236 results about "Wave equation" patented technology

According to the micro-seismic source intelligent positioning method and the model training method and system, physical laws such as a seismic wave equation are integrated, physical loss and data loss are comprehensively considered, the adaptability of the model to a complex geological environment is improved, micro-seismic source positioning challenges in the complex geological environment can be effectively dealt with, and the positioning accuracy of the micro-seismic source in the complex geological environment is improved. Noise immunity and positioning precision are improved, and more reliable technical support is provided for safety monitoring of underground engineering.

The invention discloses a microseismic source positioning method, device and system, and a storage medium. The method comprises the following steps: dividing a microseismic data sample data set into a training set and a test set; according to the training set, constructing a microseism inversion subnet containing a Swin Transform encoder, and according to the training set, constructing a microseism inversion subnet containing a Swin Transform encoder; the micro-seismic forward modeling subnet realizes seismic wave field continuation by inputting a micro-seismic source position and a speed model and utilizing a recurrent neural network structure and a convolution operator, and establishes a forward modeling subnet based on a wave equation; constructing an inversion-forward modeling closed-loop neural network according to the micro-seismic inversion subnet and the forward modeling subnet based on the wave equation; and inputting the test set into the inversion-forward closed-loop neural network to carry out micro-seismic source positioning. By adopting the technical scheme of the invention, the limitations on physical constraint, feature modeling and anti-noise capability in the prior art are overcome.

The invention provides a multiple longitudinal and transverse wave joint detection method based on a seabed crawler, which belongs to the technical field of geophysical exploration, and constructs an original longitudinal and transverse wave signal matrix by transmitting multi-frequency longitudinal and transverse wave signals and receiving stratum reflection signals. Fourier transform is utilized to extract frequency characteristics, physical analysis is carried out in combination with a wave equation, and a longitudinal and transverse wave interference matrix is constructed and weighted fusion is carried out. And constructing an error compensation matrix according to the crawl device attitude data, and performing interference compensation on the joint interference matrix. And performing time-frequency analysis through wavelet transform, extracting specific time-frequency features, inputting the specific time-frequency features into a pre-trained stratum classification prediction model, realizing anti-interference prediction on the type and thickness of the seabed stratum structure, finally drawing a seabed three-dimensional geological profile map according to a prediction result, and marking a key geological structure and a resource distribution region. The technical problem that accurate recognition and resource distribution positioning of the seabed stratum structure are affected due to much external interference in the seabed geological exploration process is solved.

The invention discloses a three-dimensional intelligent seismic velocity modeling method based on a two-dimensional self-attention U-shaped network and low-rank adaptation, and belongs to the technical field of seismic services of geophysical exploration. The problems that in the prior art, a traditional three-dimensional intelligent seismic velocity modeling method is low in efficiency and insufficient in model generalization ability are solved. The method comprises the following steps: generating a three-dimensional hybrid geological velocity model, obtaining multi-shot seismic record data based on a wave equation, obtaining a three-dimensional initial velocity model through Gaussian filtering, and obtaining an imaging result by adopting reverse time migration; carrying out dimension reduction processing on the three-dimensional data, and constructing a multi-dimensional pre-training sample set; carrying out pre-training by utilizing the training set to obtain an optimized LAUNet framework; and performing fine tuning by adopting a dual-stage collaborative optimization mechanism, and obtaining a fine-tuned LAUNet framework through a LoRA * method. The method effectively improves the model inversion efficiency, and can be applied to the establishment of a three-dimensional intelligent seismic velocity model.

The invention discloses a least square reverse time migration method and device for a three-dimensional anisotropic medium, and the method comprises the steps: building a forward equation of the three-dimensional anisotropic medium for a seismic block to be subjected to reverse time migration, and obtaining a background wave field under the three-dimensional anisotropic medium through regional forward modeling; determining a three-dimensional anisotropic medium adjoint wave field by using a pre-established wave equation of the adjoint wave field; according to the adjoint wave field and the background wave field, determining an initial gradient by using a pre-established least square reverse time migration cross-correlation equation, and obtaining a migration result according to the initial gradient; and updating an imaging result through a conjugate gradient method according to the offset result to obtain a reflected wave record.

The invention discloses a calculation method and a calculation device of an earthquake propagation direction. The calculation method comprises the steps that a wave equation of seismic time-space domain sound waves is acquired, and wave field information is acquired according to the wave equation; calculating a wave field component according to the wave field information; and substituting the wave field component and the wave field information into a pre-constructed seismic wave field propagation direction vector expression. According to the technical scheme, the situation that deviation occurs in the seismic wave propagation direction analysis can be effectively reduced, and the calculation precision is improved.

The invention discloses a thermal-fluid-solid medium seismic wave simulation method, device, program and medium, and relates to the technical field of oil and gas resource geophysical exploration, and the method comprises the following steps: constructing a first-order thermal-fluid-solid coupling wave equation in an equation coupling form; constructing a coupling wave equation staggered network finite difference discrete format; analyzing numerical stability conditions; constructing a complete matching layer absorption boundary; and performing forward modeling simulation of seismic waves in the three-layer heat-fluid-solid coupling model according to the model parameters and the seismic source parameters. The method breaks through the assumption that the classical seismic wave propagation theory is completely elastic under the isothermal or adiabatic deformation condition, considers the influence of temperature change on the propagation of seismic waves in fluid and solid media, and improves the description precision of the propagation process of the seismic waves in the heat-fluid-solid media. And the capability of inverting the underground temperature field based on seismic wave data in the later period can be effectively improved.

The invention provides a frequency dispersion curve calculation method based on a decoupling type Legendre-Gauss-Labatto spectral element method, and belongs to the technical field of discrete solution of guided wave propagation in a thin plate, and the method comprises the following steps: S1, constructing a wave equation which comprises a Cartesian space coordinate system based on an orthotropic plate, and combining a constitutive equation, a geometrical relationship under the coordinate system and guided wave displacement to obtain a wave dispersion curve; substituting into a control equation when the volume force is zero to obtain an improved three-dimensional elastic wave equation; s2, a differential matrix is constructed, wherein discretization and decoupling are carried out on a wave equation on the basis of a Lagrange interpolation basis function of a Legendre-Gauss-Labatto node; s3, explicitly embedding the stress free boundary condition into the solving process through matrix line transformation, and solving to obtain a frequency dispersion curve, the derivation process is simplified, the boundary and the interior of the material are decoupled, and the physical significance is clearer. And meanwhile, the high-precision advantage of the spectrum method is maintained, and the calculation rate is remarkably improved.

The present application belongs to the technical field of oil and gas exploration and seismic data processing, and discloses a seismic data interpolation method and system based on CBAM-Res2Unet network. The method solves the problems of limited receptive field caused by fixed convolution kernel in traditional ResUNet network and non-selective transmission of low-level features in skip connection. The method comprises: generating seismic records through wave equation forward modeling and constructing a training set containing random missing data; designing CBAM-Res2Unet network, wherein the encoder and the decoder adopt Res2Net modules containing compression excitation modules, and the multi-scale feature extraction capability is enhanced through grouped convolution and hierarchical residual connection; introducing CBAM modules in the skip connection to adaptively weight the features by using channel and spatial attention mechanisms; and adding a spectral normalization layer in the deep network to stabilize the training. The system comprises data acquisition, network generation, training and interpolation modules. Through multi-scale feature fusion, attention mechanism and stability optimization, the present application realizes high-precision interpolation of complex missing seismic data.

The embodiment of the specification discloses a self-adaptive variable grid forward modeling method for middle-deep dry hot rock mass. p , a transverse wave velocity V s and a medium density p model, pre-setting forward modeling parameters; performing self-adaptive variable grid processing on the velocity model, determining a mapping relationship between coordinate systems, and determining a wave equation under variable grid based on the mapping relationship; performing self-adaptive variable grid processing on the velocity model, determining a mapping relationship between coordinate systems, obtaining the underground medium longitudinal wave velocity, transverse wave velocity and density after variable grid, determining a wave equation under variable grid based on the mapping relationship, and generating final regular grid horizontal direction longitudinal wave field, horizontal direction transverse wave field, vertical direction longitudinal wave field and vertical direction transverse wave field information by using the mapping relationship reversely according to the wave field information in each direction at a specific moment after the variable grid, so that the memory occupation is small and the calculation speed is faster.

The invention discloses a power line real-time identification and spatial positioning method based on depth vision assistance, and relates to the technical field of power line real-time identification, and the method comprises the steps: constructing a lead identification and positioning frame with a strong generalization capability through deep fusion of a physical law and a depth vision technology; a vibration propagation model based on a wave equation can accurately capture signal interruption characteristics at a cross point, and a frequency domain fusion mechanism significantly improves the linear structure recovery capability of a backlight scene; dynamic vibration phases are coded into a continuous radiation density function by adopting an implicit neural radiation field technology, and the dependence of traditional point cloud reconstruction on dense sampling is broken through; and a dynamic deformable convolution kernel is introduced to realize self-adaptive tracking of the wire form through a physical deformation model, so that extreme working conditions such as icing can be effectively handled.

The invention discloses a robust full-waveform inversion method of a first-arrival constraint physical embedded recurrent neural network, which comprises the following steps of: solving a wave equation through forward propagation of the physical embedded recurrent neural network, generating a forward shot gather record, screening out a seismic trace with high matching degree with observation data by using first-arrival information, and participating in loss calculation to obtain a seismic trace with high matching degree with observation data; and along with the proceeding of the inversion process, the range of seismic traces participating in the inversion is gradually expanded, it is ensured that the inversion result gradually tends to a globally optimal solution, back propagation is carried out by using space-time field gradient information recorded by forward propagation of the recurrent neural network, the speed parameter is further optimized, and the inversion precision is improved. According to the method, the physical process of seismic wave propagation is embedded into the recurrent neural network, the first arrival constraint and the progressive inversion strategy are introduced, the dependence of the FWI on the initial model is remarkably reduced, and the underground velocity field structure can still be accurately reconstructed even if the initial model and a real model have remarkable deviation.

The invention belongs to the technical field of oil-gas exploration and seismic data processing, and discloses a seismic data interpolation method and system based on a CBAM-Res2Unet network. According to the method, the problems that the receptive field is limited and low-level characteristics in jump connection are not selectively transmitted due to a fixed convolution kernel in a traditional ResUNet network are solved. The method comprises the following steps: generating a seismic record through wave equation forward modeling, and constructing a training set containing random missing data; a CBAM-Res2Unet network is designed, an encoder and a decoder of the CBAM-Res2Unet network adopt Res2Net modules containing compression excitation modules, and the multi-scale feature extraction capability is enhanced through grouping convolution and layered residual connection; introducing a CBAM module in jump connection, and adaptively weighting features by using a channel and a space attention mechanism; a spectrum normalization layer is added to the deep layer of the network to stabilize training. The system comprises a data acquisition module, a network generation module, a training module and an interpolation module. According to the invention, through multi-scale feature fusion and attention mechanism and stability optimization, high-precision interpolation of complex missing seismic data is realized.

The invention discloses a surface shallow creep detection method and system based on a time reversal technology, relates to the technical field of geological engineering, and solves the problem that the surface shallow creep detection precision is relatively low. The method comprises the following steps: acquiring multi-source physical field data of an earth surface shallow layer of a target area; establishing a simulation model of the surface shallow layer based on the multi-source physical field data; sending a first signal to the surface shallow layer through an antenna, and receiving a returned second signal; performing time reversal on the second signal to obtain a third signal; based on the simulation model, simulating a signal propagation path of a third signal sent by the antenna to the surface shallow layer to obtain target time inversion data; and comparing the target time inversion data with the historical time inversion data to obtain a creep abnormal region. Creep detection is carried out by adopting the time reversal technology, the creep abnormal area can be accurately positioned by utilizing the time reversibility of the wave equation and combining the self-consistent focusing characteristic of the time reversal signal at the real source point, and the creep detection precision is improved.

The invention relates to the technical field of coal seam inversion and imaging, in particular to a reflection channel wave imaging method and system considering the layering attenuation characteristic of a thick coal seam, and the method comprises the steps: constructing a coal seam layering geologic model, setting the initial wave velocity and initial quality factor of each layer, and forming an initial parameter field; setting an artificial seismic source and a plurality of detection points, exciting a seismic source signal at the artificial seismic source, recording seismic source information, and collecting a seismic wave response signal of each detection point; performing forward modeling by using a fractional order viscoelastic wave equation considering a spatial variable quality factor; carrying out full waveform inversion to obtain an inversion model; and on the basis of the inversion model, a level set function and a self-adaptive grid division strategy are adopted to express a barrier boundary in the coal seam to execute pre-stack wave field separation reverse time migration imaging, and a coal seam structure image is generated. The method can significantly improve the imaging resolution and calculation efficiency of the coal seam structure, and achieves the high-precision recognition of the boundary of the obstacle.

A seismic energy estimation method based on generalized spherical wave propagation, relating to the field of earthquake engineering. The method comprises: determining initial seismic total energy and seismic power on the basis of seismic source characteristics and a seismic magnitude; determining a generalized spherical wave equation, and calculating an average energy flow density of propagated waves on the basis of the wave equation of spherical waves; using an earth surface spherical crown, which is projected on the zone of a seismic source surface, as a main impact zone of seismic spherical waves on an earth surface, the main impact zone being equivalent to a square and performing grid division, and calculating the hypocentral distance between the center of each grid and the center of a seismic source so as to form a hypocentral distance matrix; and expressing the generalized spherical wave energy flow density of each grid as the sum of the energy flow density of longitudinal waves and the energy flow density of transverse waves, performing grid subdivision, estimating the average amplitude of each subdivided grid mass unit within a seismic action period, and evaluating the seismic action energy of a site. The present invention estimates the action of seismic energy on the earth surface by defining the generalized spherical wave propagation of seismic source energy, thereby more accurately evaluating the distribution condition of seismic energy on the earth surface.

The invention relates to the technical field of coal seam stress prediction, in particular to a coal seam three-dimensional stress prediction and visualization method, system and device and a medium, and the method comprises the steps: setting an artificial seismic source and a detection point, exciting a seismic source signal, and collecting a seismic wave response signal and a stress value; carrying out wave field forward modeling simulation through a time fractional order viscoelastic wave equation to obtain a forward simulation wave field, and carrying out full waveform inversion to output three-dimensional wave velocity data; performing reverse time migration imaging on the seismic wave response signal to obtain a three-dimensional coal seam structure mask pattern; performing slicing processing on the three-dimensional wave velocity data and the three-dimensional coal seam structure mask pattern along the same spatial dimension, then combining the three-dimensional wave velocity data and the three-dimensional coal seam structure mask pattern into an input tensor, inputting the input tensor into a convolutional neural network, and outputting a two-dimensional stress prediction slice; and splicing the two-dimensional stress prediction slices to construct a three-dimensional stress body, generating three-dimensional stress point cloud data, and further generating a three-dimensional stress grid model and a structure-stress integrated visual three-dimensional cloud picture. According to the invention, high-precision three-dimensional stress prediction and real-time early warning of the coal seam can be realized.

The invention discloses an intelligent exploration data analysis system and method, and relates to the technical field of geological exploration, and the system comprises a test module, an analysis module and a prediction module. According to the method, geological electromagnetic and stratum original data are collected in a multi-dimensional mode, forward modeling and inversion are carried out on electromagnetic data, the relation between underground conductivity and an electromagnetic field can be accurately simulated, data errors are effectively reduced, the electromagnetic data processing accuracy is improved, a geological unit calculates a seismic wave field based on wave equation numerical simulation, and the electromagnetic data processing accuracy is improved. The prediction wave field and the observation wave field are substituted into an objective function, the stratum velocity and density are accurately inverted, the geological data processing precision is guaranteed, the joint unit organically combines an electromagnetic inversion objective function, an earthquake full-waveform inversion objective function and a parameter correlation constraint term through a joint optimization formula, multi-source data depth fusion is achieved, and the geological data processing precision is guaranteed. The limitation of single data processing is avoided, and the underground geological condition is reflected more comprehensively.

The invention relates to the technical field of elastic waves, and discloses an elastic wave full-waveform inversion method, which comprises the steps of inputting observed seismic data into a preset neural network encoder, and extracting to obtain high-dimensional feature representation; inputting the high-dimensional feature representation into a preset neural network decoder to obtain a gradient update value; obtaining an elastic parameter model based on the gradient update value and the initial elastic parameter model; obtaining Lame parameters based on the longitudinal wave velocity, the transverse wave velocity and the medium density; based on a Lame parameter and an elastic wave equation, obtaining synthetic seismic data; obtaining an objective function based on the observed seismic data and the synthesized seismic data; using the target function to iteratively update the preset neural network weight until the loss function reaches a first preset threshold value or the number of iterations reaches a second preset threshold value, and obtaining a target gradient update value; and based on the target gradient update value and the target elastic parameter model, obtaining a final target elastic parameter model so as to relieve discomfort caused by simultaneous inversion of multiple elastic parameters.

The invention discloses an elastic reverse time migration imaging method based on deviatoric stress characterization, and relates to the technical field of exploration geophysics. Deviatoric stress is introduced into a conventional elastic wave equation, and a speed-deviatoric stress elastic wave equation describing stress propagation characteristics is obtained through derivation; based on Hooke's law, P wave contribution in total partial strain is removed through partial strain decomposition, decoupling of P-S wave stress components is achieved, and correctness of amplitude, phase and physical unit of a decoupling wave field is guaranteed; and then a joint imaging condition with the average stress as a seismic source wave field and the multi-stress component as a receiving wave field is constructed, PP waves are subjected to normalization superposition through the average stress and the deviatoric stress, and PS waves are subjected to shear stress imaging. According to the method, the sensitivity to heterogeneity and local stress variation of underground media can be remarkably improved, P-S wave crosstalk and imaging noise are effectively eliminated, the imaging precision and resolution of a complex geologic structure are greatly improved, and a reliable technical means is provided for high-precision seismic exploration of complex oil and gas reservoirs.

The invention relates to a meshbelt structure simulation method with heterogeneous left and right selvedges based on parameterized segmented modeling, which comprises the following steps of: deconstructing a meshbelt into three heterogeneous functional areas of left overlock, middle main body and right connection, and independently controlling by adopting a Bezier curve, a composite wave equation and a catenary fusion model respectively; the synchronous accurate expression of the closeness of the left side overlock coil, the warp and weft interweaving stability of the main body and the mechanical rationality of the right side U-shaped connection is realized, and the problem of geometric distortion caused by unified modeling in the prior art is solved. According to the method, a cross-scale coupling equation of tension (T), a friction coefficient (mu) and linear density (rho) is introduced, and a closed-loop mapping relation of technological parameters, geometrical morphology and mechanical response is established. For example, when the tension of the braid is increased, the curvature radius of the U-shaped connecting part is automatically reconstructed according to a formula, so that parameter regulation and control are upgraded from experience trial and error to intelligent optimization of physical driving.

The invention relates to a high-order staggered grid viscous sound medium reverse time migration tunnel advanced detection method and system, and belongs to the field of tunnel engineering geophysical prospecting. According to the method, a viscoelastic anisotropic TTI medium anisotropy wave equation expressed by a fractional Laplace operator is deduced, and a viscoelastic anisotropic TTI medium first-order speed-stress elastic wave equation is solved by adopting a high-order staggered grid finite difference method. According to the invention, the wave field information at any moment is obtained, so that the propagation process of seismic waves in an underground medium is simulated more accurately. In order to solve the problem of reflection possibly caused by artificial boundaries, a PML (perfectly matched layer) absorption boundary processing method of a new attenuation function is adopted. According to the method, seismic waves can be effectively absorbed, reflection is avoided, and therefore simulation stability and accuracy are guaranteed. Generally speaking, the invention provides an accurate and stable tunnel advanced detection forward modeling method, and a reverse time migration algorithm is carried out in an attenuation TTI medium.

The invention discloses a generalized finite difference scalar wave unfavorable geology frequency dispersion analysis method and related equipment, relates to the field of unfavorable geology analysis, and mainly aims to solve the problem that the conventional unfavorable geology analysis is relatively low in flexibility and accuracy. The method comprises the following steps: generating field nodes of a target area; performing field variable approximation on the field nodes to determine a discretized wave equation; and performing frequency dispersion analysis and wave field simulation based on the discretized wave equation to obtain an output result of unfavorable geology. The method is used for the unfavorable geological frequency dispersion analysis process of the generalized finite difference scalar waves.

The present invention relates to a near-surface imaging method and system for wave equation seismic surface wave full-frequency dispersion spectrum inversion, comprising: collecting data acquisition information of a target area and inputting the data acquisition information into a grid subdivision model to obtain an observation surface wave ground acquisition system; solving the elastic wave equation to obtain simulated surface wave data in the ground acquisition system; calculating an accompanying earthquake source based on the observed surface wave data and the simulated surface wave data; cross-correlating the forward wavefield of the actual earthquake source with the reverse wavefield of the accompanying earthquake source to calculate the gradient of an updated seismic wave velocity model, and updating a network subdivision model based on the model update gradient; inputting the data to be measured into the updated grid subdivision model to obtain near-surface imaging results from wave equation seismic surface wave full-frequency dispersion spectrum inversion. Because the surface wave dispersion spectrum is used as inversion data, the method avoids manually picking dispersion curves, reduces human errors, and improves the efficiency of large-scale seismic data processing.

The invention relates to a stable Q compensation reverse time migration method for seismic exploration data, a medium and equipment, and belongs to the technical field of geophysical exploration data processing. According to the method, based on a fractional order Laplace viscous acoustic wave equation, a physically guided time-varying regularization compensation operator is constructed in a wavenumber domain, the energy amplitude of a previous time step length is introduced as a reference, an energy growth monitoring mechanism is established, and the energy growth is monitored. And designing a three-level adaptive constraint system: local energy growth constraint, high-frequency adaptive attenuation and boundary region stabilization processing, and realizing adjustment of excessive compensation and adaptive suppression of noise in the wave field continuation process. According to the method, amplitude attenuation and phase frequency dispersion caused by stratum absorption are effectively recovered, meanwhile, the stability of numerical calculation can be guaranteed, the precision and resolution of deep structure imaging are remarkably improved, and good numerical stability and anti-noise capacity are achieved.

The application discloses an explicit finite element parallel computing method for seismic wave simulation, comprising the following steps: constructing a three-dimensional computing domain, generating an unstructured finite element grid based on real terrain and velocity structure data; performing domain decomposition on the computing domain, and dividing the grid into multiple sub-regions; distributing the tasks of the sub-regions to parallel computing nodes, discretely solving a three-dimensional elastic wave equation containing a damping term by using explicit time integration and a lumped mass matrix, synchronously calculating time sequences of wave fields of the sub-regions; integrating the results to obtain seismic wave field distribution, and outputting ground motion parameters of a target region. By constructing an integrated explicit finite element parallel computing framework of a seismic source-medium-terrain, efficient, stable and high-precision simulation of seismic wave propagation under complex geological conditions is realized, and the reliability of strong ground motion prediction is significantly improved.

The invention discloses a guided wave damage detection and positioning method and system for an underwater water filling pipeline based on an SAFE-PML model. The method comprises the following steps: establishing a guided wave SAFE wave equation of a water filling pipeline waveguide system in a limited fluid domain; the guided wave SAFE wave equation of the water filling pipeline in the limited fluid domain is expanded to the water filling pipeline waveguide system in the infinite fluid domain through a PML coordinate stretching function, and a complete guided wave SAFE wave equation of the underwater water filling pipeline waveguide system is obtained; the guided wave mode speed and the wave structure existing in the complete underwater water filling pipeline are extracted; the independent guided wave mode is excited for the wave structure of the guided wave mode, and damage detection and positioning are carried out on the pipeline through the time characteristics of the reflected wave of the guided wave time domain signal. The damage detection of the underwater water filling pipeline is realized by analyzing the propagation characteristics of the underwater water filling pipeline.

The invention discloses a concrete ultrasonic propagation characteristic modeling method and system, and relates to the technical field of ultrasonic non-destructive testing, and the method comprises the steps: obtaining the rheological behavior data of unsolidified cement slurry, building a concrete slurry fractional order viscoelastic constitutive model by adopting a Caputo type fractional order derivative, and obtaining a complex modulus; constructing a frequency domain wave equation by using the complex modulus, and calculating ultrasonic attenuation coefficients under different frequencies; dividing the concrete medium into thin layers along the propagation direction, and setting the thickness and characteristic impedance of each layer; a Waterman-Truell model is used to calculate a corrected complex wave number, and a structure factor is combined to correct scattering space correlation; calculating the total attenuation value of the attenuation coefficient of each thin layer, and establishing a propagation path total attenuation model. According to the method, the frequency response consistency is enhanced, the modeling precision of the heterogeneity and the multi-scale scattering characteristic of the concrete is improved, and the method has higher simulation accuracy and physical interpretation.

The application provides a warning method and system for the tipping moment of a thermoacoustic system under Lévy noise, and relates to the technical field of thermoacoustic system stability analysis and early warning control, which comprises the following steps: based on the physical model of the thermoacoustic system, a non-uniform wave equation describing the pressure and velocity fluctuation of the system is constructed; the Galerkin modal expansion and Taylor expansion truncation are performed on the equation, and a random differential equation model is established by combining the time-varying control parameters and Lévy noise; the random differential equation model is solved by the Monte Carlo simulation and the random fourth-order Runge-Kutta numerical method, and the amplitude sequence of the thermoacoustic system changing with time is obtained; based on the probability distribution of the amplitude sequence, the change of the system dynamics characteristics is quantified by calculating the Shannon entropy, and the sequence of the Shannon entropy changing with time is obtained; the warning moment when the Shannon entropy sequence first passes through the preset threshold is determined, and the warning domain is generated according to the time difference between the warning moment and the actual tipping moment of the thermoacoustic system, so that the warning for the tipping moment of the thermoacoustic system is realized.

The present invention discloses a method for generating a reflection angle domain point spread function based on an LSTM network, belonging to the field of geophysical exploration technology, comprising the following steps: S1, selecting reference points and constructing labels through ray tracing and wave equation forward simulation; S2, training an LSTM network as a ray tracing proxy model for the entire imaging domain; S3, predicting traveltime gradients and amplitude factors through the ray tracing proxy model; S4, pairing seismic sources with receivers and calculating reflection angles through traveltime gradients; S5, solving for the illumination wave number vector and solving for the wave number domain point spread function in combination with the illumination intensity; S6, performing an inverse Fourier transform on the wave number domain point spread function to obtain a spatial domain point spread function; and S7, solving a deconvolution problem and optimizing the processing of angle gathers. The present invention can improve the computational efficiency of solving Green's functions by seismic wave ray tracing, eliminate the imaging response described by the point spread function from the imaging result, and improve the resolution of the imaging result and the balance of illumination intensity.