Geotechnical investigation risk analysis method, system, equipment, medium and product

Abstract

The invention discloses a geotechnical investigation risk analysis method, system and device, a medium and a product, and relates to the technical field of geotechnical investigation, the method comprises the following steps: obtaining geospatial data of a to-be-investigated area, the geospatial data comprising environmental data and geological data; performing survey position division on the to-be-surveyed area according to the geographic space data; acquiring investigation equipment corresponding to each investigation position; acquiring investigation operation data of each piece of investigation equipment; constructing a survey process animation model according to the geological data, the survey positions, and the survey equipment and survey operation data corresponding to each survey position; and performing investigation risk assessment on the to-be-investigated region according to a preset assessment algorithm based on the investigation process animation model. According to the invention, the efficiency of geotechnical investigation can be improved.

Description

Technical Field

[0001] The present application relates to the field of geotechnical exploration technology, and in particular to a geotechnical exploration risk analysis method, system, equipment, medium and product. Background Art

[0002] Geotechnical investigation refers to the activity of investigating, studying, analyzing and evaluating the geological, environmental characteristics and geotechnical engineering conditions of the construction site by using various surveying techniques and methods according to the requirements of the construction project. Its purpose is to identify, analyze and evaluate the geological, environmental characteristics and geotechnical engineering conditions of the construction site, and on this basis, compile survey documents, solve existing geotechnical engineering problems, and ensure the smooth progress of engineering design and construction.

[0003] In order to ensure the smooth progress of geotechnical investigation, the investigation process will be analyzed before the investigation to determine the risks in the investigation. However, traditional geotechnical investigation risk analysis is mainly based on expert evaluation, which is time-consuming and affects the efficiency of geotechnical investigation. Summary of the invention

[0004] The purpose of this application is to provide a geotechnical investigation risk analysis method, system, equipment, medium and product, which can improve the efficiency of geotechnical investigation.

[0005] To achieve the above objectives, this application provides the following solutions: In a first aspect, the present application provides a geotechnical investigation risk analysis method, comprising: Acquiring geospatial data of the area to be surveyed, wherein the geospatial data includes: environmental data and geological data; Dividing the area to be surveyed into survey locations according to the geospatial data; Acquire a survey device corresponding to each of the survey locations; Acquiring survey operation data of each of the survey equipment; Constructing a survey process animation model according to the geological data, the survey locations, and the survey equipment and survey operation data corresponding to each of the survey locations; Based on the survey process animation model, a survey risk assessment is performed on the area to be surveyed according to a preset assessment algorithm.

[0006] In a second aspect, the present application provides a geotechnical investigation risk analysis system, comprising: A data retrieval unit, used to obtain geographic spatial data of the area to be surveyed, wherein the geographic spatial data includes: environmental data and geological data; A data analysis unit, used for dividing the area to be surveyed into survey locations according to the geographic spatial data; A survey equipment acquisition unit, used to acquire the survey equipment corresponding to each of the survey locations; A survey data acquisition unit, used to acquire survey operation data of each of the survey equipment; A data simulation unit, used to construct a survey process animation model according to the geological data, the survey locations, and the survey equipment and survey operation data corresponding to each of the survey locations; An evaluation unit is used to perform an exploration risk evaluation on the area to be investigated based on the exploration process animation model and a preset evaluation algorithm.

[0007] In a third aspect, the present application provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of any of the geotechnical investigation risk analysis methods described above.

[0008] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the geotechnical investigation risk analysis methods described above.

[0009] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of any of the geotechnical investigation risk analysis methods described above.

[0010] According to the specific embodiments provided in this application, this application discloses the following technical effects: The present application provides a geotechnical investigation risk analysis method, system, equipment, medium and product, which can divide the investigation location of the area to be investigated by obtaining the environmental data and geological data of the area to be investigated. After the investigation location is divided, the investigation equipment corresponding to each investigation location will be determined, and the investigation operation data of each investigation equipment will be obtained. After obtaining the geological data, investigation location of the area to be investigated, and the investigation equipment and investigation operation data corresponding to each investigation location, an investigation process animation model will be constructed according to these data. The investigation process animation model can fully reflect the investigation process of the area to be investigated. When conducting an investigation risk assessment, the investigation process animation model can be automatically evaluated and analyzed by a preset evaluation algorithm, so as to obtain the investigation risk assessment result of the area to be investigated. This investigation risk method does not rely on expert evaluation, and the risk analysis is faster, which can speed up the geotechnical investigation. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0012] Figure 1 is a flow chart of a geotechnical investigation risk analysis method according to an exemplary embodiment; Figure 2 A schematic diagram of functional modules of a geotechnical investigation risk analysis system provided in one embodiment of the present application; Figure 3 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0013] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0014] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0015] In modern engineering construction, geotechnical exploration risk assessment plays a vital role and is widely used in many key areas. In the field of construction engineering, whether it is a towering skyscraper or a large commercial complex, geotechnical exploration risk assessment is a key link in the early preparation. By accurately detecting the stratum structure and soil mechanical properties, it is possible to gain early insight into potential crises such as foundation settlement and sand liquefaction, laying a solid foundation for building foundation design.

[0016] In terms of transportation engineering, the route planning of highways and railways and the construction of bridges and tunnels are inseparable from geotechnical exploration risk assessment. When building highways in mountainous areas, it can help identify dangerous sections prone to landslides and collapses, and effectively avoid geological disaster risks; in bridge construction, the exploration and assessment of bridge pier foundations can ensure the stability of bridges under complex geological conditions.

[0017] In the field of energy engineering, geotechnical exploration risk assessment is of utmost importance for projects such as nuclear power plants that have extremely stringent requirements on geological stability. Through detailed surveys and assessments of factors such as seismic activity and stratum stability, solid geological data support is provided for the site selection and construction of nuclear power plants, ensuring the long-term safe operation of nuclear facilities.

[0018] The same is true for water conservancy and hydropower projects. The construction of dams and hydropower stations is related to the national economy and people's livelihood. Geotechnical exploration risk assessment can comprehensively analyze the anti-sliding and seepage stability of the dam foundation, as well as the surrounding rock conditions of the underground caverns, effectively ensuring the construction safety and subsequent stable operation of water conservancy and hydropower projects. It can be said that geotechnical exploration risk assessment is an important guarantee for the smooth development and safe operation of many projects.

[0019] However, traditional geotechnical investigation risk analysis is mainly based on expert evaluation, which is time-consuming and affects the efficiency of geotechnical investigation.

[0020] In order to solve the above technical problems, the present disclosure provides a geotechnical investigation risk analysis method, system, equipment, medium and product.

[0021] Figure 1 is a flow chart of a geotechnical investigation risk analysis method according to an exemplary embodiment. Figure 1 As shown, the method includes the following steps S101-S106: In step S101, the geospatial data of the area to be surveyed is obtained.

[0022] Among them, geospatial data includes: environmental data and geological data.

[0023] The environmental data includes at least one of the following data: meteorological data, water environment data, ecological environment data and soil environment data.

[0024] The meteorological data may include at least one of the following data: temperature, precipitation, wind speed, wind direction, humidity and sunshine duration.

[0025] Temperature: including daily average temperature, monthly average temperature, annual average temperature, and extreme maximum and minimum temperatures. Temperature changes will affect the physical properties of rock and soil. For example, high temperature may cause soil moisture to evaporate, causing soil shrinkage and affecting foundation stability; low temperature may cause soil to freeze and produce frost heave.

[0026] Precipitation: This includes information on annual precipitation, seasonal distribution of precipitation, and precipitation intensity. Large amounts of precipitation may cause geological disasters such as landslides and mud-rock flows, and may also affect groundwater levels and soil moisture.

[0027] Wind speed and direction: average wind speed, maximum wind speed and prevailing wind direction. Strong winds may cause damage to ground facilities and buildings, so wind protection measures need to be considered during building planning and design.

[0028] Humidity: The humidity of the air will affect the corrosion rate of the material and is of great significance to the inspection of metal structures. A high humidity environment may also cause mold growth and affect the quality of the indoor environment.

[0029] Sunshine duration: Understanding local sunshine conditions is of great value for solar energy utilization, building lighting design, and plant growth environment assessment.

[0030] Water environment data may include: surface water conditions, and / or groundwater conditions.

[0031] Surface water conditions: including water levels, flow rates, and water quality (pH, dissolved oxygen, chemical oxygen demand, heavy metal content, etc.) of rivers, lakes, reservoirs, etc. Changes in surface water levels may affect the stability of surrounding land, and water pollution poses a potential threat to the surrounding ecological environment and human health.

[0032] Groundwater conditions: the height of the groundwater level, the law of water level changes, the direction of groundwater flow, and water quality characteristics (hardness, mineralization, corrosiveness, etc.). The rise and fall of the groundwater level will affect the bearing capacity of the foundation soil, and corrosive groundwater may cause damage to the foundation structure.

[0033] Ecological and environmental data may include: vegetation cover, and / or, biodiversity.

[0034] Vegetation coverage: vegetation type, vegetation coverage rate. Vegetation can maintain water and soil and regulate the climate. The change of vegetation coverage rate reflects the stability and changing trend of the ecological environment.

[0035] Biodiversity: the types, quantity and distribution of plants and animals in a region. The richness of biodiversity is an important indicator of ecosystem health and is crucial for ecological protection and environmental impact assessment.

[0036] Soil environmental data may include: soil type, and / or soil pollution status.

[0037] Soil type: such as sand, clay, loam, etc. Different soil types have different physical and mechanical properties and different suitability for engineering construction.

[0038] Soil pollution status: the content of heavy metals, pesticide residues, organic matter and other pollutants in the soil. Soil pollution not only affects soil quality and ecological functions, but may also cause harm to human health through the food chain.

[0039] The geological data includes at least one of the following data: stratigraphic structure data, rock mechanical property data, geological structure data, seismic data and geophysical property data.

[0040] Stratigraphic data may include: stratigraphic stratification or stratigraphic age.

[0041] Stratigraphic stratification: The distribution, thickness and lithological characteristics of different strata. Understanding the strata is crucial for engineering foundation design, tunnel construction, underground engineering construction, etc.

[0042] Stratigraphic age: Determining the geological age of strata formation helps to understand the history of geological evolution and the formation process of geological structures.

[0043] Rock mechanical properties data may include: rock strength, and / or rock deformation characteristics, Rock strength: including compressive strength, tensile strength, shear strength, etc. Rock strength is an important indicator for evaluating rock stability and bearing capacity, and is of key significance for the design and construction of rock slopes, underground caverns and other projects.

[0044] Rock deformation characteristics: such as elastic modulus, Poisson's ratio, etc., reflect the deformation ability of rock under force.

[0045] The geological structure data may include faults, and / or folds.

[0046] Fault: location, strike, dip, activity, etc. Faults are weak areas in the earth's crust that may cause earthquakes, landslides and other geological disasters, and have a significant impact on engineering construction.

[0047] Fold: The shape, scale and distribution of folds. The fold structure will affect the spatial distribution of strata and the mechanical properties of rocks.

[0048] Seismic data may include: seismic intensity, and / or, seismic activity frequency.

[0049] Earthquake intensity: It indicates the degree of damage caused by an earthquake to the ground and buildings, and is an important basis for earthquake-resistant design of engineering projects.

[0050] Frequency of earthquake activity: Understand the frequency and intensity of earthquakes in local history and assess earthquake risks.

[0051] The geophysical property data includes at least one of the following data: density, porosity and water content.

[0052] Density: The ratio of the mass to volume of rock and soil, reflecting the compactness of the rock and soil.

[0053] Porosity: The ratio of the pore volume to the total volume in rock and soil, which affects the permeability and compressibility of rock and soil.

[0054] Moisture content: The ratio of the mass of water contained in rock and soil to the mass of dry soil, which has a significant impact on the strength and deformation characteristics of rock and soil.

[0055] For example, the environmental data of the area to be surveyed can be obtained through the meteorological bureau of the area to be surveyed, and the geological data of the area to be surveyed can be obtained through the geological bureau of the area to be surveyed.

[0056] In step S102, the area to be surveyed is divided into survey locations according to the geographic space data.

[0057] In one embodiment, dividing the area to be surveyed into survey locations according to the geospatial data includes the following sub-steps S1021-S1022: S1021. Perform correlation analysis on the geographic spatial data to obtain target correlation relationships.

[0058] Specifically, step S1021 includes the following sub-steps S10211-S10214: S10211. Preprocess the geospatial data.

[0059] Preprocessing of geospatial data can include cleaning the collected environmental data and geological data, deleting or correcting erroneous data, and processing missing values ​​and outliers to ensure the quality and consistency of the data. Specifically: Among them, professional data cleaning algorithms and tools can be used to conduct a comprehensive screening of the collected environmental data and geological data. In environmental data, such as atmospheric pollutant monitoring data, erroneous data may be mixed in due to factors such as monitoring equipment failure and signal transmission interference. Similar problems also exist in geological data, such as errors in drilling data recording during geological exploration. This step establishes a data quality rule base, compares and verifies the data according to established rules, and accurately identifies erroneous data.

[0060] For erroneous data identified during the data cleaning process, targeted measures are taken based on the data source, data characteristics, and relevant field knowledge. If the erroneous data is caused by instrument calibration deviation, the erroneous data is corrected by comparing it with the instrument calibration record and standard sample data; data that cannot be corrected and whose errors seriously affect data quality are deleted.

[0061] A variety of advanced missing value filling algorithms, such as mean filling method, regression filling method, K nearest neighbor filling method, etc., are used to process missing values ​​in environmental data and geological data. For missing values ​​of temperature in a certain period of time in environmental data, appropriate algorithms can be used to fill in the missing values ​​based on the temperature change pattern in adjacent periods and the data from surrounding monitoring stations. In geological data, for missing values ​​of stratum thickness, corresponding algorithms can be used to fill in the missing values ​​based on the geological structure characteristics of the region and surrounding drilling data to ensure data integrity.

[0062] For example, when the missing values ​​account for a small proportion of the data set and deleting these missing value records will not have a significant impact on the statistical characteristics and analysis results of the overall data, these records can be deleted directly. If there are many missing values, mean filling (for numerical data, calculate the mean of the feature and fill it into the missing position), median filling (fill missing values ​​with the median, which is suitable for data with outliers) or filling based on similar samples (find other samples similar to the sample where the missing value is located, and fill it with the feature value of the similar sample).

[0063] Statistical methods and machine learning algorithms, such as the outlier detection method based on box plots and the IsolationForest algorithm, are used to detect and process outliers in the data. In environmental data, for water quality monitoring outliers that exceed the normal range, the water quality of surrounding waters and historical data are combined to determine whether they are real anomalies. If they are abnormal data, they are corrected or deleted according to the actual situation; in geological data, for outliers in geotechnical mechanics parameters, they are compared with the geological conditions of the region and similar stratum data, and corresponding processing is performed to ensure the quality and consistency of the data, providing a reliable data foundation for subsequent analysis, modeling and application based on geospatial data.

[0064] S10212. Cluster the preprocessed geographic spatial data using a clustering algorithm to obtain the correlation relationship between each data in the geographic spatial data.

[0065] Clustering is used to classify data points with similar characteristics into the same class, thereby dividing the survey area into different categories. The basis for clustering can be the similarity of geological conditions, the similarity of environmental factors, etc.

[0066] For example, the following cluster analysis formula can be used: ; Where J represents the sum of squared errors; is the point set of the ith cluster, is the centroid of the ii-th cluster, K is the number of clusters, and x is the data point, i is the centroid of the i-th cluster, Represents the data point x and the cluster center The square of the Euclidean distance between them.

[0067] In cluster analysis, since the characteristics of environmental data and geological data may have different dimensions and value ranges, in order to avoid certain characteristics from having too much influence on the clustering results, the data needs to be standardized. Commonly used standardization methods include Z-score standardization, the formula is , where x is the original data, is the mean, is the standard deviation.

[0068] This disclosure uses the K-Means algorithm, and its steps are as follows: Initialize the centroid: Randomly select K data points from the dataset as the initial centroid.

[0069] Assign data points: Calculate the Euclidean distance of each data point to the K centroids and assign the data point to the cluster with the nearest centroid.

[0070] Update the centroid: Recalculate the position of the centroid based on the data points in each cluster.

[0071] Iterative optimization: Repeat the steps of assigning data points and updating centroids until the centroids no longer change significantly or the preset maximum number of iterations is reached.

[0072] Determine the number of clusters: You can use the elbow method to plot the number of clusters for different K values. The K value corresponding to the “elbow point” where the slope of the curve changes significantly is selected as the optimal number of clusters.

[0073] S10213. Verify whether the association relationship is valid.

[0074] The validity of the mined associations can be verified through feasibility analysis and error analysis techniques.

[0075] Feasibility analysis can be verified by theoretical basis and practical application.

[0076] Verification of theoretical basis: Combine the principles of geology, environmental science and other related disciplines to analyze the discovered correlations. For example, if the correlation shows that the geological structure of a certain area is related to the concentration of a specific pollutant, analyze whether this correlation conforms to scientific logic based on the theory of the influence of geological structure on material migration and transformation. By consulting a large number of professional literature and referring to authoritative research results, ensure that the correlation is reasonable at the theoretical level.

[0077] Practical application verification: Apply the mined associations to actual scenario simulations. Build a simulation model, input different environmental data and geological data parameters, and observe the fit between the model output results and the actual situation. When simulating the relationship between water quality changes in a river basin and surrounding geological conditions, refer to historical monitoring data and field surveys to test whether the simulation results can accurately reflect the actual water quality change trends. If the simulation results are consistent with the actual situation or the error is within an acceptable range, it means that the association is feasible in practical applications.

[0078] Error analysis technology can analyze internal error indicators as well as external error indicators.

[0079] Internal error index: Calculate the clustering error sum of squares J. The smaller J is, the better the clustering effect is. You can also calculate the silhouette coefficient. The closer the silhouette coefficient is to 1, the closer the data point is to the points in the same cluster and the farther it is from the points in other clusters, and the better the clustering effect is.

[0080] External error index: If there is a known true classification result as a reference, you can use indicators such as the Rand Index and the Adjusted Rand Index to measure the consistency between the clustering result and the true classification. The closer the value is to 1, the more accurate the clustering result is.

[0081] S10214. Determine a valid association relationship as a target association relationship.

[0082] After obtaining the association relationship, you can also visualize the association relationship and display it visually.

[0083] Two-dimensional visualization, three-dimensional visualization, and geographic information system (GIS) visualization can be used.

[0084] Two-dimensional visualizations can include: scatter plots or bar charts.

[0085] Scatter plot: Select two representative features as coordinate axes, plot each data point on a two-dimensional plane, and use different colors or shapes to represent different clustering results. For example, with soil heavy metal content as the x-axis and stratum depth as the y-axis, the distribution of different clusters on these two features can be intuitively observed through a scatter plot.

[0086] Histogram: Count the average value or number of each feature in each cluster and display it using a histogram. For example, displaying the proportion of different rock types in each cluster can clearly compare the feature differences between different clusters.

[0087] For data with three important features, a 3D scatter plot or 3D surface plot can be used for visualization. For example, using groundwater level, soil moisture content, and soil pH as the three coordinate axes, plotting data points in a 3D space and distinguishing colors based on clustering results can more comprehensively display the distribution and clustering relationship of the data.

[0088] Geographic Information System (GIS) visualization can also be used: clustering results are combined with geographic spatial information and visualized on the GIS platform. Distribution maps of different clustering areas can be drawn to intuitively understand the correlation and spatial distribution patterns of environmental data and geological data in different areas. For example, the areas corresponding to different clusters are marked on the map. The darker the color, the higher the value of a certain feature in the area. This can help decision makers quickly identify the spatial differences in environmental and geological characteristics.

[0089] S1022. Divide the area to be surveyed into different survey locations according to the target association relationship.

[0090] Each target association corresponds to a survey location.

[0091] In step S103, the survey equipment corresponding to each survey location is obtained.

[0092] Appropriate survey equipment can be selected based on geological data and environmental data of the survey location.

[0093] When environmental data show that the geological conditions are relatively simple, the strata are shallow, and the rock and soil properties do not change much, a lightweight dynamic penetration instrument can be used. If more detailed rock and soil physical and mechanical properties are required, a portable static penetration instrument can be used to divide the soil layers and evaluate the soil properties by measuring the cone tip resistance and side wall friction resistance.

[0094] In cases where geological data indicates the presence of a deep overburden or where it is necessary to understand the structure of deep strata, drilling equipment should be used. For example, a rotary drill can obtain core samples and provide an intuitive understanding of the lithology, thickness, and stratification of the strata. For hard rock strata, an impact drill can be used to break the rock using impact force for drilling.

[0095] When encountering special rock and soil such as soft soil, expansive soil, collapsible loess, etc., targeted equipment should be selected. For example, for soft soil, a cross-plate shear instrument can be used to measure its shear strength; for expansive soil, a dilatometer can be used to measure its expansion rate and contraction rate.

[0096] If geological data indicates the existence of faults, folds and other structures, geological radar can be used. It can detect the distribution of underground media by emitting high-frequency electromagnetic waves and effectively identify the location, direction and scale of faults. In addition, seismographs can also be used to detect the activity of underground geological structures and analyze the propagation characteristics of seismic waves in different media to infer structural information.

[0097] In karst-developed areas, drilling equipment and geophysical methods are used in combination. Drilling can directly reveal the location and size of caves, while geophysical methods such as high-density electrical methods can detect the distribution range of underground karst over a large area, providing a basis for subsequent engineering treatment.

[0098] When conducting surveys in high temperature areas, it is necessary to select equipment that can withstand high temperatures.

[0099] In cold areas, the equipment must be cold-resistant.

[0100] If environmental data shows that the area to be surveyed often has strong winds, the equipment must have sufficient stability. For example, the measuring instrument must be equipped with a stable tripod to prevent it from being blown down by the wind. For large equipment, fixing measures must be taken to ensure its safety in strong winds.

[0101] Areas with heavy precipitation: Choose equipment with good waterproof performance.

[0102] If the groundwater level is high, the waterproof and drainage capabilities of the equipment should be considered when selecting drilling equipment. For example, when using the mud wall drilling method, it is necessary to equip appropriate mud pumps and drainage equipment to prevent the hole wall from collapsing and water accumulation in the hole.

[0103] When conducting surveys in rivers, lakes and other waters, it is necessary to use water survey equipment, such as water drilling platforms, which must have good stability and wind and wave resistance; underwater geophysical equipment such as side-scan sonar can be used to detect underwater topography and geological conditions.

[0104] When conducting surveys in mountainous areas, the equipment should be easy to carry and transport. Lightweight small drilling equipment and geophysical instruments can be selected, such as backpack geological radar and portable drilling rigs. At the same time, the convenience of equipment operation in complex terrain should be considered, such as equipping with appropriate mountaineering tools and positioning equipment.

[0105] The terrain in the plain area is relatively flat, so large and efficient survey equipment can be used. For example, large vehicle-mounted drilling machines and high-precision measuring instruments can improve the efficiency and accuracy of survey work.

[0106] In step S104, the survey operation data of each survey device is obtained.

[0107] The survey operation data of each survey equipment can be obtained through the operation manual, and the survey equipment operation data can also be obtained by actually operating the survey equipment.

[0108] In step S105, a survey process animation model is constructed based on the geological data, survey locations, and survey equipment and survey operation data corresponding to each survey location.

[0109] You can use MATLAB software and draw using the mesh function.

[0110] In one embodiment, step S105 includes the following sub-steps S1051-S1056: S1051. Construct a geological model based on geological data.

[0111] In MATLAB, we first need to create a three-dimensional model that represents the geological conditions of the survey area. Here, we use the meshgrid function to generate two-dimensional grid coordinates x and y, ranging from -5 to 5 with an interval of 0.1. Then we calculate the height value z corresponding to each grid point to simulate an undulating terrain. We use the mesh function to visualize this terrain, and we get a simple geological model that can intuitively show the general terrain characteristics of the survey area.

[0112] S1052. Construct a survey location model according to the survey location.

[0113] The survey location model represents the specific locations that need to be surveyed on the geological model. A certain number of survey points (here set to 20) are randomly generated, and their x and y coordinates are randomly selected between -5 and 5. In order to determine the height of these survey locations on the geological model, the interp2 function is used to interpolate the randomly selected x and y coordinates according to the previously generated geological model x, y and z data to obtain the corresponding z coordinate. Finally, the scatter3 function is used to draw these survey locations on the geological model as red solid points, while retaining the display of the geological model, so that the distribution of the survey locations on the terrain can be clearly seen.

[0114] S1053: construct a survey equipment model according to the survey equipment and survey operation data corresponding to each survey location.

[0115] The survey equipment model is assumed to be a simple cylinder. By defining the radius and height of the cylinder, the linspace function is used to generate the angle theta on the circumference, and then the meshgrid function is used to generate the two-dimensional grid coordinates X_cylinder and Y_cylinder of the cylinder. The repmat function is then used to generate the height coordinate Z_cylinder of the cylinder. This cylinder model is then placed on each survey point, and each survey point is looped through, and the mesh function is used to draw the cylinder model at the corresponding position and display it together with the geological model, thus obtaining the model of the survey equipment at the survey location.

[0116] S1054. Acquire exploration process simulation data corresponding to the area to be explored based on the geological model, the exploration location model and the exploration equipment model.

[0117] The above three models are combined for display. In a new graphics window, the geological model is drawn first, then the survey location is drawn, and finally the survey equipment model is drawn on the corresponding survey location. In this way, a complete combined model is formed, which comprehensively displays the geological conditions of the survey area, the survey location and the distribution of survey equipment.

[0118] You can use the save function to save all previously generated model data (including the coordinates x, y, z of the geological model, the coordinates x_points, y_points, z_points of the survey location, and the coordinates X_cylinder, Y_cylinder, Z_cylinder of the survey equipment model) into a MAT file geotechnical_model.mat for subsequent use or further analysis.

[0119] When simulation is needed, the saved model is called, and the geological body in the geological model is virtually detected according to the survey location determined by the survey location model and the operation process set by the survey equipment model. For example, when simulating the drilling process, virtual drilling is performed in the geological model according to the drill bit size, drilling speed and other parameters in the drilling equipment model according to the drilling location determined by the survey location model, and the measurement position (including drilling depth, horizontal coordinates, etc.), measurement content (such as physical and mechanical properties of rock and soil, core sample characteristics, etc.) and measurement steps (such as drilling, coring, measurement interval, etc.) during the drilling process are recorded in real time. In this way, all data in the survey process are fully acquired to form complete simulation data of the survey process.

[0120] S1055. Acquire survey process simulation data corresponding to each survey position from the survey process simulation data corresponding to the area to be surveyed.

[0121] The specific implementation process can be: First, conduct a comprehensive analysis of the acquired survey process simulation data to clarify its data storage format. This format may be a common database format (such as SQL database, NoSQL database, etc.), or stored in file form (such as CSV, JSON files, etc.). Different data storage formats determine the subsequent data extraction methods and tools.

[0122] In-depth analysis of the data structure to understand the relationship between each data field. Survey process simulation data usually contains information in multiple dimensions, such as measurement location, measurement content, measurement steps, etc. Among them, the measurement location information is a key identifier and is closely related to other information. For example, in the case of database storage, there may be a main table that records the overall survey process data, which is associated with the sub-table storing the measurement location through a specific foreign key relationship; if stored in the form of a file, the measurement location information may exist in the file as a specific field or hierarchical structure.

[0123] Extracting survey location identifiers: Based on the analysis of the data structure, determine the key information used to identify the survey location, such as geographic coordinates (longitude, latitude, altitude), survey point number, etc. For each survey location, these identifiers are unique and are the key basis for accurately screening data.

[0124] Implement filtering operations: Use data processing tools or programming languages ​​(such as Python's Pandas library, SQL query statements, etc.) to filter the overall survey process simulation data based on the extracted survey location identifiers. Taking SQL query as an example, if the survey location identifier is "location_id" and the data is stored in a table named "survey_simulation_data", you can perform a "SELECT The query statement "FROM survey_simulation_data WHERE location_id = [specific_location_id]" is used to obtain all the simulation data of the survey process corresponding to a specific survey location. For data stored in the form of files, the file reading and data processing functions in the programming language can be used to traverse the data records and filter out the data that meets the requirements according to the survey location identifier.

[0125] Data collation: collate the survey process simulation data corresponding to each selected survey location to ensure data consistency and integrity. This may include checking whether the data fields are complete and whether the data format is unified. For example, for numerical data in the measurement content, check whether there are abnormal values ​​or missing values, and process them according to preset rules.

[0126] Output results: Output the sorted data in a suitable format for subsequent analysis and application. The output format can be selected according to actual needs, such as generating a new database table, creating an independent file (such as CSV file for data analysis, JSON file for data transmission, etc.). Through the above steps, the survey process simulation data corresponding to each survey location can be accurately and efficiently obtained from the survey process simulation data corresponding to the area to be surveyed, providing strong support for subsequent detailed analysis and decision-making based on specific survey locations.

[0127] S1056: Obtain a survey process animation model according to the survey process simulation data corresponding to the area to be surveyed and the survey process simulation data corresponding to each survey position.

[0128] In the field of geotechnical engineering investigation, in order to intuitively display the investigation process, an investigation process animation model is constructed based on the investigation process simulation data corresponding to the area to be investigated and the investigation process simulation data corresponding to each investigation location. The specific steps are as follows: 1. Data preprocessing and integration.

[0129] Data consistency check: Conduct a comprehensive and detailed check on the survey process simulation data corresponding to the survey area and the survey process simulation data corresponding to each survey location to ensure data consistency in time, space, and data format. For example, confirm that the coordinate system of the measurement location is unified and the recording format of the measurement time is consistent to avoid errors in subsequent modeling due to inconsistent data.

[0130] Extraction and integration of key information: Extract key information from the two types of data, including but not limited to the spatial coordinates of the measurement location, the measurement content (such as the properties of different strata, the measured physical parameters, etc.), the sequence of measurement steps, and the time nodes corresponding to each step. Integrate these key information to form an orderly data set containing complete survey process information. For example, with time as the main line, associate the measurement content and steps of different survey locations at each time point to provide a clear data context for the subsequent animation model construction.

[0131] 2. Build the animation model framework.

[0132] Scene and object definition: According to the actual situation of the survey scene, define the animation scene and objects in the animation modeling software (such as 3DMAX, Maya, etc.). For example, create a three-dimensional terrain model representing the topography of the area to be surveyed, create corresponding survey equipment objects such as drilling rigs and detectors based on the survey equipment model, and place them in the appropriate initial position. At the same time, create three-dimensional models of different stratigraphic structures based on the geological model to provide a basic scene for the subsequent display of geological changes during the survey process.

[0133] Timeline setting: Set the timeline in the animation software based on the time information in the integrated data set. The length of the timeline should cover the time span of the entire survey process, and the accuracy of the time scale should be adjusted according to the detail of the actual survey steps to ensure that it can accurately correspond to the time point of each measurement step, providing a framework for the subsequent animation time series display.

[0134] 3. Animation keyframe settings.

[0135] Keyframe creation based on measurement positions and steps: According to the measurement step sequence of each survey position in the integrated data set, keyframes are set at the corresponding positions on the timeline. For example, when the survey equipment moves from one survey position to another, keyframes are set at the time points corresponding to the starting position and the target position to record the position change of the equipment. For the display of measurement content, such as obtaining samples of different formations during drilling, keyframes are set at the corresponding time points to show the changes in equipment status and formation samples. By setting keyframes, key state changes in the survey process can be captured.

[0136] Keyframes for attribute and parameter changes: For various attributes and parameters in the measurement content, such as physical properties such as color, hardness, and conductivity of rock and soil, and parameters of the measurement equipment (such as drilling depth, detection intensity, etc.), keyframes are set at corresponding time points on the timeline according to the changes recorded in the data set. For example, when the drilling depth increases, a keyframe is set at the corresponding time point to change the depth position of the object representing the drilling equipment in the scene, and update the display of related drilling depth parameters. Through these keyframes, the dynamic changes of various attributes and parameters over time during the survey process can be accurately displayed.

[0137] 4. Animation transition and rendering.

[0138] Transition effect setting: Set appropriate transition effects between keyframes to make the transition between different states of the animation more natural and smooth. For example, for the movement of survey equipment, a smooth linear interpolation transition method is used to simulate the uniform or variable speed movement of the equipment during actual movement; for the acquisition and display of formation samples, fade-in and fade-out transition effects are used to enhance the visual effect of the animation.

[0139] Rendering and optimization: According to actual needs, select a suitable rendering engine (such as V-Ray, Arnold, etc.) to render the animation scene. During the rendering process, adjust the material, lighting, shadow and other parameters to make the animation scene more realistic and in line with the visual effects of the actual survey environment. At the same time, optimize the animation model, reduce the number of polygons of the model, compress the texture file, etc., to improve the playback performance of the animation and ensure that the survey process animation model can be displayed smoothly on different hardware devices.

[0140] Through the above steps, it is possible to effectively construct an accurate, intuitive and visually appealing survey process animation model based on the survey process simulation data corresponding to the area to be surveyed and the survey process simulation data corresponding to each survey location, thus providing a powerful tool support for the planning, demonstration and teaching of geotechnical engineering surveys.

[0141] In step S106, based on the survey process animation model and according to a preset assessment algorithm, a survey risk assessment is performed on the area to be surveyed.

[0142] In one embodiment, based on the survey process animation model, a survey risk assessment is performed on the area to be surveyed according to a preset assessment algorithm, including the following sub-steps S1061-S1065: S1061. Acquire multiple different exploration scenarios.

[0143] Different exploration scenarios can be set up, representing potential future development paths.

[0144] For example: natural environment scenarios, geological conditions scenarios and human factors scenarios.

[0145] The following describes each scenario in detail: Natural environment scene: Mild weather scenario: During the survey period, the weather conditions are good and stable, the temperature is moderate, there is no significant precipitation, strong winds and other severe weather, and the interference with the survey work is minimal. In this scenario, the natural environment will basically not bring additional risks to the survey.

[0146] Variable climate scenario: There is a certain degree of weather variability, such as occasional light rain and breeze, which may have a slight impact on some outdoor survey operations, such as affecting the reading accuracy of measuring instruments, but the impact is limited.

[0147] Severe weather conditions: encountering extreme weather such as heavy rain, heavy snow, strong winds, lightning, etc. Heavy rains may cause geological disasters such as floods and mudslides, strong winds may affect the stability of high-altitude operations and equipment, and lightning poses a serious threat to the safety of personnel and equipment.

[0148] Geological disaster scenario: Earthquakes, landslides, ground collapse and other geological disasters occur in the survey area. These disasters will directly damage the survey equipment, interrupt the survey work, and even endanger the lives of personnel.

[0149] Geological conditions scenario: Single homogeneous geological scenario: The geological structure is simple, the rock and soil properties are uniform, and there are no obvious geological defects, such as faults, caves, etc. In this scenario, the survey work can be carried out smoothly and the accuracy of data collection is high.

[0150] Mildly complex geological scenario: There are some small-scale geological changes, such as local soil differences, small joints and fissures, etc. These changes may bring certain challenges to drilling and sampling, but they can be solved through appropriate technical means.

[0151] Moderately complex geological scenarios: There are obvious geological structures, such as faults, folds, karst development areas, etc. These complex geological conditions will increase the difficulty and uncertainty of exploration, and may cause problems such as drill sticking and hole collapse during drilling, affecting the reliability of data.

[0152] Highly complex geological scenario: The geological conditions are extremely complex, with large-scale fault fracture zones, deep soft soil layers, complex underground cave systems, etc. In this scenario, the survey work faces huge difficulties, the accuracy of data collection is difficult to guarantee, and it may cause serious engineering safety problems.

[0153] Human Factors Scenario: Standardized and efficient operation scenario: The survey team has high professional quality, strictly abides by the operating procedures, and the equipment is maintained in a timely manner and managed in an orderly manner. In this scenario, the probability of human error and equipment failure is extremely low, and the survey work can be carried out efficiently and safely.

[0154] Minor illegal operation scenario: There are a small number of irregular operating behaviors, such as failure to wear safety protection equipment correctly, slight deviations in equipment operation procedures, etc., but they have not yet caused substantial impact on the survey work.

[0155] Moderate illegal operation scenario: There are many illegal operation phenomena, such as equipment not being maintained beyond the prescribed period, drilling depth control not being performed in accordance with regulations, etc., which may lead to equipment failure or increased data errors.

[0156] Severely illegal operation scenario: The survey team is poorly managed and there are a lot of serious violations, such as working without a license, changing the survey plan without authorization, etc. In this scenario, safety accidents and data falsification are very likely to occur.

[0157] S1062. Obtain historical exploration data.

[0158] Comprehensively collect historical survey data related to the survey area or similar areas, including geological reports, meteorological records, equipment operation logs, accident statistics, personnel operation records, etc. These data should cover the survey conditions under different natural environments, geological conditions and human factors, as well as the corresponding risk events and losses.

[0159] S1063. Calibrate the exploration process animation model according to historical exploration data.

[0160] The model used for risk assessment is calibrated using the collected historical data. By continuously adjusting the parameters in the model, the output of the model is highly matched with the historical data. For example, according to the historical survey progress, equipment failure rate and casualties under different climate conditions, the parameters of the impact of climate factors on survey risks are adjusted; according to the drilling success rate and data error rate under different geological conditions in the past, the weight of geological parameters on risk assessment is calibrated. By repeatedly optimizing the model parameters, it is ensured that the model can accurately predict past survey behaviors and risk conditions.

[0161] S1064. Input each exploration scenario into the calibrated exploration process animation model to simulate the exploration process under each exploration scenario.

[0162] The different exploration scenarios set previously were input into the calibrated model. For each exploration scenario, the relevant parameter values ​​were set in detail, such as the intensity and duration of heavy rain, the speed and direction of strong winds, etc. in severe climate scenarios; in highly complex geological scenarios, the scale, direction of faults, distribution and size of karst caves, etc. were determined.

[0163] S1065. Conduct exploration risk assessment on the area to be surveyed based on the simulation results corresponding to each exploration scenario.

[0164] Specifically, step S1065 includes the following sub-steps: S10651. Obtain the risk event type based on the simulation results; S10652. Obtain the risk level of the area to be surveyed based on the type of risk event.

[0165] Run the model to simulate the development of the survey process and the impact on ecosystem services under different scenarios. During the simulation process, focus on key indicators such as survey progress, data quality, equipment reliability, personnel safety, and disturbance to the surrounding ecological environment. For example, in the simulation of geological disaster scenarios, earthquakes cause survey equipment to collapse and data to be lost, and landslides cause damage to surrounding vegetation and soil.

[0166] Identify key input parameters in the model that may affect the results of the survey risk assessment, such as meteorological parameters (temperature, precipitation, wind speed, lightning activity), geological parameters (rock and soil strength, groundwater level, fault density, degree of cave development), and human parameters (personnel operating skill level, frequency of violations, equipment maintenance quality), etc.

[0167] Local sensitivity analysis or global sensitivity analysis is used to study the sensitivity of the model output results to the changes in each parameter. Local sensitivity analysis is to fix other parameters, change the value of one parameter alone, and observe the change range of the model output; global sensitivity analysis considers the changes of multiple parameters and their interactions at the same time. For example, by gradually changing the height of the groundwater level, observing the degree of impact on the stability of the drilling equipment and the accuracy of the geological data, the sensitivity of the groundwater level parameter is determined. Through sensitivity analysis, the key uncertainty parameters that have a greater impact on the results of the exploration risk assessment are found.

[0168] Compare the simulation results under different scenarios and analyze the types of risk events that various scenarios may cause in the survey process.

[0169] Common risk events in geotechnical investigations may include: In terms of complex geological conditions, risk events include: the existence of complex geological structures such as fault zones and folds, large changes in groundwater levels, and diverse rock and soil types with large differences in properties. Geotechnical survey risks include: the possibility of unreasonable survey point layout, inability to accurately grasp the geological conditions, difficulty in determining the depth and location of drilling holes, and large discreteness of in-situ test and indoor test results, which affects the accurate judgment of geotechnical engineering properties.

[0170] In terms of adverse geological effects, risk events include: adverse geological phenomena such as landslides, collapses, mudslides, karst, etc. Geotechnical survey risks include: increasing the difficulty and danger of survey work, possibly damaging survey equipment, threatening the safety of survey personnel, and easily missing important adverse geological information, causing serious hidden dangers to subsequent engineering design and construction.

[0171] In terms of complex site environments, risk events include: the site is surrounded by buildings, roads, underground pipelines and other facilities, or is located in densely populated areas such as downtown areas and residential areas. Geotechnical survey risks include: survey operations are limited by space, which may cause damage to surrounding facilities, causing disputes and economic losses, and noise and vibration may also cause complaints from residents, affecting the progress of the survey.

[0172] In terms of special geotechnical problems, risk events include: the existence of special geotechnical materials such as soft soil, collapsible loess, expansive soil, and frozen soil. Geotechnical investigation risks include: the engineering properties of special geotechnical materials are complex, and high requirements are placed on investigation methods and techniques. For example, the high compressibility and low strength of soft soil may lead to excessive foundation settlement, and collapsible loess may deform when exposed to water. If the investigation is inaccurate, it will cause serious harm to the project.

[0173] In terms of meteorology and natural disasters, risk events include: heavy rain, floods, strong winds, earthquakes and other meteorological disasters or geological disasters. Geotechnical survey risks include: affecting the normal progress of survey work, possibly causing damage to survey equipment, casualties, making it impossible to accurately obtain survey data during the disaster, and heavy rains may change the physical and mechanical properties of rock and soil, increasing the uncertainty of survey.

[0174] Based on the comparison of scenario results, the exploration risk is evaluated and the risk level is determined. A detailed risk level assessment standard can be formulated, taking into account the possibility of risk events and the severity of the consequences. This disclosure specifies 5 risk levels: Level 1: Slightly risky.

[0175] Risk description: The geological conditions are relatively simple, there are no obvious adverse geological effects, the site is open, the surrounding environment is simple, there is no special rock and soil, the survey technology and equipment can meet the general requirements, and the meteorological conditions are normal.

[0176] Example: General farmland area with flat terrain, single rock and soil type, stable and deep groundwater level, no surrounding buildings and underground pipelines, no special rock and soil distribution, good local meteorological conditions, and rarely extreme weather.

[0177] Level 2: General risk.

[0178] Risk description: The geological conditions are basically clear, with a small number of minor adverse geological phenomena, such as the risk of small-scale shallow landslides. The site has certain limitations, such as a small number of buildings around it. There are some common geotechnical engineering problems, such as the possibility of ordinary sand liquefaction. The survey technology and equipment can basically meet the requirements, but some special tests may be required.

[0179] Example: There are some small gullies on the gentle slope at the edge of the city, and there is the possibility of local sand liquefaction. There are several old buildings around and the groundwater level is shallow. The survey needs to consider the impact on the surrounding buildings.

[0180] Level 3: Significant risk.

[0181] Risk description: The geological conditions are complex and there are obvious adverse geological effects, such as karst development areas, large-scale landslides, etc. The site environment is complex, there are important buildings, traffic arteries or dense underground pipelines around, and there are special rock and soil, such as soft soil or collapsible loess. The survey technology and equipment are somewhat difficult, and it is necessary to adopt a variety of survey methods and professional technologies.

[0182] Example: Urban construction land near mountainous areas with karst caves, important public buildings such as hospitals and schools around the site, and soft soil layers underground require the use of geophysical exploration, drilling and other means for exploration.

[0183] Level 4: High risk.

[0184] Risk description: The geological conditions are very complex and adverse geological effects are serious, such as being located on an active fault zone or in an area prone to mudslides. The site environment is extremely complex, in a bustling commercial area or a historical and cultural protection area, etc. Special geotechnical problems are prominent, such as thick layers of expansive soil or permafrost. The survey work is difficult, has high requirements for technology and equipment, and there are great safety risks.

[0185] Example: The urban core area is located near a seismically active fault zone. There is thick expansive soil underground and a large number of historically protected buildings and commercial complexes around it. During the survey, the impact on the surrounding environment needs to be strictly controlled, and it is very difficult to accurately ascertain the geological conditions.

[0186] Level 5: Extremely dangerous.

[0187] Risk description: The geological conditions are extremely complex and harsh, and there are major geological disaster risks, such as areas prone to large-scale landslides, collapses, mud-rock flows and other disasters, or extremely unstable sites with special rock and soil in high-intensity earthquake zones. The site environment is almost impossible to carry out normal survey operations, such as in military restricted areas and severely polluted areas. The survey work faces great safety risks and technical difficulties, and it is almost impossible to accurately complete the survey task under the existing conditions.

[0188] Example: An area located in a large debris flow valley where debris flow disasters often occur, the site is contaminated with radioactive materials, and the surrounding area is a military restricted area. Survey work is greatly restricted, and the safety of personnel and equipment is seriously threatened.

[0189] Through the analysis of the results, a scientific basis is provided for exploration decisions so that appropriate risk response measures can be taken to reduce exploration risks.

[0190] In one embodiment, the benefits and trade-offs of the area to be surveyed can also be obtained based on the simulation results corresponding to each exploration scenario; the benefits may be reflected in the acceleration of the survey progress, the reduction of costs, the improvement of data quality, etc.; the trade-offs involve the choice between different goals. For example, in order to speed up the survey progress, it may be necessary to increase equipment investment or reduce the accuracy of data collection.

[0191] The method disclosed in the present invention can accurately simulate the survey process through modeling technology by using the environmental data, geological data and survey equipment operation data of the survey area, and analyze the simulation process according to a preset evaluation algorithm to determine the survey risk. This method has a faster risk analysis and does not rely too much on expert evaluation, which can speed up the speed of geotechnical survey.

[0192] It is worth noting that the present disclosure can be established based on a cloud platform, that is, the execution subject in each of the above embodiments can be a cloud platform. During the geotechnical survey process, the survey operation data of the survey equipment can be directly transmitted to the cloud platform system during the survey, and the subsequent cloud platform system can process and analyze the survey operation data based on the acquired geospatial data and the survey operation data uploaded by the survey equipment, so as to achieve timely early warning of survey risks and reduce the difficulty of geotechnical survey.

[0193] Specifically, the cloud platform obtains the geospatial data of the area to be surveyed, and the geospatial data includes: environmental data and geological data; the cloud platform will also divide the survey area into survey locations based on the geospatial data; the cloud platform will also obtain the survey equipment corresponding to each survey location; the cloud platform will also obtain the survey operation data of each survey equipment; the cloud platform will also construct a survey process animation model based on the geological data, survey location, and the survey equipment and survey operation data corresponding to each survey location; the cloud platform will also conduct survey risk assessment on the area to be surveyed based on the survey process animation model and according to a preset assessment algorithm.

[0194] Based on the same inventive concept, the embodiment of the present application also provides a geotechnical investigation risk analysis system for implementing the geotechnical investigation risk analysis method involved above. The implementation scheme for solving the problem provided by the system is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more geotechnical investigation risk analysis system embodiments provided below can refer to the limitations of the geotechnical investigation risk analysis method above, and will not be repeated here.

[0195] In an exemplary embodiment, Figure 2 As shown, a geotechnical investigation risk analysis system is provided, comprising: The data retrieval unit 11 is used to obtain the geographic spatial data of the area to be surveyed, and the geographic spatial data includes: environmental data and geological data; A data analysis unit 12, used for dividing the area to be surveyed into survey locations according to the geographic spatial data; A survey equipment acquisition unit 13, used to acquire the survey equipment corresponding to each of the survey locations; A survey data acquisition unit 14, used to acquire survey operation data of each of the survey equipment; A data simulation unit 15 is used to construct a survey process animation model according to the geological data, the survey locations, and the survey equipment and the survey operation data corresponding to each of the survey locations; The evaluation unit 16 is used to perform an exploration risk evaluation on the area to be investigated based on the exploration process animation model and according to a preset evaluation algorithm.

[0196] In one embodiment, the data analysis unit 12 is specifically used for: Performing correlation analysis on the geographic spatial data to obtain a target correlation relationship; According to the target association relationship, the area to be surveyed is divided into different survey locations.

[0197] In one embodiment, in terms of performing correlation analysis on the geospatial data, the data analysis unit 12 is specifically configured to: Preprocessing the geospatial data; Clustering the preprocessed geographic spatial data using a clustering algorithm to obtain the correlation relationship between each data in the geographic spatial data; Verifying whether the association is valid; The valid association relationship is determined as the target association relationship.

[0198] In one embodiment, the data simulation unit 15 is specifically used for: constructing a geological model based on the geological data; constructing a survey location model according to the survey location; Constructing a survey equipment model according to the survey equipment and the survey operation data corresponding to each of the survey locations; Acquire survey process simulation data corresponding to the area to be surveyed according to the geological model, the survey location model and the survey equipment model; Acquire the survey process simulation data corresponding to each of the survey locations from the survey process simulation data corresponding to the area to be surveyed; The survey process animation model is obtained according to the survey process simulation data corresponding to the area to be surveyed and the survey process simulation data corresponding to each of the survey positions.

[0199] In one embodiment, in terms of conducting a survey risk assessment on the area to be surveyed according to the survey process animation model, the data simulation unit 15 is specifically used to: Access multiple different exploration scenarios; Access to historical exploration data; calibrating the survey process animation model according to the historical survey data; Inputting each of the exploration scenarios into the calibrated exploration process animation model to simulate the exploration process under each of the exploration scenarios; According to the simulation results corresponding to each of the exploration scenarios, an exploration risk assessment is performed on the area to be surveyed.

[0200] In one embodiment, the evaluation unit 16 is specifically configured to: According to the simulation results, the risk event type is obtained; The risk level of the area to be surveyed is obtained according to the risk event type.

[0201] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 3As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a geotechnical exploration risk analysis method is implemented.

[0202] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0203] In an exemplary embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0204] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0205] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0206] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0207] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0208] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0209] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0210] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A geotechnical investigation risk analysis method, characterized in that: The geotechnical investigation risk analysis method comprises: Acquiring geospatial data of the area to be surveyed, wherein the geospatial data includes: environmental data and geological data; Dividing the area to be surveyed into survey locations according to the geospatial data; Acquire a survey device corresponding to each of the survey locations; Acquiring survey operation data of each of the survey equipment; Constructing a survey process animation model according to the geological data, the survey locations, and the survey equipment and survey operation data corresponding to each of the survey locations; Based on the survey process animation model, a survey risk assessment is performed on the area to be surveyed according to a preset assessment algorithm.

2. The geotechnical investigation risk analysis method according to claim 1, characterized in that: The dividing of the area to be surveyed into survey positions according to the geographic spatial data comprises: Performing correlation analysis on the geographic spatial data to obtain a target correlation relationship; According to the target association relationship, the area to be surveyed is divided into different survey locations.

3. The geotechnical investigation risk analysis method according to claim 2, characterized in that: The performing correlation analysis on the geospatial data includes: Preprocessing the geospatial data; Clustering the preprocessed geographic spatial data using a clustering algorithm to obtain the correlation relationship between each data in the geographic spatial data; Verifying whether the association is valid; The valid association relationship is determined as the target association relationship.

4. The geotechnical investigation risk analysis method according to claim 1, characterized in that: The step of constructing a survey process animation model according to the geological data, the survey locations, and the survey equipment and survey operation data corresponding to each of the survey locations includes: constructing a geological model based on the geological data; constructing a survey location model according to the survey location; Constructing a survey equipment model according to the survey equipment and the survey operation data corresponding to each of the survey locations; Acquire survey process simulation data corresponding to the area to be surveyed according to the geological model, the survey location model and the survey equipment model; Acquire the survey process simulation data corresponding to each of the survey locations from the survey process simulation data corresponding to the area to be surveyed; The survey process animation model is obtained according to the survey process simulation data corresponding to the area to be surveyed and the survey process simulation data corresponding to each of the survey positions.

5. The geotechnical investigation risk analysis method according to claim 1, characterized in that: The method of performing a survey risk assessment on the area to be surveyed based on the survey process animation model and according to a preset assessment algorithm includes: Access multiple different exploration scenarios; Access to historical exploration data; calibrating the survey process animation model according to the historical survey data; Inputting each of the exploration scenarios into the calibrated exploration process animation model to simulate the exploration process under each of the exploration scenarios; According to the simulation results corresponding to each of the exploration scenarios, an exploration risk assessment is performed on the area to be surveyed.

6. The geotechnical investigation risk analysis method according to claim 5, characterized in that: The method of conducting a risk assessment of the area to be surveyed based on the simulation results includes: According to the simulation results, the risk event type is obtained; The risk level of the area to be surveyed is obtained according to the risk event type.

7. A geotechnical investigation risk analysis system, characterized in that: The geotechnical investigation risk analysis system comprises: A data retrieval unit, used to obtain geographic spatial data of the area to be surveyed, wherein the geographic spatial data includes: environmental data and geological data; A data analysis unit, used for dividing the area to be surveyed into survey locations according to the geographic spatial data; A survey equipment acquisition unit, used to acquire the survey equipment corresponding to each of the survey locations; A survey data acquisition unit, used to acquire survey operation data of each of the survey equipment; A data simulation unit, used to construct a survey process animation model according to the geological data, the survey locations, and the survey equipment and survey operation data corresponding to each of the survey locations; An evaluation unit is used to perform an exploration risk evaluation on the area to be investigated based on the exploration process animation model and a preset evaluation algorithm.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the geotechnical investigation risk analysis method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the geotechnical investigation risk analysis method described in any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the geotechnical investigation risk analysis method described in any one of claims 1 to 6 are implemented.

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