44 results about "Seismic processing" patented technology

The invention discloses a seismic first arrival wave pickup method and device based on a multi-input attention mechanism network, multi-domain data and multiple network advantages are fused to realize first arrival automatic pickup, and compared with manual pickup, the efficiency is greatly improved, and the result is more objective; compared with a traditional automatic pickup method, the method is higher in precision and stability under different signal-to-noise ratios. Meanwhile, through hyper-parameter optimization, the generalization ability is high, reliable data can be provided for subsequent seismic processing, the advantages are outstanding under complex geological conditions, and the method is of great significance to geological analysis and resource exploration.

The invention provides an inverse Q filtering seismic processing system based on artificial intelligence, and the system comprises a historical Q calculation module which calculates a depth domain Q value sequence through a Lee empirical formula, and converts the depth domain Q value sequence into a corresponding frequency band depth domain Q value sequence in combination with a seismic wave dominant frequency; the time-depth conversion module is used for performing convolution on the seismic wavelets and the reflection coefficients to generate synthetic seismic records, and converting a depth domain Q value sequence into a time domain Q value sequence by using a time-depth relationship; the model construction module is used for training a convolutional neural network to generate a Q prediction model by taking the amplitude, the frequency, the phase and the time domain Q value of historical seismic waves as training data; and the inverse Q filtering processing module inputs the multiband parameters of the current seismic wave to the Q prediction model, outputs a time domain Q prediction value, and performs multiband compensation on amplitude attenuation, frequency loss and phase distortion of the seismic wave by adopting an inverse Q filtering formula. According to the method, the defect of insufficient precision of a traditional Q compensation method is avoided, and the calculation efficiency is greatly improved.

Examples of methods and systems are disclosed. The methods may include receiving seismic data regarding a subsurface region of interest, wherein the seismic data comprises a plurality of time-space waveforms, and generating, using statistical sampling, a plurality of pilot waveforms based on the plurality of time-space waveforms. The methods may also include forming a training seismic dataset comprising an input training dataset and an output training dataset, wherein the input training dataset is based on the plurality of time-space waveforms and the output training dataset is based on the plurality of pilot waveforms. The methods may further include training, using the seismic processing system and the training seismic dataset, a machine-learning (ML) model to predict the output training dataset, at least in part, from the input training dataset.

The invention provides a seismic data output method of a seismic processing interpretation system, and belongs to the field of seismic exploration. The method comprises the following implementation steps: step 1, establishing a processing flow; 2, acquiring parameters input by a user; step 3, filtering data of the elastic distributed data set RDD according to parameters input by a user; step 4, outputting the channel header temporary file and the channel data temporary file in parallel; 5, extracting file header information of the header file from the elastic distributed data set RDD, and writing the file header information into an independent info file; step 6, merging the trace header temporary files to obtain an hdr file as an output file; merging the trace data temporary files to obtain a data file as an output file; and outputting the data file, the hdr file and the info file. According to the invention, the output efficiency of the seismic data is effectively improved.

This invention relates to a method for identifying the boundary of anticlines, belonging to the field of oil and gas field exploration and development technology. First, seismic data is acquired, and spectral analysis is performed on the seismic data. The phase of the seismic data is rotated, and the rotated data is interpreted using relative isochronous stratigraphic layers. The interpreted seismic top layer is flattened, and the flattened seismic data is used to determine stratigraphic slices. Based on the amplitude attributes and lateral differences of the stratigraphic slices, the planar morphology of the anticline is identified. This method saves the cost of high-resolution seismic processing and solves the problem of increased uncertainty in imaging results caused by high resolution.

The invention relates to the technical field of petroleum seismic exploration software engineering, and particularly discloses an operation state management method and device for a seismic processing system, and the method comprises the steps: submitting an operation to a Yarn platform, and enabling the operation to flow according to the operation state of the Yarn platform; the method comprises the following steps: a Pi platform obtains an operation state of circulation of a Yarn platform, and converts the operation state of circulation of the Yarn platform into an operation state of circulation of the Pi platform; and carrying out business processing on the operation state transferred by the Pi platform through the operation management service of the Pi platform. According to the method, after a job is submitted to Yarn, the job state is transferred according to the state of Yarn, pi obtains the job state of the corresponding job, and the job state is converted; different business processing flows are executed according to different operation states and operation management services, so that correct operation in an operation life cycle is ensured, actual production requirements are met, and the stability of cluster operation and the smoothness of business processing are ensured.

A computer-implemented method for seismic processing includes receiving a seismic training input image, generating, using a first portion of a machine learning model, a first output based at least in part on the seismic training input image, generating, using a second portion of the machine learning model, a second output based at least in part on the seismic training input image, generating a loss function based at least in part on comparing at least two of the first output, a deterministic first label synthetically generated and representing a deterministic ground truth for the first output, the second output, and a non-deterministic second label representing a non-deterministic ground truth for the second output, and refining the first portion, the second portion, or both of the machine learning model based at least in part on the loss function.

The invention relates to the field of seismic processing system workflow data circulation, and particularly discloses a seismic processing workflow channel header word data circulation method and device, and the method comprises the steps: creating a global channel header word memory management object; performing dynamic memory management on each module object, a relationship between modules and a relationship between a corresponding module and a corresponding header word in the workflow based on the global header word memory management object; dynamically expanding and updating the header word; and dynamically obtaining the latest header word information of the corresponding module, and carrying out related display or application calculation. According to the seismic processing work flow channel header word data circulation method provided by the invention, a global header word memory management data structure is designed, so that dynamic management recording of a module relationship is realized, circulation of latest header word information of a module in a work flow is realized, and the flow efficiency is improved. And the dynamic change circulation requirement of the processing business process on the header word is effectively met.

This invention provides a high-resolution intelligent seismic processing method and system incorporating physical information. The processing method includes: acquiring stacked one-dimensional seismic data; preprocessing the one-dimensional seismic data to obtain a training set and estimating the initial non-attenuated wavelet; constructing a deep network model based on the absorption and attenuation characteristics of the one-dimensional seismic data; learning an attenuation compensation operator; and applying the attenuation compensation operator to non-stationary seismic records to obtain stationary seismic records. This method does not require known Q-values ​​and fully utilizes existing well logging data and non-attenuated wavelets, enabling the acquisition of more stable compensation results.

The invention belongs to the technical field of exploration-seismic processing interpretation, and particularly relates to a non-stretching distortion change correction method for split moving. According to the method, pre-stack seismic data to be dynamically corrected and time-speed pairs are input, the wavelength corresponding to each time-speed pair is calculated, the event center track and the dynamic correction value corresponding to each time-speed pair are calculated, dynamic correction value assignment is carried out in the half-wavelength range of the two sides of the event center, and the dynamic correction value is calculated. The method comprises the seven steps of obtaining the dynamic correction values of sampling points in other areas, splitting moving dynamic correction and outputting a non-stretching distortion change correction result, so that sampling points of an event in each seismic channel have the same dynamic correction value, and in the moving process, the sampling points before dynamic correction are split into data after dynamic correction. It is guaranteed that the amplitude of one sampling point is moved only once, and therefore stretching distortion is effectively avoided. The method makes full use of the number of effective channels for superposing the shallow and middle layers, and improves the imaging quality of the superposing shallow and middle layers.

The present disclosure relates to the technical field of seismic processing, and particularly relates to an interpolation method and device based on prior data, equipment, a storage medium and a computer program. The method comprises the following steps: acquiring seismic data, performing τ-P positive conversion on the seismic data in a preset data processing domain to obtain converted data; selecting unaliasing and preset numerical aliasing data in the converted data, and collecting the selected unaliasing and preset numerical aliasing data into to-be-processed data; performing five-dimensional interpolation on the to-be-processed data to obtain an interpolation result; and performing five-dimensional regularization processing on the seismic data according to the interpolation result to obtain a processing result. The present application can adapt to interpolation processing based on prior data.

This invention relates to a pre-stack noise suppression method for seismic data, belonging to the field of seismic exploration technology. The method includes the following steps: 1) After decompiling and defining the observation system of the acquired seismic data, static correction, spherical diffusion compensation, and surface wave suppression are performed sequentially; 2) The first arrival time of the surface wave suppressed seismic data is corrected to a relatively uniform time, and then random noise and residual noise from the surface wave suppression process are suppressed; 3) The first arrival time of the noise-suppressed seismic data is reverse-corrected to restore the first arrival time to its state before correction. This method can effectively suppress shallow noise interference in near-offset data while better preserving the detailed structure of the seismic data, improving the accuracy of seismic processing; and avoids other noise interference introduced by general processing methods that apply strong noise suppression to achieve the purpose of suppressing shallow noise in near-offset data, thus improving the amplitude fidelity of the processing.

The invention discloses an oil-gas-water interface prediction method and system based on a time-lapse earthquake, and belongs to the technical field of development-earthquake processing interpretation. The prediction method comprises the following steps: constructing a three-dimensional porosity model; establishing an original water saturation model, and determining an original oil-gas-water interface height; determining rock mechanical parameters; based on the three-dimensional porosity model, the original water saturation model and the rock mechanical parameters in combination with a time-lapse seismic amplitude difference formula, calculating a residual value of a model time-lapse seismic amplitude difference and an observation time-lapse seismic amplitude difference, and searching for an optimal oil-gas-water interface height change and a porosity value which enable the residual value to be minimum; according to the optimal oil-gas-water interface height change, the porosity value and the original oil-gas-water interface height, current water saturation change is predicted, and remaining oil-gas distribution is obtained. By inverting the change of the height of the oil-gas-water interface before and after the time-lapse earthquake, the water saturation change condition of the target horizon can be obtained at the same time, and the problems that the nonlinear inversion data calculation amount is large and the result is not convergent are effectively solved.

This invention discloses an adaptive multi-scale high-resolution seismic processing method that integrates time-frequency features, belonging to the field of seismic exploration data processing technology. This method constructs a Transformer-based encoder-decoder network architecture, combines continuous wavelet transform to achieve time-frequency feature fusion, and employs an adaptive multi-scale partitioning strategy based on K-Means energy clustering and a dual attention mechanism to capture local and global dependencies in seismic data, ultimately improving the resolution of the seismic data. This invention addresses the over-reliance of traditional methods on geological assumptions and professional knowledge, and the shortcomings of existing deep learning methods in utilizing time-frequency features and multi-scale modeling. It possesses stronger generalization and transfer capabilities, making it suitable for processing seismic data with complex geological structures.

This invention discloses a method for elastic modulus inversion based on diffraction wave information. The method includes: acquiring a three-dimensional seismic data volume of diffraction waves; obtaining near-, middle-, and far-field angularly stacked data of diffraction waves based on the three-dimensional seismic data volume; obtaining a P-wave diffraction coefficient formula suitable for pre-stack inversion based on the P-wave reflection coefficient formula; determining the diffraction coefficient based on the P-wave diffraction coefficient formula; obtaining near-, middle-, and far-field angularly stacked data of the whole wavefield based on layer interpretation; obtaining wavelet data corresponding to near-, middle-, and far-field gathers based on the near-, middle-, and far-field angularly stacked data of the whole wavefield; converting the layer velocity in the whole-wavefield seismic processing into layer velocity P-wave and S-wave modulus and density; using the layer velocity P-wave and S-wave modulus and density as background parameters of the inversion objective function; constructing and inverting the diffraction wave elastic modulus inversion objective function based on the wavelet data and diffraction coefficients; obtaining the elastic modulus anomaly in the target layer caused by heterogeneous disturbance by solving the objective function; and using the elastic modulus anomaly to identify and predict heterogeneous bodies in the strata.

The invention provides an application multistage communication method and device based on the same message body and a medium, and belongs to the field of oil-gas exploration and development. The method comprises the following steps: step 1, establishing a message body; step 2, establishing a message receiving and sending service; and step 3, performing multi-stage communication of the message based on the message body. According to the method, the message body is established, the messages can be transmitted between the applications (or processes) based on the message body, each application (or process) can receive the messages of other applications (or processes) and can also send the messages to other applications (or processes), and multi-stage message communication is formed between the applications (or processes) in the processing and interpreting integrated platform. The usability of the earthquake processing platform is greatly improved, the data processing time is shortened, the data processing timeliness is improved, and the service is provided for exploration and development of conventional oil gas and coal bed gas.

This invention discloses a high-resolution seismic processing method and system, storage medium, and electronic device, applied to the field of seismic data processing. Addressing the problem that existing techniques suffer from poor spectral extension effects and difficulty in identifying thin-layer earthquakes, this invention, based on time-frequency analysis, performs deconvolution, harmonic decomposition, and basis pursuit inversion on the time-frequency spectrum of seismic data. This achieves high-frequency reconstruction of the time-frequency spectrum, improving the resolution of seismic data and forming a novel spectral extension method. Compared to previous spectral recovery methods, this method achieves better spectral extension effects on more complex strata, with higher resolution and signal-to-noise ratio.

The present invention provides a method, device, equipment and storage medium for acquiring surface data, the method comprising: using a controllable vibrator to excite the first end of the source receiving channel to acquire first surface data of the controllable vibrator; using an artificial weight to excite the first end of the source receiving channel to acquire second surface data of the artificial weight; wherein the artificial weight and the controllable vibrator are located at the same first end of the source receiving channel; converting the first surface data into first surface data that conforms to a target format, and converting the second surface data into second surface data that conforms to the target format; based on the first surface data that conforms to the target format and the second surface data in the target format, acquiring first fused surface data corresponding to the first end. The surface data acquired by this method can solve the interference problem of the controllable vibrator on the near-source receiving channel and improve the resolution of seismic processing data.

The invention relates to the technical field of seismic data processing and analysis, in particular to a seismic data storage method and system based on lake-warehouse integration, and the method comprises the steps: collecting seismic data, and constructing a data storage module based on a Hudi frame through a lake-warehouse integrated architecture; designing a random forest-isolated forest hybrid model, inputting the seismic data into the random forest-isolated forest hybrid model, sequentially performing noise suppression, missing value interpolation and abnormal seismic phase detection, and extracting seismic features to obtain seismic processing data; training a random forest-isolated forest hybrid model based on the seismic processing data, and inputting to-be-detected seismic data into the trained random forest-isolated forest hybrid model to obtain a prediction result; storing the seismic processing data and the prediction result to a data storage module; and in combination with a Hudi framework and a Spark Streaming stream processing engine, performing minute-level dynamic rendering on a prediction result, and then performing visual display. And full-link optimization of seismic data from acquisition, cleaning, storage to analysis is realized.

A method of modeling a subsurface area of a seabed using fewer seismic sensors than a seismic sensors that generate sufficient data to permit a desired model of the subsurface area. Seismic datasets are received from the fewer seismic sensors. The fewer seismic sensors are located at points defined in relation to the seabed. Boundary conditions of a seismic wavefield at a fluid-solid interface between the seabed and water above the seabed are identified. An estimation, from the seismic datasets and the boundary conditions, is made of one or more virtual datasets. Each of the virtual datasets includes corresponding estimated data for additional points defined in relation to the seabed. The points and the additional points, combined, are sufficient to permit the desired model of the subsurface area. A subsurface model of the subsurface area is generated by modeling the subsurface area using the seismic datasets and the virtual datasets.

The invention belongs to the technical field of reservoir prediction, and particularly provides a reservoir gas-bearing evaluation method based on a seismic wave elastic parameter difference ratio, and the method comprises the steps: obtaining a seismic processing sub-offset superposition data volume of a target region; well seismic fine calibration and horizon tracking are carried out; performing pre-stack inversion to obtain a transverse wave impedance data body and a Poisson's ratio data body of the target area; calculating a transverse wave impedance difference and a Poisson's ratio difference between the target reservoir and the cover layer by using the transverse wave impedance data body and the Poisson's ratio data body based on horizon calibration; determining an effective closure threshold value of the cover layer; and according to the construction formula, calculating the sealing coefficient of the target reservoir and the cover layer, and according to the effective sealing threshold value of the cover layer and the sealing coefficient of the target reservoir and the cover layer, determining whether the sealing performance is effective or not, and determining the gas-bearing property of the target reservoir. The problem that the gas-bearing property of the unconventional natural gas reservoir cannot be effectively predicted in the prior art is solved, and the effectiveness of the gas-bearing property of the unconventional natural gas reservoir such as limestone and deep coal rock gas can be evaluated.

This invention belongs to the field of seismic processing in oil and gas exploration, and relates to an optimization method and system for super gathers in seismic velocity analysis. The method, without compromising the fidelity of subsequent processed data, adds seismic head information to low signal-to-noise ratio gather data used for seismic velocity analysis, enabling flexible extraction of super gathers and CMP gathers. This suppresses linear and random noise in the super gathers, and is further supplemented by filtering and amplitude equalization to enhance the energy of the dominant frequency band of reflected waves. This improves the signal-to-noise ratio of super gathers in velocity analysis of oil and gas exploration data, mitigates the energy cluster divergence problem in the velocity spectrum, and achieves high-precision velocity analysis. The method of this invention can make the velocity spectrum energy clusters more focused, improve the signal-to-noise ratio of super gathers, and enhance the energy of the dominant frequency band of reflected waves, thereby significantly improving the accuracy and efficiency of velocity picking, obtaining more accurate velocities, and improving the signal-to-noise ratio and imaging accuracy of seismic data.

The earthquake processing method comprises the following steps: receiving an earthquake waveform which is acquired from an earthquake receiver and contains underground area structure information; generating a back-propagating wavefield by back-propagating seismic data over time based on the initial model system; generating a forward propagation wavefield by forward propagation over time using a given wavelet or processed seismic data; generating a delay time common imaging point gather (DTCIGs) based on the back propagation wave field and the forward propagation wave field; extracting model precision information from the DTCIGs for analysis and / or quality control; determining a model error from the model precision information and / or DTCIGs for analysis and / or quality control; and adjusting the initial model system based on the model error to generate an adjusted / updated model.

Examples of methods and systems for determining a true absolute-amplitude seismic dataset are disclosed. The methods include obtaining an observed seismic dataset, where the observed seismic dataset includes observed seismic traces containing primary reflections and multiple reflections, and selecting a primary-free time window of the observed seismic traces that contains only observed multiple reflections. The methods further include, using a seismic processing system, determining output seismic traces within the primary-free time window using a multiple prediction method, where determining output seismic traces include determining a scalar multiplier based, at least in part, on the output seismic traces, and determining the true absolute-amplitude seismic dataset based, at least in part, on the observed seismic dataset and the scalar multiplier.

The present invention discloses a fiber-optic downhole seismic exploration method for "double-complex" areas, which is applied to the field of downhole geophysics. It addresses the problem that existing technologies cannot effectively collect data in "double-complex" areas, and thus cannot obtain the accurate velocity and thickness of shallow thick conglomerates. The present invention preprocesses fiber-optic downhole seismic data to obtain reliable deep micro-logging data and fiber-optic seismic exploration data, extracts velocity and thickness information of the surface layer, geophysical parameters of the medium-deep complex area, and reservoir information, and can obtain the velocity and thickness of special lithology in the surface complex area, and provide well control parameters of the medium-deep layer for well drive seismic processing.

The invention provides a log collection and display method and device for distributed seismic processing operation, and belongs to the field of petroleum seismic exploration software engineering. The log collection and display method for the distributed seismic processing operation comprises the following steps: step 1, asynchronously sending an operation process log; step 2, establishing a log collection job daemon process; step 3, filtering and combining the job process log files; and step 4, outputting and displaying the information of the job process log. According to the method, the distributed logs are collected, stored and displayed in a classified mode, so that a user directly reads the file to check log content, and the operation process and the positioning problem of the job can be quickly known.

A computing system for providing standardized seismic processing workflows includes a workflow template registry configured to register a plurality of workflow templates that each include one or more steps that produce output seismic data. The computing system also includes a workflow execution track template registry configured to register a plurality of track templates. Each track template includes one or more of the workflow templates. The computing system also includes a workflow execution graphical user interface configured to enable a definition of a seismic processing project. The seismic processing project includes a plurality of tracks and a sequence of seismic processing activities. The computing system also includes a workflow execution dispatcher configured to cause the one or more steps to interact with a cloud computing environment. The computing system also includes an output data registry.

The invention relates to the technical field of oil and gas field seismic data processing, in particular to a fidelity evaluation method and device for time domain seismic processing post-stack data, and the method comprises the steps: carrying out the waveform cross-correlation analysis of a seismic synthesis record of a target well in a research area and seismic data around the target well, so as to generate a cross-correlation coefficient; matching the seismic synthesis record with a wave peak amplitude value and / or a wave trough amplitude value of the seismic data around the target well to generate an amplitude energy matching degree; and evaluating the fidelity of the time domain seismic processing post-stack data according to the cross correlation coefficient and the amplitude energy matching degree. According to the method, the objectivity of seismic data processing result data evaluation can be improved, the evaluation efficiency and precision are improved, and a scientific basis is provided for subsequent exploration decision making.

The invention provides a json-based data element information management method, system, equipment and medium, and belongs to the technical field of seismic processing / interpretation system data backup processing, and the method comprises the following steps: S1, starting an application system export function, and obtaining and exporting data element information of an application system through api; s2, writing the data element information into a json file according to a design hierarchical structure; s3, downloading the unstructured data of the application system according to the data element information; s4, initiating a data import function, extracting data meta-information from the json file, and recovering the data meta-information into the application system; and S5, uploading the downloaded unstructured data to an application system according to the data element information in the json file. According to the method, expansion management can be conveniently carried out, and the compatibility of old version data and the stability of a program are improved.

The present invention discloses a method and device for initial pre-stack migration velocity modeling based on geological constraints, which belongs to the field of oil and gas seismic exploration. The present invention collects data to obtain the stratigraphic reflection layer and fault data of the velocity control layer of the three-dimensional seismic pre-stack time migration data body, establishes a structural grid model in the time domain, determines the velocity control points of each layer segment, obtains the initial velocity model, and combines it with the constrained tomographic inversion near-surface velocity model to construct an initial pre-stack migration velocity model based on geological constraints. The modeling method proposed in the present invention processes the original data into a frequency that matches the processing frequency when determining the velocity control points of each layer segment, so that the obtained velocity is closer to the velocity of the real formation. The present invention can solve the problem of poor initial migration effect in conventional processing, greatly improve the accuracy of seismic data migration imaging, provide more reliable basic data for seismic exploration, and facilitate promotion and application in other three-dimensional seismic processing.