Method and system for determining three-dimensional initial crustal stress field of underground cavern

Abstract

The invention provides a method for determining a three-dimensional initial crustal stress field of an underground cavern, and relates to the technical field of geological exploration, and the method comprises the steps: building a preliminary crustal stress field model based on field data; the established preliminary crustal stress field model is subjected to inversion optimization, so that an error between crustal stress data obtained through model simulation and actually measured crustal stress data is reduced to a preset threshold value, and an optimized crustal stress field model is obtained; and monitoring the actual change characteristics of the surrounding rock after the hydrogeological conditions are changed, comparing the actual change characteristics with the theoretical change characteristics of the surrounding rock obtained by simulation based on the optimized crustal stress field model, and optimizing the optimized crustal stress field model to obtain a determined initial crustal stress field. According to the method, the accuracy of evaluating the initial crustal stress field can be improved.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method and system for determining a three-dimensional initial geostress field of an underground cavern. Background Art

[0002] Before excavation for underground engineering construction, an accurate assessment of the initial geostress field is required to effectively predict the stability of the surrounding rock, optimize support design, and guide the construction process. In the process of determining the three-dimensional initial geostress field of deep underground caverns, the underground rock strata usually have complex stratification, structure (such as faults, folds, etc.), and different mechanical properties, which leads to complex geostress distribution and poses a great challenge to modeling. Currently, the numerical simulation of geostress field relies on a large number of input parameters, such as the mechanical properties of rock and soil, boundary conditions, initial stress, etc. However, the acquisition of these parameters often relies on limited experimental data or estimates, which can easily lead to modeling deviations and affect the accuracy of the geostress field model. Summary of the Invention

[0003] In order to address the deficiencies of the prior art, the present invention aims to provide a method and system for determining the three-dimensional initial geostress field of an underground cavern, so as to improve the accuracy of the initial geostress field assessment.

[0004] To achieve the above objectives, according to some embodiments, a first aspect of the present invention provides a method for determining a three-dimensional initial geostress field in an underground cavern, comprising:

[0005] Establish a preliminary geostress field model based on field data;

[0006] The preliminary geostress field model established by inversion optimization reduces the error between the geostress data obtained by model simulation and the actual measured geostress data to within a preset threshold, thereby obtaining an optimized geostress field model;

[0007] The actual change characteristics of the surrounding rock after the hydrogeological conditions change are monitored, compared with the theoretical change characteristics of the surrounding rock obtained by simulation based on the optimized geostress field model, and the optimized geostress field model is optimized to obtain a determined initial geostress field.

[0008] A second aspect of the present invention provides a system for determining a three-dimensional initial geostress field in an underground cavern, comprising:

[0009] a preliminary geostress field model building module configured to build a preliminary geostress field model based on field data;

[0010] an inversion module configured to inversely optimize the preliminary geostress field model established so as to reduce the error between the geostress data obtained through model simulation and the actually measured geostress data to within a preset threshold, thereby obtaining an optimized geostress field model;

[0011] The secondary simulation optimization module is configured to monitor the actual change characteristics of the surrounding rock after the hydrogeological conditions change, compare the theoretical change characteristics of the surrounding rock obtained by simulation based on the optimized geostress field model, optimize the optimized geostress field model, and obtain a determined initial geostress field.

[0012] A third aspect of the present invention provides an electronic device comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to complete the steps of the above-mentioned method for determining the three-dimensional initial ground stress field of an underground cavern.

[0013] A fourth aspect of the present invention provides a computer-readable storage medium for storing computer instructions, which, when executed by a processor, completes the steps of the above-mentioned method for determining the three-dimensional initial geostress field of an underground cavern.

[0014] A fifth aspect of the present invention provides a computer program product, comprising a computer program / instruction, which, when executed by a processor, implements the steps of the above-mentioned method for determining the three-dimensional initial geostress field of an underground cavern.

[0015] Compared with the prior art, the present invention has the following beneficial effects:

[0016] The present invention provides a method and system for determining the three-dimensional initial geostress field of an underground cavern, which can solve the problem of poor applicability and accuracy of the geostress field inversion mathematical model when there is insufficient on-site stress test data or complex geological environmental conditions. On the basis of the traditional optimized geostress field obtained by inversion, a simulation verification of the changes in the surrounding rock after the hydrogeological conditions change is added. The change in hydrogeological conditions has a more complex impact on the changes in the geostress field. After the hydrogeological conditions change (after snowmelt or precipitation scenarios), the actual change characteristics of the surrounding rock and the theoretical change characteristics of the surrounding rock obtained by simulating the optimized geostress field are collected, and the model is optimized by secondary simulation. When the difference between the simulation result and the actual change characteristics is less than a preset value, the optimized model is determined to be the initial geostress field. Compared with relying solely on experimental data or static measurements, the stress changes brought about by natural scenarios provide a dynamic verification method. This dynamic verification method can not only confirm the accuracy of the initial geostress field, but also monitor and adjust the model in real time during actual application, further improving the reliability of the project. Furthermore, compared to traditional micro-level inversion optimization of geostress field models, monitoring the actual changes in surrounding rock after snowmelt or precipitation further optimizes and verifies the model at a macro level. This can improve model accuracy in situations where field stress test data is insufficient or geological conditions are complex. Verification under different scenarios (such as snowmelt and precipitation) ensures the reliability of the initial geostress field. Through multiple iterations and verifications, safety risks caused by inaccurate geostress fields are reduced, ensuring the stability and reliability of the engineering design.

[0017] Advantages of additional aspects of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0019] Figure 1 A flowchart of a method for determining the three-dimensional initial geostress field of an underground cavern provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0020] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0021] Example 1

[0022] The first embodiment of the present invention provides a method for determining the three-dimensional initial geostress field of an underground cavern, which can solve the problem of poor applicability and accuracy of the geostress field inversion mathematical model when there is insufficient on-site stress test data or complex geological environment conditions. Figure 1 As shown, the method includes:

[0023] S1. Establish a preliminary geostress field model based on field data;

[0024] S2. Inversely optimizing the preliminary geostress field model established so that the error between the geostress data obtained through model simulation and the actual measured geostress data is reduced to within a preset threshold, thereby obtaining an optimized geostress field model;

[0025] S3. Monitor the actual changes in the surrounding rock after changes in hydrogeological conditions, compare them with the theoretical changes in the surrounding rock obtained by simulation based on the optimized geostress field model, optimize the optimized geostress field model, and determine the initial geostress field. The actual changes in the surrounding rock include deformation patterns and the development of fractures in the surrounding rock.

[0026] Due to the complexity of underground rock formations, the distribution of the geostress field is often affected by multiple factors, including the mechanical properties of the rock and soil, geological structure, boundary conditions, etc. Therefore, in step S1, it is first necessary to establish a preliminary geostress field mathematical model. In this embodiment, the preliminary geostress field model is constructed based on at least one of the following two types of data:

[0027] Geotechnical investigation data, including physical and mechanical properties of underground rock and soil layers (such as density, Young's modulus, Poisson's ratio, etc.) and hydrogeological data (such as groundwater level and permeability). Considering the subsequent model validation based on environmental conditions (such as snowmelt or precipitation), the geotechnical investigation data should at least include hydrogeological data.

[0028] On-site ground stress measurement data is obtained through downhole measurement, drilling testing and other means to obtain actual ground stress data.

[0029] These data will be used as input and combined with numerical simulation methods (such as finite element method, discrete element method, etc.) to construct a preliminary geostress field model.

[0030] For example, a detailed geotechnical survey is first conducted, including drilling, sampling, laboratory testing, etc., to obtain data on the physical and mechanical properties of the underground rock and soil layers. At the same time, a hydrogeological survey is conducted to understand the flow direction of groundwater and water level changes. On-site geostress testing is performed using stress measuring instruments (such as piezoelectric sensors, strain gauges, geostress measurement holes, etc.) to obtain actual geostress data. Based on the geotechnical survey data and on-site geostress measurement data, a preliminary three-dimensional geostress field model is established using numerical simulation methods such as the finite element method (FEM).

[0031] In step S2, after the preliminary geostress field model is constructed, since the actual measurement data often have certain errors or incompleteness, the preliminary model often cannot fully and accurately reflect the actual situation of the underground rock formation. Therefore, it is necessary to optimize the model using inversion technology. The core idea of inversion technology is: by comparing the numerical simulation results and the field measured data (such as surrounding rock strain, deformation, etc.), the optimized geostress field is reversely derived. The specific steps are: input the preliminary geostress field model into the numerical simulation system to simulate the deformation and stress distribution of the surrounding rock; compare the simulation results with the actual measurement data and calculate the error; reversely adjust the model parameters (such as the elastic modulus, friction coefficient, initial geostress, etc. of the rock formation) according to the error, and gradually reduce the error through multiple iterations so that the simulation results are consistent with the actual measurement data to obtain the optimized geostress field model.

[0032] The in-situ stress distribution simulated by the preliminary model is compared with actual in-situ stress measurement data to calculate errors (such as stress differences and surrounding rock deformation). Based on the error inversion, the model parameters are adjusted to gradually align the simulation results with the measured data. The inversion algorithm may use a least squares method, optimization algorithm, or genetic algorithm. Multiple iterations of optimization are performed until the error is reduced to within a preset threshold.

[0033] In step S3, after the optimized geostress field model is obtained, it is further verified and optimized again. This process is carried out by comparing the optimized geostress field simulation results with the actual change characteristics of the surrounding rock after the hydrogeological conditions change. Specifically, the hydrogeological condition changes can be verified in the following scenarios:

[0034] In the snowmelt scenario, considering the possible hydrological changes in the underground rock formations, especially during the snowmelt season, the groundwater pressure may change, thus affecting the distribution of the geostress field;

[0035] In precipitation scenarios, changes in precipitation may cause groundwater level fluctuations, which in turn affect the stress state of underground rock formations.

[0036] By actually monitoring the strain, deformation and other characteristics of the surrounding rock in scenarios of snowmelt and / or precipitation changes, and comparing them with the theoretical change characteristics obtained by simulating the optimized geostress field model, if the error is less than the preset value, it can be considered that the mathematical model at this time can truly simulate the geostress, and the initial geostress field is determined based on the model at this time.

[0037] In specific scenarios such as snowmelt or precipitation, continue to monitor dynamic changes in surrounding rock deformation, crack development, and other dynamic changes, and collect relevant data. Compare the measured data with the numerical simulation results based on the optimized geostress field. If the difference between the theoretical value and the measured value is less than the preset error range, the optimized geostress field is considered to be the initial geostress field. The advantage of this verification method is that it uses the stress fluctuations caused by natural changes in actual scenarios for verification, which can increase the applicability and accuracy of the model, especially when there is insufficient field data or complex environmental conditions. This not only makes the determination of the initial geostress field more accurate, but also enhances the safety and operability of the project.

[0038] In some embodiments, hydrogeological change data is calculated based on infiltration water data associated with snowmelt or precipitation scenarios; based on the hydrogeological change data, theoretical change characteristics of the surrounding rock are obtained in combination with optimized ground stress field simulation.

[0039] During natural events such as snowmelt and precipitation, groundwater infiltration can change, affecting the hydrogeological conditions of the subsurface rock formations. These changes are typically reflected in variations in parameters such as groundwater level, soil saturation, and permeability. Monitoring equipment (such as infiltration meters and water level gauges) can be installed on-site to regularly collect infiltration data related to snowmelt or precipitation. This infiltration data can be used to calculate groundwater flow patterns and hydrogeological properties of the rock and soil (such as permeability coefficient, water flow velocity, and groundwater level fluctuations). This process can be calculated using hydrological models (such as Richards' equation and Darcy's law), reflecting the distribution and variations of water flow in the subsurface rock formations. The permeability coefficient determines the ability of water to penetrate the soil; the water flow velocity determines the rate of water flow through the subsurface rock formations; and groundwater level fluctuations can be used to estimate changes in hydrological conditions by long-term monitoring of water level fluctuations during snowmelt and precipitation. Hydrogeological changes can directly affect the stress state of the rock formations, especially in aquifers or areas with high groundwater saturation. Water infiltration can cause the rock formation to expand or compress, thereby altering the stress distribution. By calculating and analyzing hydrogeological data, we can obtain the factors affecting the stress field of underground rock formations by hydrological changes, and provide the necessary input for the subsequent optimization of the mathematical model of the ground stress field.

[0040] After obtaining hydrogeological variation data, these data are used as input parameters and combined with an optimized geostress field model for secondary simulation. The optimized geostress field model already considers the mechanical properties of the rock and soil and the distribution of initial geostresses during the inversion process, and the hydrogeological data provides the basis for further dynamic adjustments to the model. Numerical simulations can predict the stress state, deformation pattern, and fracture development of the surrounding rock under snowmelt or precipitation scenarios. Based on the hydrogeological variation data, numerical simulations can account for the effects of groundwater infiltration and provide detailed predictions of theoretical rock deformation characteristics (such as stress increase and decrease, deformation, and failure). The simulation results reveal the stress and deformation characteristics of the surrounding rock under the influence of hydrogeological variation. For example, groundwater rise caused by snowmelt may cause rock compression, while water changes caused by precipitation may cause rock expansion. Next, the theoretical rock deformation characteristics derived from the hydrogeological variation and optimized geostress field simulations are compared with actual monitoring data (such as actual strain, deformation, and fracture development in the surrounding rock). If the error between the two is less than the preset threshold, it indicates that the optimized mathematical model of the geostress field can accurately describe the stress changes of the underground rock formation under natural variation conditions.

[0041] It can be understood that by incorporating data on hydrogeological changes caused by snowmelt or precipitation, it is possible to accurately simulate stress changes in underground rock formations under dynamically changing environmental conditions. This not only provides a more accurate verification method for determining the initial geostress field, but also enables real-time adjustment of the stress field model during project implementation to respond to environmental changes. Hydrogeological changes directly affect the stress state of rock formations, especially in areas with significant hydrological fluctuations (such as those with large groundwater level fluctuations). Ignoring these effects can lead to errors in the stress field model. By incorporating hydrogeological change data into the optimization process, the impact of natural conditions on the geostress field can be more accurately reflected, thereby improving the accuracy of the model. Furthermore, this method is validated based on macro-level precipitation or snowfall scenarios, eliminating the need to collect complex geostress data. It is therefore more suitable for determining geostress fields in situations where field stress test data is insufficient or the geological environment is complex. This method enhances the model's adaptability in practical applications and can cope with changes in various natural scenarios, such as snowmelt, precipitation, and groundwater flow, making the model more consistent with actual geological conditions and thus improving the safety of underground cavern design and construction.

[0042] In some embodiments, the geotechnical survey data in step S1 also includes the geotechnical surface slope. In this case, the preliminary geostress field model is additionally added with the seepage water data calculated based on the geotechnical surface slope, thereby increasing the influence of the seepage water in subsequent optimization to improve the simulation accuracy.

[0043] The slope of the rock and soil surface directly determines the direction and velocity of water flow. In areas with larger slopes, water generally flows downhill, and the flow of infiltrated water will also occur along the slope surface. In areas with smaller slopes, water flow may be slower, and the distribution of infiltrated water may be more uniform. In areas with larger slopes, groundwater is more likely to flow along the slope surface and the flow rate is faster, resulting in faster water penetration into the underground rock layer. This may lead to drastic changes in the local moisture content and stress state of the rock and soil layer. In areas with smaller slopes, the water flow rate is slower, the water penetration may be more uniform, and the penetration depth may also be greater, but the speed is slower and the changes are more gradual. When calculating the amount of infiltrated water, it is necessary to consider the impact of the slope of the rock and soil surface on the water flow. Generally speaking, the greater the slope, the greater the water flow rate and infiltration volume; in areas with smaller slopes, the water flow rate is slower and the infiltration volume is relatively small. The following methods can be used to calculate the amount of infiltrated water based on slope:

[0044] Darcy's law is used to calculate the infiltration rate of water in the soil layer. It is combined with the slope parameter to further adjust the infiltration rate. The greater the slope, the stronger the driving force of groundwater flow and the greater the infiltration rate.

[0045] Hydrological model, using a more complex hydrological model (such as Richards equation), takes slope as one of the input parameters, combines the soil permeability coefficient and water flow direction, and calculates the infiltration water volume under different slopes.

[0046] Geotechnical investigations are used to obtain information on the slope of underground rock and soil layers. Slope can be determined through field measurements, geological surveys, or remote sensing. Contour lines or digital elevation models (DEMs) are typically used to calculate slope. Darcy's law or hydrological models are used to combine this slope information to calculate infiltration water volume.

[0047] The process of calculating infiltration water based on slope includes:

[0048] Determine the slope area and its impact area;

[0049] Calculate the infiltration rate and amount of infiltrated water for each slope area. For areas with larger slopes, the infiltration rate is higher, and its impact on the ground stress field needs to be considered.

[0050] Taking into account factors such as rock and soil permeability, soil type, and water level, the amount of infiltrated water at a specific slope is determined.

[0051] After obtaining the infiltration water volume data, it is combined with the mathematical model of the ground stress field to simulate the impact of changes in infiltration water volume on the surrounding rock. These changes in infiltration water volume will change the hydrological conditions of the underground rock formation, thereby affecting its stress state, deformation, and crack development.

[0052] It is understandable that calculating the amount of seepage water based on the slope of the rock surface can more accurately reflect the impact of water flow on the seepage of underground rock formations under different terrains and slopes. The slope affects the flow rate and direction of groundwater, which in turn affects the hydrological characteristics of the underground rock formation. Through this calculation method, more accurate seepage water data can be obtained. Incorporating seepage water data calculated based on slope into the mathematical model of the geostress field can more realistically reflect the impact of hydrogeological changes under natural conditions on underground rock formations, especially in areas with multiple hydrological changes. Changes in the amount of seepage water can cause the expansion, compression or expansion of cracks in the rock formation, all of which directly affect the accuracy of the initial geostress field. By accurately calculating the impact of slope on seepage water and combining it with the optimized mathematical model of the geostress field, more reliable basic data can be provided for underground cavern design. This helps to predict and analyze the behavior of surrounding rock under different natural conditions and improve engineering safety.

[0053] The slope of the rock surface affects the direction and velocity of groundwater flow. The steeper the slope, the greater the horizontal component and velocity of the flow. The effect of slope on flow can be measured by adjusting the hydraulic head difference. For areas with steeper slopes, the hydraulic head difference increases, thereby increasing the infiltration rate. Darcy's law can be adjusted based on the slope using the following formula:

[0054]

[0055] Among them, h top and h bottom where represents the water level at each end of the slope; L is the length of the horizontal path along the slope; and θ is the slope angle of the rock surface. Substituting the slope angle θ into the formula can correct the calculation of the hydraulic head difference, thereby affecting the water infiltration rate.

[0056] For example, once the infiltration velocity v is calculated, the next step is to determine the amount of water that infiltrates. The amount of water that infiltrates is proportional to the infiltration velocity and is affected by factors such as the thickness and permeability of the soil layer, as well as the length of the water flow path. The amount of water that infiltrates, Q, can be calculated using the following formula: Q = v * A, where v is the water flow's infiltration velocity and A is the cross-sectional area of the water flow. By calculating the infiltration velocity at different slopes, the amount of water that infiltrates under different slope conditions can be obtained. The specific amount of water that infiltrates will vary with the slope, soil type, and permeability coefficient, so the calculation needs to be adjusted according to the specific geotechnical characteristics. In addition to slope and infiltration velocity, the amount of water that infiltrates is also affected by other factors, such as the permeability of the geotechnical layer (permeability coefficient K): rock layers with higher permeability will infiltrate more water, while rock layers with lower permeability will infiltrate less water. Soil type: Different types of soil (such as clay, sand, gravel, etc.) have different permeability coefficients, which affect the infiltration velocity and amount of water flow. The length of the water flow path, L: A longer water flow path may cause the water to infiltrate gradually, thus affecting the final amount of water that infiltrates.

[0057] In some embodiments, the inverse optimization process is implemented based on artificial excavation, and the ground stress state is changed by artificial excavation to perform inverse optimization on the model.

[0058] First, the support scheme is determined based on the preliminary geostress field model;

[0059] Subsequently, ground stress monitoring is performed periodically during the excavation process to obtain real-time stress data;

[0060] Based on the real-time stress data obtained after excavation, the ground stress field model is updated using numerical simulation and inversion techniques.

[0061] In some embodiments, updating the geostress field model using numerical simulation and inversion techniques includes:

[0062] Encode the measured data to form genotypes;

[0063] The stress field is calculated by numerical simulation, and the error between the simulation result and the measured data is compared as the fitness function;

[0064] The parameters of the stress field are optimized through crossover and mutation operations in the genetic algorithm.

[0065] The method provided in this embodiment uses a numerical simulation method to establish a preliminary mathematical model of the geostress field. The preliminary model is determined based on at least one of geotechnical survey data and on-site geostress measurement data, the geotechnical survey data including hydrogeological data. The preliminary mathematical model of the geostress field is optimized by inversion technology using a combination of measured data and numerical simulation to obtain an optimized geostress field. When the difference between the actual change characteristics of the surrounding rock collected after snowmelt or precipitation and the theoretical change characteristics of the surrounding rock obtained based on the optimized geostress field simulation is less than a preset value, the optimized geostress field is determined to be the initial geostress field. Compared with relying solely on experimental data or static measurements, the stress changes caused by natural scenarios provide a dynamic verification method. This dynamic verification method not only confirms the accuracy of the initial geostress field, but also enables real-time monitoring and adjustment of the model during actual application, further improving the reliability of the project. The model can be continuously optimized through inversion technology under complex geological conditions, improving the accuracy of geostress field prediction. It can be verified in different scenarios (such as snowmelt, precipitation, etc.) to ensure the reliability of the initial geostress field. Through multiple iterations and verifications, the safety risks caused by inaccurate ground stress fields were reduced, ensuring the stability and reliability of the engineering design.

[0066] Example 2

[0067] This embodiment provides a system for determining a three-dimensional initial geostress field in an underground cavern, comprising:

[0068] a preliminary geostress field model building module configured to build a preliminary geostress field model based on field data;

[0069] an inversion module configured to inversely optimize the preliminary geostress field model established so as to reduce the error between the geostress data obtained through model simulation and the actually measured geostress data to within a preset threshold, thereby obtaining an optimized geostress field model;

[0070] The secondary simulation optimization module is configured to monitor the actual change characteristics of the surrounding rock after the hydrogeological conditions change, compare the theoretical change characteristics of the surrounding rock obtained by simulation based on the optimized geostress field model, optimize the optimized geostress field model, and obtain a determined initial geostress field.

[0071] It should be noted here that the various modules in this embodiment correspond one-to-one to the steps of the method in Example 1, and the specific implementation process is the same, which will not be repeated here.

[0072] Example 3

[0073] This embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to complete the steps of the method in the first embodiment.

[0074] The processor may include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), or LA (Programmable Logic Array). The processor may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0075] The memory may include one or more computer-readable media, which may be non-transitory. The memory may also include high-speed random access memory and non-volatile memory, such as one or more magnetic disk storage devices or flash memory storage devices. In some embodiments, the non-transitory computer-readable medium in the memory is used to store at least one computer program, which is executed by the processor to implement the method for determining the three-dimensional initial geostress field of an underground cavern provided in the embodiments of the present disclosure.

[0076] Those skilled in the art will appreciate that the electronic device provided in this embodiment may include more or fewer components, or combine certain components, or adopt different component arrangements.

[0077] Example 4

[0078] This embodiment provides a computer-readable storage medium for storing computer instructions. When the computer instructions are executed by a processor, the steps of the method in the first embodiment are completed.

[0079] Example 5

[0080] This embodiment provides a computer program product, including a computer program / instruction, which implements the steps of the method in embodiment 1 when executed by a processor.

[0081] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that includes one or more available media integrated therein. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0082] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A method for determining the three-dimensional initial geostress field of an underground cavern, characterized in that: include: Establish a preliminary geostress field model based on field data; The preliminary geostress field model established by inversion optimization reduces the error between the geostress data obtained by model simulation and the actual measured geostress data to within a preset threshold, thereby obtaining an optimized geostress field model; The actual change characteristics of the surrounding rock after the hydrogeological conditions change are monitored, compared with the theoretical change characteristics of the surrounding rock obtained by simulation based on the optimized geostress field model, and the optimized geostress field model is optimized to obtain a determined initial geostress field.

2. The method for determining the three-dimensional initial geostress field of an underground cavern according to claim 1, wherein: The field data includes at least one of geotechnical investigation data and field stress measurement data, and the geotechnical investigation data includes at least hydrogeological data.

3. The method for determining the three-dimensional initial geostress field of an underground cavern according to claim 2, wherein: The geotechnical investigation data also includes the geotechnical surface slope; the geotechnical surface slope is used to calculate the amount of infiltration water.

4. The method for determining the three-dimensional initial geostress field of an underground cavern according to claim 1, wherein: The monitoring of actual change characteristics of surrounding rocks after changes in hydrogeological conditions includes monitoring actual change characteristics of surrounding rocks in scenarios of snowmelt and / or precipitation changes; the actual change characteristics of surrounding rocks include surrounding rock deformation patterns and surrounding rock crack development conditions.

5. The method for determining the three-dimensional initial geostress field of an underground cavern according to claim 4, wherein: The method for obtaining the theoretical change characteristics of the surrounding rock includes: calculating hydrogeological change data based on the seepage water data associated with the snowmelt or precipitation scene; and obtaining the theoretical change characteristics of the surrounding rock based on the hydrogeological change data in combination with the optimized ground stress field simulation.

6. The method for determining the three-dimensional initial geostress field of an underground cavern according to claim 1, wherein: When the error between the actual change characteristics of the surrounding rock and the simulated theoretical change characteristics of the surrounding rock is less than a preset value, the initial ground stress field is determined according to the optimized ground stress field model at this time.

7. A system for determining the three-dimensional initial geostress field of an underground cavern, characterized in that: include: a preliminary geostress field model building module configured to build a preliminary geostress field model based on field data; an inversion module configured to inversely optimize the preliminary geostress field model established so as to reduce the error between the geostress data obtained through model simulation and the actually measured geostress data to within a preset threshold, thereby obtaining an optimized geostress field model; The secondary simulation optimization module is configured to monitor the actual change characteristics of the surrounding rock after the hydrogeological conditions change, compare the theoretical change characteristics of the surrounding rock obtained by simulation based on the optimized geostress field model, optimize the optimized geostress field model, and obtain a determined initial geostress field.

8. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to complete the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that Used to store computer instructions, which, when executed by a processor, complete the steps of the method according to any one of claims 1 to 6.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

Images