171 results about "Waveform inversion" patented technology

The present invention presents a method for determining shallow water flow risk using seismic data. The seismic data can be processed to enhance its stratigraphic resolution by sub-sampling the seismic data to less than a two-millisecond interval. Performing a stratigraphic analysis on the seismic data and evaluating the seismic attributes of the seismic data can be used to select a control location. A pre-stack waveform inversion is applied to seismic data at a selected control location to provide an elastic model, which includes pressure-wave velocity and shear-wave velocity. The shallow water flow risk is then determined using the elastic model by comparing the pressure-wave velocity to the shear-wave velocity. A post-stack inversion can be applied on the seismic data using the elastic model to model a 3D volume to determine the shallow water flow risk across the 3D volume.

Seismic data processing methods and computing systems are presented. In one embodiment, a method is disclosed that includes simulating a set of simulated seismic data from a set of acquired seismic data; separating the simulated seismic data into a plurality of data sets, wherein one set of data is matched in the acquired seismic data and one set of data is unmatched in the acquired seismic data; conforming the simulated seismic data and the acquired seismic data to one another using separated, simulated seismic data unmatched by a counterpart in the acquired seismic data from the acquired seismic data; and performing an inversion between the acquired seismic data and the separated, simulated seismic data after they are conformed to one another.

The invention relates to a high voltage DC power transmission line shielding failure current waveform inversion recovery method. When the transmission line suffers the lightning stroke, the transient state traveling wave is spread and transmitted by the power transmission line, so the transient response at the protection installation place is different. The transmission line is equivalent to a natural lightning current air-termination system, and when the shielding failure happens, the prior traveling wave fault location technology can precisely locate the lightning stroke point; the parameters of the power transmission line can be obtained by measuring and analyzing on line; and with the transfer function of the transmission line deduced by the method, the lightning current waveform at the lightning stroke point can be finally obtained by carrying out the phase amplitude transformation, noise reduction, and Prony fit process, and deconvolution operation of on the transient voltage which is obtained through a high-speed collection at the protection installation place of the transmission line.

There is provided a seismic imaging technology for imaging a subsurface structure by processing measured data reflected from the subsurface structure after a wave from a source wave has been propagated to the subsurface structure. According to an aspect, there is provided a seismic imaging method for obtaining imaging data of a subsurface structure through waveform inversion using a macro-velocity model as an initial value, wherein the macro-velocity model which is used as the initial value for the waveform inversion is calculated by: calculating a velocity difference function which is a difference between a real velocity and an initial velocity model, wherein the velocity difference function is a ratio of measured seismic scattered energy and modeled scattered energy based on the initial velocity model; and calculating the macro-velocity model by updating the initial velocity model with the velocity difference function.

A seismic imaging technology, and more specifically, an imaging technology for modelling a subsurface structure by updating a velocity model of each frequency band in the ascending, descending order or any random order of frequency

The purpose of the present disclosure is to directly compute the difference between the velocity of the actual subsurface velocity and an initial guess of the velocity.

According to one aspect of the present invention, a seismic imaging apparatus for performing iterative application of the direct waveform inversion to image a subsurface structure of an area to be measured may include a waveform inverter to update a reference velocity model while changing a frequency band in a set order, by using parameter perturbation that is obtained from a virtual scattering source and an updated reference wavefield.

Provided are an apparatus and method for imaging the subsurface structure of a target area by using waveform inversion. In the apparatus and method, the subsurface structure of a target area is estimated using waveform inversion of a seismic signal in the frequency domain, the Laplace domain, or the Laplace-Fourier domain, and an objective function is defined by applying a weighting function such that the objective function makes a different contribution for each frequency, each Laplace damping constant, or each Laplace-Fourier damping constant. The objective function is not limited to a particular type of objective function and a weighting function can be automatically determined when a gradient vector for each frequency, each Laplace damping constant, or each Laplace-Fourier damping constant is normalized. In addition, a gradient direction for all frequencies can be defined by applying another weighting function to the sum of respective gradient vectors for all frequencies, all Laplace damping constants, or all Laplace-Fourier damping constants, wherein the weighting function can also be automatically determined by normalization.

A method for expediently processing and inverting elastic wave data to reduce the amount of data and to determine a physical properties model of the material medium and a source properties model. The data are processed to generate waveforms containing the phase difference between compressional- and shear-wave arrivals using auto-correlation, cross-correlation, or deconvolution of said data sensed at each of an arrangement of sensors, whereby said lengthy elastic wave data records are reduced substantially in time. Said waveform data are thereafter inverted using waveform inversion by modifying the source term in the equation of motion, wherein the source term is mathematically expressed as a product of time-independent source properties volume defined at every location in space within said material medium and a space-independent source-time function, whereby no prior knowledge of the number of sources, spatial distribution of source location, source amplitude, or source focal mechanism is needed.

The invention discloses an accurate detection method for the voltage travelling wave of a transmission line fault based on waveform inversion. According to the method, special voltage travelling wave sensors are mounted on grounding wires of capacitive equipment, as capacitive voltage transformers (CVT), of transformer stations at the two ends of a power transmission line; the special voltage travelling wave sensors are utilized to detect a primary voltage traveling wave signal after the transmission line fault and output a secondary voltage traveling wave signal; and a high-frequency transfer function model of the special voltage travelling wave sensors is used to establish a high-frequency inversion function model of the special voltage travelling wave sensors, according to the high-frequency inversion function model, a random resonance-deconvolution inversion algorithm is designed for waveform inversion, the primary voltage traveling wave signal is output and inversed, and accurate inversion from the second voltage traveling wave signal to the primary voltage traveling wave signal is realized. According to the invention, the problem of waveform distortion generated when the primary voltage traveling wave signals is transformed by the special voltage travelling wave sensors, and the primary voltage traveling wave signal can be detected accurately and effectively.

The invention discloses a full waveform joint inversion method for improving high steep structure velocity inversion efficiency, and belongs to the petroleum geophysical exploration field. The method comprises the steps: establishing an observation system by inputting the initial velocity field, the shot record and the focus wavelet; utilizing traditional reverse time migration to obtain the imaging result which is taken as a reflection coefficient model, and applying linear forward modeling and linear wave field back propagation; calculating the gradient directions of two prism waveforms and adding the gradient directions together to calculate the inverse gradient direction of the prism waveform, using the linear search method or a parabolic fitting method to calculate the updated step, and using the calculated gradient direction and step to update the velocity; using the conventional full waveform inversion method to update the velocity again, and determining whether or not to satisfy the error condition; if not, using the updated velocity as the input velocity, and updating the velocity again; and if so, outputting the inversion result. The full waveform joint inversion method for improving high steep structure velocity inversion efficiency reduces the dependency about whether the high steep structure information is missing in the initial model, and improves the inversion accuracy and efficiency for the high steep structure.

Provided is seismic imaging, particularly, reverse-time migration for generating a real subsurface image from modeling parameters calculated by waveform inversion, etc. A frequency-domain reverse-time migration apparatus includes: a source estimator configured to estimate sources from data measured on a plurality of receivers; and a migration unit configured to receive information about the sources estimated by the source estimator and to perform reverse-time migration in the frequency domain. The source estimator estimates the sources by updating an initial source vector using incremental changes according to a full Newton method. In more detail, the migration unit includes: a back-propagation unit configured to back-propagate the measured data; a virtual source estimator configured to estimate virtual sources from the sources estimated by the source estimator; and a convolution unit configured to convolve the back-propagated measured data with the virtual sources and to output the results of the convolution.

There is provided a method of direct waveform inversion of turning waves (311, 312, 313) to determine parameters characterizing properties of the earth or sub-sections of the earth, particularly of parts of the earth which are capable of trapping hydrocarbons with the inversion yielding from the wavefield of turning waves information representing or being equivalent to velocities or slownesses and/or the gradient of velocities or slownesses, particularly by evaluating wavefield data in the vicinity of turning points (33). The method can be applied sequentially as a survey sinking method.

The invention discloses a resolution controllable envelope generating operator-based multi-scale full-waveform inversion method. The method includes the following steps that: a resolution controllable resolution envelope generating operator is built, and the frequency band range of seismic data used for inversion is controlled by adjusting parameters; a full-waveform inversion method is built according to the resolution controllable resolution envelope generating operator, and the gradient of an objective function relative to model parameters and the calculation formula of iteration step size are inferred; and a steepest descent method is adopted to iteratively update the model parameters until algorithm conditions are satisfied. The method has better capacity of overcoming the problem of cycle skipping, is more suitable for the modeling of a lithologic oil and gas reservoir velocity model, and has more obvious advantages when seismic data are lack of low-frequency information or dominant frequencies in the seismic data are too high. With the resolution controllable envelope generating operator-based multi-scale full-waveform inversion method of the present invention adopted, the seismic data on which the resolution-controllable envelope generating operator has acted has enough low-frequency information regardless of whether the seismic data have sufficient low-frequency information or not; and the parameters can be adjusted, and multi-scale inversion can be realized.

The invention discloses an undulating ground surface waveform inversion method based on an auxiliary coordinate system, and belongs to the technical field of geophysical prospecting for petroleum. The method comprises the steps: firstly carrying out the inversion of a curved mesh region through employing a preliminary wave waveform inversion method in an auxiliary coordinate system, so as to obtain a renewed near-surface speed; secondly carrying out speed updating through employing full-waveform inversion global speed field in the auxiliary coordinate system, so as to overcome the impact on deep speed field inversion from an inaccurate near-surface speed; and finally carrying out speed inversion from low frequency to high frequency through employing a time domain multi-scale inversion method, so as to overcome the dependency of a waveform inversion method on a preliminary speed model. The method can achieve the good inversion of a speed field of a severely undulating ground surface, and provides an accurate offset speed field for high-precision imaging method.

The invention discloses a seismic phase feature recognition waveform inversion method based on a full convolutional neural network. The method comprises the steps of: preliminarily screening a seismicwave time window through a conventional seismic facies screening method FLEXWIN, manually screening data with higher quality as a training set, building a full convolutional neural network, and training the full convolutional neural network through the training set; performing seismic phase identification and window division on seismic waveform data by using the full convolutional neural network;and comparing the waveform similarity between the theoretic and observed data in the windows, and screening the waveform meeting the fitting condition to perform waveform inversion. Through a full convolutional neural network seismic phase feature recognition technology, the problem of efficient waveform window pickup in waveform inversion is solved, the problem of periodic jump is effectively improved, and the convergence rate of waveform inversion is increased.

The invention provides a constrained tomography speed modeling method based on reverse ray tracing. The constrained tomography speed modeling method based on reverse ray tracing comprises the steps of: extracting angle domain common image gathers; automatically fitting the residual curvature of the extracted angle gathers, and calculating a travel time residual by means of a conversion relationship between the travel time residual and a depth residual; by means of a reverse ray tracing method, recording a ray arc length, and calculating a sensitivity matrix; calculating a slow degree disturbance and updating a speed model; and stacking the front depth migration and the extracted angle domain common image gathers, iterating the steps until all controlled layers are updated. The constrained tomography speed modeling method based on reverse ray tracing realizes high migration speed analysis efficiency and high precision in waveform inversion. On condition that a waveform inversion technique cannot be applied in practice, tomography speed inversion has certain advantages and theoretical advantages as a speed updating method.

The invention provides a seismic full-waveform inversion method and device, and relates to the technical field of seismic exploration, and the method comprises the steps: obtaining single-shot seismic data, and generating an initial physical property parameter model based on the single-shot seismic data; updating the initial physical property parameter model according to the single-shot seismic data and a forward modeling process based on a preset forward modeling neural network to obtain a target physical property parameter model, wherein the preset forward simulation neural network is a neural network based on physical constraints. According to the method, the propagation law of seismic waves can be simulated through participation of physical constraints, the preset forward modeling neural network becomes a neural network suitable for complex media and earth surface conditions, and the preset forward modeling neural network can avoid precision loss caused by grid rule subdivision under the complex media and earth surface conditions. The forward modeling process in the seismic full-waveform inversion process is completed through the preset forward modeling simulation neural network, and the calculation efficiency and precision of seismic full-waveform inversion can be improved.

The invention discloses a three-dimensional longitudinal wave impedance full-waveform inversion method and an apparatus. The method comprises the following steps of determining an adjoining equation, longitudinal wave speed gradient, density gradient and longitudinal wave impedance gradient calculating formulas corresponding to a time-domain three-dimensional first-order speed-stress variable density sound wave equation; determining a forward-propagating wave field and a residual reverse back-propagating wave field by adopting a high-order staggered-mesh finite difference method according to the time-domain three-dimensional first-order speed-stress variable density sound wave equation and the corresponding adjoining equation; determining the longitudinal wave speed gradient, the density gradient and the longitudinal wave impedance gradient according to the forward-propagating wave field, the residual reverse back-propagating wave field, and the longitudinal wave speed gradient, density gradient and longitudinal wave impedance gradient calculating formulas; and updating a parameter model by adopting a local optimization algorithm according to the longitudinal wave speed gradient, the density gradient and the longitudinal wave impedance gradient to output a three-dimensional longitudinal wave impedance full-waveform inversion result satisfying a convergence condition. The feasibility of an inversion process can be improved. Great numerical dispersion suppressing capabilities can be further achieved.

The invention discloses a pre-conditioned time domain elastic medium multi-parameter full-waveform inversion method, which comprises the following steps of: S1, selecting a plurality of scale frequency groups to pre-process observation data and seismic wavelets; S2, calculating target seismic source wavelet and a plurality of parameter initial models through staggered grid finite difference forward modeling to obtain a simulated observation record, and acquiring a wave field residual error by subtracting an observation record under each scale from the simulated observation record under the corresponding scale; S3, solving a conjugate operator of a positive operator through adopting an adjoint state method, and acquiring a residual wave field through utilizing the wave field residual error;S4, calculating parameter gradients of a parameter initial model through using the residual wave field and the simulated observation record, and preprocessing all the parameter gradients; S5, optimizing the initial iteration step length through employing a parabola fitting method; and S6, updating a formula and all parameter models through adopting an LBFGS method model to obtain a multi-parameter inversion result. According to the pre-conditioned time domain elastic medium multi-parameter full-waveform inversion method, the efficiency, effect and stability of multi-parameter full-waveform inversion are effectively improved.

The invention provides a CO2 gas drive front edge position judgment method and a model training method and device and relates to the technical field of CO2 sealing monitoring. The model training method comprises the steps: obtaining vertical seismic profile data of sample logging; performing full-waveform inversion on the vertical seismic profile data to obtain a full-waveform inversion result; inputting the vertical seismic profile data and the full-waveform inversion result into a preset neural network model for training; and obtaining a CO2 gas drive front edge position judgment model. Timeshifting ground seismic data of multiple periods are input into the CO2 gas drive front edge position judgment model which is trained in advance, reservoir parameters of the multiple periods are output, and the CO2 gas drive front edge position is obtained through the analysis of a difference data body. According to the method, the ground earthquake and the VSP data are fully utilized, the resolution is not reduced while the large observation range of the ground earthquake data is ensured, and the calculated amount of full waveform inversion is reduced.

A Laplace transform system comprising a processor, a measured time domain wavefield, a velocity model, and Laplace damping constants, wherein the processor is programmed to calculate a substantially about zero frequency component of a Fourier transform of a time domain damped wavefield, wherein the time domain damped wavefield is damped by the Laplace damping constants to obtain long wavelength velocity information for deeper subsurface regions.

The invention concerns a passive monitoring method to detect the presence of and characterize a micro-seismic event (3) occurring in the subsurface, by processing seismic data recorded by a plurality of seismic receivers (R1, Rn) arranged on the earth surface (4), said seismic data comprising acquisition noise and a wave field (6) generated by the micro-seismic event, said wave field being drowned in the noise, the method comprising the performing of waveform inversion directly on the seismic data recorded by the seismic receivers with no prior detection of the wave field generated by the micro-seismic event.

The invention relates to a towing cable earthquake data and little OBS data combined waveform inversion method, and belongs to the field of full-waveform inversion speed modeling of ocean seismic prospecting. The method mainly comprises the following steps that 1) observed towing cable and OBS earthquake record data is obtained, and preprocessed; 2) seismic wavelets are extracted by a higher-orderstatistical method; 3) forward and backward wave fields corresponding to a towing cable earthquake record as well as those corresponding to an OBS earthquake record are calculated; 4) a gradient field of an objective function is calculated on the basis of an adjoint state method; 5) a conjugate gradient field and a correction of a speed model are calculated; 6) the speed model is updated in an iteration way; and 7) whether an iteration ending condition is met is determined, if NO, the step 3) is returned to, and otherwise, a result is output. The problem that waveform inversion only via the towing cable earthquake record lacks low-frequency earthquake information and is in accurate in an inversion result can be solved.