Geotechnical Investigation Risk Analysis Method, System, Equipment, Medium and Product

Abstract

The present application discloses a method, system, device, medium and product for geotechnical investigation risk analysis, which relates to the technical field of geotechnical investigation. The method includes obtaining geospatial data of the area to be investigated, where the geospatial data includes environmental data and geological data; dividing the investigation locations in the area to be investigated according to the geospatial data; obtaining the investigation equipment corresponding to each investigation location; obtaining the investigation operation data of each investigation equipment; constructing an investigation process animation model based on the geological data, the investigation locations, and the investigation equipment and investigation operation data corresponding to each investigation location; and performing an investigation risk assessment on the area to be investigated based on the investigation process animation model according to a preset evaluation algorithm. The present application can improve the efficiency of geotechnical investigation.

Description

Technical Field

[0001] The present application relates to the technical field of geotechnical investigation, and particularly to a method, system, device, medium and product for geotechnical investigation risk analysis. Background Art

[0002] Geotechnical investigation refers to the activity of investigating, researching and analyzing and evaluating the geological, environmental characteristics and geotechnical engineering conditions of a construction site by using various survey techniques and means according to the requirements of a construction project. The purpose is to identify, analyze and evaluate the geological, environmental characteristics and geotechnical engineering conditions of the construction site, and on this basis, prepare investigation 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 is analyzed before the investigation to determine the risks in the investigation. However, the traditional geotechnical investigation risk analysis is mainly based on expert evaluation, and the expert evaluation takes a long time, which affects the efficiency of geotechnical investigation. Summary of the Invention

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

[0005] To achieve the above purpose, the present application provides the following solutions:

[0006] In the first aspect, the present application provides a method for geotechnical investigation risk analysis, including:

[0007] Obtain the geospatial data of the area to be investigated, where the geospatial data includes: environmental data and geological data;

[0008] Divide the investigation locations of the area to be investigated according to the geospatial data;

[0009] Obtain the investigation equipment corresponding to each of the investigation locations;

[0010] Obtain the investigation operation data of each of the investigation equipment;

[0011] Construct an investigation process animation model according to the geological data, the investigation locations, and the investigation equipment and the investigation operation data corresponding to each of the investigation locations;

[0012] Based on the investigation process animation model, perform an investigation risk assessment on the area to be investigated according to a preset evaluation algorithm.

[0013] In the second aspect, the present application provides a system for geotechnical investigation risk analysis, including:

[0014] A data retrieval unit for obtaining the geospatial data of the area to be surveyed, where the geospatial data includes environmental data and geological data;

[0015] A data analysis unit for dividing the survey locations of the area to be surveyed according to the geospatial data;

[0016] A survey equipment acquisition unit for obtaining the survey equipment corresponding to each of the survey locations;

[0017] A survey data acquisition unit for obtaining the survey operation data of each of the survey equipment;

[0018] A data simulation unit for constructing an animation model of the survey process according to the geological data, the survey locations, and the survey equipment and the survey operation data corresponding to each of the survey locations;

[0019] An evaluation unit for performing a survey risk assessment on the area to be surveyed based on the animation model of the survey process according to a preset evaluation algorithm.

[0020] In a third aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the steps of the geotechnical survey risk analysis method described in any one of the above.

[0021] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the geotechnical survey risk analysis method described in any one of the above.

[0022] In a fifth aspect, the present application provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the steps of the geotechnical survey risk analysis method described in any one of the above.

[0023] According to the specific embodiments provided by the present application, the present application discloses the following technical effects:

[0024] The present application provides a geotechnical investigation risk analysis method, system, device, medium and product. It can divide the investigation locations of the area to be investigated by obtaining the environmental data and geological data of the area to be investigated. After dividing the investigation locations, it will determine the investigation equipment corresponding to each investigation location and obtain the investigation operation data of each investigation equipment. After obtaining the geological data, investigation locations, and the corresponding investigation equipment and investigation operation data of each investigation location in the area to be investigated, it will construct an investigation process animation model based on these data. This investigation process animation model can fully reflect the process of investigating the area to be investigated. When conducting the investigation risk assessment, it can automatically evaluate and analyze the investigation process animation model through a preset evaluation algorithm, so as to obtain the investigation risk assessment result of the area to be investigated. This method of investigating risks does not rely on expert evaluation, and the risk analysis is relatively fast, which can accelerate the speed of geotechnical investigation. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0026] Figure 1 is a flowchart of a geotechnical investigation risk analysis method shown according to an exemplary embodiment;

[0027] Figure 2 is a schematic diagram of the functional modules of a geotechnical investigation risk analysis system provided by an embodiment of the present application;

[0028] Figure 3 is a schematic diagram of the structure of a computer device provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0029] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, rather than all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0030] To make the above objects, features, and advantages of the present application more obvious and understandable, the present application will be further described in detail below with reference to the drawings and specific embodiments.

[0031] In modern engineering construction, geotechnical exploration risk assessment plays a crucial role and is widely applied in multiple key fields. 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 preliminary preparation. By accurately detecting the stratum structure and soil mechanical properties, potential crises such as foundation settlement and sand liquefaction can be identified in advance, laying a solid safety foundation for building foundation design.

[0032] In the aspect of transportation engineering, the route planning of roads and railways and the construction of bridges and tunnels are inseparable from geotechnical exploration risk assessment. When building roads in mountainous areas, it can help identify dangerous sections prone to landslides and collapses, effectively avoiding the risks of geological disasters; in bridge construction, the exploration and assessment of pier foundations can ensure the stability of bridges under complex geological conditions.

[0033] In the field of energy engineering, for projects such as nuclear power plants that have extremely strict requirements for geological stability, geotechnical exploration risk assessment is of utmost importance. Through detailed exploration, factors such as seismic activity and stratum stability are evaluated, providing solid geological data support for the site selection and construction of nuclear power plants to ensure the long-term safe operation of nuclear facilities.

[0034] The same is true for water conservancy and hydropower engineering. 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 and the surrounding rock conditions of underground caverns, effectively guaranteeing 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 progress and safe operation of many projects.

[0035] However, traditional geotechnical exploration risk analysis mainly relies on expert assessment, which takes a long time and affects the efficiency of geotechnical exploration.

[0036] To solve the above technical problems, the present disclosure provides a geotechnical exploration risk analysis method, system, device, medium and product.

[0037] Figure 1 It is a flowchart of a geotechnical exploration risk analysis method shown according to an exemplary embodiment. As Figure 1 shown, the method includes the following steps S101 - S106:

[0038] In step S101, geospatial data of the area to be explored is obtained.

[0039] Among them, the geospatial data includes: environmental data and geological data.

[0040] The environmental data includes at least one of the following data: meteorological data, water environment data, ecological environment data, and soil environment data.

[0041] Meteorological data may include at least one of the following data: air temperature, precipitation, wind speed, wind direction, humidity, and sunshine duration.

[0042] Air temperature: including daily average air temperature, monthly average air temperature, annual average air temperature, as well as extreme maximum and minimum air temperatures. Changes in air temperature can affect the physical properties of rock and soil. For example, high temperatures may cause soil moisture evaporation, resulting in soil shrinkage and affecting foundation stability; low temperatures may cause soil freezing and frost heaving.

[0043] Precipitation: involves information such as annual precipitation, seasonal distribution of precipitation, precipitation intensity, etc. Heavy precipitation may trigger geological disasters such as landslides and debris flows, and also affect the groundwater level and soil humidity.

[0044] Wind speed and wind direction: average wind speed, maximum wind speed, and dominant wind direction. Strong winds may cause damage to ground facilities and buildings, and wind prevention measures need to be considered in building planning and design.

[0045] Humidity: The magnitude of air humidity affects the corrosion rate of materials, which is of great significance for the investigation of metal structures. A high-humidity environment may also lead to the growth of mold, affecting the indoor environmental quality.

[0046] Sunshine duration: Understanding the local sunshine conditions is of great value for aspects such as solar energy utilization, building daylighting design, and plant growth environment assessment.

[0047] Water environment data may include: surface water conditions, and / or, groundwater conditions.

[0048] Surface water conditions: including the water level, flow rate, water quality (acidity and alkalinity, dissolved oxygen, chemical oxygen demand, heavy metal content, etc.) of water bodies such as rivers, lakes, and reservoirs. Changes in the water level of surface water may affect the stability of the surrounding land, and water quality pollution poses a potential threat to the surrounding ecological environment and human health.

[0049] Groundwater conditions: the level of the groundwater table, the law of water level change, the flow direction of groundwater, and water quality characteristics (hardness, salinity, corrosivity, etc.). The rise and fall of the groundwater table will affect the bearing capacity of foundation soil, and corrosive groundwater may damage the foundation structure.

[0050] Ecological environment data may include: vegetation cover, and / or, biodiversity.

[0051] Vegetation cover: vegetation type, vegetation coverage rate. Vegetation can play a role in soil and water conservation and climate regulation, and changes in the vegetation coverage rate reflect the stability and change trend of the ecological environment.

[0052] Biodiversity: The types, quantities, and distributions of animals and plants within a region. The richness of biodiversity is an important indicator for measuring the health of an ecosystem and is crucial for ecological protection and environmental impact assessment.

[0053] Soil environmental data may include: soil type, and / or, soil pollution status.

[0054] Soil type: Such as sandy soil, clay soil, loam soil, etc. Different soil types have different physical and mechanical properties and different applicability to engineering construction.

[0055] Soil pollution status: The content of pollutants such as heavy metals, pesticide residues, and organic matter in the soil. Soil pollution not only affects soil quality and ecological functions but may also pose hazards to human health through the food chain.

[0056] Geological data includes at least one of the following data: stratigraphic structure data, rock mechanical property data, geological structure data, seismic data, and geotechnical physical property data.

[0057] Stratigraphic structure data may include: stratigraphic layering or stratigraphic age.

[0058] Stratigraphic layering: The distribution, thickness, and lithological characteristics of different strata. Understanding stratigraphic layering is crucial for engineering foundation design, tunnel construction, underground engineering construction, etc.

[0059] Stratigraphic age: Determining the geological age of the formation of strata helps to understand the geological evolution history and the formation process of geological structures.

[0060] Rock mechanical property data may include: rock strength, and / or, rock deformation characteristics.

[0061] 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 crucial for the design and construction of projects such as rock slopes and underground chambers.

[0062] Rock deformation characteristics: Such as elastic modulus, Poisson's ratio, etc., which reflect the deformation ability of rocks under the action of forces.

[0063] Geological structure data may include: faults, and / or, folds.

[0064] Fault: The location, strike, dip, activity status, etc. of the fault. Faults are weak zones in the earth's crust and may trigger geological disasters such as earthquakes and landslides, having a significant impact on engineering construction.

[0065] Fold: The shape, scale, and distribution of the fold. Fold structures will affect the spatial distribution of strata and the mechanical properties of rocks.

[0066] Seismic data may include: seismic intensity, and / or, seismic activity frequency.

[0067] Seismic intensity: It represents the degree of damage caused by an earthquake to the ground and buildings, and is an important basis for engineering seismic design.

[0068] Seismic activity frequency: Understand the frequency and intensity of historical earthquakes in the local area to evaluate seismic risks.

[0069] Geotechnical physical property data includes at least one of the following data: density, porosity, and water content.

[0070] Density: The ratio of the mass of geotechnical materials to their volume, reflecting the compactness of geotechnical materials.

[0071] Porosity: The ratio of the pore volume to the total volume in geotechnical materials, affecting the permeability and compressibility of geotechnical materials.

[0072] Water content: The ratio of the mass of water contained in geotechnical materials to the mass of dry soil, which has a significant impact on the strength and deformation characteristics of geotechnical materials.

[0073] Exemplarily, environmental data of the area to be surveyed can be obtained from the local meteorological bureau, and geological data of the area to be surveyed can be obtained from the local geological bureau.

[0074] In step S102, the survey locations of the area to be surveyed are divided according to the geospatial data.

[0075] In one embodiment, dividing the survey locations of the area to be surveyed according to the geospatial data includes the following sub-steps S1021 - S1022:

[0076] S1021. Conduct a correlation analysis on the geospatial data to obtain the target correlation relationship.

[0077] Specifically, step S1021 includes the following sub-steps S10211 - S10214:

[0078] S10211. Preprocess the geospatial data.

[0079] Preprocessing the geospatial data may include cleaning the collected environmental data and geological data, deleting or correcting incorrect data, and handling missing values and outliers to ensure the quality and consistency of the data. Specifically:

[0080] Among them, professional data cleaning algorithms and tools can be adopted to conduct a comprehensive screening of the collected environmental data and geological data. In environmental data, for example, air pollutant monitoring data may be mixed with incorrect data due to factors such as monitoring equipment failures and signal transmission interferences. Similar problems also exist in geological data, such as errors in borehole data records during geological exploration. In this step, by establishing a data quality rule library, the data is compared and verified according to established rules to accurately identify incorrect data.

[0081] For the incorrect data identified during the data cleaning process, targeted measures are taken based on the data source, data characteristics, and relevant domain knowledge. If the incorrect data results from instrument calibration deviations, it is corrected by comparing with instrument calibration records and standard sample data; for data that cannot be corrected and whose errors seriously affect data quality, it is deleted.

[0082] Use a variety of advanced missing value imputation algorithms, such as mean imputation, regression imputation, K-nearest neighbor imputation, etc., to handle the missing values in environmental data and geological data. For the missing temperature values in a certain period of environmental data, according to the temperature change pattern in adjacent periods and combined with data from surrounding monitoring stations, an appropriate algorithm can be used for imputation. In geological data, for the missing values of formation thickness, corresponding algorithms can be adopted based on the geological structure characteristics of the area and surrounding borehole data to ensure the integrity of the data.

[0083] For example, when the proportion of missing values in the dataset is small 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 directly deleted. If there are many missing values, mean imputation (for numerical data, calculate the mean of the feature and fill it in the missing position), median imputation (use the median to fill the missing values, suitable for data with outliers), or imputation based on similar samples (by finding other samples similar to the sample with missing values and using the feature value of the similar sample to fill) can be used.

[0084] Use statistical methods and machine learning algorithms, such as outlier detection methods based on box plots, IsolationForest algorithms, etc., to detect and process outliers in the data. In environmental data, for water quality monitoring outliers that exceed the normal range, combined with the water quality conditions of the surrounding waters and historical data, determine whether it is a real outlier. If it is an abnormal data, it is corrected or deleted according to the actual situation; in geological data, for outliers of geotechnical mechanical parameters, corresponding processing is carried out by comparing with the geological conditions of the area and data of the same type of strata, so as to ensure the quality and consistency of the data and provide a reliable data basis for subsequent analysis, modeling, and application based on geospatial data.

[0085] S10212. Use a clustering algorithm to cluster the preprocessed geospatial data to obtain the correlation relationships among the various data in the geospatial data.

[0086] By clustering, data points with similar characteristics are grouped into the same class, thus dividing the exploration area into different classes. The basis for clustering can be the similarity of geological conditions, the similarity of environmental factors, etc.

[0087] Exemplarily, the following clustering analysis formula can be used:

[0088] ;

[0089] where J represents the sum of squared errors; is the set of points in the i-th cluster, is the centroid of the ii-th cluster, K is the number of clusters, x is the data point belonging to the data point, i is the centroid of the i-th cluster, represents the squared Euclidean distance between the data point x and the cluster center .

[0090] In clustering analysis, since the characteristics of environmental data and geological data may have different dimensions and value ranges, in order to avoid some characteristics having too much influence on the clustering result, it is necessary to standardize the data. Commonly used standardization methods include Z-score standardization, and the formula is , where x is the original data, is the mean, is the standard deviation.

[0091] This disclosure uses the K-Means algorithm, and its steps are as follows:

[0092] Initialize the centroid: Randomly select K data points from the data set as the initial centroids.

[0093] Assign data points: Calculate the Euclidean distance from each data point to the K centroids, and assign the data point to the cluster where the nearest centroid is located.

[0094] Update the centroid: Recalculate the position of the centroid according to the data points within each cluster.

[0095] Iterative optimization: Repeat the steps of assigning data points and updating the centroid until the centroid no longer changes significantly or reaches the preset maximum number of iterations.

[0096] Determine the number of clusters: The elbow method can be used to plot the curve for different K values, and select the K value corresponding to the "elbow point" with a significant change in slope in the curve as the optimal number of clusters.

[0097] S10213. Verify whether the association relationship is valid.

[0098] The feasibility analysis and error analysis techniques can be used to verify whether the mined association relationship is valid.

[0099] The feasibility analysis can adopt theoretical basis verification and practical application verification.

[0100] Theoretical basis verification: Combine the principles of relevant disciplines such as geology and environmental science to analyze the mined association relationship. For example, if the association relationship indicates that there is a connection between the geological structure of a certain area and the concentration of specific pollutants, based on the theory of the impact of geological structure on the migration and transformation of substances, analyze whether this association conforms to scientific logic. By consulting a large number of professional literatures and referring to authoritative research results, ensure that the association relationship is reasonable at the theoretical level.

[0101] Practical application verification: Apply the mined association relationship to the simulation of actual scenarios. Build a simulation model, input different environmental data and geological data parameters, and observe the degree of fit between the model output results and the actual situation. When simulating the association between the water quality change in a certain river basin and the surrounding geological conditions, refer to historical monitoring data and on-site investigation situations to test whether the simulation results can accurately reflect the actual water quality change trend. If the simulation results are consistent with the actual situation or the error is within an acceptable range, it indicates that this association relationship is feasible in practical applications.

[0102] The error analysis technique can analyze internal error indicators or external error indicators.

[0103] Internal error indicators: Calculate the sum of squared clustering errors J. The smaller J is, the better the clustering effect. The silhouette coefficient can also be calculated. The closer the silhouette coefficient is to 1, it indicates that the distance between the data points and the points within the same cluster is relatively close, and the distance from the points in other clusters is relatively far, and the clustering effect is better.

[0104] External error indicators: If there is a known true classification result as a reference, indicators such as the Rand index and adjusted Rand index can be used to measure the consistency degree between the clustering result and the true classification. The value closer to 1 indicates that the clustering result is more accurate.

[0105] S10214. Determine the valid association relationship as the target association relationship.

[0106] After obtaining the association relationship, the association relationship can also be visualized and displayed visually.

[0107] Two-dimensional visualization can be adopted, three-dimensional visualization can also be adopted, and geographical information system (GIS) visualization can also be adopted.

[0108] Two-dimensional visualization can include: scatter plots or bar charts.

[0109] Scatter plot: Select two representative features as the coordinate axes, plot each data point on a two-dimensional plane, and use different colors or shapes to represent different clustering results. For example, taking the soil heavy metal content as the x-axis and the formation depth as the y-axis, the distribution of different clusters on these two features can be visually observed through the scatter plot.

[0110] Bar chart: Statistically calculate the average value or quantity of each feature in each cluster and display it using a bar chart. For example, showing the proportion of different rock types in each cluster can clearly compare the feature differences between different clusters.

[0111] For data with three important features, a three-dimensional scatter plot or a three-dimensional surface plot can be used for visualization. For example, taking the groundwater level, soil water content, and soil pH as the three coordinate axes, plot the data points in three-dimensional space and distinguish them by color according to the clustering results, so as to more comprehensively display the data distribution and clustering relationship.

[0112] Geographic Information System (GIS) visualization can also be adopted: Combine the clustering results with geographic spatial information and conduct visual display on the GIS platform. The distribution map of different clustering regions can be drawn to intuitively understand the correlation relationship and spatial distribution law of environmental data and geological data in different regions. For example, mark the regions corresponding to different clusters on the map, and the darker the color, the higher the value of a certain feature in that region, which can help decision-makers quickly identify the spatial differences in environmental and geological features.

[0113] S1022. Divide the area to be surveyed into different survey locations according to the target correlation relationship.

[0114] Each target correlation relationship corresponds to a survey location.

[0115] In step S103, obtain the survey equipment corresponding to each survey location.

[0116] Appropriate survey equipment can be selected based on the geological data and environmental data of the survey location.

[0117] When the environmental data shows that the geological conditions are relatively simple, the formation is shallow and the geotechnical properties change little, a light dynamic penetrometer can be selected. If more detailed geotechnical physical and mechanical properties are required, a portable static penetrometer can be used in combination to divide soil layers and evaluate soil properties by measuring the cone tip resistance and sidewall friction resistance.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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.

[0122] When conducting surveys in high temperature areas, it is necessary to select equipment that can withstand high temperatures.

[0123] In cold areas, the equipment must be cold-resistant.

[0124] 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.

[0125] Areas with heavy precipitation: Choose equipment with good waterproof performance.

[0126] 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.

[0127] 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.

[0128] When conducting surveys in mountainous areas, the equipment should be easy to carry and transport. Lightweight small-scale drilling equipment and geophysical exploration instruments can be selected, such as backpack geological radars and portable drills. At the same time, the operational convenience of the equipment in complex terrains should be considered, such as equipping appropriate mountaineering tools and positioning devices.

[0129] In plain areas, the terrain is relatively flat, and large-scale and efficient survey equipment can be selected. For example, large vehicle-mounted drilling machines and high-precision measuring instruments can improve the efficiency and accuracy of survey work.

[0130] In step S104, the survey operation data of each survey device is obtained.

[0131] The survey operation data of each survey device can be obtained through the operation manual, or the survey device operation data can be obtained through actual operation of the survey device.

[0132] In step S105, according to the geological data, survey locations, and the corresponding survey devices and survey operation data at each survey location, an animation model of the survey process is constructed.

[0133] MATLAB software can be used and the mesh function can be adopted for plotting.

[0134] In one embodiment, step S105 includes the following sub-steps S1051 - S1056:

[0135] S1051. Construct a geological model according to the geological data.

[0136] In MATLAB, first, a three-dimensional model representing the geological conditions of the survey area needs to be created. Here, the meshgrid function is used to generate two-dimensional grid coordinates x and y, whose range is from -5 to 5 with an interval of 0.1. Then, the height value z corresponding to each grid point is calculated to simulate a undulating terrain. The mesh function is used to visualize this terrain, and thus a simple geological model is obtained, which can intuitively display the general terrain features of the survey area.

[0137] S1052. Construct a survey location model according to the survey locations.

[0138] The exploration location model represents the specific locations on the geological model where exploration needs to be carried out. A certain number (set to 20 here) of exploration points are randomly generated, and their x and y coordinates are randomly selected between -5 and 5. To determine the height of these exploration locations on the geological model, the interp2 function is used to perform interpolation calculations on the randomly selected x and y coordinates based on the previously generated x, y, and z data of the geological model to obtain the corresponding z coordinates. Finally, the scatter3 function is used to plot these exploration locations as red solid dots on the geological model while retaining the display of the geological model, so that the distribution of the exploration locations on the terrain can be clearly seen.

[0139] S1053. Construct an exploration equipment model based on the exploration equipment and exploration operation data corresponding to each exploration location.

[0140] The exploration 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 angles 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 used to generate the height coordinate Z_cylinder of the cylinder. Then this cylinder model is placed at each exploration point. By looping through each exploration point, the mesh function is used to draw the cylinder model at the corresponding position and display it together with the geological model, so that the model of the exploration equipment at the exploration location is obtained.

[0141] S1054. Obtain the exploration process simulation data corresponding to the area to be explored based on the geological model, exploration location model, and exploration equipment model.

[0142] The above three models are combined and displayed. In a new figure window, first draw the geological model, then draw the exploration locations, and finally draw the exploration equipment model at the corresponding exploration locations, thus forming a complete combined model that comprehensively displays the geological conditions, exploration locations, and the distribution of exploration equipment in the exploration area.

[0143] The save function can be used to save all the previously generated model data (including the coordinates x, y, z of the geological model, the coordinates x_points, y_points, z_points of the exploration locations, and the coordinates X_cylinder, Y_cylinder, Z_cylinder of the exploration equipment model) to a MAT file geotechnical_model.mat for subsequent use or further analysis.

[0144] When simulation is required, the saved model is called, and virtual exploration is performed on the geological bodies in the geological model according to the exploration location determined by the exploration location model and the operation process set by the exploration equipment model. For example, when simulating the drilling process, according to parameters such as the bit size and drilling speed in the drilling equipment model, virtual drilling is carried out at the drilling position determined by the exploration location model in the geological model, and the measurement positions (including drilling depth, horizontal coordinates, etc.), measurement contents (such as physical and mechanical properties of rock and soil, core sample characteristics, etc.) and measurement steps (such as drilling, coring, measurement intervals, etc.) during the drilling process are recorded in real time. In this way, all data during the exploration process are comprehensively obtained to form complete exploration process simulation data.

[0145] S1055. Obtain the exploration process simulation data corresponding to each exploration location from the exploration process simulation data corresponding to the area to be explored.

[0146] The specific implementation process can be as follows:

[0147] First, comprehensively analyze the obtained exploration 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 the form of files (such as CSV, JSON files, etc.). Different data storage formats determine the subsequent data extraction methods and tools.

[0148] Deeply analyze the data structure to understand the relationships between various data fields. The exploration process simulation data usually contains information in multiple dimensions, such as measurement positions, measurement contents, measurement steps, etc. Among them, the measurement position information is used as a key identifier and is closely related to other information. For example, in the case of database storage, there may be a main table recording the overall exploration process data, which is associated with a sub-table storing measurement positions through specific foreign key relationships; if stored in the form of files, the measurement position information may exist in the file in a specific field or hierarchical structure.

[0149] Extract the exploration location identifier: Based on the analysis of the data structure, determine the key information used to identify the exploration location, such as geographical coordinates (longitude, latitude, altitude), exploration point numbers, etc. For each exploration location, these identifiers are unique and are the key basis for accurately screening data.

[0150] Implement the screening operation: Use data processing tools or programming languages (such as the Pandas library in Python, SQL query statements, etc.) to screen the overall exploration process simulation data according to the extracted exploration location identifier. Taking an SQL query as an example, if the exploration location identifier is "location_id" and the data is stored in a table named "survey_simulation_data", the query can be executed by "SELECT" The query statement "FROM survey_simulation_data WHERE location_id = [specific_location_id]" is used to obtain all the survey process simulation data corresponding to a specific survey location. For data stored in file form, the file reading and data processing functions in programming languages can be utilized to traverse the data records and filter out the required data based on the survey location identifier.

[0151] Data cleaning: Clean the survey process simulation data corresponding to each surveyed location that has been filtered out to ensure data consistency and integrity. This may include checking whether data fields are complete and whether data formats are unified. For example, for numerical data in the measurement content, check whether there are outliers or missing values and process them according to preset rules.

[0152] Output result: Output the cleaned 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 independent files (such as CSV files for data analysis and JSON files for data transmission, etc.). Through the above steps, the survey process simulation data corresponding to each surveyed 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 surveyed locations.

[0153] S1056. Obtain the 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 surveyed location.

[0154] In the field of geotechnical engineering survey, in order to visually display the survey process, a survey process animation model is constructed based on the survey process simulation data corresponding to the area to be surveyed and the survey process simulation data corresponding to each surveyed location. The specific steps are as follows:

[0155] I. Data preprocessing and integration.

[0156] Data consistency check: Conduct a comprehensive and detailed check on the survey process simulation data corresponding to the area to be surveyed and the survey process simulation data corresponding to each surveyed location to ensure data consistency in terms of time, space, and data format. For example, confirm that the coordinate systems of the measurement locations are unified and the recording formats of the measurement times are consistent to avoid errors in subsequent modeling caused by inconsistent data.

[0157] Key information extraction and integration: Extract key information from two types of data, including but not limited to the spatial coordinates of the measurement positions, the measurement content (such as the properties of different strata, the measured physical parameters, etc.), the sequence of measurement steps, and the corresponding time nodes for each step. Integrate this key information to form an ordered data set containing complete exploration process information. For example, taking time as the main line, associate the measurement content and steps at different exploration positions at each time point to provide a clear data context for subsequent animation model construction.

[0158] II. Animation model framework construction.

[0159] Scene and object definition: According to the actual situation of the exploration scene, define the animation scene and objects in animation modeling software (such as 3DMAX, Maya, etc.). For example, create a three-dimensional terrain model representing the topography of the area to be explored, create corresponding exploration equipment objects based on the exploration equipment models, such as drilling rigs, detectors, etc., and place them in appropriate initial positions. At the same time, create three-dimensional models of different stratum structures according to the geological model to provide a basic scene for subsequent display of geological changes during the exploration process.

[0160] Timeline setting: Based on the time information in the integrated data set, set the timeline in the animation software. The length of the timeline should cover the time span of the entire exploration process, and the accuracy of the time scale should be adjusted according to the detail level of the actual exploration steps to ensure that it can accurately correspond to the time points of each measurement step, providing a framework for subsequent time-series display of the animation.

[0161] III. Animation key frame setting.

[0162] Creation of key frames based on measurement positions and steps: According to the sequence of measurement steps at each exploration position in the integrated data set, set key frames at the corresponding positions on the timeline. For example, when the exploration equipment moves from one exploration position to another, set key frames 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 from different strata during the drilling process, set key frames at the corresponding time points to show the changes in the equipment state and the strata samples. By setting key frames, capture the key state changes during the exploration process.

[0163] Key Frames for Attribute and Parameter Changes: For various attributes and parameters in the measurement content, such as physical attributes of rock and soil like color, hardness, conductivity, and parameters of the measurement equipment (e.g., drilling depth, detection intensity), key frames are set at corresponding time points on the timeline according to the recorded changes in the dataset. For example, when the drilling depth increases, a key frame 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 displayed drilling depth parameter. Through these key frames, the dynamic changes of various attributes and parameters over time during the exploration process are precisely demonstrated.

[0164] IV. Animation Transition and Rendering.

[0165] Transition Effect Setting: Appropriate transition effects are set between key frames to make the transition of the animation between different states more natural and smooth. For example, for the movement of exploration equipment, a smooth linear interpolation transition method is adopted to simulate the uniform or variable-speed movement of the equipment during actual movement; for the acquisition and display of formation samples, transition effects such as fade-in and fade-out are used to enhance the visual effect of the animation.

[0166] Rendering and Optimization: According to actual requirements, a suitable rendering engine (such as V - Ray, Arnold, etc.) is selected to render the animation scene. During the rendering process, parameters such as materials, lighting, and shadows are adjusted to make the animation scene more realistic and conform to the visual effect of the actual exploration environment. At the same time, the animation model is optimized, reducing the number of polygons of the model, compressing texture files, etc., to improve the playback performance of the animation and ensure that the animation model of the exploration process can be smoothly displayed on different hardware devices.

[0167] Through the above steps, it is possible to effectively construct an accurate, intuitive, and visually appealing animation model of the exploration process based on the exploration process simulation data corresponding to the area to be explored and the exploration process simulation data corresponding to each exploration location, providing strong tool support for the planning, demonstration, and teaching of geotechnical engineering exploration.

[0168] In step S106, based on the animation model of the exploration process, the exploration risk of the area to be explored is evaluated according to a preset evaluation algorithm.

[0169] In one embodiment, based on the animation model of the exploration process, the exploration risk of the area to be explored is evaluated according to a preset evaluation algorithm, including the following sub-steps S1061 - S1065:

[0170] S1061. Obtain multiple different exploration scenarios.

[0171] Different exploration scenarios can be set to represent potential future development paths.

[0172] For example: natural environment scenarios, geological condition scenarios, and human factor scenarios.

[0173] The following details each scenario:

[0174] Natural environment scenarios:

[0175] Mild weather scenario: During the exploration period, the weather conditions are good and stable, the temperature is moderate, and there is no obvious precipitation, strong wind or other adverse weather, with minimal interference to the exploration work. In this scenario, the natural environment basically does not bring additional risks to the exploration.

[0176] Variable climate scenario: There are certain degrees of weather changes, such as occasional light rain and gentle breeze, which may have a slight impact on some outdoor exploration operations. For example, it may affect the reading accuracy of measurement instruments, but the impact is limited.

[0177] Severe climate scenario: Encounter extreme weather such as heavy rain, heavy snow, strong wind, and lightning. Heavy rain may trigger geological disasters such as floods and debris flows. Strong wind will affect high-altitude operations and the stability of equipment, and lightning poses a serious threat to the safety of personnel and equipment.

[0178] Geological disaster scenario: Geological disasters such as earthquakes, landslides, and ground collapses occur in the exploration area. These disasters will directly damage the exploration equipment, interrupt the exploration work, and even endanger the lives of personnel.

[0179] Geological condition scenarios:

[0180] Single homogeneous geology scenario: The geological structure is simple, the geotechnical properties are uniform, and there are no obvious geological defects such as faults and karst caves. In this scenario, the exploration work can proceed relatively smoothly, and the accuracy of data collection is relatively high.

[0181] Mildly complex geology scenario: There are some small-scale geological changes, such as local soil property differences and small joint fissures. These changes may pose certain challenges to drilling and sampling work, but can be solved through appropriate technical means.

[0182] Moderately complex geology scenario: There are obvious geological structures, such as faults, folds, and karst development areas. These complex geological conditions will increase the difficulty and uncertainty of exploration, and may lead to problems such as sticking of drill pipes and collapse of boreholes during drilling, affecting the reliability of data.

[0183] Highly complex geology scenario: The geological conditions are extremely complex, with large-scale fault fracture zones, thick soft soil layers, and complex underground karst cave systems. In this scenario, the exploration work faces great difficulties, the accuracy of data collection is difficult to guarantee, and serious engineering safety problems may be caused.

[0184] Human factor scenarios:

[0185] 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.

[0186] 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.

[0187] 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.

[0188] 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.

[0189] S1062. Obtain historical exploration data.

[0190] 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.

[0191] S1063. Calibrate the exploration process animation model according to historical exploration data.

[0192] 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.

[0193] S1064. Input each exploration scenario into the calibrated exploration process animation model to simulate the exploration process under each exploration scenario.

[0194] 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.

[0195] S1065. Conduct a risk assessment of the area to be surveyed based on the simulation results corresponding to each exploration scenario.

[0196] Specifically, step S1065 includes the following sub-steps:

[0197] S10651. Obtain the types of risk events based on the simulation results.

[0198] S10652. Obtain the risk levels of the area to be surveyed based on the types of risk events.

[0199] Run the model to simulate the development of the exploration process and its impact on ecosystem services under different scenarios. During the simulation, key indicators such as exploration progress, data quality, equipment reliability, personnel safety, and disturbance to the surrounding ecological environment are focused on. For example, in the simulation of geological disaster scenarios, the situation of exploration equipment collapsing and data loss caused by earthquakes, as well as the degree of damage to surrounding vegetation and soil by landslides, are simulated.

[0200] Identify the key input parameters in the model that may affect the results of the exploration risk assessment, such as meteorological parameters (temperature, precipitation, wind force, lightning activity), geological parameters (rock and soil strength, groundwater level, fault density, karst cave development degree), human parameters (personnel operation skill level, frequency of violation behaviors, equipment maintenance quality), etc.

[0201] Adopt local sensitivity analysis or global sensitivity analysis methods to study the sensitivity of the model output results to the change of each parameter. Local sensitivity analysis is to fix other parameters and change the value of one parameter alone to 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, observe the degree of influence on the stability of drilling equipment and the accuracy of geological data, and determine the sensitivity of the groundwater level parameter. Through sensitivity analysis, identify the key uncertainty parameters that have a greater impact on the results of the exploration risk assessment.

[0202] Compare the simulation results under different scenarios and analyze the types of risk events generated by various scenarios during the exploration process.

[0203] Risk events in the common geotechnical exploration process may include:

[0204] In terms of complex geological conditions, risk events include: the existence of complex geological structures such as fault zones and folds, large changes in the groundwater level, and diverse types and significant property differences of rock and soil masses. Geotechnical exploration risks include: it may lead to unreasonable layout of exploration points, inability to accurately grasp the geological situation, difficulty in determining the drilling depth and location, large discreteness of in-situ test and laboratory test results, and affect the accurate judgment of geotechnical engineering properties.

[0205] In terms of adverse geological actions, risk events include: adverse geological phenomena such as landslides, collapses, debris flows, karsts, etc. Geotechnical exploration risks include: increasing the difficulty and danger of exploration work, possibly damaging exploration equipment, threatening the safety of exploration personnel, and easily missing important adverse geological information, posing serious hidden dangers to subsequent engineering design and construction.

[0206] In terms of complex site environments, risk events include: there are facilities such as buildings, roads, and underground pipelines around the site, or it is in a densely populated area such as a downtown area or a residential area. Geotechnical exploration risks include: exploration operations are restricted by space, may cause damage to surrounding facilities, trigger disputes and economic losses, and noise, vibration, etc. may also cause complaints from residents, affecting the exploration progress.

[0207] In terms of special geotechnical problems, risk events include: the existence of special soils such as soft soils, collapsible loess, expansive soils, and frozen soils. Geotechnical exploration risks include: the engineering properties of special soils are complex, with high requirements for exploration methods and technologies. For example, the high compressibility and low strength of soft soils may lead to excessive foundation settlement, and collapsible loess may undergo collapsible deformation when encountering water. If the exploration is inaccurate, it will cause serious harm to the project.

[0208] In terms of meteorology and natural disasters, risk events include: meteorological disasters or geological disasters such as heavy rains, floods, strong winds, and earthquakes. Geotechnical exploration risks include: affecting the normal progress of exploration work, possibly causing damage to exploration equipment and casualties, making it impossible to accurately obtain exploration data during disasters, and heavy rains, etc. may change the physical and mechanical properties of rock and soil masses, increasing the uncertainty of exploration.

[0209] According to the comparison of scenario results, evaluate the exploration risks and determine the risk levels. A detailed risk level assessment standard can be formulated, comprehensively considering the possibility of risk events occurring and the severity of the consequences. This disclosure designates 5 risk levels:

[0210] Level 1: Slight risk.

[0211] Risk description: The geological conditions are relatively simple, there are no obvious adverse geological actions, the site is open, the surrounding environment is simple, there are no special soils, the exploration technology and equipment can meet the conventional requirements, and the meteorological conditions are normal.

[0212] Example: A general farmland area with flat terrain, single rock and soil type, stable and deep groundwater level, no buildings and underground pipelines around, no distribution of special soils, good local meteorological conditions, and few extreme weather conditions.

[0213] Level 2: General risk.

[0214] 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.

[0215] 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.

[0216] Level 3: Significant risk.

[0217] 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.

[0218] 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.

[0219] Level 4: High risk.

[0220] 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.

[0221] 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.

[0222] Level 5: Extremely dangerous.

[0223] 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.

[0224] Example: In an area located in a large debris flow valley, debris flow disasters often occur, there is radioactive substance pollution within the site, and it is surrounded by a military restricted area. The exploration work is extremely restricted, and the safety of personnel and equipment is seriously threatened.

[0225] Through result analysis, provide a scientific basis for exploration decision-making, so as to take corresponding risk response measures and reduce exploration risks.

[0226] In one embodiment, it is also possible to obtain the benefits and trade-offs of the area to be explored according to the simulation results corresponding to each exploration scenario; among them, the benefits may be reflected in aspects such as the acceleration of exploration progress, the reduction of costs, and the improvement of data quality; the trade-offs involve the choice between different objectives. For example, in order to accelerate the exploration progress, it may be necessary to increase equipment investment or reduce the accuracy of data collection.

[0227] The method designed by the present disclosure can accurately simulate the exploration process through the environmental data, geological data, and exploration equipment operation data of the exploration area, and analyze the simulation process according to the preset evaluation algorithm, so as to determine the exploration risks. This method has a relatively fast risk analysis speed, does not rely too much on expert evaluation, and can accelerate the speed of geotechnical exploration.

[0228] It should be noted that the present disclosure can be established based on a cloud platform, that is, the execution entity in each of the above embodiments can be a cloud platform. During the geotechnical exploration process, the exploration operation data of the exploration equipment can be directly transmitted to the cloud platform system during exploration. Subsequently, the cloud platform system can process and analyze based on the obtained geospatial data and the exploration operation data uploaded by the exploration equipment, so as to achieve timely early warning of exploration risks and reduce the difficulty of geotechnical exploration.

[0229] Specifically, the cloud platform obtains the geospatial data of the area to be explored, and the geospatial data includes: environmental data and geological data; the cloud platform will also divide the exploration locations of the area to be explored according to the geospatial data; the cloud platform will also obtain the exploration equipment corresponding to each exploration location; the cloud platform will also obtain the exploration operation data of each exploration equipment; the cloud platform will also construct an exploration process animation model according to the geological data, exploration locations, and the exploration equipment and exploration operation data corresponding to each exploration location; the cloud platform will also conduct exploration risk assessment on the area to be explored based on the exploration process animation model according to the preset evaluation algorithm.

[0230] Based on the same inventive concept, an embodiment of the present application further provides a geotechnical investigation risk analysis system for implementing the geotechnical investigation risk analysis method involved above. The implementation solutions provided by this system to solve problems are similar to those recorded in the above method. Therefore, the specific limitations in one or more embodiments of the geotechnical investigation risk analysis system provided below can refer to the limitations on the geotechnical investigation risk analysis method in the above text, and will not be elaborated here.

[0231] In an exemplary embodiment, as Figure 2 shown, a geotechnical investigation risk analysis system is provided, including:

[0232] A data retrieval unit 11, configured to obtain the geospatial data of the area to be investigated, where the geospatial data includes: environmental data and geological data;

[0233] A data analysis unit 12, configured to divide the area to be investigated into investigation locations according to the geospatial data;

[0234] An investigation equipment acquisition unit 13, configured to obtain the investigation equipment corresponding to each of the investigation locations;

[0235] An investigation data acquisition unit 14, configured to obtain the investigation operation data of each of the investigation equipment;

[0236] A data simulation unit 15, configured to construct an animation model of the investigation process according to the geological data, the investigation locations, and the investigation equipment and the investigation operation data corresponding to each of the investigation locations;

[0237] An evaluation unit 16, configured to perform an investigation risk assessment on the area to be investigated based on the animation model of the investigation process according to a preset evaluation algorithm.

[0238] In one embodiment, the data analysis unit 12 is specifically configured to:

[0239] Perform a correlation analysis on the geospatial data to obtain a target correlation relationship;

[0240] Divide the area to be investigated into different investigation locations according to the target correlation relationship.

[0241] In one embodiment, in terms of performing a correlation analysis on the geospatial data, the data analysis unit 12 is specifically configured to:

[0242] Preprocess the geospatial data;

[0243] Cluster the preprocessed geospatial data using a clustering algorithm to obtain the correlation relationship between each data in the geospatial data;

[0244] Verify whether the association relationship is valid;

[0245] Determine the valid association relationship as the target association relationship.

[0246] In one embodiment, the data simulation unit 15 is specifically configured to:

[0247] Construct a geological model according to the geological data;

[0248] Construct a survey location model according to the survey location;

[0249] Construct a survey equipment model according to the survey equipment and the survey operation data corresponding to each of the survey locations;

[0250] Obtain the 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;

[0251] Obtain 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;

[0252] Obtain the 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 of the survey locations.

[0253] In one embodiment, in terms of performing a survey risk assessment on the area to be surveyed according to the survey process animation model, the data simulation unit 15 is specifically configured to:

[0254] Obtain a plurality of different exploration scenarios;

[0255] Obtain historical exploration data;

[0256] Calibrate the survey process animation model according to the historical exploration data;

[0257] Input each of the exploration scenarios into the calibrated survey process animation model to simulate the exploration process under each of the exploration scenarios;

[0258] Perform a survey risk assessment on the area to be surveyed according to the simulation results corresponding to each of the exploration scenarios.

[0259] In one embodiment, the evaluation unit 16 is specifically configured to:

[0260] Obtain the risk event type according to the simulation result;

[0261] Obtain the risk level of the area to be surveyed according to the risk event type.

[0262] In an exemplary embodiment, a computer device is provided. The computer device can be a server or a terminal, and its internal structure diagram can be as shown in Figure 3 . The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, 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. Among them, 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 external devices. The communication interface of the computer device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, it implements a geotechnical investigation risk analysis method.

[0263] Those skilled in the art can understand that Figure 3 the structure shown in is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this 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 different component arrangements.

[0264] In an exemplary embodiment, a computer device is further provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, it implements the steps in the above method embodiments.

[0265] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by the processor, it implements the steps in the above method embodiments.

[0266] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by the processor, it implements the steps in the above method embodiments.

[0267] 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 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 need to comply with relevant regulations.

[0268] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. 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 methods. Among them, any reference to a memory, database, or other medium used in the various embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAM), magnetoresistive random access memories (MRAM), ferroelectric random access memories (FRAM), phase change memories (PCM), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0269] The databases involved in the various embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the various embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logics, data processing logics based on quantum computing, etc., without limitation.

[0270] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, 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, it should be considered as the scope described in this specification.

[0271] In this article, specific examples are used to elaborate on the principles and implementation manners of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present 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; 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.

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 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.

6. 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, configured to perform an exploration risk evaluation on the area to be investigated based on the exploration process animation model and a preset evaluation algorithm; The evaluation unit is specifically used for: 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.

7. 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 5.

8. 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 5 are implemented.

9. 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 5 are implemented.

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