Geological disaster data analysis method and device based on finite element method and wave equation

Abstract

The invention discloses a geological disaster data analysis method and device based on a finite element method and a wave equation. The method comprises the following steps: arranging acquisition equipment in a monitoring area to acquire seismic data and geological environment data of a geological disaster monitoring area; setting an inversion equation comprising a data equation and a target equation based on the wave equation; the inversion equation is solved through alternate iteration, and medium attributes and an overall wave field are recovered; deducing the seismic data according to a finite element method and the wave equation to obtain a medium elastic parameter, a longitudinal wave velocity, a transverse wave velocity, a density and a background value thereof; and inputting the processed seismic data and the geological environment data into the inversion equation for inversion to obtain the geological disaster type, scale and position of the geological disaster monitoring area. According to the method, the wave equation is combined with the finite element method, so that complex geological structures and boundary conditions can be processed, and geological disasters can be simulated and analyzed more accurately.

Description

Technical Field

[0001] The present invention relates to the technical field of geological disaster data analysis, and in particular to a geological disaster data analysis method and device, and computing equipment based on a finite element method and a wave equation. Background Art

[0002] Geological disasters (such as landslides, mud-rock flows, etc.) pose a huge threat and loss to human society. By analyzing the development and influencing factors of different types of geological disasters, targeted monitoring equipment can be deployed on site for real-time monitoring to analyze abnormal deformations such as tilt and vibration of the disaster body. However, in many cases, monitoring equipment is interfered by environmental factors such as satellite signals, which can easily lead to false alarms and missed alarms, wasting manpower and material resources and causing adverse effects.

[0003] Existing geological monitoring methods mainly rely on geological surveys, geological mapping and manual monitoring to analyze geological disasters by observing changes in geological phenomena, but this is often time-consuming and labor-intensive, and it is difficult to capture small changes in geological disasters. Alternatively, the possibility of geological disasters can be inferred by analyzing seismic waveform data to obtain the structure and physical properties of the crust, but professional seismic equipment is required and the cost is high. Although some monitoring methods analyze the dynamic changes of the geological environment by monitoring geological environmental data (such as precipitation, surface displacement, soil moisture content, etc.), it is difficult to form a unified analysis model because the address environmental data are usually scattered. Existing geological monitoring methods often only focus on a single data source (such as seismic data or geological environmental data), while ignoring the correlation and complementarity between different data sources, resulting in incomplete data analysis results and difficulty in accurately reflecting the true situation of geological disasters. Although some geological disaster analysis methods (such as geophysical exploration methods) can provide relatively accurate results, the model is highly complex and the calculation is large, requiring professional equipment and talent support.

[0004] To solve the above problems, the present invention proposes a geological disaster data analysis method based on the finite element method and the wave equation. By combining the wave equation with the finite element method, it is able to handle complex geological structures and boundary conditions, thereby more accurately simulating and analyzing geological disasters. Summary of the invention

[0005] In view of the above problems, the present invention provides a geological disaster data analysis method and device, and computing equipment based on the finite element method and wave equation.

[0006] According to one aspect of the present invention, a method for analyzing geological hazard data based on finite element method and wave equation is provided, comprising: Deploy collection equipment in the monitoring area to collect seismic data and geological environment data in the geological disaster monitoring area, wherein the collection equipment includes a rain gauge, a displacement meter, a soil moisture meter, a meteorological monitoring station, a surface inclinometer, a vibration sensor, an anchor meter and a seismograph; An inversion equation including a data equation and a target equation is set based on the wave equation; the medium properties and the overall wave field are restored by solving the inversion equation through alternating iterations; wherein the inversion parameters of the inversion equation are the compressibility coefficient, shear compliance and density contrast in the wave equation; Derivation of the seismic data according to the finite element method and the wave equation to obtain medium elastic parameters, longitudinal wave velocity, shear wave velocity, density and background values ​​thereof; The processed seismic data and the geological environment data are input into the inversion equation for inversion to obtain the type, scale and location of the geological disasters in the geological disaster monitoring area.

[0007] In an optional manner, the seismic data includes seismic waveform data, ground vibration acceleration, vibration frequency and vibration direction; The geological environment data include precipitation, surface displacement, displacement direction, soil water content, soil humidity, soil temperature, air temperature, air relative humidity, surface inclination angle, anchor stress, anchor strain and anchor elongation.

[0008] In an optional manner, the expression of the data equation is: , in, is the observed seismic wave field; is the theoretical wave field calculated by the wave equation; is the observation error; are the inhomogeneity coefficient and anisotropy coefficient of the medium respectively; , is the elastic modulus at the ith discrete point, for The average value of , is the shear modulus at the ith discrete point, for The average value of is the number of discrete points; For space; For time.

[0009] In an optional manner, the expression of the objective equation is: , in, is the inversion parameter vector, , is the compression factor, is the shear flexibility, is the density contrast; , , are weight factors, which are used to balance the contributions among field value, gradient value and Laplace value; is the integration area; , are the gradient operator and the Laplace operator respectively.

[0010] In an optional manner, the wave equation is expressed as: , in, is the damping coefficient, , is the longitudinal wave velocity at the ith discrete point, is the average value of the longitudinal wave velocity, is the number of discrete points; is the square of the wave speed; is the result of Laplace operator acting on seismic wave field u; is the external force source term, which is related to the geological environment data. , is the strength of the jth force source, is the location of the force source, is the Dirac function, is the number of force sources.

[0011] In an optional manner, the derivation of the seismic data according to the finite element method and the wave equation to obtain medium elastic parameters, longitudinal wave velocity, shear wave velocity, density and background values ​​thereof further comprises: Divide the monitoring area into multiple triangular finite elements, and the vertices of each finite element include the degrees of freedom in the x, y, and z directions; The displacement distribution within each finite element is described by a polynomial shape function, and the elastic modulus, Poisson's ratio, and density are specified for each finite element; Solving the wave equation according to an implicit time integration method to obtain the node displacement at each time step; The elastic parameters of the medium, the longitudinal wave velocity, the shear wave velocity, the density and the background values ​​thereof are derived according to the node displacement.

[0012] In an optional manner, the expression of the implicit time integral is: , in, is the mass matrix, , is the density, and is the shape function, is the integration area; is the damping matrix; is the stiffness matrix, , It is a double point product; is the node displacement at the n+1th time step; is the node displacement at the nth time step; is the time step; is the external force vector at the n+1th time step.

[0013] In an optional manner, the inversion parameters of the inversion equation are: , in, As input parameters, it includes seismic data and geological environment data; is the weight coefficient; m is the number of parameters; It is the type of geological disaster; is the scale of geological disasters; For the location of geological hazards; Factors that affect the types of geological disasters.

[0014] According to another aspect of the present invention, there is provided a geological disaster data analysis device based on finite element method and wave equation, comprising: A data acquisition module is used to deploy acquisition equipment in the monitoring area to collect seismic data and geological environment data in the geological disaster monitoring area, wherein the acquisition equipment includes a rain gauge, a displacement meter, a soil moisture meter, a meteorological monitoring station, a surface inclinometer, a vibration sensor, an anchor meter and a seismograph; An inversion equation setting module is used to set an inversion equation including a data equation and a target equation based on a wave equation; by solving the inversion equation through alternating iterations, the medium properties and the overall wave field are restored; wherein the inversion parameters of the inversion equation are the compressibility coefficient, shear compliance and density contrast in the wave equation; A finite element processing module, used for deducing the seismic data according to the finite element method and the wave equation to obtain medium elastic parameters, longitudinal wave velocity, shear wave velocity, density and background values ​​thereof; The geological disaster inversion module is used to input the processed seismic data and the geological environment data into the inversion equation for inversion to obtain the type, scale and location of the geological disasters in the geological disaster monitoring area.

[0015] According to another aspect of the present invention, there is provided a computing device, comprising: a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute operations corresponding to the above-mentioned geological disaster data analysis method based on the finite element method and the wave equation.

[0016] According to the scheme provided by the present invention, collection equipment is arranged in the monitoring area to collect seismic data and geological environment data in the geological disaster monitoring area, wherein the collection equipment includes a rain gauge, a displacement meter, a soil moisture meter, a meteorological monitoring station, a surface inclinometer, a vibration sensor, an anchor meter and a seismograph; an inversion equation including a data equation and a target equation is set based on the wave equation; the inversion equation is solved by alternating iteration to obtain the restored medium properties and the overall wave field; wherein the inversion parameters of the inversion equation are the compression coefficient, shear flexibility and density contrast in the wave equation; the seismic data is derived according to the finite element method and the wave equation to obtain the medium elastic parameters, longitudinal wave velocity, shear wave velocity, density and its background value; the processed seismic data and the geological environment data are input into the inversion equation for inversion to obtain the type, scale and location of the geological disasters in the geological disaster monitoring area. The present invention can comprehensively collect seismic data and geological environment data in the geological disaster monitoring area by arranging a variety of collection equipment, and can more accurately analyze geological disasters by fusion analysis of multi-source data. By setting the inversion equation based on the wave equation and solving it through alternating iterations, the properties of the medium and the overall wave field can be restored, which not only improves the accuracy of the inversion, but also reveals the physical mechanism of the occurrence of geological disasters. The elastic parameters, longitudinal wave velocity, shear wave velocity, density and background values ​​of the medium are derived through the finite element method and the wave equation, which can more accurately simulate the process of geological disasters. By adjusting the parameters of the inversion equation, it can adapt to different types of geological disasters and monitoring areas.

[0017] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings: Figure 1A schematic flow chart of a geological disaster data analysis method based on finite element method and wave equation according to an embodiment of the present invention is shown; Figure 2 The schematic diagram of the arrangement of the acquisition device of the embodiment of the present invention is shown Figure 1 ; Figure 3 The schematic diagram of the arrangement of the acquisition device of the embodiment of the present invention is shown Figure 2 ; Figure 4 A schematic diagram showing elastic parameters of a medium and a background of an embodiment of the present invention is shown; Figure 5 A schematic diagram showing the spectrum of seismic signals at different stages according to an embodiment of the present invention is shown; Figure 6 A schematic diagram of a framework of a geological disaster data analysis device based on a finite element method and a wave equation according to an embodiment of the present invention is shown; Figure 7 A schematic diagram of the structure of a computing device according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0019] The exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present invention and to enable the scope of the present invention to be fully communicated to those skilled in the art.

[0020] Figure 1 FIG. 1 is a flow chart of a method for analyzing geological hazard data based on finite element method and wave equation according to an embodiment of the present invention. Specifically, Figure 1 As shown, the following steps are included: Step S101, deploying acquisition equipment in the monitoring area to collect seismic data and geological environment data in the geological disaster monitoring area, wherein the acquisition equipment includes a rain gauge, a displacement meter, a soil moisture meter, a meteorological monitoring station, a surface inclinometer, a vibration sensor, an anchor meter and a seismograph.

[0021] In this embodiment, by integrating multiple collection devices such as rain gauges, displacement meters, soil moisture meters, meteorological monitoring stations, surface inclinometers, vibration sensors, anchor meters and seismographs, and transmitting the collected data to the central monitoring system, comprehensive and real-time monitoring of earthquake data and geological environment data in the geological disaster monitoring area can be carried out.

[0022] Specifically, Figure 2 , Figure 3As shown in Table 1, the collection equipment is deployed according to the geological characteristics, historical disaster records and meteorological conditions of the geological disaster monitoring area. For example, displacement meters and surface inclinometers are deployed at the edge of the landslide body, and rain gauges and soil moisture meters are deployed in areas prone to water accumulation. The collection equipment transmits data to the central monitoring system via wired or wireless means. Wireless transmission methods can use communication technologies such as 4G / 5G, LoRa, and NB-IoT. The layout of the collection equipment is shown in Table 1: Table 1 Device Type Layout location quantity model Rain gauge Water-prone areas upstream of landslide 2 units TR-525M (Automatic Rain Gauge) Displacement Meter Landslide edge 4 units LVDT (Linear Variable Differential Transformer) Series Soil moisture meter Inside and around the landslide 3 units EC-5 (Soil Moisture Sensor) Weather Monitoring Station Open area near landslide 1 unit AWS310 (Automatic Weather Station) Surface inclinometer Slope of landslide 2 units MS5837-02BA03 (dual-axis tilt sensor) Vibration Sensor Inside and around the landslide 2 units 4524B (Acceleration sensor) Anchor cable meter Landslide reinforcement project area 1 unit DVM600 (Digital Anchor Dynamometer) Seismograph Near the landslide 1 unit GS-11D (Broadband Seismograph) The 4524B accelerometer in Table 1 is used to monitor the vibration inside the landslide body, the DVM600 digital anchor dynamometer is used to monitor the stress of the anchor cables in the landslide body reinforcement project, and the GS-11D broadband seismograph is used to monitor the propagation of seismic waves.

[0023] In this embodiment, the seismic data includes seismic waveform data, ground vibration acceleration, vibration frequency and vibration direction. The geological environment data includes precipitation, surface displacement, displacement direction, soil moisture, soil humidity, soil temperature, air temperature, air relative humidity, surface inclination angle, anchor stress, anchor strain and anchor elongation. Among them, the seismic data is obtained by the method of blasting, and the blasting method includes single source excitation and multi-source mixed sampling. Single source excitation means that only one blasting point is excited each time, and underground geological information is obtained by recording and analyzing the reflected seismic wave signal. Multi-source mixed sampling refers to the simultaneous or almost simultaneous excitation of multiple blasting points, and the seismic information is extracted by optimizing the sampling method.

[0024] Step S102, setting an inversion equation including a data equation and a target equation based on the wave equation; solving the inversion equation by alternating iteration to obtain restored medium properties and overall wave field; wherein the inversion parameters of the inversion equation are the compressibility coefficient, shear compliance and density contrast in the wave equation.

[0025] In this embodiment, due to the nonlinear relationship between seismic data and underground medium properties, prestack seismic inversion based on the integral wave equation can effectively handle the nonlinear relationship. Based on the wave equation, an inversion equation including a data equation and a target equation is set, and the medium properties and the overall wave field are restored by alternating iterative solutions, which can directly invert the elastic parameters (such as compressibility, shear compliance) and density contrast of the underground medium, and has higher imaging accuracy than traditional methods.

[0026] Specifically, an inversion equation including a data equation and a target equation is set based on the wave equation. The data equation is used to describe the relationship between the observed seismic data and the underground medium properties, and the target equation is used to constrain the inversion process to ensure the rationality of the inversion results. The inversion parameters in the inversion equation, namely the compression coefficient, shear flexibility and density contrast in the wave equation, are determined, and the underground geological structure is interpreted according to the inversion results. For example, starting from a smooth low-frequency background field, the data equation and the target equation are alternately solved iteratively, the multiplicative regularization method is used to solve the inversion parameters in the conjugate gradient framework, and the optimized scattering series Neumann sequence is used to obtain the overall wave field.

[0027] In an optional manner, the expression of the data equation is: , in, is the observed seismic wave field; is the theoretical wave field calculated by the wave equation; is the observation error; are the inhomogeneity coefficient and anisotropy coefficient of the medium respectively; , is the elastic modulus at the ith discrete point, for The average value of , is the shear modulus at the ith discrete point, for The average value of is the number of discrete points; For space; For time.

[0028] In this embodiment, by introducing the inhomogeneity coefficient and anisotropy coefficient of the medium, the underground medium can be described more accurately. Specifically, the theoretical wave field is calculated according to the wave equation and the medium parameters. According to the seismic wave field data and the theoretical wave field, the inhomogeneity coefficient and anisotropy coefficient of the medium are estimated by the data equation. The medium parameters (such as elastic modulus, shear modulus, etc.) are continuously updated by the alternating iteration method until the observed error term meets the preset convergence condition or reaches the maximum number of iterations.

[0029] In an optional manner, the expression of the objective equation is: , in, is the inversion parameter vector, , is the compression factor, is the shear flexibility, is the density contrast; , , are weight factors, which are used to balance the contributions among field value, gradient value and Laplace value; is the integration area; , are the gradient operator and the Laplace operator respectively.

[0030] In this embodiment, the target equation realizes multi-scale constraints on the inversion parameters by integrating the errors of field values ​​(i.e., seismic wave fields, gradient values, and Laplace values), thereby improving the stability of the inversion results. Specifically, the target equation is solved and the inversion parameter vector is updated according to the alternating direction multiplier method (ADMM), the conjugate gradient method, or other optimization algorithms. During the iteration process, the theoretical wave field is continuously calculated according to the current inversion parameter vector, and compared with the observed wave field, and the inversion parameter vector is updated by minimizing the target equation. According to the preset convergence conditions (such as the decrease in the value of the objective function is less than a certain threshold or the number of iterations reaches a preset upper limit), it is judged whether the inversion process converges.

[0031] In an optional manner, the wave equation is expressed as: , in, is the damping coefficient, , is the longitudinal wave velocity at the ith discrete point, is the average value of the longitudinal wave velocity, is the number of discrete points; is the square of the wave speed; is the result of Laplace operator acting on seismic wave field u; is the external force source term, which is related to the geological environment data. , is the strength of the jth force source, is the location of the force source, is the Dirac function, is the number of force sources.

[0032] In this embodiment, by introducing the damping coefficient, the wave equation can more accurately simulate the propagation and attenuation behavior of seismic waves in the strata, thereby improving the accuracy of seismic wave simulation. By introducing the external force source term, various external factors in the geological environment (such as faults, abnormal bodies, etc.) can be considered, thereby enhancing the applicability of the model.

[0033] Specifically, the number of discrete points, P-wave velocity, average P-wave velocity and other parameters are determined based on the exploration data. The number of external force sources, the strength and location of each force source are determined based on the geological environment data. The determined parameters are substituted into the wave equation and solved by the finite element method to obtain the distribution of the seismic wave field.

[0034] Step S103, deriving the seismic data according to the finite element method and the wave equation to obtain medium elastic parameters, longitudinal wave velocity, shear wave velocity, density and background values ​​thereof.

[0035] In this embodiment, through the derivation of the wave equation, multiple physical parameters of the medium can be simultaneously inverted, including elastic parameters (such as Lame constant, shear modulus, etc.), longitudinal wave velocity, shear wave velocity, density and its background value, etc.

[0036] Specifically, seismic exploration data are collected, including information such as the propagation time, amplitude, and frequency of seismic waves. An initial finite element model is established based on the geological background and geophysical characteristics of the exploration area. The wave equation is discretized by the finite element method to form a series of linear equations. The size and shape of the finite element grid are determined based on the sampling interval and spatial distribution of the seismic data. The elastic parameters, longitudinal wave velocity, shear wave velocity, and density of the medium are inverted by using seismic data and discretized wave equations through an iterative solution method. During the iteration process, the parameters of the finite element model are continuously adjusted to minimize the difference between the simulated seismic wave field and the observed data. In the inverted parameter distribution map, the background value of the medium parameter is extracted by statistical analysis or filtering processing. Among them, the background value represents the average physical properties of the formation, which is used to identify geological anomalies and evaluate the stability of the formation. The inverted parameters are compared and verified with the known geological information, and the geological structure is interpreted and predicted based on the inverted parameter distribution map.

[0037] In an optional manner, the derivation of the seismic data according to the finite element method and the wave equation to obtain medium elastic parameters, longitudinal wave velocity, shear wave velocity, density and background values ​​thereof further comprises: Divide the monitoring area into multiple triangular finite elements, and the vertices of each finite element include the degrees of freedom in the x, y, and z directions; The displacement distribution within each finite element is described by a polynomial shape function, and the elastic modulus, Poisson's ratio, and density are specified for each finite element; Solving the wave equation according to an implicit time integration method to obtain the node displacement at each time step; The elastic parameters of the medium, the longitudinal wave velocity, the shear wave velocity, the density and the background values ​​thereof are derived according to the node displacement.

[0038] In this embodiment, dividing the monitoring area into multiple triangular finite elements can more accurately capture the complexity and inhomogeneity of the geological structure. The displacement distribution within each finite element is described by a polynomial shape function, and the wave equation is solved using an implicit time integration method, which can more accurately extract the background value of the medium parameter.

[0039] Specifically, the monitoring area is divided into multiple triangular finite elements, and the vertices of each finite element include degrees of freedom in the x, y, and z directions to describe the propagation of seismic waves in three-dimensional space. Physical parameters such as elastic modulus, Poisson's ratio, and density are specified for each finite element, and polynomial shape functions are used to describe the displacement distribution within each finite element to ensure the continuity and smoothness of the displacement. According to the implicit time integration method (such as the Newmark-β method), the wave equation is discretized and solved. At each time step, the displacement value of the node is obtained by iterative calculation. Using the node displacement values ​​obtained by the solution and combined with the physical parameters of the finite element model, the elastic parameters, longitudinal wave velocity, shear wave velocity, and density of the medium are obtained through the inversion algorithm. Then, as Figure 4 As shown, the background values ​​of these parameters are extracted through statistical analysis and other methods.

[0040] In an optional manner, the expression of the implicit time integral is: , in, is the mass matrix, , is the density, and is the shape function, is the integration area; is the damping matrix; is the stiffness matrix, , It is a double point product; is the node displacement at the n+1th time step; is the node displacement at the nth time step; is the time step; is the external force vector at the n+1th time step.

[0041] In this embodiment, the implicit time integration method is used to ensure the stability and efficiency of the solution process. Through the displacement information of multiple time steps, the high-frequency components in the wave equation can be better processed to avoid numerical oscillation. The implicit time integration expression contains the mass matrix, damping matrix and stiffness matrix, which can reflect the physical properties of the medium and the propagation law of seismic waves.

[0042] Specifically, according to the geological model and physical parameters of the monitoring area, the mass matrix, damping matrix and stiffness matrix as well as the corresponding medium density, shape function and integral area are constructed.

[0043] The time step is set according to the propagation speed of seismic waves and the size of the monitoring area. The implicit time integral expression is converted into a linear equation system, and the node displacement of each time step is solved using numerical solution methods (such as iteration method, direct method, etc.). The elastic parameters, longitudinal wave velocity, shear wave velocity, density and background value of the medium are obtained by combining the physical parameter inversion of the finite element model with the node displacement obtained by the solution.

[0044] Step S104, inputting the processed seismic data and the geological environment data into the inversion equation for inversion, and obtaining the type, scale and location of the geological disasters in the geological disaster monitoring area.

[0045] Specifically, the geological disaster inversion equation of the geological disaster monitoring area is constructed according to the cause mechanism of geological disasters and geological environment characteristics. The processed seismic data and geological environment data are input into the inversion equation for inversion calculation to solve the type (such as landslide, debris flow, etc.), scale (such as the volume of landslide body, the flow rate of debris flow, etc.) and location (such as longitude and latitude coordinates, altitude) of geological disasters, and the inversion results are output in graphical and tabular forms to formulate geological disaster prevention and control measures and emergency plans. Figure 5 As shown in the figure, the above processing is performed on a certain lake time period, and finally the time period is divided into three stages to obtain the time spectrum, which are the three stages of burst (before burst, during burst, and stabilization after burst).

[0046] In an optional manner, the inversion parameters of the inversion equation are: , in, As input parameters, it includes seismic data and geological environment data; is the weight coefficient; m is the number of parameters; It is the type of geological disaster; is the scale of geological disasters; For the location of geological hazards; Factors that affect the types of geological disasters.

[0047] In this embodiment, the inversion equation is in the form of a logistic regression function, which can handle the nonlinear relationship between the input parameters and the type, scale and location of geological hazards.

[0048] According to the scheme provided by the present invention, collection equipment is arranged in the monitoring area to collect seismic data and geological environment data in the geological disaster monitoring area, wherein the collection equipment includes a rain gauge, a displacement meter, a soil moisture meter, a meteorological monitoring station, a surface inclinometer, a vibration sensor, an anchor meter and a seismograph; an inversion equation including a data equation and a target equation is set based on the wave equation; the inversion equation is solved by alternating iteration to obtain the restored medium properties and the overall wave field; wherein the inversion parameters of the inversion equation are the compression coefficient, shear flexibility and density contrast in the wave equation; the seismic data is derived according to the finite element method and the wave equation to obtain the medium elastic parameters, longitudinal wave velocity, shear wave velocity, density and its background value; the processed seismic data and the geological environment data are input into the inversion equation for inversion to obtain the type, scale and location of the geological disasters in the geological disaster monitoring area. The present invention can comprehensively collect seismic data and geological environment data in the geological disaster monitoring area by arranging a variety of collection equipment, and can more accurately analyze geological disasters by fusion analysis of multi-source data. By setting the inversion equation based on the wave equation and solving it through alternating iterations, the properties of the medium and the overall wave field can be restored, which not only improves the accuracy of the inversion, but also reveals the physical mechanism of the occurrence of geological disasters. The elastic parameters, longitudinal wave velocity, shear wave velocity, density and background values ​​of the medium are derived through the finite element method and the wave equation, which can more accurately simulate the process of geological disasters. By adjusting the parameters of the inversion equation, it can adapt to different types of geological disasters and monitoring areas.

[0049] Figure 6 The schematic diagram of the structure of the geological disaster data analysis device based on the finite element method and the wave equation of the embodiment of the present invention is shown. The geological disaster data analysis device based on the finite element method and the wave equation includes: The data acquisition module 610 is used to deploy acquisition equipment in the monitoring area to collect seismic data and geological environment data in the geological disaster monitoring area, wherein the acquisition equipment includes a rain gauge, a displacement meter, a soil moisture meter, a meteorological monitoring station, a surface inclinometer, a vibration sensor, an anchor meter and a seismograph; The inversion equation setting module 620 is used to set the inversion equation including the data equation and the target equation based on the wave equation; the medium properties and the overall wave field are restored by solving the inversion equation through alternating iteration; wherein the inversion parameters of the inversion equation are the compressibility coefficient, shear compliance and density contrast in the wave equation; The finite element processing module 630 is used to derive the seismic data according to the finite element method and the wave equation to obtain medium elastic parameters, longitudinal wave velocity, shear wave velocity, density and background values ​​thereof; The geological disaster inversion module 640 is used to input the processed seismic data and the geological environment data into the inversion equation for inversion to obtain the type, scale and location of the geological disasters in the geological disaster monitoring area.

[0050] Figure 7 The schematic diagram of the structure of the computing device embodiment of the present invention is shown. The specific embodiment of the present invention does not limit the specific implementation of the computing device.

[0051] like Figure 7 As shown, the computing device may include: a processor (processor) 702, a communication interface (Communications Interface) 704, a memory (memory) 706, and a communication bus 708.

[0052] Wherein: the processor 702, the communication interface 704, and the memory 706 communicate with each other through the communication bus 708. The communication interface 704 is used to communicate with other devices such as the network element of the client or other servers. The processor 702 is used to execute the program 710, which can specifically execute the relevant steps in the above-mentioned embodiment of the geological disaster data analysis method based on the finite element method and the wave equation.

[0053] Specifically, the program 710 may include program codes, which include computer operation instructions.

[0054] The processor 702 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention. The one or more processors included in the computing device may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0055] The memory 706 is used to store the program 710. The memory 706 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0056] According to the scheme provided by the present invention, collection equipment is arranged in the monitoring area to collect seismic data and geological environment data in the geological disaster monitoring area, wherein the collection equipment includes a rain gauge, a displacement meter, a soil moisture meter, a meteorological monitoring station, a surface inclinometer, a vibration sensor, an anchor meter and a seismograph; an inversion equation including a data equation and a target equation is set based on the wave equation; the inversion equation is solved by alternating iteration to obtain the restored medium properties and the overall wave field; wherein the inversion parameters of the inversion equation are the compression coefficient, shear flexibility and density contrast in the wave equation; the seismic data is derived according to the finite element method and the wave equation to obtain the medium elastic parameters, longitudinal wave velocity, shear wave velocity, density and its background value; the processed seismic data and the geological environment data are input into the inversion equation for inversion to obtain the type, scale and location of the geological disasters in the geological disaster monitoring area. The present invention can comprehensively collect seismic data and geological environment data in the geological disaster monitoring area by arranging a variety of collection equipment, and can more accurately analyze geological disasters by fusion analysis of multi-source data. By setting the inversion equation based on the wave equation and solving it through alternating iterations, the properties of the medium and the overall wave field can be restored, which not only improves the accuracy of the inversion, but also reveals the physical mechanism of the occurrence of geological disasters. The elastic parameters, longitudinal wave velocity, shear wave velocity, density and background values ​​of the medium are derived through the finite element method and the wave equation, which can more accurately simulate the process of geological disasters. By adjusting the parameters of the inversion equation, it can adapt to different types of geological disasters and monitoring areas.

[0057] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and further may be divided into multiple submodules or subunits or subcomponents. All features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device disclosed in this manner may be combined in any combination, except that at least some of such features and / or processes or units are mutually exclusive. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature that provides the same, equivalent or similar purpose. In addition, those skilled in the art will appreciate that, although some embodiments herein include certain features included in other embodiments but not other features, the combination of features of different embodiments is meant to be within the scope of the present invention and to form different embodiments. For example, in the following claims, any one of the claimed embodiments may be used in any combination. The present invention may be implemented by means of hardware including several different elements and by means of a suitably programmed computer. In a unit claim that lists several means, several of these means may be embodied by the same hardware item. The steps in the above embodiments should not be understood as limiting the execution order unless otherwise specified.

Claims

1. A geological disaster data analysis method based on finite element method and wave equation, characterized in that: include: Deploy collection equipment in the monitoring area to collect seismic data and geological environment data in the geological disaster monitoring area, wherein the collection equipment includes a rain gauge, a displacement meter, a soil moisture meter, a meteorological monitoring station, a surface inclinometer, a vibration sensor, an anchor meter and a seismograph; An inversion equation including a data equation and a target equation is set based on the wave equation; the medium properties and the overall wave field are restored by solving the inversion equation through alternating iterations; wherein the inversion parameters of the inversion equation are the compressibility coefficient, shear compliance and density contrast in the wave equation; Derivation of the seismic data according to the finite element method and the wave equation to obtain medium elastic parameters, longitudinal wave velocity, shear wave velocity, density and background values ​​thereof; The processed seismic data and the geological environment data are input into the inversion equation for inversion to obtain the type, scale and location of the geological disasters in the geological disaster monitoring area.

2. The geological disaster data analysis method based on finite element method and wave equation according to claim 1 is characterized in that: The seismic data includes seismic waveform data, ground vibration acceleration, vibration frequency and vibration direction; The geological environment data include precipitation, surface displacement, displacement direction, soil water content, soil humidity, soil temperature, air temperature, air relative humidity, surface inclination angle, anchor stress, anchor strain and anchor elongation.

3. The geological disaster data analysis method based on finite element method and wave equation according to claim 1 is characterized in that: The expression of the data equation is: ， in, is the observed seismic wave field; is the theoretical wave field calculated by the wave equation; is the observation error; are the inhomogeneity coefficient and anisotropy coefficient of the medium respectively; , is the elastic modulus at the ith discrete point, for The average value of , is the shear modulus at the ith discrete point, for The average value of is the number of discrete points; For space; For time.

4. The geological disaster data analysis method based on finite element method and wave equation according to claim 3 is characterized in that: The expression of the objective equation is: ， in, is the inversion parameter vector, , is the compression factor, is the shear flexibility, is the density contrast; , , are weight factors, which are used to balance the contributions among field value, gradient value and Laplace value; is the integration area; , are the gradient operator and the Laplace operator respectively.

5. The geological disaster data analysis method based on finite element method and wave equation according to claim 4 is characterized in that: The expression of the wave equation is: ， in, is the damping coefficient, , is the longitudinal wave velocity at the ith discrete point, is the average value of the longitudinal wave velocity, is the number of discrete points; is the square of the wave speed; is the result of Laplace operator acting on seismic wave field u; is the external force source term, which is related to the geological environment data. , is the strength of the jth force source, is the location of the force source, is the Dirac function, is the number of force sources.

6. The geological disaster data analysis method based on finite element method and wave equation according to claim 1 is characterized in that: The derivation of the seismic data according to the finite element method and the wave equation to obtain medium elastic parameters, longitudinal wave velocity, shear wave velocity, density and background values ​​thereof further comprises: Divide the monitoring area into multiple triangular finite elements, and the vertices of each finite element include the degrees of freedom in the x, y, and z directions; The displacement distribution within each finite element is described by a polynomial shape function, and the elastic modulus, Poisson's ratio, and density are specified for each finite element; Solving the wave equation according to an implicit time integration method to obtain the node displacement at each time step; The elastic parameters of the medium, the longitudinal wave velocity, the shear wave velocity, the density and the background values ​​thereof are derived according to the node displacement.

7. The geological disaster data analysis method based on finite element method and wave equation according to claim 6 is characterized in that: The expression of the implicit time integral is: ， in, is the mass matrix, , is the density, and is the shape function, is the integration area; is the damping matrix; is the stiffness matrix, , It is a double point product; is the node displacement at the n+1th time step; is the node displacement at the nth time step; is the time step; is the external force vector at the n+1th time step.

8. The geological disaster data analysis method based on finite element method and wave equation according to claim 1 is characterized in that: The inversion parameters of the inversion equation are: ， in, As input parameters, it includes seismic data and geological environment data; is the weight coefficient; m is the number of parameters; It is the type of geological disaster; is the scale of geological disasters; For the location of geological hazards; Factors that affect the types of geological disasters.

9. A geological disaster data analysis device based on finite element method and wave equation, characterized in that: include: A data acquisition module is used to deploy acquisition equipment in the monitoring area to collect seismic data and geological environment data in the geological disaster monitoring area, wherein the acquisition equipment includes a rain gauge, a displacement meter, a soil moisture meter, a meteorological monitoring station, a surface inclinometer, a vibration sensor, an anchor meter and a seismograph; An inversion equation setting module is used to set an inversion equation including a data equation and a target equation based on a wave equation; by solving the inversion equation through alternating iterations, the medium properties and the overall wave field are restored; wherein the inversion parameters of the inversion equation are the compressibility coefficient, shear compliance and density contrast in the wave equation; A finite element processing module, used for deducing the seismic data according to the finite element method and the wave equation to obtain medium elastic parameters, longitudinal wave velocity, shear wave velocity, density and background values ​​thereof; The geological disaster inversion module is used to input the processed seismic data and the geological environment data into the inversion equation for inversion to obtain the type, scale and location of the geological disasters in the geological disaster monitoring area.

10. A computing device comprising: A processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute operations corresponding to the geological disaster data analysis method based on the finite element method and the wave equation described in any one of claims 1-8.

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