A landslide crack evolution monitoring method and device based on weak scattering wave imaging

Abstract

The application provides a landslide crack evolution monitoring method and device based on weak scattering wave imaging, and relates to the technical field of geological disaster early warning and high-resolution imaging of earthquakes, and the method comprises the following steps: acquiring scattered wave field data in common offset seismic data of a target region; searching for an optimal energy stacking path of each imaging point in a dip angle channel corresponding to the scattered wave field data under energy symmetry constraint according to a preset dip angle domain scattered wave event fitting formula and a target function constructed by taking maximum stacking energy as a target, so as to obtain a target energy value of each imaging point; and performing energy truncation on noise imaging points in each imaging point through an energy distribution curve, so as to obtain a target imaging result of a landslide crack evolution structure of the target region. In this way, the scattered wave signal is extracted and stacked by searching for the optimal energy stacking path and combining the energy truncation algorithm based on the energy distribution curve, and dynamic and fine identification of shallow to middle cracks is realized.

Description

Technical Field

[0001] This invention relates to the field of geological disaster early warning and high-resolution earthquake imaging technology, and in particular to a method and device for monitoring landslide crack evolution based on weak scattering wave imaging. Background Technology

[0002] In mountainous areas with frequent earthquakes or intense rainfall, landslides are a common occurrence and a significant contributor to casualties and economic losses. Landslides are often preceded by underground processes such as crack propagation, rock softening, and localized shear failure, exhibiting characteristics of suddenness, gradual progression, and concealment. Traditional methods, such as InSAR (Interferometric Synthetic Aperture Radar) deformation monitoring, tiltmeter measurements, GPS (Global Positioning System) location, or crack inspection, primarily focus on the surface layer and are insufficient for real-time identification of early abnormal evolutions in shallow and intermediate underground structures.

[0003] In recent years, scattered waves have been used in seismic exploration as wavefield signals responding to small-scale discontinuous structures (such as cracks and fracture pinch-out points), and their imaging capabilities are significantly higher than those of traditional reflected waves. However, because the phase axis morphology of scattered waves in the dip domain is highly sensitive to migration velocity errors, and accurate migration velocity acquisition is difficult, traditional horizontal stacking imaging methods struggle to achieve effective convergence of scattered wave energy, resulting in insufficient structure identification capabilities. Summary of the Invention

[0004] The purpose of this invention is to provide a method and device for monitoring the evolution of landslide cracks based on weak scattering wave imaging, so as to achieve dynamic and precise identification of shallow to mid-level cracks.

[0005] In a first aspect, the present invention provides a method for monitoring the evolution of landslide cracks based on weak scattering wave imaging, comprising: Acquire scattered wave field data from co-offset seismic data of the target area; Based on the preset in-phase axis fitting formula of the scattering wave in the tilt domain and the objective function constructed with the goal of maximizing superposition energy, under the constraint of energy symmetry, the optimal energy superposition path of each imaging point in the tilt field data corresponding to the scattering wave field is searched to obtain the target energy value of each imaging point. By truncating the energy of noisy imaging points in each imaging point using the energy distribution curve, the target imaging results of the landslide crack evolution structure in the target area are obtained.

[0006] In an optional implementation, the scattered wave field data in the co-offset seismic data of the target area is acquired, including: Acquire co-offset seismic data for the target area; The scattered wave field data is obtained by separating the scattered wave field from the co-offset seismic data.

[0007] In an optional implementation, the in-phase axis fitting formula for the tilt-domain scattered wave is a quadratic function of the tilt angle. Based on the objective function constructed using the preset in-phase axis fitting formula for the tilt-domain scattered wave, under energy symmetry constraints, the optimal energy superposition path for each imaging point in the tilt-domain trace corresponding to the scattered wave field data is searched to obtain the target energy value for each imaging point, including: The Kirchhoff migration algorithm is used to migrate the scattered wave field data to the dip domain to obtain the dip gather; For each imaging point in the tilt channel set, based on the energy values ​​of the imaging point at different offset tilt angles and different times, the quadratic coefficients of the tilt domain scattered wave phase axis fitting formula are searched within a preset range of quadratic coefficients to obtain the target quadratic coefficients that satisfy the energy symmetry constraint and maximize the function value of the objective function. The tilt domain scattered wave phase axis fitting formula under the target quadratic coefficients is determined as the optimal energy superposition path for the imaging point, and the superposition energy value under the optimal energy superposition path is determined as the target energy value for the imaging point.

[0008] In an optional implementation, the objective function is: ; in, Indicates the offset angle. This represents the formula for fitting the in-phase axis of the scattered wave in the tilt domain, where A represents... The coefficient of the quadratic term, A min Let A represent the minimum value of A. max This represents the maximum value of A. Indicates the focused imaging point of the inclined channel. The energy value at that location, This represents the value with the maximum superposition energy after traversing all A values.

[0009] In an optional implementation, the energy symmetry constraint is: ; in, This is the default value.

[0010] In an optional implementation, the energy of noisy imaging points in each imaging point is truncated using the energy distribution curve to obtain the target imaging result of the landslide crack evolution structure in the target area, including: The target energy values ​​of each imaging point are sorted in ascending order to obtain the sorting result; Based on the sorting results, construct the energy distribution curves of the imaging points in the offset tilt domain, and calculate the curvature of each imaging point; Based on the sorting position corresponding to the imaging point with the largest curvature, determine the noisy imaging points in each imaging point; The target imaging result is obtained by setting the target energy value of the noise imaging point in each imaging point to 0.

[0011] In an optional implementation, the curvature of the imaging point is calculated using a difference approximation.

[0012] Secondly, the present invention provides a landslide crack evolution monitoring device based on weak scattering wave imaging, comprising: The acquisition module is used to acquire scattered wave field data from co-offset seismic data of the target area; The search module is used to search for the optimal energy superposition path of each imaging point in the tilt field data corresponding to the scattering wave field data, based on the preset tilt domain scattering wave phase axis fitting formula and the objective function constructed with the goal of maximizing superposition energy, under the constraint of energy symmetry, so as to obtain the target energy value of each imaging point. The truncation module is used to truncate the energy of noise imaging points in each imaging point through the energy distribution curve, so as to obtain the target imaging results of the landslide crack evolution structure in the target area.

[0013] Thirdly, the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program that can run on the processor, and the processor executes the computer program to implement the landslide crack evolution monitoring method based on weak scattering wave imaging according to any of the foregoing embodiments.

[0014] Fourthly, the present invention provides a computer-readable storage medium storing a computer program, wherein the computer program, when run by a processor, executes the landslide crack evolution monitoring method based on weak scattering wave imaging as described in any of the foregoing embodiments.

[0015] The method and apparatus for monitoring landslide crack evolution based on weak scattered wave imaging provided by this invention include: acquiring scattered wave field data from co-offset seismic data of the target area; searching for the optimal energy superposition path for each imaging point in the dip-domain scattered wave phase axis fitting formula and an objective function constructed with the goal of maximizing superposition energy, under energy symmetry constraints, to obtain the target energy value for each imaging point; and truncating the energy of noisy imaging points in each imaging point using the energy distribution curve to obtain the target imaging result of the landslide crack evolution structure in the target area. In this way, by searching for the optimal energy superposition path based on the preset dip-domain scattered wave phase axis fitting formula and an objective function constructed with the goal of maximizing superposition energy, and combining the energy truncation algorithm based on the energy distribution curve to extract and superimpose the scattered wave signal, dynamic and precise identification of shallow to mid-level cracks is achieved. Attached Figure Description

[0016] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0017] Figure 1 A schematic flowchart of a landslide crack evolution monitoring method based on weak scattering wave imaging provided in an embodiment of the present invention; Figure 2 A schematic flowchart of another landslide crack evolution monitoring method based on weak scattering wave imaging provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of a landslide crack evolution monitoring device based on weak scattering wave imaging, provided in an embodiment of the present invention. Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0018] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] To address the problems of traditional horizontal stacking imaging methods, this invention provides a landslide crack evolution monitoring method and device based on weak scattering wave imaging. This method can effectively improve the resolution and stability of scattering wave imaging, providing an efficient and practical technical approach for the dynamic identification of underground structures during the landslide incubation period. It helps to identify and dynamically track hidden underground structures during the landslide incubation stage, thereby improving the level of early disaster warning.

[0020] Based on the dynamics and kinematics of scattered waves in the tilt domain, this invention proposes a GSS (Global Signal Search Algorithm)-DET (Diffracted Wave Energy Truncation Algorithm). This algorithm first utilizes the energy symmetry and morphological stability of scattered waves in the tilt domain to construct an objective function for searching the globally optimal superposition path, thereby achieving precise focusing on small-scale discontinuities. Subsequently, a truncation strategy is introduced to effectively eliminate non-target noise imaging points, enhancing imaging clarity and reliability.

[0021] To facilitate understanding of this embodiment, a detailed description of a landslide crack evolution monitoring method based on weak scattering wave imaging disclosed in this embodiment of the invention will be provided first.

[0022] This invention provides a method for monitoring landslide crack evolution based on weakly scattered wave imaging, which can be executed by an electronic device with data processing capabilities. See also... Figure 1 The diagram shows a flowchart of a landslide crack evolution monitoring method based on weak scattering wave imaging. The method mainly includes the following steps S110 to S130: Step S110: Obtain the scattered wave field data from the co-offset seismic data of the target area.

[0023] The aforementioned target area is the region to be processed for monitoring the evolution of landslide cracks. Offset refers to the horizontal distance between the seismic source and receiver. Co-offset seismic data includes all seismic traces with the same offset (i.e., all records where the distance between the source and receiver remains constant). Each seismic trace corresponds to seismic wave propagation information at a specific location, such as time (reflecting depth), amplitude (intensity), and phase. Scattered wavefield data can be obtained by separating the scattered wavefield from the co-offset seismic data.

[0024] In some possible embodiments, step S110 may include: acquiring co-offset seismic data of the target area; separating the scattered wave field from the co-offset seismic data to obtain scattered wave field data. The separation of the scattered wave field may be performed using methods such as multichannel singular spectrum decomposition or tilt filtering.

[0025] Step S120: Based on the preset tilt domain scattered wave phase axis fitting formula and the objective function constructed with the goal of maximizing superposition energy, under the energy symmetry constraint, the optimal energy superposition path for each imaging point in the tilt field data corresponding to the scattered wave field is searched to obtain the target energy value of each imaging point.

[0026] The tilt gather is obtained by offsetting the scattered wave field data to the tilt domain. The tilt gather includes the energy values ​​of each imaging point at different offset tilt angles and at different times. According to the Taylor approximation, the shape of the in-phase axis of the scattered wave in the tilt domain approximates a parabola. Based on this, in this embodiment, the fitting formula for the in-phase axis of the scattered wave in the tilt domain can be a quadratic function of the offset tilt angle. The coefficients of the quadratic term in the fitting formula can control the opening direction and curvature of the parabola; these coefficients can also be called curvature. A range of values ​​for the quadratic term coefficients is given in advance. By traversing all quadratic term coefficients, the target quadratic term coefficient with the maximum superposition energy is found. Therefore, the fitting formula for the in-phase axis of the scattered wave in the tilt domain under the target quadratic term coefficient is the optimal energy superposition path, i.e., the fitted tilt domain scattered wave in-phase axis. The superposition energy value of the imaging point under the optimal energy superposition path is the target energy value of the imaging point. Simultaneously, to avoid erroneous search results caused by non-scattering, a symmetric constraint term for scattered wave energy is introduced based on the above objective function, i.e., an energy symmetric constraint. During the search process, only the quadratic term coefficients that satisfy this energy symmetric constraint are considered.

[0027] In some possible embodiments, the in-phase axis fitting formula for the scattering wave in the tilt domain is a quadratic function of the offset tilt angle. Based on this, step S120 above may include: using the Kirchhoff migration algorithm to offset the scattered wave field data to the tilt domain to obtain a tilt gather; for each imaging point in the tilt gather, according to the energy value of the imaging point in the tilt gather at different offset tilt angles and different times, searching for the quadratic coefficients of the in-phase axis fitting formula for the scattering wave in the tilt domain within a preset range of quadratic coefficients to obtain the target quadratic coefficients that satisfy the energy symmetry constraint and maximize the function value of the objective function; determining the in-phase axis fitting formula for the scattering wave in the tilt domain under the target quadratic coefficients as the optimal energy superposition path for the imaging point, and determining the superposition energy value under the optimal energy superposition path as the target energy value for the imaging point.

[0028] In one possible implementation, the above objective function can be: ; in, Indicates the offset angle. , This represents the formula for fitting the phase axis of the scattered wave in the tilt domain. A express The coefficient of the quadratic term, A min express A The minimum value, A max express A The maximum value, Indicates the focused imaging point of the inclined channel. The energy value at that location, This indicates traversing all A The value of the maximum superimposed energy.

[0029] In one possible implementation, the above energy symmetry constraint can be: ; in, This is a preset value, and its range is (0,1).

[0030] Step S130: Energy truncation is performed on the noise imaging points in each imaging point using the energy distribution curve to obtain the target imaging result of the landslide crack evolution structure in the target area.

[0031] To improve the quality of imaging results, noise suppression can be performed on the imaging results. In this embodiment, the inherent difference in energy level between effective signal imaging points and noisy imaging points is utilized to achieve separation between the two.

[0032] In some possible embodiments, step S130 may include: sorting the target energy values ​​of each imaging point in ascending order to obtain a sorting result; constructing an energy distribution curve of the imaging points in the offset tilt domain based on the sorting result, and calculating the curvature of each imaging point; determining the noise imaging point in each imaging point based on the sorting position corresponding to the imaging point with the largest curvature; and obtaining the target imaging result by setting the target energy value of the noise imaging point in each imaging point to 0.

[0033] Optionally, the curvature of the aforementioned imaging point can be calculated using a difference approximation. The formula for calculating the curvature of the imaging point is as follows: ; in, C i Indicates the sorting position is i The curvature of the imaging point; F i Indicates the sorting position is i The target energy value of the imaging point; express F i The first difference, ; express F i The second difference, .

[0034] The landslide crack evolution monitoring method based on weak scattered wave imaging provided in this invention searches for the optimal energy superposition path based on a preset dip-domain scattered wave phase axis fitting formula and an objective function constructed with the goal of maximizing superposition energy. Combined with an energy truncation algorithm based on the energy distribution curve, the scattered wave signal is extracted and superimposed, thereby realizing dynamic and precise identification of shallow to mid-level cracks.

[0035] To facilitate understanding, the Kirchhoff migration algorithm will be used as an example to provide a detailed introduction to the above-mentioned landslide crack evolution monitoring method based on weak scattering wave imaging.

[0036] This invention proposes a high-resolution scattered wave monitoring method for the evolution of underground fissures during the landslide incubation period. Based on the high sensitivity of scattered waves to small-scale discontinuous underground structures (such as tensile fractures and weak zones), this method combines dip-domain imaging technology with a Global Signal Search (GSS) algorithm and a Dispersed Wave Energy Truncation (DET) algorithm to extract and superimpose scattered wave signals, achieving dynamic and precise identification of shallow to mid-level fissures. The steps include: acquiring and separating scattered wave seismic data from the landslide hazard zone (i.e., the target area); constructing a dip-domain scattered wave phase axis search objective function and performing constraint optimization based on energy symmetry; using energy distribution curves for truncation to suppress noise imaging points; and finally obtaining a high-resolution focused image of the underground evolution structure. This method has low dependence on the accuracy of the migration velocity model, strong imaging robustness, and is suitable for early warning applications of geological disasters in mountainous areas.

[0037] See Figure 2 The flowchart of another landslide crack evolution monitoring method based on weak scattered wave imaging is shown. The method includes the following steps S210 to S270: Step S210: Obtain the common offset seismic data of the area to be processed.

[0038] Step S220: Separate the weakly scattered wave field in the co-offset seismic data.

[0039] In step S230, the Kirchhoff migration algorithm is used to migrate the separated scattered wave field to the tilt domain, and under the energy symmetry constraint, the optimal stacking path for each imaging point is searched through the global signal search algorithm to obtain the target energy value of each imaging point.

[0040] The horizontal coordinate in the dip domain is the dip angle. The vertical axis represents time. t Because the shape of the in-phase axis of the scattered wave in the tilt domain is approximately parabolic. Vertex is often located place, and Each imaging point at a given location may contain scattered waves, therefore it is necessary to... At each imaging point (0, t The optimal superposition path (corresponding to the in-phase axis of the scattered wave) is searched.

[0041] In the separated wavefield of step S220, the scattered wave, as the target wavefield, has the highest energy. Therefore, for each imaging point ( When searching for the optimal superposition path, it is only necessary to find the parabola with the highest superposition energy. For example, At this point, the approximate formula for the in-phase axis of the scattered wave can be written as: traverse all curvatures ( A By finding the parabola with the highest superposition energy, the optimal superposition path for that imaging point can be determined. The formula for the objective function is as follows: .

[0042] To avoid erroneous search results caused by non-scattering, the following energy symmetry constraint term for scattered waves is introduced based on the above objective function: .

[0043] By setting a constraint parameter to constrain the difference in total energy between the left and right sides of the search curve under the current curvature, if the constraint is satisfied, the curve is considered the optimal superposition path for the current imaging point. If the constraint is not satisfied, the point is considered not to be a scattered wave imaging point, and its energy is set to 0.

[0044] Step S240: Sort the target energy values ​​of each imaging point from smallest to largest.

[0045] The sorting result can be represented as: .

[0046] Step S250: Construct the optimal energy distribution curve of the imaging points in the offset tilt domain based on the sorting results, and calculate the curvature of each imaging point by differential approximation.

[0047] curvature of imaging point C i for: .

[0048] Step S260: Traverse all valid indices, determine the position of maximum curvature, and set the energy value corresponding to the valid index that is greater than the position of maximum curvature to 0.

[0049] The aforementioned valid index refers to the sorting position of valid imaging points. Valid imaging points are those with target energy values ​​greater than a preset energy threshold. This preset energy threshold can be set according to actual needs and is not limited here. The maximum curvature position (i.e., the sorting position corresponding to the imaging point with the largest curvature) is the inflection point of the energy distribution. This inflection point corresponds to the transition position of the energy sequence from high-amplitude scattering imaging points to low-amplitude noise imaging points. The maximum curvature position can be expressed as: .

[0050] Find the position of maximum curvature After that, it will be greater than Valid indexes i The corresponding energy is set to 0: .

[0051] Step S270: By using the energy index mapping relationship of the original imaging points, the imaging points after energy truncation are restored to their original spatial positions to obtain the target imaging result.

[0052] This allows us to obtain the location, distribution, and evolution trend of underground micro-discontinuities (such as cracks and fracture zones), which can be used for monitoring during the landslide incubation period.

[0053] In this embodiment, by introducing a global signal search (GSS) strategy, accurate focusing of scattered wave energy can be achieved without the need for a high-precision migration velocity model, effectively reducing the dependence on velocity modeling. Combined with the scattered wave energy truncation algorithm (DET), non-target noise points can be effectively identified and eliminated, improving the signal-to-noise ratio of imaging. This method can serve as a powerful supplement to existing surface observation methods such as InSAR and GPS, constructing an integrated "surface-subsurface" landslide disaster monitoring system and enhancing the ability to identify risks during the incubation period. This technology is highly adaptable and suitable for landslide disaster early warning and dynamic monitoring needs in various geological environments such as transportation arteries, high slopes, and water conservancy facilities, and has broad prospects for promotion and application.

[0054] Corresponding to the above-described method for monitoring landslide crack evolution based on weak scattering wave imaging, this invention also provides a device for monitoring landslide crack evolution based on weak scattering wave imaging. See [link to related document]. Figure 3 The diagram shows a structural schematic of a landslide crack evolution monitoring device based on weak scattering wave imaging. The device includes: The acquisition module 301 is used to acquire the scattered wave field data in the co-offset seismic data of the target area; The search module 302 is used to search for the optimal energy superposition path of each imaging point in the tilt field data corresponding to the scattered wave field data under the energy symmetry constraint, based on the preset tilt domain in-phase axis fitting formula and the objective function constructed with the maximum superposition energy as the objective. This results in the target energy value of each imaging point. The truncation module 303 is used to truncate the energy of noise imaging points in each imaging point through the energy distribution curve, so as to obtain the target imaging result of the landslide crack evolution structure in the target area.

[0055] The landslide crack evolution monitoring device based on weak scattered wave imaging provided by this invention searches for the optimal energy superposition path based on a preset dip-domain scattered wave phase axis fitting formula and an objective function constructed with the goal of maximizing superposition energy. Combined with an energy truncation algorithm based on the energy distribution curve, it extracts and superimposes the scattered wave signal, thereby realizing dynamic and precise identification of shallow to mid-level cracks.

[0056] Furthermore, the acquisition module 301 is specifically used for: acquiring co-offset seismic data of the target area; separating the scattered wave field from the co-offset seismic data to obtain scattered wave field data.

[0057] Furthermore, the aforementioned tilt-domain scattered wave phase axis fitting formula is a quadratic function of the offset tilt angle; the search module 302 is specifically used to: use the Kirchhoff migration algorithm to offset the scattered wave field data to the tilt domain to obtain the tilt gather; for each imaging point in the tilt gather, based on the energy value of the imaging point at different offset tilt angles and different times, search for the quadratic coefficients of the tilt-domain scattered wave phase axis fitting formula within a preset range of quadratic coefficients to obtain the target quadratic coefficients that satisfy the energy symmetry constraint and maximize the function value of the objective function; determine the tilt-domain scattered wave phase axis fitting formula under the target quadratic coefficients as the optimal energy superposition path for the imaging point, and determine the superposition energy value under the optimal energy superposition path as the target energy value for the imaging point.

[0058] Furthermore, the objective function described above is: ; in, Indicates the offset angle. This represents the formula for fitting the phase axis of the scattered wave in the tilt domain. A express The coefficient of the quadratic term, A min express A The minimum value, A max express A The maximum value, Indicates the focused imaging point of the inclined channel. The energy value at that location, This indicates traversing all A The value of the maximum superimposed energy.

[0059] Furthermore, the above energy symmetry constraint is as follows: ; in, This is the default value.

[0060] Furthermore, the aforementioned truncation module 303 is specifically used to: sort the target energy values ​​of each imaging point in ascending order to obtain a sorting result; construct the energy distribution curve of the imaging points in the offset tilt domain based on the sorting result, and calculate the curvature of each imaging point; determine the noise imaging point in each imaging point based on the sorting position corresponding to the imaging point with the largest curvature; and obtain the target imaging result by setting the target energy value of the noise imaging point in each imaging point to 0.

[0061] Furthermore, the curvature of the aforementioned imaging points is obtained through differential approximation calculation.

[0062] The landslide crack evolution monitoring device based on weak scattering wave imaging provided in this embodiment has the same implementation principle and technical effect as the aforementioned landslide crack evolution monitoring method based on weak scattering wave imaging embodiment. For the sake of brevity, any parts not mentioned in the embodiment of the landslide crack evolution monitoring device based on weak scattering wave imaging can be referred to the corresponding content in the aforementioned landslide crack evolution monitoring method embodiment based on weak scattering wave imaging.

[0063] like Figure 4 As shown, an electronic device 400 provided in this embodiment of the invention includes: a processor 401, a memory 402 and a bus. The memory 402 stores a computer program that can run on the processor 401. When the electronic device 400 is running, the processor 401 and the memory 402 communicate through the bus. The processor 401 executes the computer program to realize the above-mentioned landslide crack evolution monitoring method based on weak scattering wave imaging.

[0064] Specifically, the memory 402 and processor 401 mentioned above can be general-purpose memory and processor, without any specific limitations here.

[0065] This invention also provides a computer-readable storage medium storing a computer program. When executed by a processor, this computer program performs the landslide crack evolution monitoring method based on weak scattering wave imaging described in the preceding method embodiments. The computer-readable storage medium includes various media capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), RAM, magnetic disk, or optical disk.

[0066] In this document, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" in this document means any combination of at least two of any one or more elements. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.

[0067] In all examples shown and described herein, any specific values ​​should be interpreted as merely exemplary and not as limitations; therefore, other examples of exemplary embodiments may have different values.

[0068] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0069] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of modules is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interface; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0070] The modules described as separate components may or may not be physically separate. Similarly, the components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0071] In addition, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0072] 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; and these 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.

Claims

1. A method for monitoring the evolution of landslide cracks based on weak scattering wave imaging, characterized in that, include: Acquire scattered wave field data from co-offset seismic data of the target area; Based on the preset in-phase axis fitting formula of the scattering wave in the tilt domain and the objective function constructed with the goal of maximizing superposition energy, under the constraint of energy symmetry, the optimal energy superposition path of each imaging point in the tilt channel corresponding to the scattering wave field data is searched to obtain the target energy value of each imaging point. By truncating the energy of the noise imaging points in each imaging point using the energy distribution curve, the target imaging result of the landslide crack evolution structure in the target area is obtained. The tilt-domain scattered wave phase axis fitting formula is a quadratic function of the offset tilt angle. The step of searching for the optimal energy superposition path for each imaging point in the tilt gather corresponding to the scattered wave field data, under energy symmetry constraints, based on the objective function constructed using the preset tilt-domain scattered wave phase axis fitting formula, to obtain the target energy value for each imaging point, includes: using the Kirchhoff migration algorithm to offset the scattered wave field data to the tilt domain, obtaining a tilt gather; for each imaging point in the tilt gather, searching for the quadratic coefficients of the tilt-domain scattered wave phase axis fitting formula within a preset range of quadratic coefficients, based on the energy values ​​of the imaging point at different offset tilt angles and different times, to obtain the target quadratic coefficients that satisfy the energy symmetry constraints and maximize the function value of the objective function; determining the tilt-domain scattered wave phase axis fitting formula under the target quadratic coefficients as the optimal energy superposition path for the imaging point, and determining the superposition energy value under the optimal energy superposition path as the target energy value for the imaging point. The objective function is: ； in, Indicates the offset angle. This represents the formula for fitting the phase axis of the scattered wave in the tilt domain. A express The coefficient of the quadratic term, A min express A The minimum value, A max express A The maximum value, Indicates the focused imaging point of the inclined channel. The energy value at that location, This indicates traversing all A The value of the maximum superimposed energy.

2. The landslide crack evolution monitoring method based on weak scattering wave imaging according to claim 1, characterized in that, The acquisition of scattered wave field data from the co-offset seismic data of the target area includes: Acquire co-offset seismic data for the target area; The scattered wave field is separated from the co-offset seismic data to obtain scattered wave field data.

3. The landslide crack evolution monitoring method based on weak scattering wave imaging according to claim 1, characterized in that, The energy symmetry constraint is: ； in, This is the default value.

4. The landslide crack evolution monitoring method based on weak scattering wave imaging according to claim 1, characterized in that, The step of truncating the energy of noisy imaging points in each imaging point using the energy distribution curve to obtain the target imaging result of the landslide crack evolution structure in the target area includes: The target energy values ​​of each imaging point are sorted in ascending order to obtain the sorting result; Based on the sorting results, construct the energy distribution curve of the imaging points in the offset tilt domain, and calculate the curvature of each imaging point; Based on the sorting position corresponding to the imaging point with the largest curvature, the noisy imaging points in each of the imaging points are determined; The target imaging result is obtained by setting the target energy value of the noise imaging point in each of the imaging points to 0.

5. The landslide crack evolution monitoring method based on weak scattering wave imaging according to claim 4, characterized in that, The curvature of the imaging point is obtained by differential approximation calculation.

6. A landslide crack evolution monitoring device based on weak scattering wave imaging, characterized in that, include: The acquisition module is used to acquire scattered wave field data from co-offset seismic data of the target area; The search module is used to search for the optimal energy superposition path of each imaging point in the tilt field data corresponding to the scattered wave field data, based on the preset tilt domain in-phase axis fitting formula and the objective function constructed with the goal of maximizing superposition energy, under the constraint of energy symmetry, so as to obtain the target energy value of each imaging point. The truncation module is used to truncate the energy of the noise imaging points in each of the imaging points through the energy distribution curve, so as to obtain the target imaging result of the landslide crack evolution structure in the target area. The in-phase axis fitting formula for the scattered wave in the tilt domain is a quadratic function of the offset tilt angle. The search module is specifically used to: offset the scattered wave field data to the tilt domain using the Kirchhoff migration algorithm to obtain a tilt gather; for each imaging point in the tilt gather, based on the energy values ​​of the imaging point at different offset tilt angles and different times, search for the quadratic coefficients of the in-phase axis fitting formula for the scattered wave in the tilt domain within a preset range of quadratic coefficients to obtain target quadratic coefficients that satisfy energy symmetry constraints and maximize the function value of the objective function; determine the in-phase axis fitting formula for the scattered wave in the tilt domain under the target quadratic coefficients as the optimal energy superposition path for the imaging point, and determine the superposition energy value under the optimal energy superposition path as the target energy value for the imaging point; The objective function is: ； in, Indicates the offset angle. This represents the formula for fitting the phase axis of the scattered wave in the tilt domain. A express The coefficient of the quadratic term, A min express A The minimum value, A max express A The maximum value, Indicates the focused imaging point of the inclined channel. The energy value at that location, This indicates traversing all A The value of the maximum superimposed energy.

7. An electronic device comprising a memory and a processor, wherein the memory stores a computer program executable on the processor, characterized in that, When the processor executes the computer program, it implements the landslide crack evolution monitoring method based on weak scattering wave imaging as described in any one of claims 1-5.

8. A computer-readable storage medium storing a computer program thereon, characterized in that, The computer program is executed by the processor to perform the landslide crack evolution monitoring method based on weak scattering wave imaging as described in any one of claims 1-5.

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