploration site.

9. An electronic device, characterized in that, The system includes a memory and a processor. The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the geotechnical engineering comprehensive evaluation method based on multi-source exploration data as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it implements the geotechnical engineering comprehensive evaluation method based on multi-source exploration data as described in any one of claims 1-7.

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