129 results about "Full waveform" patented technology

The invention belongs to the technical field of seismic exploration, and discloses a robust full-waveform inversion method, system and device based on generative modeling, and a medium, and the method comprises the steps: obtaining seismic observation data; the method comprises the following steps: starting from random Gaussian noise, establishing a model space comprising a plurality of initial velocity models through an unconditional score model, and determining a global optimal initial velocity model of the model space by adopting a strategy search algorithm; de-noising is carried out on the global optimal initial velocity model based on back diffusion, seismological observation data are introduced as observation constraints, the velocity model is updated by calculating the mismatch gradient of forward modeling data of the current velocity model and the seismological observation data, and an implicit condition sample is obtained; performing forward diffusion processing on the implicit condition sample to obtain a speed model for a subsequent annealing time step; and when the annealing process reaches a preset condition, outputting a final speed model. According to the method, the robustness and accuracy of full-waveform inversion are improved, and the bottleneck problem of traditional full-waveform inversion is solved.

The invention discloses a stratigraphic water content layering inversion method based on a shallow seismic full waveform, and relates to the technical field of geophysical exploration data processing, and the method comprises the following steps: 1, under the same survey line condition, synchronously obtaining a seismic wave full waveform, complex impedance and an induced polarization frequency spectrum; 2, constructing a layered initial model containing a layer boundary line and an in-layer water content initial value; based on the layered initial model, executing dual-domain quantile alignment interface keeping iteration until convergence, and obtaining a final layer boundary line and an in-layer water content field; the double-domain quantile alignment interface maintaining iteration comprises the following steps: updating an in-layer moisture content field and a layer boundary line according to a seismic wave full waveform; and performing total variation regularization processing on the updated in-layer water content field to maintain the transition characteristic of the layer boundary line. According to the method, an efficient and reliable solution with actual guidance value is provided for mineral resource exploration, geological structure detection, groundwater survey and engineering geology evaluation.

The invention discloses a method for quantitatively evaluating the three-dimensional shape of a thinning defect in a plate under ultrasonic guided wave field undersampling scanning, belongs to the field of industrial nondestructive testing, and particularly relates to high-precision three-dimensional shape reconstruction and thickness loss quantification of a corrosion defect in a metal plate shell structure (such as aerospace skin, a pressure vessel wall, an oil pipeline and the like). According to the method, sparse sampling guided wave field reconstruction, full waveform inversion (FWI) and priori knowledge constraint are fused, Shannon sampling theorem limitation is broken through, efficient measurement of corrosion depth, contour and distribution under the conditions of a single excitation source and a limited view angle is achieved, and the method is suitable for rapid online detection in a complex industrial environment.

The invention relates to a biological tissue full-waveform inversion ultrasonic tomography method which comprises the following steps: placing ultrasonic transducers in a pure water medium with known sound velocity, and recording ultrasonic signal data of each transducer array element; setting a virtual source array in each transducer array element, constructing an optimization problem of sound source directivity and receiver response, and performing iterative optimization to obtain a final response coefficient and a virtual source signal of each transducer array element; the method comprises the following steps: fixing a biological tissue to be detected in an ultrasonic transducer, and collecting experimental observation signals received by each transducer array element; setting a sound velocity model to carry out forward simulation, taking the obtained virtual source signal as a sound source output, interacting with the sound velocity model, and multiplying by a response coefficient to obtain a forward simulation signal; and performing iterative updating on the sound velocity model according to the experimental observation signal and the forward simulation signal to obtain an ultrasonic tomography result. Compared with the prior art, the method has good flexibility and anti-noise capability, and the quality of the reconstructed image is remarkably improved.

Method and apparatus for performing a traveltime-based seismic full waveform inversion using the frequency-dependent Hann window and the source-independent scheme to generate a final velocity model of subsurface formations are provided. The method includes positioning seismic data recording sensors in the survey region; blasting at points of incidence in the survey region to generate seismic waves; and sensing and recording the seismic waves using the seismic data recording sensor. The recorded seismic waves are seismic data. The method further includes transmitting the seismic data to a computer system including one or more memories and storing the seismic data in one or more memories; storing a source wavelet in the one or more memories; performing, by the computer system, a forward modeling operation using the source wavelet; and generating, by the computer system, the final velocity model using the seismic full waveform inversion with the forward modeling operation.

The invention discloses a weighted exponential decay instantaneous phase inversion method based on automatic differentiation. Under the framework of automatic differential, the underground velocity model can be inversed by using phase and waveform information at the same time, and the advantages of constructing an initial model at the early stage of inversion and improving the resolution of the model at the later stage of inversion are combined. The method comprises the following steps: firstly, performing Hilbert transform on seismic wave data, extracting index instantaneous phase information of observation data and simulation data, and constructing a weighted instantaneous phase inversion objective function by introducing an attenuation coefficient and combining waveform information; secondly, carrying out back propagation on the loss of the objective function based on an automatic differential framework, and solving an update gradient; and finally, updating the speed model by using an SDG optimizer. According to the method, a layered multi-scale inversion effect can be realized by adjusting attenuation factor values, an objective function is constructed by weighting exponential attenuation phase information and waveform information, a better initial model is constructed before a conventional multi-scale full-waveform inversion process, the problem of cycle jump of full-waveform inversion is relieved, and the inversion efficiency is improved. And finally, a high-precision inversion result is obtained.

The present application relates to the technical field of flow measurement and industrial monitoring, in particular to a full waveform diagnosis and adaptive gas flow measurement system; comprising full waveform acquisition, feature extraction, diagnostic analysis, dynamic weight calculation and health degree evaluation modules; the system obtains acoustic channel characteristics through digital sampling and multi-dimensional analysis of ultrasonic echoes; the core is to dynamically adjust the weight of each acoustic channel according to the waveform similarity and sound velocity deviation index to obtain the standard flow and generate the measurement health index; the present application realizes the transformation from single feature analysis to full waveform physical state deconstruction, can accurately distinguish scale, noise and turbulence anomalies, and overcomes the defect that the traditional technology cannot identify the root cause of the fault.

Systems and methods for using cross-well seismic data to image reservoir structures illuminated with sources located in a lateral well and receivers located in one or more nearby lateral wells. The systems and methods include numerical FWI algorithms and workflows based on an elastic vertical transverse isotropy (VTI) anisotropic full waveform inversion (EFWI) engine. The EFWI engine is used for inversions based on the cross-well seismic data and additional data (e.g., well logs, vertical seism profiles). Inversion results include 2D / 3D maps of elastic properties (e.g., velocity, anisotropy, density, attenuation) of subsurface. The EFWI engine includes a wave propagation modeling accounting for various seismic waves propagating in the subsurface.

The invention discloses a waveform feature extraction method and system for irregular waveforms of a hyperspectral laser radar, and aims at solving the problem that asymmetric waveforms, weak echoes and overlapped echoes in multi-channel full-waveform laser radar signals are difficult to accurately decompose, modeling full-waveform signals collected by multiple spectral channels into superposition of echo components and background noise. A multi-channel waveform is preprocessed through noise threshold and pulse width combined constraint, the waveform position is determined by adopting a gravity center discrimination method, and time synchronization calibration of each channel signal is realized in combination with a multi-echo quality index. The method further utilizes a cubic B-spline function to carry out modeling on transmitted waveforms of all spectrum channels, carries out weighted accumulation on multi-channel echo signals to enhance weak echo signals, and adopts a multi-channel interconnection decomposition optimization strategy to realize accurate extraction of irregular waveform features under the constraint condition of keeping time parameters of sub-echoes of all the channels consistent.

The invention belongs to the technical field of seismic exploration, and relates to a strong interference seismic data seismic source function inversion method based on transverse local regularization, and the method comprises the steps: applying transverse local regularization constraint in a seismic source function waveform inversion process to guarantee the transverse continuity and precision of an inversion result; the nonlinearity of inversion and the degree of dependence on a speed model are reduced by using near-channel short-time data, and the overall calculation efficiency of the algorithm is ensured; seismic source function inversion is carried out under a full-waveform inversion framework, and an inversion result theoretically has the advantages of high precision and high resolution; the advantages of a cross-correlation objective function and a transverse local regularization algorithm are combined, a high-quality seismic source function inversion result can be obtained under the condition of strong interference, the transverse continuity of the inversion result is enhanced by utilizing mutual constraint between adjacent seismic source functions, and the problem of dependency of an initial seismic source is overcome to a large extent. According to the method, a seismic source function inversion result with high precision and good transverse consistency can be stably obtained under the condition that strong interference exists in seismic data.

The application discloses a two-dimensional distributed optical fiber sensing full waveform simulation method based on a discrete elastic lattice, and belongs to the technical field of seismic wave field simulation and distributed optical fiber sensing. The application comprises the following steps: receiving seismic wave data of a target geological medium layer; setting a two-dimensional calculation region according to the spatial distribution of the longitudinal wave velocity, the transverse wave velocity and the density parameters of the seismic wave, and taking the two-dimensional calculation region as a numerical simulation carrier of seismic wave propagation; discretizing the two-dimensional calculation region into a plurality of particle nodes, and connecting adjacent particle nodes through elasticity to form a discrete elastic lattice, so as to represent the mechanical properties of the stratum medium; and according to the density parameters, the longitudinal wave velocity, the transverse wave velocity or the equivalent elastic parameters of the stratum medium, the elastic connection between the particle nodes is endowed with corresponding elastic coefficients. The application provides a reliable numerical tool for DAS deployment design, data interpretation and seismological inversion, and can be widely applied to the fields of earthquake monitoring, oil and gas exploration, geological disaster warning and the like.

The invention provides a Sigmoid modulation phase correlation surface wave full waveform inversion method and system. The method comprises the following steps: acquiring a surface wave seismic record and constructing an initial S wave velocity model; performing forward modeling to generate a synthetic record; calculating instantaneous phase correlation of observation and synthetic records to construct an amplitude-independent target function; modulating the target function by using a Sigmoid function, and mapping the value of the target function to a predetermined interval; and calculating a gradient based on the modulated target function and iteratively updating the speed model until a termination condition is met, and outputting a final model. According to the method, the smooth saturation and bounded output characteristics of the Sigmoid function are utilized, the target function response is converted into a self-adaptive gradient scaling mechanism, a self-stabilization optimizer is introduced for the inversion process, and the convergence domain is widened by applying smooth constraint, so that the dependence on the initial model precision is reduced, and the first success rate and the result reliability of inversion under complex conditions are improved.

This disclosure relates to a method, apparatus, and product for full-waveform reflection inversion based on dynamic graphic warping, applicable to the field of seismic exploration technology. In this disclosure, seismic data of the target area is acquired; wavefield simulation is performed based on the seismic data to determine the background wavefield and scattered wavefield. Based on dynamic graphic warping, full-waveform reflection inversion is performed on the background wavefield and scattered wavefield to determine the inversion target model. The inversion target model is optimized to determine the target image of the target area. Determining the inversion target model through the dynamic graphic warping algorithm can improve the resolution of the inversion target model and reduce the model's ambiguity and computational load. Furthermore, iterative optimization of the inversion target model can improve imaging quality. Simultaneously, using the dynamic graphic warping algorithm can reduce the accuracy requirements of high wavenumber models, enabling more accurate imaging of complex geological features. Therefore, the accuracy of imaging is improved.

The invention discloses a multi-scale full-waveform inversion method and device based on dynamic least square mapping, electronic equipment and a storage medium. The method comprises the following steps: acquiring expected low-frequency seismic data based on a dynamic least square mapping method; and carrying out multi-scale full-waveform inversion based on the expected low-frequency seismic data. According to the method, the low-frequency information of the seismic data is expanded through a dynamic least square mapping method, the missing low-frequency component of the seismic data is made up, multi-scale full-waveform inversion of frequency bands is carried out on the basis, and the inversion accuracy is improved. The problem of cycle jump caused by insufficient precision of an initial model or loss of low-frequency information of seismic data in full-waveform inversion can be effectively avoided, and the precision of full-waveform inversion is improved.

The application discloses a hydraulic fracturing fracture monitoring method and device based on Krauklis wave full waveform inversion, and comprises the following steps: obtaining a forward data set containing Krauklis wave and an actual data set of Krauklis wave; using full waveform inversion to invert the hydraulic fracturing fracture; periodically using full waveform inversion to image the fracturing fracture and periodically monitoring the hydraulic fracturing fracture. The application fully utilizes the relationship between the waveform characteristics of Krauklis wave, such as propagation along the fluid layer in the fracture, strong amplitude, strong frequency dispersion and low frequency propagation speed, and the fracture geometry, is based on the numerical solution of the elastic wave equation, adopts full wave field information, and thus provides a high-resolution and high-precision fracture fine structure image, so as to serve quantitative fracturing monitoring and fracture effect evaluation.

The invention discloses a rapid inversion method based on a radar electromagnetic model in a high-cold and high-altitude geological environment, and the core idea of the method is that a two-parameter wave field forward modeling model is constructed based on a Maxwell electromagnetic field equation, a time window-based convolution type objective function is utilized, and a real source function is not needed. Source-independent full-waveform inversion of single-offset GPR data is realized, an SVD method is introduced to automatically extract a reference waveform and determine the length of a time window, direct wave and reflected wave information is effectively separated, and the inversion calculation overhead is remarkably reduced in cooperation with a multi-scale frequency and random sub-source sampling strategy. According to the method, high-precision reconstruction can be performed on the underground dielectric constant and the conductivity on the premise that accurate source waveforms are not needed, and the practicability and the real-time performance of plateau area non-contact radar detection are remarkably improved.

The invention provides an ultrasonic sound velocity detection method for the water content of concrete, and belongs to the technical field of concrete water content detection.The ultrasonic sound velocity detection method comprises the steps that a decoupling quantitative model of ultrasonic sound velocity, porosity and saturation is established, and multi-angle data acquisition is conducted through a two-way single-transmitting three-receiving method or an orthogonal opposite measurement method; rebar interference sound paths are eliminated by using a metal obstacle constrained linear interpolation tracking method, coarse-to-fine progressive sound velocity field reconstruction is realized through a layered adaptive inversion model, grid encryption and full-waveform inversion optimization are performed on a high-gradient region, and finally sound velocity distribution is converted into a moisture content distribution cloud picture. The technical problem that high-precision spatial distinguishing cannot be achieved for the internal moisture content distribution of the reinforced concrete is solved.

The invention provides a deep ground space surrounding rock fracture detection identification and modeling method, and relates to the field of geological engineering. The method comprises the following steps: carrying out multi-measuring-line scanning and preprocessing data by adopting a ground penetrating radar system; multi-scale waveform attributes are extracted, and crack features are extracted through time-frequency analysis; identifying crack space parameters in combination with multiple methods and performing preliminary three-dimensional positioning; obtaining underground medium and fracture parameters based on full waveform inversion; calculating three types of connectivity of the fracture network; a three-dimensional geometric model is constructed and visualized according to the fusion result; and verifying and optimizing by combining measured data. According to the method, full-waveform inversion and multi-scale attribute analysis are fused, multi-scale crack high-precision identification and three-dimensional visualization are achieved, the automation degree is high, man-made subjectivity is reduced, the method is suitable for the fields of heat storage roadways, tunnel engineering, mine safety and the like, and a scientific basis is provided for engineering design, construction, operation and maintenance.

A method is described for seismic imaging including receiving a full waveform inversion (FWI) image of a subsurface volume of interest including complex geology; transforming the FWI image to the Fourier domain to generate a Fourier domain image; performing a multi-dimensional low-cut filter of the Fourier domain image to generate a low-cut filter image; phase rotating by 90 degrees the low-cut filter image to generate a phase-rotated image; performing an inverse Fourier transform on the phase-rotated image to generate a transformed image; and displaying the transformed image on a graphical display. The method is executed by a computer system.

The application provides a tunnel seismic and electrical method joint inversion method and system based on structural constraints, constructs resistivity models and wave velocity models of different detection distances; performs seismic and electrical method single inversion, calculates a structural constraint term for a common joint inversion area of the resistivity model and the wave velocity model according to inversion results; based on the characteristics of the structural constraint, different coefficients are set for the structural constraint term to balance the data term and the structural constraint term, to obtain the final structural constraint term, which is alternately added to the loss functions of the seismic and electrical methods, to obtain respective joint inversion results based on the structural constraint. The application can optimize the tunnel full waveform inversion and improve the effect of the joint inversion.

The invention discloses a construction method, system, equipment and medium of an oil and gas reservoir velocity-temperature model, and particularly relates to the technical field of model construction, and the technical key points are as follows: obtaining environmental thermodynamic parameters of an underground oil and gas reservoir medium and sound pressure components of seismic waves; constructing a thermal-acoustic coupling medium seismic wave propagation model based on an elastic theory and an acoustic approximation theory; based on a thermal-acoustic coupling medium seismic wave propagation model, forward modeling is carried out by using a staggered grid finite difference method, and a simulated sound pressure component of a seismic wave is obtained through simulation; acquiring an actual seismic sound pressure component, and constructing a target function by minimizing an error between the actual seismic sound pressure component and the simulated sound pressure component; implementing full-waveform inversion by using a gradient descent method, and solving an objective function to obtain an optimal model parameter; and performing parameter updating on the thermal-acoustic coupling medium seismic wave propagation model by using the optimal model parameters to obtain an updated oil and gas reservoir velocity-temperature model.

The present application provides a kind of geologic multi-source constraint adaptive full waveform inversion method and system, constructs multiple complementary constraint norms, organically fuses multiple modal prior information, forms unified multi-source constraint framework, compared with traditional single type prior constraint, the present application can more comprehensively utilize available prior information, guide inversion to the direction that both conforms to geophysical data and geological understanding converges;While introducing adaptive regularization parameter strategy based on Bayes theory, realize the adaptive update of weight factor, avoid the subjectivity and randomness caused by the dependence of regularization parameter on experience selection in traditional method, make the inversion result more stable, and do not need tedious manual parameter adjustment, can dynamically adjust the constraint strength according to the data noise level, enhance the guiding role of prior constraint in low signal-to-noise ratio, more rely on observation data in high signal-to-noise ratio;At the same time, through the combination of model compression and forward simulation calculation, the calculation efficiency is greatly improved.

This invention discloses a knowledge-guided method for separating P-waves and S-waves in complex geological structures, applied to the field of seismic data processing. It addresses the problem that existing technologies struggle to effectively separate P-waves and S-waves in complex geological structures. First, this invention utilizes a recurrent neural network for elastic wave full-waveform inversion to obtain knowledge representations of P-waves and S-waves in complex structures. Second, using these knowledge representations, a dual-branch autoencoder network is constructed. One branch separates P-waves under the guidance of the P-wave knowledge representation, while the other branch separates S-waves under the guidance of the S-wave knowledge representation. Finally, an autoencoder network architecture is constructed that comprehensively constrains wavefield reconstruction error, P-wave knowledge-guided error, and S-wave knowledge-guided error. Theoretical analysis and numerical calculations demonstrate that the proposed method can effectively separate P-waves and S-waves in complex geological structures, reducing dependence on data samples and exhibiting a certain degree of robustness.

This invention relates to a tunnel full-waveform inversion method based on spectral element forward modeling and physical information neural network, comprising: collecting engineering geological data and obtaining physical property parameters; establishing a two-dimensional finite element model and obtaining spatial information; constructing a wavefield model and performing wavefield forward modeling simulation to obtain synthetic full-waveform data; collecting measured waveform data and preprocessing it, performing time registration and normalization processing on the preprocessed measured waveform data and synthetic full-waveform data, and extracting multiple features; constructing a parameter training set; constructing and training a physical information neural network model, constructing a comprehensive loss function during the training process; and using the physical information neural network model to perform full-waveform inversion. This invention deeply integrates finite element forward modeling, full-waveform inversion, and physical information neural network, taking into account both data fitting and physical consistency, significantly improving the quantitative accuracy and reliability of tunnel advanced geological prediction.

The invention discloses a laser ranging target identification method based on deep learning, particularly relates to the technical field of laser radar signal processing, and is used for solving the problem that an entity target and volume scattering interference are difficult to distinguish in a complex meteorological environment. The method comprises the following steps: firstly, analyzing a full-waveform echo signal, extracting an asymmetric skewness value and a flight time offset, and constructing a four-dimensional signal set containing physical scattering characteristics; then, a medium penetration rate index and a space scattering dispersion index are calculated, and a signal-to-clutter ratio confidence index is generated to quantify signal-to-noise features; utilizing the index to constrain graph topology construction, establishing connection only among nodes with consistent physical attributes, generating attribute isomorphic signal sub-graphs, and performing graph convolution feature aggregation; and finally, calculating a theoretical echo window in combination with a historical track state and a motion model, and weighting, updating and outputting a target detection list by using time sequence characteristics. According to the invention, environmental noise interference is effectively blocked, and the detection robustness of the laser ranging system in a severe environment is improved.

The invention relates to the technical field of coal seam exploration, in particular to a coal reservoir porosity testing method based on full waveform inversion. In order to solve the problem that the existing coal reservoir porosity testing method is inaccurate and incomplete in testing, the invention provides a novel coal reservoir porosity testing method based on full-waveform inversion, which comprises the steps of seismic data acquisition, data preprocessing, rock physical mapping model establishment, full-waveform inversion, porosity conversion and precision control. The spatial resolution of the porosity of the coal reservoir obtained by the testing method can reach the meter level to the sub-meter level.

The invention discloses an electric spark source multidirectional detection system and method based on a polarization effect, the system comprises a source drill rod, a capacitance drill rod, a conductive drill rod and a console, discharge electrodes respectively correspond to excitation ports in different orientations, and three space orthogonal excitation ports are formed in this way for time-sharing excitation. Three pure transverse wave sources with known polarization directions are manufactured, so that the detection precision is improved for subsequent inversion analysis; obtaining a three-component seismic trace record data set corresponding to the three seismic sources; processing the data set to obtain three groups of azimuth data; thirdly, defining a model parameter vector and determining a full-waveform inversion function; according to the method, an adjoint state method is adopted to obtain a gradient direction enabling an objective function to descend, an L-BFGS algorithm is utilized to iteratively update model parameters, and finally, an optimal solution is utilized to be combined with three groups of azimuth data to carry out full-waveform inversion, so that azimuth anisotropy information of a detection area is obtained. And the accurate identification of the disaster geologic body in the detection target area is realized by fusing the multidirectional detection data.

A method can include receiving seismic data of a subsurface region; performing an iterative full waveform inversion using at least a portion of the seismic data to generate a model of the subsurface region, where the performing includes, after one or more iterations of the full waveform inversion, automatically selecting one or more parts of the seismic data for inclusion in the at least a portion of the seismic data based on data classification using one or more quality attributes; and outputting the model of the subsurface region.

Method and apparatus for constructing seismic velocity models of the underground geologic formation using full waveform inversion are provided. The method evaluates velocity model accuracy by measuring local traveltime differences between recorded seismic data and synthetic data. The travetime misfit may be calculated with a hybrid L1 / L2 norm that relatively lowers down the influence of large traveltime difference in each iteration and ensures the inversion stability. The method tolerates poor quality initial model and generates high resolution models.

The invention provides a Gaussian mixture clustering constraint full-waveform inversion method, system and device and a medium, and belongs to the technical field of geophysical exploration, and the method comprises the steps: constructing an initial speed model; obtaining an observation data matrix based on a real speed model; performing reverse time migration imaging by using the initial velocity model and the observation data matrix to obtain a reflection amplitude image; generating a main body mask according to a Gaussian mixture model and the reflection amplitude image; obtaining a boundary mask based on the main body mask; according to the main body mask and the boundary mask, processing by combining time domain full waveform inversion to obtain a weighted gradient; and adopting a multi-scale frequency strategy and an optimization algorithm, carrying out iterative updating on the initial velocity model based on the weighted gradient until a convergence condition is met, and outputting a final velocity model. According to the method, the complex geological boundary imaging precision is improved, and meanwhile, the dependence on an initial model is reduced.