20 results about "Seismic processing" patented technology

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.

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.

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 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 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.

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 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.

The invention discloses a seismic processing and prediction method for shallow water braided river delta reservoir sedimentary microfacies description. The method comprises the following steps: 1) performing spectral analysis and frequency division on an original seismic data volume; 2) performing resampling on low-frequency, high-frequency and original seismic data volumes; (3) time depth calibration is conducted on the vertical well; 4) extracting a well-side seismic trace in a target interval; 5) performing time-frequency spectrum analysis on the seismic trace beside the well; 6) constructing sample data by taking the well point sedimentary microfacies as a label; 7) obtaining a single well target interval sample; 8) summarizing all vertical well samples to form a sample set; according to the shallow water braided river delta reservoir interior sedimentary microfacies classification method, the problem that the sedimentary microfacies are difficult to accurately identify and describe by conventional seismic attributes and a traditional method under the conditions of multi-stage superposition of sedimentary units in a shallow water braided river delta reservoir and strong heterogeneity is solved.

The application discloses a method and system for frequency protection imaging of seismic data in a fiber well, and is applied to the field of geophysical exploration. In view of the problem of frequency reduction of vertical seismic far offset data, the application adopts a linear observation system to collect multi-shot point seismic data in a well, and then processes the collected seismic data to obtain near-wellhead point seismic processed data and all-point well seismic processed data. A single-channel pure data is obtained by extracting one channel of data in the near-wellhead point seismic processed data, removing the channel head and retaining only the data part. Then, the all-point well seismic processed data is subjected to acoustic inversion processing according to the single-channel pure data to obtain pseudo-acoustic inversion processed data. Finally, the pseudo-acoustic inversion processed data is subjected to band-pass filtering and boundary cutting processing to obtain a frequency protection imaging result.

The present specification provides a pre-stack depth migration velocity modeling method and device for a double complex structure area, for a medium-deep layer, seed point interval velocity value sets are determined based on well logging data of a target straight well and seismic processing velocity spectrum data, and then the interval velocity values in the seed point interval velocity value sets are polynomial fitted to determine a velocity trend surface of a deeper layer; multiple iterations are performed, and at each iteration, interpolation is performed between adjacent two interval velocity trend surfaces, small layers are divided, and tomographic inversion is used to continuously correct a new velocity trend surface. As can be seen, the method can control macro large amplitude structure forms by controlling polynomial fitting parameters and adjusting the fitting degree of the velocity boundary surface and the actual geological conditions, can control the macro large amplitude structure forms, and in the subsequent velocity model correction process through multiple iterations, continuously adjusts and increases the velocity trend surface, gradually depicts the micro small amplitude structure forms, and finally obtains a high-precision pre-stack depth migration velocity model, meeting the needs of more complex migration algorithms for migration imaging.

The invention discloses a shale gas geological partition evaluation method under a complex background, which comprises the following steps: acquiring shale quality characteristics of a shale gas exploratory well or an evaluation well of a development block, and carrying out longitudinal and plane characteristic comparative analysis; determining fine features of development area construction; through carrying out earthquake processing and interpretation, the structure unit characteristics are determined; determining the influence of the development zone fault on shale gas preservation; compiling a target stratum structure map, and compiling a development block target stratum burial depth map in combination with the surface elevation information; compiling a target stratum dip angle map on the basis of the target stratum structure map; determining natural fracture characteristics of a target layer of a development area; determining the longitudinal stress interlayer distribution condition of the target layer of the development area; solving the minimum horizontal stress gradient of the development area; determining the maximum principal stress direction of the development block; and according to the data, in combination with the geological characteristics of the development area, preferably selecting parameters which fully reflect the gas content and compressibility of the development area, and carrying out geological zoning standard evaluation research, so that a geological zoning result of the development area is obtained on the basis.

The present application provides a buried hill structure identification method based on the fusion of gravity-magnetic-electromagnetic-seismic exploration technology, comprising: step 1, establishing a rock and stratum geology-geophysical model to clarify the geophysical basis for buried hill structure identification; step 2, performing fine processing and inversion of gravity and magnetic data, separating and extracting buried hill structure gravity and magnetic anomalies, and obtaining three-dimensional apparent density and apparent magnetic susceptibility bodies of the buried hill structure by inversion; step 3, performing fine processing and inversion of electromagnetic data to obtain a depth domain apparent resistivity profile; step 4, performing post-stack seismic processing and gravity-magnetic-electromagnetic low-frequency model constrained inversion to obtain a wave impedance inversion profile; and step 5, performing mutual verification of gravity-magnetic-electromagnetic-seismic to implement the buried hill geological target. The buried hill structure identification method based on the fusion of gravity-magnetic-electromagnetic-seismic exploration technology promotes the development of current buried hill oil and gas exploration technology, fully utilizes the advantages of various exploration technologies, improves the identification accuracy and reliability of buried hill geological targets, and provides a geophysical basis for buried hill oil and gas exploration.

The invention provides a multi-granularity interaction module plug-in method and device and a storage medium, and belongs to the field of oil and gas exploration and development. The method comprises the following steps: S100, defining a multi-granularity plug-in specification; s200, obtaining a plug-in manager, and defining functions of the plug-in manager; and S300, loading the interactive plug-in. The method is suitable for application collaborative management of more and more complex integrated seismic processing and interpretation platforms, the convenience and efficiency of the platform can be improved, the usability of the seismic processing and interpretation platform is greatly improved, the data processing time is shortened, the data processing timeliness is improved, and services are provided for exploration and development of conventional oil gas and coal bed gas.