A dynamic assessment and early warning method and system for active fault earthquake risk

Abstract

The present application relates to the field of earthquake monitoring and early warning, in particular to a dynamic evaluation and early warning method and system for active fault earthquake risk, which constructs and optimizes an active fault earthquake detection system according to historical information of an active fault monitoring area; a three-dimensional equidistant grid model of the active fault is established, and information collection points in the active fault earthquake detection system are screened according to an error analysis model of the collection points to determine target monitoring points of the system; information of the active fault is monitored through the detection system and the target monitoring points to obtain active fault earthquake monitoring data; the relative displacement of the active fault is predicted based on the monitoring data and the three-dimensional equidistant grid model, and the evaluation and early warning of the active fault earthquake are realized in combination with the relative displacement and the active fault earthquake monitoring data. The present application can monitor the active fault in real time and analyze the movement of the active fault, realize the evaluation and early warning of the active fault earthquake, and accurately predict the possibility and influence range of the earthquake.

Description

Technical Field

[0001] This invention relates to the field of earthquake monitoring and early warning technology, specifically to a method and system for dynamic assessment and early warning of earthquake hazard along active faults. Background Technology

[0002] Active faults are the primary geological structural basis for earthquakes, and their activity is closely related to earthquake occurrence. Accurate monitoring of the state of active faults helps in achieving dynamic assessment of seismic hazard and early warning of earthquake safety. Existing earthquake monitoring methods can detect seismic activity to some extent, but they have many limitations.

[0003] Regarding system construction: Traditional methods, when designing earthquake detection systems, lack analysis of the actual situation of active faults. They simply deploy monitoring equipment without considering the activity patterns and environmental differences of different active faults. This results in the monitoring system being unable to monitor key areas of active faults, ultimately affecting the comprehensiveness and accuracy of the data. Furthermore, traditional methods lack a monitoring point selection mechanism and cannot deploy information collection points based on the characteristics, activity patterns, and error characteristics of active faults. This leads to significant biases in the collected data, failing to reflect the actual situation of active faults and thus affecting the assessment of the overall activity status of active faults.

[0004] In terms of earthquake assessment and early warning: Traditional methods rely solely on comparative analysis based on single data or simple models when conducting earthquake assessment and early warning, failing to comprehensively consider factors such as the structure and geological conditions of active faults. This results in low accuracy and reliability of earthquake prediction results, making it impossible to accurately determine the likelihood of earthquakes occurring and their impact range, and failing to provide a scientific and effective basis for disaster prevention and mitigation decisions. Summary of the Invention

[0005] To address the shortcomings of existing methods and meet the needs of practical applications, this study aims to achieve the scientific and efficient operation of monitoring equipment systems and information collection, obtain more accurate earthquake monitoring data, and analyze earthquake conditions by combining factors such as active fault structure and geological environment. This will improve the accuracy and reliability of earthquake prediction results, provide decision support for disaster prevention and mitigation, and effectively enhance the overall level of earthquake monitoring and early warning. On the one hand, this invention provides a method for dynamic assessment and early warning of active fault earthquake hazard. The method includes the following steps: constructing and optimizing an active fault earthquake detection system based on historical information of the active fault monitoring area; establishing a three-dimensional equidistant grid model of the active fault monitoring area; screening information acquisition points in the active fault earthquake detection system according to the acquisition point error analysis model and the three-dimensional equidistant grid model, and determining target monitoring points in the active fault earthquake detection system; monitoring the active fault monitoring area through the active fault earthquake detection system and the target monitoring points to obtain active fault earthquake monitoring data; predicting the relative displacement of the active fault monitoring area based on the active fault earthquake monitoring data and the three-dimensional equidistant grid model; and combining the relative displacement and the active fault earthquake monitoring data to achieve assessment and early warning of active fault earthquakes.

[0006] This invention improves the accuracy and comprehensiveness of earthquake monitoring information. Based on the structure of active faults and three-dimensional models, it can analyze and predict the structure and movement of active faults at different levels and locations, providing accurate reference for earthquake prediction and safety early warning.

[0007] Optionally, the step of constructing and optimizing the active fault seismic detection system based on historical information of the active fault monitoring area includes: acquiring historical information of the active fault monitoring area; analyzing the earthquake frequency and seismic energy of the active fault monitoring area based on the historical information; and constructing and optimizing the active fault seismic detection system based on the earthquake frequency and seismic energy. The scientifically sound and reasonable monitoring system layout and parameter settings of this invention can reduce system equipment maintenance and update costs, while improving the feasibility and accuracy of system operation.

[0008] Optionally, establishing a three-dimensional equidistant grid model of the active fault monitoring area includes: analyzing the propagation relationship between seismic energy and seismic signal waves based on the historical information; determining the extent information of the active fault monitoring area based on the historical information; and setting the three-dimensional division spacing of the active fault monitoring area with reference to the extent information, the propagation relationship, the seismic frequency, and the seismic energy. This invention can clearly define the boundaries and key areas of the monitoring area, more accurately capture seismic signals, reduce data errors, and improve the accuracy of monitoring data.

[0009] Optionally, establishing a three-dimensional equidistant grid model of the active fault monitoring area includes: introducing a rounding function; determining the number of grid divisions for the active fault monitoring area based on the rounding function and the three-dimensional grid spacing; and constructing a three-dimensional equidistant grid model of the active fault monitoring area based on the number of grid divisions. This invention determines the number of grid divisions based on a rounding function, ensuring that each grid has a clear boundary and number. During seismic monitoring data acquisition, monitoring equipment can be arranged in an orderly manner according to the grid numbers, improving the management efficiency and practicality of active fault information.

[0010] Optionally, the step of screening information acquisition points in the active fault seismic detection system based on the acquisition point error analysis model and the three-dimensional equidistant grid model, and determining the target monitoring points in the active fault seismic detection system, includes: pre-laying out information acquisition points in the active fault seismic detection system based on earthquake frequency, earthquake energy, and the three-dimensional equidistant grid model; establishing an acquisition point positioning error evaluation function; analyzing the positioning error of different information acquisition points using the acquisition point positioning error evaluation function and the historical information, and obtaining the positioning error results for different information acquisition points. This invention, by pre-laying out information acquisition points based on the characteristics and actual conditions of active faults, allows acquisition points to be more rationally distributed in the key areas of active faults.

[0011] Optionally, the step of screening information acquisition points in the active fault seismic detection system based on the acquisition point error analysis model and the three-dimensional equidistant grid model, and determining the target monitoring points in the active fault seismic detection system, includes: setting a positioning error threshold with reference to the historical information and the three-dimensional equidistant grid model; and screening information acquisition points in the active fault seismic detection system based on the positioning error threshold and the positioning error results to determine the target monitoring points in the active fault seismic detection system. This invention, by screening to obtain target monitoring points, can avoid constructing monitoring stations in areas with large positioning errors and poor monitoring effects, thus reducing system maintenance and management costs.

[0012] Optionally, the step of monitoring the active fault monitoring area using the active fault seismic detection system and the target monitoring point to obtain active fault seismic monitoring data includes: monitoring the active fault monitoring area based on the active fault seismic detection system and the target monitoring point to obtain initial monitoring information of the active fault monitoring area; filtering, correcting, and integrating the basic seismic information in the initial monitoring information to obtain optimized basic seismic information; establishing a microseismic information processing function; using the microseismic information processing function to process the microseismic information in the initial monitoring information to obtain processed microseismic information; and integrating the optimized basic seismic information and the processed microseismic information to obtain active fault seismic monitoring data.

[0013] This invention processes and integrates basic seismic information and microseismic information separately, which can comprehensively cover various seismic information in the active fault monitoring area, and can more realistically reflect the seismic activity characteristics and evolution laws of active faults, providing a richer information foundation for earthquake research and safety prediction.

[0014] Optionally, the step of predicting the relative displacement of the active fault monitoring area based on the active fault earthquake monitoring data and the three-dimensional equidistant grid model, and combining the relative displacement and the active fault earthquake monitoring data to realize the assessment and early warning of active fault earthquakes includes: performing multi-layer linear structure analysis on the active fault monitoring area based on the three-dimensional equidistant grid model to obtain the single-layer linear structure of the active fault monitoring area; obtaining the mass information, acceleration and velocity information, and geological parameter information corresponding to the single-layer linear structure based on the active fault earthquake monitoring data; constructing the differential equation of relative displacement motion of the single-layer linear structure according to Newton's second law, the mass information, the acceleration and velocity information, and the geological parameter information; and analyzing the relative displacement motion of the single-layer linear structure through the differential equation of relative displacement motion of the single-layer linear structure.

[0015] This invention performs multi-layer linear structure analysis on active fault monitoring areas, which can decompose complex monitoring areas into multiple single-layer linear structures. It can take into account the geological characteristics and structural differences of different areas in detail, and more accurately simulate the movement of each layer under seismic action, laying the foundation for subsequent seismic hazard assessment.

[0016] Optionally, the step of predicting the relative displacement of the active fault monitoring area based on the active fault earthquake monitoring data and the three-dimensional equidistant grid model, and combining the relative displacement and the active fault earthquake monitoring data to achieve the assessment and early warning of active fault earthquakes includes: constructing a set of active fault motion matrix equations based on the multi-layer linear structure of the active fault monitoring area, the relative displacement motion, and the differential equations of the relative displacement motion of the single-layer linear structure; analyzing the overall displacement of the active fault monitoring area based on the set of active fault motion matrix equations; establishing an active fault resistance expression; analyzing the resistance status of the single-layer linear structure through the active fault resistance expression; analyzing the overall resistance status of the active fault monitoring area based on the multi-layer linear structure and the resistance status; introducing a seismic hazard level assessment standard; obtaining earthquake prediction results for the active fault monitoring area based on the relative displacement motion, the overall displacement, the resistance status, the overall resistance status, and the three-dimensional equidistant grid model; and comparing the earthquake prediction results with the seismic hazard level assessment standard to analyze the seismic hazard level of the active fault monitoring area.

[0017] This invention employs a hierarchical analysis approach, progressing from single-layer linear structures to multi-layer linear structures, and then to the entire active fault monitoring area. This approach clearly reveals the interactions and influences within the active fault's internal structure, facilitating an accurate understanding of the seismic activity characteristics of the active fault and providing an assessment basis for subsequent earthquake assessment and safety early warning.

[0018] Secondly, to efficiently execute the dynamic assessment and early warning method for active fault seismic hazard provided by this invention, this invention also provides a dynamic assessment and early warning system for active fault seismic hazard, including a processor, an input device, an output device, and a memory. The processor, input device, output device, and memory are interconnected. The memory stores a computer program, which includes program instructions. The processor is configured to call the program instructions to execute the dynamic assessment and early warning method for active fault seismic hazard as described in the first aspect of this invention. The dynamic assessment and early warning system for active fault seismic hazard of this invention has a compact structure and stable performance, and can stably execute the dynamic assessment and early warning method for active fault seismic hazard provided by this invention, thereby improving the overall applicability and practical application capability of this invention. Attached Figure Description

[0019] Figure 1 This is a flowchart of the dynamic assessment and early warning method for seismic hazard of active faults according to the present invention; Figure 2 This is a schematic diagram showing the historical earthquake frequency and historical energy percentage of the active faults according to the present invention. Figure 3 This is a structural diagram of the active fault earthquake hazard dynamic assessment and early warning system of the present invention. Detailed Implementation

[0020] See Figure 1 Existing monitoring and assessment methods have limitations in terms of data accuracy, comprehensiveness, and dynamic adaptability, making it difficult to meet the needs of earthquake hazard assessment and early warning in disaster prevention and mitigation. To improve the operational efficiency of the monitoring system and integrate multiple factors such as fault structure characteristics for comprehensive analysis, thereby enhancing the accuracy and reliability of earthquake prediction results, providing a scientific basis for disaster prevention and mitigation, and further strengthening the level of earthquake monitoring and early warning, this invention provides a dynamic assessment and early warning method for earthquake hazard along active faults. The method includes the following steps: S1. Referring to the field of earthquake monitoring and early warning, this embodiment constructs and optimizes an active fault earthquake detection system based on historical information of active fault monitoring areas. This is beneficial for more accurately grasping the patterns of earthquake activity and obtaining accurate active fault monitoring data. The specific implementation details are as follows: First, obtain historical information about the active fault monitoring area.

[0021] In this embodiment, it is necessary to comprehensively and systematically collect all monitoring data of the active fault monitoring area within a specific historical time period. The data sources include seismic monitoring station records, geological exploration reports, satellite remote sensing data, etc., and the data content should include, but is not limited to, key information such as the time, energy magnitude, and spatial location of earthquakes. In a specific embodiment, earthquake occurrence time accurate to the second helps in subsequent analysis of the time series characteristics of seismic activity; energy data can be used to assess the intensity and impact range of earthquakes in the active fault monitoring area; and the spatial location information of the active fault helps to clarify the specific location of earthquakes on the active fault, providing data reference for subsequent earthquake assessment and safety analysis.

[0022] Then, based on historical monitoring information of the active fault monitoring area, the embodiment further understands the frequency and energy proportion of the active fault monitoring area, and constructs and optimizes the active fault seismic detection system on this basis, which is conducive to the accurate monitoring and effective identification of active fault seismic activity.

[0023] I. Analysis of earthquake frequency in active fault monitoring areas In this embodiment, the collected historical monitoring data is analyzed to further analyze the frequency of earthquakes in different time periods. Furthermore, based on historical monitoring information of active faults, the total number of earthquakes is set as... A certain frequency range The number of earthquakes within the range is set to The proportion of earthquake events within this frequency range is set as follows: Earthquake frequency satisfies the following relationship In addition, a diagram illustrating the frequency proportions of earthquakes during the historical data collection period was created based on the statistical results. Please refer to [link / reference needed] for details. Figure 2 (a) It intuitively presents the proportion of earthquake events of different frequency ranges in the total frequency in the active fault monitoring area, which can clearly grasp the distribution characteristics of earthquake frequency, and can further analyze whether there is a concentration of earthquake events of a certain frequency range in the active fault monitoring area.

[0024] II. Analysis of the energy proportion in the active fault monitoring area Similarly, historical monitoring data is analyzed to determine seismic energy over different time periods. The statistical analysis can include calculating the total seismic energy for each month within a given year, or the total seismic energy for each day within a given month. In this example, based on historical monitoring information of active faults, the total seismic energy of the active fault monitoring area is set as... A certain energy range The internal seismic energy is set to The proportion of earthquake energy in this energy range is set as follows: And the proportion of earthquake energy satisfies the following relationship: Furthermore, for a detailed diagram illustrating the energy proportions during historical data collection periods, please refer to [link to relevant documentation]. Figure 2 (b) It intuitively presents the proportion of earthquake events of different energy ranges in the total energy, which helps to quickly understand the distribution characteristics of earthquake energy in the active fault monitoring area, and can also accurately determine whether there are concentrated occurrences of high-energy earthquake events.

[0025] III. Analysis of the frequency and energy proportion of microseismic events in the active fault monitoring area Further analysis is needed to classify and statistically analyze microseismic events in the active fault monitoring area. Based on energy levels, the monitoring area can be divided into two intervals: those with energy above the fifth power and those below the fourth power. Combining this with the above analysis of earthquake frequency and energy proportions, it is clear that microseismic events with energy above the fifth power are very infrequent, accounting for only a small percentage of the total frequency. Microseismic events of the fourth power or lower account for a very high proportion of the total frequency. On the other hand, from the perspective of energy proportion, it can be seen that the energy proportion of powers 5 and above reaches a certain level. Those below the fourth power only account for The above analysis results indicate that stress changes are relatively large during the acquisition of active fault monitoring information. Although high-energy, low-frequency events occur infrequently, they play a significant role in and influence the active fault seismic monitoring data. Therefore, when constructing a seismic detection system, it is necessary to fully consider the important impact of microseismic events on seismic hazard and safety early warning.

[0026] Finally, an active fault seismic detection system was constructed and optimized based on earthquake frequency and energy.

[0027] In constructing an active fault seismic detection system, the seismic detection equipment in this embodiment is selected based on historical monitoring information of active faults, earthquake frequency and energy, and the geological conditions of the active fault location. If the active fault frequently experiences low-frequency, high-energy earthquakes, equipment sensitive to low-frequency signals should be selected. The aforementioned equipment should possess characteristics such as high precision, high sensitivity, and wide bandwidth to further ensure the accuracy of measurement data and reduce errors. It should be able to capture weak seismic signals and cover seismic signals of different frequency ranges to meet the seismic monitoring needs of various types of active faults.

[0028] Further system equipment deployment is then carried out. In this embodiment, seismic detection equipment is deployed primarily based on factors such as the strike, length, and width of the active fault, as well as the surrounding topography. The strike of the active fault is then set to be consistent with... The included angle of the axis is The length of the active fault monitoring area is Width is The system equipment can be determined through calculation. The upward deployment spacing. Furthermore, the monitoring area covered by the equipment can be calculated and analyzed based on factors such as the propagation speed of seismic waves, the area of ​​the monitoring region, and the monitoring range of the equipment, which is beneficial for forming a comprehensive, multi-layered active fault seismic detection system.

[0029] In this embodiment, the active fault seismic detection system needs to be optimized by referring to the frequency and energy ratio of microseismic events in the active fault monitoring area.

[0030] A microseismic monitoring system was synchronously installed in the system, which selected a system with a built-in signal transmission module. The seismic sensor covers a wide frequency band and can effectively capture microseismic signals of different frequencies, especially high-energy microseismic signals. Simultaneously, data is transmitted through an independent data transmission channel to ensure that the microseismic monitoring data is transmitted to the data processing center in a timely and accurate manner, avoiding interference and data loss during transmission. In this embodiment, fiber optic communication is used to ensure the real-time performance and reliability of data transmission.

[0031] The active fault seismic detection system is equipped with a two-way control and transmission function. This function allows for remote monitoring and intelligent adjustment of the operating status of different seismic sensors, enabling real-time monitoring of equipment operation and ensuring consistently good system performance. Furthermore, the system possesses anti-interference capabilities, capable of filtering and denoising various interference signals. The digital filtering technology used in this embodiment can be designed based on the frequency characteristics of seismic signals and interference signals to remove interference, thus improving the quality and accuracy of seismic monitoring data.

[0032] A full-process data management mechanism is established in the active fault seismic detection system. In this embodiment, data caching technology and error retransmission mechanism are adopted in the data transmission stage to ensure that data is not lost or damaged during transmission; in the data processing stage, data is classified, stored and analyzed; a data storage database is established, which can classify and store data according to different times, locations, earthquake types, etc., which is conducive to subsequent data query and comparative analysis, and provides technical support for subsequent earthquake assessment and safety early warning.

[0033] By constructing and optimizing the active fault seismic detection system through the above steps, it is beneficial to achieve real-time and accurate monitoring of active fault seismic activity.

[0034] S2. Establish a three-dimensional equidistant grid model of the active fault monitoring area. Based on the acquisition point error analysis model and the three-dimensional equidistant grid model, screen the information acquisition points in the active fault seismic detection system and determine the target monitoring points in the active fault seismic detection system.

[0035] First, the embodiment establishes a three-dimensional equally spaced grid model of the active fault monitoring area. In the field of active fault monitoring, the grid model helps to accurately understand the seismic activity patterns of different active fault monitoring areas and predict earthquake risks.

[0036] The first step is to analyze the propagation relationship between earthquake energy and seismic signal waves based on historical information.

[0037] In this embodiment, multiple microseismic signals of different energy levels were selected from historical information of the active fault monitoring area and simulated and analyzed in the monitoring area. It was found that when an earthquake occurs, the rock fracturing at the epicenter will generate elastic waves. Among these elastic waves, the P-wave arrives first. Since the vibration direction of the P-wave particles is consistent with the wave propagation direction, similar to the extension and contraction of a spring, these waves can propagate effectively in solids, liquids, and gases, and their propagation speed inside the Earth is relatively fast. Therefore, they become the earliest waves recorded by seismographs in seismic waves.

[0038] Because P-waves propagate at high speeds, they reach the Earth's surface before the more destructive S-waves and surface waves. Based on this characteristic, in this embodiment, P-waves are defined as... Earthquake energy is , The amplitude from the initial wave to the peak wave is Further derivation and analysis determined the earthquake energy of active faults and The propagation relationship of wave amplitude from initial to peak value is given, and satisfies the following relationship: , in, express Wave amplitude from initial to peak value Represents the first fitted parameter. Indicates earthquake energy. Indicates the second fitting parameter. This represents the third fitting parameter. The above relationship is an important foundation for inverting and calculating seismic energy. It can accurately reflect the propagation law of seismic energy in the subsurface medium and provides a key theoretical basis for subsequent model construction and seismic analysis.

[0039] Furthermore, to ensure the effective application of the propagation relation in practical applications, this embodiment introduces a logarithmic form to optimize it, thereby satisfying the following relation: , in, express Wave amplitude from initial to peak value Indicates the reference amplitude. Represents the first fitted parameter. Indicates earthquake energy. Indicates reference energy. Represents the new fitted parameters in logarithmic form.

[0040] Fitting parameters during active fault monitoring The determination and setting are mainly based on large historical data and fitting analysis. In one embodiment, a curve fitting method was used, which finds the best function match of the data by minimizing the sum of squared errors. The above propagation relationship can transform the problem into solving a function that makes the data optimal. smallest Value, of which Indicates the number of data points. and They represent the first Data points Since the relationship between wave initial arrival peak amplitude and seismic energy is nonlinear, in practical applications, parameters can be continuously adjusted using iterative algorithms. The value is used to gradually reduce the error between the fitted curve and the actual data, and finally obtain the optimal parameter estimate.

[0041] The second step is to determine the extent of the active fault monitoring area based on historical information.

[0042] Based on a comprehensive analysis of the actual distribution of active faults and the sensor installation locations, this embodiment defines the monitoring area for active faults. First, based on the actual geographical extent of the monitoring area, the coordinates of the area are clearly defined, specifically represented as follows: , , These respectively represent the monitoring areas of active faults in The minimum and maximum coordinate values ​​in the three directions provide clear boundary conditions for subsequent 3D model construction and mesh generation.

[0043] The third step involves setting the three-dimensional division spacing of the active fault monitoring area based on reference range information, propagation relationships, earthquake frequency, and earthquake energy.

[0044] Based on the established information on the monitoring area of ​​active faults and their propagation relationships, and considering factors such as earthquake frequency and energy, the implementation example rationally sets the three-dimensional spacing of the active fault monitoring area. The specific settings are as follows: directional spacing is , directional spacing is , directional spacing is The determination of the spacing in different directions requires comprehensive consideration of multiple factors. The size of the monitoring area directly affects the choice of spacing. Large-scale monitoring areas require relatively large spacing to reduce the amount of calculation and model complexity. The complexity of seismic activity is also an important reference factor. Areas with frequent and complex seismic activity require more refined spacing to capture seismic information more accurately. In addition, monitoring accuracy is also a key factor in determining the size of the spacing. High-precision monitoring requirements correspond to smaller spacing.

[0045] The fourth step involves introducing a rounding function and determining the number of grid divisions for the active fault monitoring area based on the rounding function and the three-dimensional grid spacing.

[0046] To accurately calculate the number of grid divisions in the active fault monitoring area, this embodiment introduces a floor function, which converts real numbers to integers in mathematical calculations. Based on the floor function and the pre-defined three-dimensional grid spacing, the number of grid divisions in the active fault monitoring area can be quickly determined. The number of grid divisions satisfies the following calculation formula: , in, This indicates the number of grid divisions in the active fault monitoring area. This represents the floor function. This formula allows for the precise calculation of the number of grid divisions in three-dimensional space for the active fault monitoring area. Based on this, the monitoring area is divided into several small cubic grids of the same size, providing crucial quantitative data for the subsequent construction of a three-dimensional equidistant grid model.

[0047] The fifth step is to construct a three-dimensional equidistant grid model of the active fault monitoring area based on the number of grid divisions.

[0048] In one embodiment, based on the calculated number of grid divisions, the entire monitoring area is divided into several small cubic grids of the same size. These small cubic grids are neatly arranged to form a regular three-dimensional grid structure, providing a reference framework for the subsequent layout of data acquisition points. This facilitates the even distribution of data acquisition points within the monitoring area, thereby enabling the comprehensive and accurate acquisition of earthquake-related information. Furthermore, the three-dimensional equidistant grid model provides a basis for error analysis, facilitating the assessment and correction of potential errors during monitoring, further improving the accuracy of earthquake monitoring results.

[0049] Based on the number of grid divisions, a three-dimensional equidistant grid model of the active fault monitoring area is finally constructed. The above model, based on the setting of the number of grid divisions and spacing parameters, transforms the active fault monitoring area into a regular three-dimensional grid structure, providing a reference for subsequent earthquake assessment and analysis as well as earthquake risk prediction. It can more intuitively and accurately analyze the distribution characteristics and propagation patterns of earthquake activity in three-dimensional space.

[0050] Then, based on the acquisition point error analysis model and the three-dimensional equidistant grid model, the information acquisition points in the active fault seismic detection system are screened, and the target monitoring points in the active fault seismic detection system are determined. Accurately selecting information acquisition points in the active fault seismic detection system can improve the accuracy and reliability of seismic monitoring.

[0051] The first step, in order to ensure that relevant earthquake information can be captured comprehensively and accurately, involves pre-laying out information acquisition points in the active fault earthquake detection system based on earthquake frequency, earthquake energy, and a three-dimensional equidistant grid model.

[0052] Based on the characteristics of active faults, analyze the geometric parameters such as strike, dip angle, and displacement of active faults, as well as their dynamic characteristics such as activity rate and activity period. For fault segments with faster activity rates and larger displacements, the density of information collection points can be appropriately increased.

[0053] To further clarify the objectives of earthquake monitoring, information collection points should be optimized and laid out based on different monitoring needs. Among them, the focus should be on monitoring microseismic activity, which requires the extensive deployment of collection points in areas where microseismic activity may occur. If it is necessary to study the propagation law of seismic waves, collection points should be set up reasonably along the propagation path of seismic waves.

[0054] Referring to the three-dimensional equidistant grid model, the active fault monitoring area is divided into several small cubic grids of the same size, providing a framework for the layout of information acquisition points. Data acquisition points are pre-arranged at key grid locations such as grid vertices and centers, which can ensure that the acquisition points are evenly distributed within the monitoring area, thereby fully covering the monitoring area and obtaining more comprehensive and richer seismic information.

[0055] Since existing earthquake data monitoring methods are insufficient to meet the accuracy requirements, and monitoring systems are affected by environmental conditions and equipment operation, analyzing the positioning error of active fault earthquake detection systems helps ensure the accuracy of earthquake source location.

[0056] The second step in this embodiment is to establish a positioning error evaluation function for the collection points, and to analyze the positioning error of different information collection points using the positioning error evaluation function and historical information, and to obtain the positioning error results of different information collection points.

[0057] Based on practical application requirements and analytical perspectives, this embodiment divides the positioning error of data acquisition points into horizontal positioning error and vertical positioning error. The horizontal positioning error is used to analyze the positioning accuracy of active fault earthquakes on the horizontal plane, while the vertical positioning error is used to analyze the positioning accuracy on the vertical plane.

[0058] Simulation experiments were conducted based on a three-dimensional equidistant grid model of the active fault monitoring area. During the experiment, historical data was used to simulate earthquake occurrences at different locations. The data collection results of different data collection points were recorded. By comparing the processed source location with the actual source location, the expected value of the location error could be obtained.

[0059] To quantitatively evaluate the positioning error of different data acquisition points in the system, a positioning error evaluation function for acquisition points was established, which satisfies the following relationship: , in, Indicates the active fault monitoring area The horizontal positioning error result at the point, This represents the total number of repeated experiments. Indicates the active fault monitoring area The new epicenter location is calculated by repeating the calculation. Indicates the active fault monitoring area The location of the point Indicates the active fault monitoring area The vertical positioning error at the point. The above formula allows for the understanding and analysis of the positioning errors of different data acquisition points in both the horizontal and vertical directions.

[0060] The third step is to set the positioning error threshold based on historical information and a 3D equidistant grid model.

[0061] The positioning error threshold is an important basis for screening information collection points. In this embodiment, the positioning error threshold is determined based on a three-dimensional equidistant grid model of the active fault monitoring area, historical monitoring data, and practical experience.

[0062] In this embodiment, the horizontal plane positioning error is generally smaller in the track alignment direction than in the transport alignment direction. Therefore, referring to historical monitoring data can help understand the distribution characteristics and trends of positioning errors in different areas, providing data support for threshold setting. Considering both monitoring requirements and practical application, the maximum positioning error in this embodiment is... Set at Minimum positioning error within the range Set at Within this range, the aforementioned threshold range ensures both monitoring accuracy and practical operability. Since horizontal and vertical errors further affect the spatial positioning accuracy of active faults, it is necessary to control the vertical positioning error based on the monitoring requirements and environmental conditions of the active faults. Specifically, based on the horizontal positioning error threshold setting and actual monitoring needs, the vertical positioning error threshold should be further determined. This ensures that the overall positioning error remains within an acceptable range.

[0063] The fourth step is to screen the information acquisition points in the active fault seismic detection system based on the positioning error threshold and the positioning error results, so as to determine the target monitoring points in the active fault seismic detection system.

[0064] In one embodiment, the horizontal and vertical positioning errors of each pre-laid data acquisition point are checked individually. The positioning error of each acquisition point is compared with a positioning error threshold to determine whether the acquisition point meets the monitoring requirements. If the positioning error of a data acquisition point exceeds the positioning error threshold range, i.e. or (The vertical error threshold is set similarly), then the data collection point is considered to not meet the monitoring requirements and needs to be removed; if the positioning error is within the threshold range, i.e. and The data acquisition point is retained as the system's data acquisition target point. The data acquisition target point finally determined through the above screening process can meet the accuracy requirements of active fault earthquake monitoring, providing a reliable guarantee for accurately obtaining earthquake information.

[0065] The above implementation steps can gradually complete the verification and screening of data acquisition points in the active fault earthquake detection system, which not only helps improve the performance and reliability of the active fault earthquake monitoring system, but also provides strong support for earthquake research and disaster prevention.

[0066] S3. Utilize the active fault seismic detection system and target monitoring points to monitor the active fault monitoring area, thereby obtaining accurate and reliable active fault seismic monitoring data. The specific implementation steps are as follows: The first step is to monitor the active fault monitoring area based on the active fault seismic detection system and target monitoring points to obtain the initial monitoring information of the active fault monitoring area.

[0067] In this embodiment, each grid point is selected sequentially based on a three-dimensional equally spaced grid model. It is assumed that the earthquake occurred at that grid point. Based on seismic wave propagation theory, the propagation characteristics of seismic waves in the subsurface medium are fully considered, such as the difference in propagation speed due to different media and the attenuation law followed by seismic waves during propagation. Using the determined energy and... The propagation relationship between the initial wave amplitude and the peak wave amplitude is used for inversion calculation.

[0068] , in, express Wave amplitude from initial to peak value Represents the first fitted parameter. Indicates earthquake energy. Indicates the second fitting parameter. This represents the third fitting parameter.

[0069] For each grid point in the three-dimensional equidistant grid model, the seismic energy value needs to be continuously adjusted. Based on the aforementioned propagation relationship, the energy value at that energy level is calculated. The amplitude from the initial wave to the peak value, when calculated When the peak amplitude of the first arrival wave reaches the minimum value that the active fault seismic detection system can record, this energy value is the minimum energy value that can trigger the active fault seismic detection system to record an active fault at that point. Simultaneously, the minimum triggering energy value corresponding to each grid point is recorded, ultimately forming a set of minimum triggering energies for each grid point. This set can intuitively reflect the sensitivity of different locations to seismic signals, providing a reference for seismic monitoring data acquisition and safety early warning.

[0070] Next, the active fault seismic detection system collects seismic signal data of the active fault area in real time at each data acquisition target point according to the preset sampling frequency and parameters. The data includes key information such as the waveform, amplitude, and frequency of seismic waves, as well as metadata such as data acquisition time and location, providing basic information for subsequent earthquake assessment and safety analysis.

[0071] Data collected from various data acquisition target points are integrated based on a three-dimensional, equally spaced grid model. For each grid point, seismic signal data related to that grid point are collected from surrounding data acquisition target points. This data is then stored and managed according to the overall data structure to form the initial seismic monitoring dataset for active faults. ,in Indicates the first The data sample contains various characteristic information of the seismic signal and the corresponding grid point location information.

[0072] The second step involves screening, correcting, and integrating the basic seismic information from the initial monitoring data to obtain optimized basic seismic information.

[0073] In one embodiment, basic earthquake information in the initial earthquake monitoring dataset is screened to check whether the amplitude value of each data point exceeds a reasonable range, ensuring the accuracy and reliability of the data. Various influencing factors during seismic wave propagation are fully considered, such as the impact of topography on the propagation speed and attenuation of seismic waves, thereby correcting the propagation path and propagation time of seismic waves. This improves the accuracy of the data and makes it more consistent with reality. Based on earthquake characteristics such as magnitude, focal depth, and epicenter location, the corrected data is classified, integrating data belonging to the same earthquake monitoring point to form a complete earthquake event data record. Simultaneously, corresponding identification information, such as earthquake event number and occurrence time, is added to each earthquake monitoring point to facilitate subsequent data analysis and processing, improving the system's data management efficiency.

[0074] The third step is to establish a microseismic information processing function and use the microseismic information processing function to process the microseismic information in the initial monitoring information to obtain the processed microseismic information.

[0075] Based on utilization The microseismic location principle, which locates the initial arrival of the wave, determines the triggering conditions for the microseismic signal. In this embodiment, the microseismic monitoring system can only be triggered if the peak amplitude of the initial arrival received by at least four sensors is greater than or equal to three times the ambient background noise. Each data sample in the initial earthquake monitoring data set is judged one by one, and microseismic signal data that meets the triggering conditions are selected to ensure that the microseismic signals processed subsequently have high reliability.

[0076] Using microseismic signals acquired by sensors, and based on the fundamental principles of seismic wave energy propagation and attenuation, the following analytical formulas are derived, assuming that seismic waves propagate in a homogeneous medium and follow the laws of energy conservation and attenuation: , in, express Wave amplitude from initial to peak value Represents the composite constant. This indicates the microseismic energy of an active fault. This indicates the distance from the microseismic source of the active fault to the system's sensors. This represents the signal attenuation coefficient. The aforementioned composite constant incorporates factors related to sensor characteristics, medium characteristics, etc.; the signal attenuation coefficient reflects the attenuation characteristics of seismic waves propagating in the medium.

[0077] Due to the energy of seismic waves With amplitude (as mentioned above) Wave amplitude from first peak The amplitude is directly proportional to the square of the quantity related to it (represented by energy), as can be seen from the fundamental physical relationship between energy and amplitude. ,Right now ,in, This represents constants related to the medium, sensor, etc. The term is a compensation term that takes into account the energy attenuation and exponential decay during propagation. Because the energy is more dispersed and attenuation is greater with greater distance, the above equation is further transformed and solved. We can obtain: , At the same time You can then obtain: , In calculating the source locations and source energies of multiple microseismic signals at different energy levels within an active fault, the source location is determined using known sensor locations and microseismic signal arrival times, employing microseismic location algorithms such as geometric and linear positioning methods. The distance from the source to the sensor can then be calculated based on the source and sensor locations. Furthermore, the multiple energy levels of the microseismic signals are calculated using the nonlinear least squares method. Based on the data, the comprehensive constant can be determined. and signal attenuation coefficient .

[0078] In this embodiment, the microseismic signal data is further processed. Based on the propagation relationship, the energy of the microseismic signal is estimated and corrected more accurately, which can improve the accuracy of microseismic energy calculation. At the same time, combined with a three-dimensional equidistant grid model, the microseismic signal data is correlated with the corresponding grid points to analyze the distribution characteristics and variation patterns of microseismic activity in different grid regions, providing information support for understanding the microseismic activity of active faults.

[0079] The fourth step involves integrating and optimizing the basic seismic information and the processed microseismic information to obtain active fault seismic monitoring data. In one embodiment, integrating the optimized basic seismic information and the processed microseismic information yields a complete and accurate active fault seismic monitoring dataset. This dataset covers various types of seismic information in the active fault monitoring area, providing data support for subsequent seismic analysis, fault activity research, and disaster early warning, and helping to more scientifically and accurately assess the seismic risk of active faults.

[0080] S4. Based on active fault earthquake monitoring data and a three-dimensional equidistant grid model, predict the relative displacement of the active fault monitoring area. Combine the relative displacement data with the active fault earthquake monitoring data to achieve assessment and early warning of active fault earthquakes. The specific implementation details are as follows: In the field of earthquake assessment, accurately predicting the relative displacement of active fault monitoring areas is of great significance for earthquake hazard assessment and seismic design of engineering projects. In this embodiment, the relative displacement of active fault monitoring areas is first predicted based on active fault seismic monitoring data and a three-dimensional equidistant grid model.

[0081] The first step is to perform multi-layer linear structure analysis on the active fault monitoring area based on a three-dimensional equidistant grid model in order to obtain the single-layer linear structure of the active fault monitoring area.

[0082] The aforementioned three-dimensional equidistant grid model provides a basic framework for structural analysis of the active fault monitoring area. Based on the implementation details, the model features a uniform grid spacing, dividing the active fault monitoring area in three-dimensional space. Vertically, the area is divided into multiple levels; horizontally, each level is further subdivided into smaller grids.

[0083] The above-described classification method allows for a comprehensive and in-depth understanding of the structural characteristics of active fault monitoring areas. On one hand, it clearly identifies the geological material composition of each layer, which contains different types of rocks, soils, and other geological materials. Differences in the physical and mechanical properties of these materials significantly impact seismic response. On the other hand, it accurately grasps the spatial distribution of different layers, such as the vertical thickness variations, where different thicknesses at different locations reflect the complexity of the geological structure; and the horizontal extension, as understanding the extension of fault zones in different directions helps determine the extent of earthquake impact. Furthermore, it allows for analysis of the connections between different layers, such as the continuity of faults between different layers. Some faults may penetrate multiple layers, while others may only exist in certain layers. The interaction mechanisms between different structural layers influence each other during earthquakes, altering seismic wave propagation and structural response.

[0084] Based on the above analysis, a complete multi-layered linear structure of the active fault monitoring area was finally obtained. In the embodiment, the active fault monitoring area comprises a total of... The aforementioned structural model will provide an accurate geometric and mechanical model for subsequent earthquake analysis and safety early warning, further ensuring an accurate grasp and targeted analysis of the structural characteristics of active faults.

[0085] The second step involves obtaining mass information, acceleration and velocity information, and geological parameter information for a single-layer linear structure based on active fault seismic monitoring data.

[0086] Analyzing and processing seismic monitoring data of active faults can yield multifaceted information corresponding to single-layer linear structures. When a monitoring area of ​​an active fault with a multi-layer linear structure is subjected to horizontal seismic action, a third... The mass of the layer is The acceleration response is The speed response is The displacement response is The damping coefficient is The lateral stiffness matrix elements are: The first unit of ground displacement caused by the application The static displacement vector of the layer is ; Horizontal seismic excitation acceleration is The above parameters are key information for analyzing the seismic response of a single-story linear structure.

[0087] The third step involves constructing the differential equations of relative displacement motion for a single-layer linear structure based on Newton's second law, the mass information, acceleration and velocity information, and geological parameters.

[0088] In this embodiment, a force analysis is performed on a single-layer linear structure in the active fault monitoring area. According to Newton's second law, the inertial force acting on an object is opposite in direction to the acceleration and its magnitude is equal to the mass multiplied by the acceleration. Therefore, the first... The inertial force on the layer is The damping force is opposite in direction to the velocity, and its magnitude is proportional to the damping coefficient and the velocity. Therefore, the first... The damping force on the layer is The elastic restoring force is opposite in direction to the displacement, and its magnitude is determined by the lateral stiffness and displacement. Therefore, the first... The elastic restoring force on the layer is The equivalent load caused by ground motion will result in an additional equivalent load on the structure, the magnitude of which is... .

[0089] Furthermore, based on the force balance relationship, the differential equation for the relative displacement motion of a single-layer linear structure in the active fault monitoring area is as follows: , in, This indicates the quality of a single-layer linear structure within the active fault monitoring area. This represents the acceleration response of a single-layer linear structure within the active fault monitoring area. This indicates the damping of a single-layer linear structure within the active fault monitoring area. This indicates the velocity response of a single-layer linear structure within the active fault monitoring area. This represents the lateral stiffness matrix of a single-layer linear structure within the active fault monitoring area. This represents the displacement response of a single-layer linear structure within the active fault monitoring area. This represents the static displacement vector caused by a unit ground displacement. This represents the horizontal seismic excitation acceleration of a single-layer linear structure in the active fault monitoring area. The equation is logically sound and fully considers the inertial force, damping force, elastic restoring force, and equivalent load caused by ground motion experienced by the object under seismic action, conforming to the principle of Newton's second law that the net force on an object is equal to its mass multiplied by its acceleration.

[0090] The fourth step involves analyzing the relative displacement motion of a single-story linear structure using the differential equation of its relative displacement motion. In one embodiment, the constructed differential equation of relative displacement motion of the single-story linear structure can be solved numerically to obtain the acceleration, velocity, and displacement responses of the single-story linear structure at different times. Analyzing this response data reveals the motion characteristics of the single-story linear structure under seismic loading, such as the maximum displacement value and its trend, providing a foundation for further analysis of the overall displacement of multi-story linear structures.

[0091] The fifth step is to construct a set of motion matrix equations for the active fault based on the multi-layer linear structure, relative displacement motion, and differential equations of relative displacement motion of the single-layer linear structure in the active fault monitoring area.

[0092] In one embodiment, the relative displacement motion analysis results of a single-layer linear structure can be integrated to obtain the relative displacement situation in the active fault monitoring area, that is, the relative displacement motion matrix equation of a multi-layer linear structure can be constructed.

[0093] The quality matrix is This represents the quality matrix of the active fault monitoring area, which is related to the quality of each layer. Since the active fault monitoring area comprises a total of... Layers, therefore the quality matrix It is A diagonal matrix that satisfies the following relationship: , in, This represents the quality matrix of the active fault monitoring area. Indicates the first The quality of the layer.

[0094] Damping matrix The elements in the table reflect the damping characteristics of each layer. In this embodiment, Rayleigh damping is used, which satisfies the following relationship: , in, This represents the damping matrix of the active fault monitoring area. The damping coefficient is... This represents the quality matrix of the active fault monitoring area. For another damping coefficient, This represents the lateral stiffness matrix of the active fault monitoring area.

[0095] For the interlaminar shear model, the lateral stiffness matrix The following relationship must be satisfied: , The embodiment is set , , These are the acceleration response vector, velocity response vector, and displacement response vector, respectively, and they satisfy the following relationships: Acceleration response vector ; Velocity response vector ; Displacement response vector ; Due to the static displacement vector matrix for The dimensionless matrix, horizontal seismic excitation acceleration It is a scalar vector, and has the following form: Based on the above matrix and multi-layer linear structure, the motion matrix equations of the active fault in this embodiment satisfy the following relationship: , The sixth step involves analyzing the overall displacement of the active fault monitoring area based on the equations of the active fault motion matrix. In one embodiment, the equations are solved numerically to obtain the overall acceleration, velocity, and displacement responses of the active fault monitoring area at different times. Analyzing these response data provides a comprehensive understanding of the overall displacement of the active fault monitoring area under seismic loading, including but not limited to the spatial distribution characteristics of displacement, the location and time of the maximum displacement, etc. This information is of significant guiding importance for assessing earthquake disaster risk and developing earthquake mitigation measures.

[0096] In summary, the above implementation steps can accurately predict the relative displacement of the active fault monitoring area, further providing analytical basis and reference information for earthquake prediction and safety early warning.

[0097] Then, the resistance status of the active fault monitoring area was analyzed based on active fault seismic monitoring data and a three-dimensional equidistant grid model.

[0098] The first step is to establish the expression for the resistance of active faults.

[0099] The mechanical properties of active fault monitoring areas exhibit unique complexity when subjected to cyclic loading such as earthquakes. Specifically, the stiffness of the material differs significantly from its initial stiffness during unloading and reloading, resulting in a clear path dependence in the resistance of the active fault monitoring area. Therefore, in practical applications, the magnitude of the resistance of the active fault monitoring area cannot be directly determined based solely on the initial lateral stiffness. To accurately describe the resistance of the active fault monitoring area, this embodiment establishes a resistance analysis formula for a single-layer linear structure within the active fault monitoring area, satisfying the following relationship: , in, This indicates the resistance of a single-layer linear structure in the active fault monitoring area. This represents the functional relationship between resistance, displacement, and velocity in a single-layer linear structure. This represents the displacement response of a single-layer linear structure within the active fault monitoring area. This indicates the velocity response of a single-layer linear structure within the active fault monitoring area.

[0100] The resistance of a single-layer linear structure in an active fault monitoring area reflects the structure's ability to resist deformation and failure under seismic loading; functional relationship It can be determined comprehensively through experimental data, theoretical analysis, and actual monitoring data to accurately reflect the law of resistance changing with displacement and velocity; the displacement response of a single-layer linear structure in the active fault monitoring area describes the displacement changes of the structure under seismic action; the velocity response of a single-layer linear structure in the active fault monitoring area reflects the dynamic change characteristics of the velocity of the structure during the earthquake.

[0101] The second step is to analyze the resistance status of a single-layer linear structure using the expression for resistance to active faults.

[0102] Obtaining the expression for the resistance of active faults Then, by substituting the displacement response data and velocity response data obtained from actual monitoring into the expression, the resistance values ​​of a single-story linear structure under different seismic actions at different times can be calculated.

[0103] Analyzing the resistance values ​​can reveal the resistance variation patterns of a single-story linear structure during an earthquake. In one embodiment, analyzing the resistance-time curve helps determine whether the resistance peaks or troughs at a certain stage of the earthquake, and the reasons for these peaks and troughs. Further research into the quantitative relationship between resistance, displacement, and velocity can determine under what displacement or velocity conditions the structure's resistance reaches its maximum or minimum. Comparing the resistance changes of a single-story linear structure under different earthquake events allows for the assessment of differences in the structure's resistance performance under different earthquake intensities and frequencies. The results of these analyses contribute to a deeper understanding of the mechanical behavior of a single-story linear structure under earthquake loading, providing a foundation for subsequent assessments of the resistance status of the entire active fault monitoring area.

[0104] The third step is to analyze the overall resistance of the active fault monitoring area based on the multi-layered linear structure and resistance status. In this embodiment, the active fault monitoring area consists of a multi-layered linear structure. To comprehensively evaluate the overall resistance of this monitoring area, it is necessary to consider the resistance status of each layer. Furthermore, by combining the resistance expressions of each layer, the overall resistance expression of the multi-layered linear structure in the active fault monitoring area can be obtained, satisfying the following relationship: , in, This indicates the number of linear structures in the active fault monitoring area. The expression, presented in matrix form, clearly shows the relationship between the resistance of each structural layer and its displacement and velocity response, providing a basis for further analysis of the overall resistance.

[0105] In analyzing the displacement motion of active faults, the existing analytical equations do not consider the influence of resistance. To more accurately predict the displacement motion of active faults under seismic loading, this embodiment introduces the aforementioned resistance term into the active fault displacement motion analysis equation. For the active fault displacement motion analysis equation, considering the influence of resistance, the relative displacement motion prediction function of the multi-layer linear structure can be further expressed as: By solving the displacement motion prediction function after introducing the resistance term, the relative displacement motion of the active fault monitoring area under earthquake action can be obtained. Furthermore, in one embodiment, the prediction results are verified and corrected by combining actual monitoring data to verify the accuracy and feasibility of the prediction results. This is conducive to accurately assessing the safety of the active fault monitoring area under earthquake action and provides a scientific basis for earthquake disaster prevention and planning and management of the active fault monitoring area.

[0106] After completing the analysis of displacement movement and resistance status in the active fault monitoring area, it is necessary to introduce a scientific and comprehensive seismic hazard assessment standard as an important basis for measuring the seismic hazard level of active faults.

[0107] In this embodiment, the seismic hazard assessment standard is formulated by comprehensively considering multiple factors, which can accurately define different seismic hazard levels. These factors include historical seismic activity, geological structural features, fault activity, seismic wave propagation characteristics, and the seismic resistance of buildings and infrastructure. For the seismic activity history, the frequency of earthquakes of different magnitudes occurring in the region within a certain period of time needs to be considered. In terms of geological structure, parameters such as fault strike, dip angle, and slip rate are analyzed. The seismic resistance of buildings is assessed based on relevant seismic design codes, evaluating their potential damage under different seismic actions. By comprehensively considering relevant factors, the seismic hazard level is divided into several levels. In this embodiment, four levels are mainly included: low hazard, medium hazard, high hazard, and extremely high hazard, and specific quantitative indicators and characteristic descriptions are specified for each level.

[0108] Subsequently, based on the relative displacement, overall displacement, resistance status, and overall resistance status, as well as the three-dimensional equidistant grid model, the earthquake prediction results for the active fault monitoring area are obtained.

[0109] In one embodiment, solving the displacement motion analysis equation of the active fault allows for the acquisition of the relative displacement motion of the monitored area under seismic loading, including the displacement, velocity, and acceleration responses of single-story structures. Simultaneously, combining this with a three-dimensional equidistant grid model enables further analysis of the overall displacement, revealing the propagation and distribution characteristics of seismic waves within the monitored area. Furthermore, based on the resistance expression and the overall resistance expression, the resistance status and overall resistance of the monitored area under different seismic loading can be assessed, including the resistance variation patterns and peak resistance values ​​of single-story structures and the entire region. Combining the above information yields comprehensive and detailed earthquake prediction results, including but not limited to the time range, magnitude range, impact range, and potential damage extent of the earthquake.

[0110] Finally, the earthquake prediction results are compared with the earthquake hazard assessment criteria to analyze the earthquake hazard level of the active fault monitoring area.

[0111] Based on the above earthquake prediction results, the monitoring area of ​​active faults will be further assessed. During the assessment process, multiple key factors need to be considered to ensure the accuracy and reliability of the assessment results.

[0112] In one embodiment, the maximum displacement is one of the important indicators for measuring the degree of damage to active faults caused by earthquakes. By analyzing the maximum displacement values ​​of each single-story structure in the earthquake prediction results and combining them with the allowable displacement values ​​of active faults, the safety of active fault structures under earthquake action can be assessed. If the maximum displacement exceeds the design allowable value, it indicates that the active fault structure will suffer serious damage.

[0113] In one embodiment, the maximum acceleration reflects the magnitude of the impact force of seismic waves on the active fault structure. A higher maximum acceleration will cause the active fault structure to generate a larger inertial force, thereby causing vibration and deformation of the active fault. By comparing the predicted maximum acceleration with the seismic design acceleration of the structure with relevant specifications and standards, it can be determined whether the active fault and related structures can withstand the above-mentioned acceleration.

[0114] In one embodiment, the damage level of the active fault structure can be assessed by combining the resistance status of the active fault and the overall resistance status, as well as the displacement and acceleration response under seismic action. Quantitative indicators such as the damage index can be used to describe the damage state of the active fault, and the damage state can be divided into four levels: minor damage, moderate damage, severe damage, and collapse.

[0115] According to the earthquake classification standard, the above analysis results are compared with the classification standard one by one. In the example, the full classification standard will clearly define the range of indicators such as maximum displacement, maximum acceleration and structural damage degree corresponding to different safety levels. Through comparative analysis, the earthquake safety level of the active fault monitoring area can be determined, and it can be further divided into four levels: safe, basically safe, relatively dangerous and dangerous.

[0116] Finally, the earthquake prediction results of the active fault monitoring area are compared and analyzed with the seismic hazard assessment standards. This allows for a comprehensive analysis from multiple dimensions, including the probability of earthquake occurrence, the potential degree of damage, and the scope of impact. In one embodiment, if the earthquake prediction results indicate a high probability of a high-magnitude earthquake occurring in the active fault monitoring area in the near future, and the predicted maximum displacement, maximum acceleration, and other indicators exceed the standard values ​​corresponding to a higher hazard level, while the structural damage assessment also indicates the possibility of large-scale severe damage, then the seismic hazard level of the active fault monitoring area can be determined to be high. Conversely, if the probability of an earthquake occurring in the active fault monitoring area is low, and all indicators are within the low-hazard level range, then the seismic hazard level of the active fault monitoring area can be determined to be low.

[0117] The above analysis and comparison can ultimately yield the seismic hazard assessment results for the active fault monitoring area. These results will provide a scientific basis for earthquake disaster prevention and mitigation planning, seismic design, and emergency response plan formulation in the active fault monitoring area, and will help to effectively reduce the impact and damage of earthquake disasters on active faults.

[0118] Please see Figure 3 In an optional embodiment, to efficiently execute the dynamic assessment and early warning method for active fault seismic hazard provided by this invention, this invention also provides a dynamic assessment and early warning system for active fault seismic hazard. In this system, input devices, a processor, an output device, and a memory are interconnected. The memory stores a computer program, which includes program instructions. The processor is configured to call the program instructions and execute the specific steps of the relevant embodiments of the dynamic assessment and early warning method for active fault seismic hazard provided by this invention. The dynamic assessment and early warning system for active fault seismic hazard of this invention has a complete and stable structure, and can efficiently execute the dynamic assessment and early warning method for active fault seismic hazard of this invention, improving the overall applicability and practical application capability of this invention.

[0119] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the present invention.

Claims

1. A method for dynamic assessment and early warning of seismic hazard along active faults, characterized in that, Includes the following steps: Based on historical information of active fault monitoring areas, an active fault seismic detection system was constructed and optimized. A three-dimensional equidistant grid model of the active fault monitoring area is established. Based on the acquisition point error analysis model and the three-dimensional equidistant grid model, information acquisition points in the active fault seismic detection system are screened, and target monitoring points in the active fault seismic detection system are determined, including: Information acquisition points in the active fault seismic detection system are pre-arranged based on earthquake frequency, earthquake energy, and the three-dimensional equidistant grid model. Establish a function to evaluate the location error of the data collection point; The positioning error of different information acquisition points is analyzed using the acquisition point positioning error evaluation function and the historical information, and the positioning error results of different information acquisition points are obtained. The positioning error of different information acquisition points includes horizontal positioning error and vertical positioning error. The horizontal positioning error is analyzed to determine the positioning accuracy of active fault earthquakes on the horizontal plane, and the vertical positioning error is analyzed to determine the positioning accuracy on the vertical plane. Information monitoring of the active fault monitoring area is carried out through the active fault earthquake detection system and the target monitoring point to obtain active fault earthquake monitoring data; Based on the active fault earthquake monitoring data and the three-dimensional equidistant grid model, the relative displacement of the active fault monitoring area is predicted, and the assessment and early warning of active fault earthquakes are realized by combining the relative displacement data and the active fault earthquake monitoring data. The prediction of the relative displacement of the active fault monitoring area based on the active fault seismic monitoring data and the three-dimensional equidistant grid model includes: Based on the aforementioned three-dimensional equidistant grid model, a multi-layer linear structure analysis is performed on the active fault monitoring area to obtain the single-layer linear structure of the active fault monitoring area; Based on the active fault earthquake monitoring data, the mass information, acceleration and velocity information, and geological parameter information of the single-layer linear structure are obtained. Based on Newton's second law, the mass information, the acceleration and velocity information, and the geological parameter information, a differential equation for the relative displacement motion of a single-layer linear structure is constructed. The relative displacement motion of the single-layer linear structure is analyzed using the differential equation of relative displacement motion.

2. The method for dynamic assessment and early warning of seismic hazard of active faults according to claim 1, characterized in that, The construction and optimization of the active fault seismic detection system based on historical information of the active fault monitoring area includes: Obtain historical information on the active fault monitoring area; Based on the historical information, analyze the earthquake frequency and earthquake energy in the active fault monitoring area; An active fault seismic detection system was constructed and optimized based on the earthquake frequency and energy.

3. The method for dynamic assessment and early warning of seismic hazard of active faults according to claim 2, characterized in that, The establishment of a three-dimensional equidistant grid model for the active fault monitoring area includes: Based on the historical information, the propagation relationship between earthquake energy and earthquake signal waves is analyzed; The extent of the active fault monitoring area is determined based on the historical information. The three-dimensional division spacing of the active fault monitoring area is set with reference to the range information, the propagation relationship, the earthquake frequency, and the earthquake energy.

4. The method for dynamic assessment and early warning of seismic hazard of active faults according to claim 3, characterized in that, The establishment of a three-dimensional equidistant grid model for the active fault monitoring area includes: Introduce the floor function; The number of grid divisions for the active fault monitoring area is determined based on the rounding function and the three-dimensional division interval. A three-dimensional equidistant grid model of the active fault monitoring area is constructed based on the number of grid divisions.

5. The method for dynamic assessment and early warning of seismic hazard of active faults according to claim 1, characterized in that, The process of screening information acquisition points in the active fault seismic detection system based on the acquisition point error analysis model and the three-dimensional equidistant grid model, and determining the target monitoring points in the active fault seismic detection system, includes: The positioning error threshold is set with reference to the historical information and the three-dimensional equidistant grid model; The information acquisition points in the active fault earthquake detection system are screened based on the positioning error threshold and the positioning error results to determine the target monitoring points in the active fault earthquake detection system.

6. The method for dynamic assessment and early warning of seismic hazard of active faults according to claim 1, characterized in that, The process of monitoring the active fault monitoring area using the active fault seismic detection system and the target monitoring point to obtain active fault seismic monitoring data includes: Based on the active fault seismic detection system and the target monitoring point, information monitoring is carried out in the active fault monitoring area to obtain the initial monitoring information of the active fault monitoring area; The basic seismic information in the initial monitoring information is screened, corrected, and integrated to obtain optimized basic seismic information; Establish a microseismic information processing function; The microseismic information in the initial monitoring information is processed using the microseismic information processing function to obtain the processed microseismic information; The optimized basic seismic information and the processed microseismic information are integrated to obtain active fault seismic monitoring data.

7. The method for dynamic assessment and early warning of seismic hazard of active faults according to claim 1, characterized in that, The method of predicting the relative displacement of the active fault monitoring area based on the active fault earthquake monitoring data and the three-dimensional equidistant grid model, and combining the relative displacement data with the active fault earthquake monitoring data to achieve the assessment and early warning of active fault earthquakes includes: Based on the multi-layer linear structure of the active fault monitoring area, the relative displacement motion, and the differential equation of the relative displacement motion of the single-layer linear structure, a set of motion matrix equations for the active fault is constructed. The overall displacement of the active fault monitoring area is analyzed based on the motion matrix equations of the active fault. Establish the expression for the resistance of active faults; The resistance status of a single-layer linear structure is analyzed using the active fault resistance expression. The overall resistance of the active fault monitoring area is analyzed based on the described multi-layer linear structure and the described resistance status. Introduce earthquake hazard level assessment standards; Based on the relative displacement, overall displacement, resistance status, and overall resistance status, as well as the three-dimensional equidistant grid model, earthquake prediction results for the active fault monitoring area are obtained. The earthquake prediction results are compared with the earthquake hazard assessment criteria to analyze the earthquake hazard level of the active fault monitoring area.

8. A dynamic assessment and early warning system for seismic hazard of active faults, characterized in that, The system includes a processor, an input device, an output device, and a memory, which are interconnected. The memory stores a computer program, which includes program instructions. The processor is configured to invoke the program instructions to execute the dynamic assessment and early warning method for seismic hazard of active faults as described in any one of claims 1-7.

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