17 results about "Seismic migration" patented technology

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.

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.

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 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 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.

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 application relates to the field of geophysical signal processing, and proposes a method, device, equipment and medium for seismic migration data fusion, wherein the method comprises: obtaining seismic migration data corresponding to a plurality of blocks respectively and selecting a reference block based on the characteristics of a target layer 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 relevant wavelets of the plurality of blocks respectively at the target layer and constructing target wavelets; calculating the frequency difference between the target wavelets and each relevant wavelet to construct a wavelet reconstruction factor, so as to perform frequency correction; and fusing the frequency-corrected seismic migration data of the overlapping area and the non-overlapping area between the plurality of blocks to obtain the fusion result of the seismic migration data. The scheme disclosed in the present application solves the problems of energy, frequency difference and boundary imaging difference encountered in the splicing processing of different three-dimensional block migration results.

The invention provides a pre-stack crack prediction evaluation method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring a plurality of pre-stack azimuth gathers of different azimuth angles; performing dip angle filtering on each seismic offset data volume of different azimuth angles by using a frequency domain-based filtering algorithm to obtain a plurality of filtering data volumes of different azimuth angles; and performing ellipse phase fitting on each filtering data body of different azimuth angles to obtain a crack prediction result. A filtering algorithm based on a frequency domain is utilized to carry out frequency domain filtering on seismic migration data volumes with different azimuth angles, fracture seismic response characteristics can be highlighted, anisotropy characteristics caused by factors such as deposition can be effectively suppressed, anisotropy caused by fractures can be effectively identified, three-dimensional space distribution characteristics of fracture development can be provided, and the method is applicable to the field of seismic data processing. More bases are provided for fractured high-quality reservoir evaluation, and the prediction accuracy can be effectively improved.