36 results about "Seismic migration" patented technology

The invention relates to the technical field of seismic inversion, and particularly discloses a variational reasoning full-waveform inversion method and device based on geological prior information, and the method comprises the steps: constructing a plurality of filters; acting the plurality of filters obtained by construction on a seismic migration section to calculate a correlation coefficient matrix; according to a logging information fitting theory variation function, performing low-rank approximation on the calculated correlation coefficient matrix to obtain a correlation coefficient matrix after low-rank approximation; randomly generating a plurality of speed samples based on the correlation coefficient matrix after low-rank approximation; calculating the gradient of the objective function according to the plurality of speed samples; according to the gradient of the objective function, calculating the gradient of posteriori distribution by using a Bayesian formula; and based on the gradient of the full waveform inversion posteriori distribution, utilizing a Stein variational gradient descent algorithm to carry out multiple times of iterative updating on the plurality of speed samples, and outputting a target speed model obtained by inversion of the plurality of speed samples. According to the scheme, the multiplicity of inversion is reduced, and the inversion efficiency is improved.

The invention relates to the technical field of seismic exploration, in particular to a seismic offset angle gather generation method and device, equipment and a medium. The method comprises the following steps: acquiring pre-stack seismic data of a work area after preprocessing; performing pre-stack time migration on the pre-stack seismic data, and performing grouping accumulation according to inclination angles in the pre-stack time migration process to generate an inclination angle gather; according to the inclination angle gather, picking up Fresnel zone boundaries of reflection events of all imaging points according to preset intervals; stable-phase offset is carried out by using the picked Fresnel zone boundary, and an offset angle gather of stable-phase control is generated according to grouping accumulation of incident angles in the offset process. The problems that an existing method for generating an angle gather through pre-stack depth migration is difficult in interval velocity modeling and high in calculation cost are solved.

A computer implemented method that enables drill bit source focusing is described. The method includes obtaining, using at least one hardware processor, correlated drill bit gathers comprising a direct arrival from a downhole source to surface receivers; identifying, using the at least one hardware processor, at least one window around first breaks in the correlated drill bit gathers captured by the surface receivers, wherein the first breaks are isolated / bounded the at least one window; redatuming, using the at least one hardware processor, seismic data within the at least one window captured by respective surface receivers to generate source images; and generating, using the at least one hardware processor, a seismic migration image by multiplying the generated source images.

A method for estimating uncertainty in seismic-derived depth prognoses of a subsurface region includes receiving an initial velocity model of a subsurface region based on seismic data associated with the subsurface region, performing a seismic de-migration on initial post-migration seismic data obtained from the initial velocity model to obtain pre-migration seismic data, and perturbing one or more of the components of the initial velocity model to produce a plurality of perturbed velocity models that are each different from the initial velocity model. The method further includes performing a seismic migration of the pre-migration seismic data using the perturbed velocity model to obtain perturbed post-migration seismic data for each of the plurality of perturbed velocity models, estimating a depth error from a depth prognosis obtained from a selected subset of the perturbed velocity models based on characteristics of the perturbed post-migration seismic data, and estimating a depth uncertainty from the estimated depth error.

The application discloses a kind of multi-information fusion's speed modeling method and device, the method includes, after seismic migration, the imaging data A of acquisition, data phase control type mask B, seismic structure interpretation horizon and fault data C, well logging velocity curve data D and seismic velocity field data E;Edge feature of imaging data A is extracted by edge detection technique, and the structural skeleton data F of seismic image is obtained;Phase control type mask B is fused with structural skeleton data F, and phase control structure guide data G is obtained;Seismic structure interpretation data C is added in phase control structure guide data G, and space interpolation guide data H is formed;Through two-step interpolation extrapolation, the space interpolation distance weight field Q corresponding to space interpolation guide data H and well logging velocity interpolation filling model P are obtained;Classification mask M is established for well logging velocity interpolation filling model P;Two-step filling is carried out to class mask M, and multi-information fusion model R is obtained.

This invention relates to the technical field of seismic data interpretation, and discloses a method and computer equipment for identifying the locations of beaded reflections in carbonate rocks. The identification method includes: S1, obtaining a two-dimensional seismic migration profile; S2, extracting typical beaded reflections, determining their dimensions, statistically analyzing their structural morphology, and constructing adaptive hit-and-miss structural element pairs; S3, using a hit-and-miss transformation to identify locations that match the adaptive hit-and-miss structural element pairs. This invention's identification method extracts multiple typical beaded reflections, constructs adaptive hit-and-miss structural element pairs, and only identifies locations that match these pairs. Based on a hit-and-miss transformation algorithm, this algorithm has low hardware requirements, high computational efficiency, and high accuracy.

This invention relates to the field of seismic imaging technology and discloses a method, apparatus, equipment, and medium for forward modeling of seismic acoustic waves in a viscoelastic-acoustic (VTI) medium. The method includes: obtaining a desired Q value; calculating the viscoelastic velocity of the seismic acoustic wave based on the desired Q value; fitting parameters of a generalized standard linear body model; constructing a wave equation for the seismic acoustic wave in the VTI medium based on the generalized standard linear body model; and solving the wave equation for the seismic acoustic wave in the VTI medium using the finite difference method and the viscoelastic velocity. This invention solves the problem that traditional seismic simulations cannot simultaneously consider seismic anisotropy and seismic attenuation, significantly improving the accuracy and applicability of seismic simulations, as well as the accuracy of seismic simulations in complex terrain, geology, and oil and gas reservoir areas. It provides a foundation for subsequent high-precision seismic velocity modeling and seismic migration imaging.

The invention discloses a method for quickly determining a seismic horizon by using a depth domain migration speed. According to the method, macroscopic seismic horizon information is rapidly extracted by analyzing the structural feature information of the depth domain seismic migration velocity, reliable seismic horizon basic data is provided for constructing a complex area, horizon recognition efficiency is remarkably improved, and the workload of interpretation personnel is greatly reduced. The method is characterized in that the horizon picking process has adaptive updating capability, macroscopic seismic horizon information of a work area can be rapidly and stably extracted, the depth change trend of an underground structure is accurately reflected, and the continuity of the seismic horizon in the transverse direction is ensured.

A method can include obtaining a P-wave velocity model (476) and velocity ratio data (411) for a geological region of interest. The method can also include generating an initial S-wave velocity model (420) for the geological region of interest based on the P-wave velocity model (476) and the velocity ratio data (411). The method can also include determining a plurality of velocity boundaries within the initial S-wave velocity model (420) using a trained model. The method can also include updating the initial S-wave velocity model (420) using the velocity boundaries, automatically selected cross-correlation lag values based on a plurality of seismic gather, and migration velocity analysis to produce an updated S-wave velocity model (470). The method also includes generating a combined velocity model for the geological region of interest using the updated S-wave velocity model (470) and the P-wave velocity model (476).

This invention discloses a method for rapidly determining seismic horizons using depth-domain migration velocity. This method analyzes the structural characteristics of depth-domain seismic migration velocities to quickly extract macroscopic seismic horizon information, providing reliable seismic horizon baseline data for structurally complex areas, significantly improving the efficiency of horizon identification and greatly reducing the workload of interpreters. The method is characterized by its adaptive updating capability in the horizon picking process, enabling rapid and stable extraction of macroscopic seismic horizon information for the work area, accurately reflecting the depth variation trend of subsurface structures, and ensuring the lateral continuity of seismic horizons.

The invention relates to a VTI medium least square reverse time migration method and system suitable for an Adam gradient optimization algorithm, and belongs to the field of seismic migration imaging, and the method specifically comprises the following steps: carrying out the subtraction of conventional approximate longitudinal and transverse wave reflectivity models C33 and C55 with the background speed of the conventional approximate longitudinal and transverse wave reflectivity models C33 and C55, carrying out the division, carrying out the normalization processing, and constructing a real longitudinal and transverse wave reflection coefficient model. And linear forward modeling is carried out on the basis of a VTI medium first-order stress velocity elastic wave equation. And expressing the linearized forward modeling in a deep learning framework in an RNN convolution form to obtain a simulated seismic record of the linearized forward modeling. And making a difference between the simulated seismic record and the actual seismic record, and establishing a target function. And optimizing the gradient by using an Adam gradient optimization algorithm in deep learning, and updating the longitudinal and transverse wave reflection coefficient model by using the optimized gradient until the precision requirement is met. According to the method, the precision of gradient optimization is improved, the problem of extremely slow convergence is solved, and finally a more accurate least square reverse time migration result is obtained.

The invention relates to the field of geophysical signal processing, and provides a seismic migration data fusion method, device, equipment and medium, and the method comprises the steps: obtaining seismic migration data corresponding to a plurality of blocks, and selecting a reference block based on the features of a target stratum and a geological task; constructing an amplitude correction sequence, and performing energy correction on the seismic migration data based on the amplitude correction sequence; extracting correlation wavelets of the plurality of blocks in the target layer and constructing target wavelets; calculating a frequency difference between the target wavelet and each related wavelet to construct a wavelet reconstruction factor so as to perform frequency correction; and fusing the seismic migration data after the frequency correction of the overlapped areas and the non-overlapped areas among the plurality of blocks to obtain a fusion result of the seismic migration data. According to the scheme disclosed by the invention, the problems of energy, frequency difference and boundary imaging difference in splicing processing of different three-dimensional block migration results are solved.

The invention discloses an interlayer multiple identification and model construction method and device, a medium and equipment. The method comprises the steps that logging data and a seismic migration profile of a working area are obtained, the logging data comprise at least one of an acoustic logging curve and logging stratified data, and a longitudinal wave speed two-dimensional numerical model and a density two-dimensional numerical model are constructed in the main measuring line direction or the connection measuring line direction based on the logging data. The constructed longitudinal wave velocity two-dimensional numerical model and density two-dimensional numerical model provide accurate data for the establishment of subsequent models. And based on the longitudinal wave velocity two-dimensional numerical model and the density two-dimensional numerical model, generating zero well spacing VSP simulation data by using a seismic exploration numerical simulation method, and constructing an inter-layer multiple model based on the zero well spacing VSP simulation data. The interlayer multiple wave model constructed by the method is closer to the multiple waves actually generated in the working area, and the interlayer multiple waves in the working area can be accurately identified by identifying the interlayer multiple waves through the wave field features of the interlayer multiple wave model.

The invention discloses an underground water migration channel attribute extraction method and device. The method comprises the following steps: in a seismic exploration process, acquiring seismic migration data and speed data of seismic waves propagating in an underground medium; determining an offset inclination angle of the offset reflected wave in the offset profile according to the seismic offset data; determining a demigration inclination angle of the reflected wave in a demigration profile according to the migration inclination angle of the migration reflected wave in the migration profile and the speed data; filtering reflected waves in the target seismic data along the direction of the demigration dip angle to extract diffracted waves in the target seismic data; diffraction attributes of the diffracted waves are determined, and the diffraction attributes refer to seismic response characteristics when the seismic waves diffract on the underground discontinuous geological interface. According to the method and the device, the technical problem that the underground water migration channel is difficult to observe due to the fact that the attribute of the diffracted wave is difficult to directly extract in the prior art is solved.

The invention discloses an automatic analysis method for seismic migration velocity, comprising the steps of: obtaining pre-stack seismic data of a target work area; determining an imaging stacking section corresponding to the pre-stack seismic data; determining a plurality of time windows and an objective function, and inverting to obtain a migration velocity value; determining a migration velocity model of the target work area according to the migration velocity values ​​corresponding to all time windows; and performing pre-stack time migration imaging on the pre-stack seismic data based on the migration velocity model to obtain a new imaging stacking section. The invention first obtains an imaging stacking section through the pre-stack seismic data of the target work area, selects a time window, and then inverts to obtain a migration velocity value corresponding to the time window based on the objective function, the migration velocity value is more accurate, the migration velocity model established according to the migration velocity value is more accurate, and the pre-stack time migration imaging is performed on the pre-stack seismic data based on the migration velocity model to obtain a new imaging stacking section, and the imaging effect is better.

The specification relates to the technical field of seismic inversion, and specifically discloses a variational inference full waveform inversion method and device based on geological prior information, wherein the method comprises: constructing multiple filters; applying the constructed multiple filters to a seismic migration profile to calculate a correlation coefficient matrix; fitting a theoretical variation function to the calculated correlation coefficient matrix according to well logging data to obtain a low-rank approximation correlation coefficient matrix; randomly generating multiple velocity samples based on the low-rank approximation correlation coefficient matrix; calculating the gradient of an objective function according to the multiple velocity samples; calculating the gradient of a posterior distribution by using a Bayesian formula according to the gradient of the objective function; and performing multiple iterative updates on the multiple velocity samples by using a Stein variational gradient descent algorithm based on the gradient of the full waveform inversion posterior distribution, and outputting a target velocity model obtained by inverting the multiple velocity samples. The above scheme reduces the multi-solution of inversion and improves the inversion efficiency.

The present application relates to a kind of diffracted wave separation methods based on multi-feature reuse hollow convolutional neural network.Based on hollow convolution and multi-feature reuse module, neural network is built, training data set is constructed by synthesizing data and actual data, neural network is trained, L1-multiple scale structural similarity index hybrid function is used to measure the distance between network output and label in training to obtain optimal network model;Seismic common offset data or poststack data are input into optimal network model, and separated diffracted wave data are obtained;According to seismic migration velocity file, the diffracted wave data separated by multi-feature reuse hollow convolutional neural network are migrated and imaged.This method can effectively remove steep dip reflection while preserving diffracted wave energy, and can solve the problems of diffracted energy loss and reflection residue in the process of diffracted wave separation.For the case where diffracted wave and reflection event cross, the separated diffracted wave is more complete.

The application provides a velocity model updating method and device based on seismic-logging data difference, which comprises the following steps: obtaining seismic data and logging data; synthesizing model seismic data according to the logging data; calculating the local similarity of the model seismic data and the seismic data by using the LSIM method to obtain a time offset; generating updated logging velocity according to the time offset and logging velocity in the logging data; obtaining initial seismic migration velocity; and generating updated seismic migration velocity according to the logging velocity, the updated logging velocity and the initial seismic migration velocity. The application quantifies misplacement and updates seismic migration velocity by using the local similarity technology, realizes high precision and geological consistency of the velocity model, improves the resolution of the velocity model, and helps to solve the velocity model construction problem in complex strata or anisotropic regions, and has a wide application prospect.

A method for estimating uncertainty in seismic-derived depth prognoses of a subsurface region includes receiving an initial velocity model of a subsurface region based on seismic data associated with the subsurface region, performing a seismic de-migration on initial post-migration seismic data obtained from the initial velocity model to obtain pre-migration seismic data, and perturbing one or more of the components of the initial velocity model to produce a plurality of perturbed velocity models that are each different from the initial velocity model. The method further includes performing a seismic migration of the pre-migration seismic data using the perturbed velocity model to obtain perturbed post-migration seismic data for each of the plurality of perturbed velocity models, estimating a depth error from a depth prognosis obtained from a selected subset of the perturbed velocity models based on characteristics of the perturbed post-migration seismic data, and estimating a depth uncertainty from the estimated depth error.

The invention belongs to the technical field of seismic migration imaging, and particularly relates to a migration imaging profile generation method based on inclination angle scanning. The method comprises the following steps: extracting a dip angle domain common imaging point gather of original seismic data; carrying out superposition imaging on all dip angle domain common imaging point gathers to obtain an initial migration imaging profile; performing dip angle scanning on the initial migration imaging profile to obtain a true stratum dip angle field; according to the true stratum dip angle field and the initial imaging profile, determining a dip angle effective imaging area of the target imaging point, and obtaining a dip angle domain common imaging point gather in the dip angle effective imaging area; and carrying out superposition imaging on the inclination angle domain common imaging point gather in the inclination angle effective imaging area to obtain a final migration imaging section. According to the method, the migration noise of the Gaussian beam depth migration imaging profile is reduced, the signal-to-noise ratio of the Gaussian beam depth migration imaging profile is enhanced, the signal-to-noise ratio of the generated migration imaging profile is higher, the migration imaging profile is more accurate and reliable, and subsequent seismic interpretation processing is facilitated.

The present invention discloses a method for calculating a seismic migration point spread function based on local time and space optimization, which relates to the field of exploration geophysical technology, including: acquiring data; calculating amplitude and complex travel time; Fourier transform and filtering; calculating a point scattering data volume; calculating a frequency spectrum; filtering and performing an inverse Fourier transform to obtain a point scattering response; calculating a Green's function and offsetting the point scattering data volume to a local space near the scattering point to calculate a point spread function; obtaining a simplified point spread function; calculating and weighting the point spread function; calculating a seismic image using a traditional adjoint migration method and decomposing it into local images; and deconvolution to obtain a reconstructed deconvolved image. The present invention calculates Gaussian beam-based born modeling and migration on a coarse grid based on local rays, interpolates the point spread function onto a fine image grid, and applies a high-dimensional Gaussian function to attenuate artifacts far from the center of the point spread function, which can significantly improve computational efficiency and obtain deep, high-quality imaging results.

A method for generating a high-resolution pseudo-reflectivity image of a subsurface region includes receiving seismic data associated with a subsurface region and captured by one or more seismic receivers, constructing a velocity model of the subsurface region based on the received seismic data, performing a seismic migration of the received seismic data based on the constructed velocity model to obtain migrated seismic data, computing polarized normal vectors associated with one or more subsurface reflectors of the subsurface region based on the migrated seismic data, and generating a pseudo-reflectivity image of the subsurface region based on both the computed polarized normal vectors.

A method for estimating uncertainty of an output of a velocity model of a subsurface region includes receiving seismic data associated with a subsurface region and captured by one or more seismic receivers, constructing a velocity model of the subsurface region based on the received seismic data, performing a seismic migration of the received seismic data based on the constructed velocity model to obtain migrated seismic data, generating a semblance panel from the migrated seismic data, and estimating an uncertainty of the output of the velocity model based on the generated semblance panel.

The invention belongs to the technical field of seismic migration imaging, and particularly relates to a Gaussian beam form optimization method based on minimum mean square width constraint. According to the method, symmetric matrix parameters representing the optimal initial form of a Gaussian beam in a plane perpendicular to a central ray are calculated, a smooth objective function represented by the initial parameters is minimized, and a novel Gaussian beam is constructed; a green function is analyzed through integral superposition fitting of a novel Gaussian beam to solve an integral weight coefficient, then the green function and an uplink and downlink continuation wave field are constructed, and an imaging value at an underground imaging point is extracted by applying a deconvolution imaging condition. Compared with a traditional Gaussian beam migration method, the Gaussian beam form optimization method based on the minimum mean square width constraint solves the contradiction between the imaging precision of a near-surface layer and the imaging precision of a middle-deep layer, enables a migration result profile to be more accurate and reliable, and facilitates subsequent interpretation processing.

The application provides a well seismic migration imaging method, comprising the following steps: step 1, acquiring well seismic common shot gathers for migration imaging, an initial velocity model and an initial quality factor model; step 2, determining a lateral grid interval for migration, an effective frequency band range and a main frequency of the common shot gathers; step 3, determining a migration velocity model and a migration quality factor model; step 4, acquiring observation parameters corresponding to each common shot gather, determining a migration aperture and an effective imaging range; step 5, solving a wave equation based on a numerical algorithm, acquiring imaging time and a corresponding source wave field of the shot; step 6, realizing migration imaging of the common shot gather by using an imaging condition; and step 7, superimposing single-shot migration profiles of all shots to obtain a final migration profile. The well seismic migration imaging method has high calculation efficiency, small storage capacity, high imaging profile resolution and high signal-to-noise ratio, and can be directly applied to seismic attribute inversion.

The invention provides a method, a device and equipment for generating an accelerated amplitude-preserved offset angle gather by utilizing machine learning. The method comprises the following steps: acquiring preprocessed three-dimensional pre-stack seismic data; generating all migration angle gathers of a to-be-imaged area from the three-dimensional pre-stack seismic data through pre-stack time migration imaging; selecting a part of typical lines of a to-be-imaged area, and obtaining an amplitude-preserved offset angle gather by adopting an imaging domain Hessian array diagonalization approximate true amplitude gather generation method; taking the offset angle gathers of all CDP point gathers of the typical line as input data, and taking the amplitude-preserving offset angle gathers corresponding to the input data as labels to establish a training data set; training a deep learning neural network by using the training data set to obtain a trained neural network; and processing the to-be-imaged full-region offset angle gather by using the trained neural network to obtain a full-region amplitude-preserved offset angle gather. According to the invention, the efficiency of generating the three-dimensional seismic migration imaging amplitude-preserved migration angle gather can be greatly improved, and an amplitude-preserved migration stack section can be obtained.

The application relates to a VTI medium least square reverse time migration method and system suitable for an Adam gradient optimization algorithm, and belongs to the field of seismic migration imaging. C 33 And C 55 After being subtracted from and divided by the background velocity respectively, normalization processing is performed to construct a real P-S wave reflectivity model. Linearization forward modeling is performed on the basis of a first-order stress velocity elastic wave equation of a VTI medium. The linearization forward modeling is expressed in the form of RNN convolution in a deep learning framework to obtain simulated seismic records of the linearization forward modeling. A target function is established by subtracting the simulated seismic records from actual seismic records. An Adam gradient optimization algorithm in deep learning is used to optimize the gradient, and the P-S wave reflectivity model is updated by using the optimized gradient until the accuracy requirement is met. The application improves the accuracy of gradient optimization, solves the problem of extremely slow convergence, and finally obtains more accurate least square reverse time migration results.

The application provides a method and device for seismic migration imaging, computer equipment and storage medium, and belongs to the technical field of geophysical exploration. The method comprises the following steps: obtaining seismic wave data corresponding to an oil and gas reservoir in a to-be-measured work area; determining forward simulation parameter, conjugate transpose migration operator parameter and sensitive kernel function parameter corresponding to the oil and gas reservoir; determining reflectivity vector corresponding to the oil and gas reservoir based on the forward simulation parameter, the conjugate transpose migration operator parameter and the sensitive kernel function parameter; determining migration parameter between forward seismic wave data corresponding to the reflectivity vector of each iteration and the seismic wave data through iterative calculation of a preset number of iterations, and determining the reflectivity vector corresponding to the minimum migration parameter; and determining the transverse wave stacking profile and the longitudinal wave stacking profile corresponding to the reflectivity vector. Since the forward data closest to the actual seismic wave data is determined through the least square method, the accuracy of the determined stacking profile is improved.

The application discloses a front abnormality early warning method and system based on a tunneling seismic migration result, and the method comprises the following steps: acquiring a tunneling seismic signal corresponding to cutting at a set interval distance of each travel mileage in front of a tunneling head currently monitored by an observation system, and processing the tunneling seismic signal to obtain an abnormal interface of a front position corresponding to each set interval distance of a tunneling machine; extracting a midpoint of a tangent line segment of the abnormal interface of the front position corresponding to each set interval distance as an abnormal point in the abnormal interface to obtain all abnormal points extracted after multiple set interval distances; and performing cluster analysis on all the abnormal points, collecting the abnormal points in a set range according to a cluster radius, determining an abnormal area, and early warning; and the application can realize dynamic and real-time early warning in front of a tunneling roadway, and guide safe and efficient tunneling of a mine.

The present invention discloses a method and system for updating a seismic velocity model based on well-controlled structural constraints, including: improving the accuracy and continuity of the velocity model. The main steps include converting the time domain velocity model to the depth domain, creating a preliminary structural model, and using logging data to constrain correction. Then, the logging velocity data is processed by Bucks averaging and the velocity change trend is fitted according to the corrected structural model to update and interpolate the depth domain velocity model. For new logging data, the velocity model is further optimized through local correction and velocity reconstruction, and finally applied to the seismic offset imaging process. The advantages of the present invention are: reducing the depth error of geological structure picking, and effectively reducing the computational burden of reconstructing the full-area velocity model caused by the addition of new logging data. By optimizing data utilization and computing resource management, the efficiency of seismic data processing is improved, and the reliability and interpretation ability of seismic imaging results are enhanced.