11 results about "Earthquake map" patented technology

A method for predicting a property of a subsurface formation, includes: drilling one or more wellbores into the subsurface formation at a well location; conducting a seismic survey at the well location to construct a primary seismic image volume, the primary seismic image volume dataset comprises at least a pressure wave velocity vp, a shear velocity vs, and a density rho, in both time and frequency domains; conducting well logging at the one or more wellbores to generate logging information at the well location; generating an auxiliary seismic image volume for seismic-guided property prediction using Kriging at the well location; generating a prediction operator based on the primary seismic image volume, the auxiliary seismic image volume and the well logging information; feeding a seismic image volume and the prediction operator into a property prediction engine; and generating the predicted property of the subsurface formation.

This invention provides a method and system for automatic vertex picking of DAS-based microseismic events, relating to the field of microseismic location technology. The method includes acquiring multi-channel data corresponding to microseismic events and performing demodulation analysis to form multi-channel waveform data; performing correlation analysis on the waveform data from different channels to establish an automatic picking correlation model; performing image transformation based on the automatic picking correlation model to form corresponding grayscale images; and performing location discrimination analysis based on the grayscale images to determine the event vertex channel. This method improves the interpretation accuracy and reliability of geological analysis of seismic images by removing noise while preserving geological structural features such as faults and strata.

The application discloses a salt-underground seismic image quality evaluation method and device, equipment and a storage medium. The salt-underground seismic image quality evaluation method comprises the following steps: acquiring a salt-underground seismic image to be evaluated, and uniformly setting at least two quality detection points in the salt-underground seismic image; determining a linear quality score relationship between an expert score result of a quality detection point and an optimal image attribute based on the expert score result of the quality detection point and an attribute value of the optimal image attribute corresponding to the quality detection point; and determining a predicted expert score result of the quality detection point based on the linear quality score relationship, and performing quality grade evaluation on the salt-underground seismic image to be evaluated. Through the technical solution, objective, rapid and accurate evaluation of a large amount of seismic images is realized.

The application provides a seismic wave impedance inversion method and system based on deep learning, comprising the following steps: S1, constructing and preprocessing a data set; S2, constructing and training a DA-TransUNet model; extracting features of an input seismic image through a convolutional neural network of the DA-TransUNet model, extracting local features, and generating skip connection features; extracting global features through a Transformer network based on the local features; S3, performing upsampling processing through the convolutional neural network of the DA-TransUNet model, fusing the skip connection features with features of a current layer of a decoder, and obtaining a fusion result as an upsampling result; and S4, constructing a final seismic image prediction result. Through the DA-TransUNet network architecture, the application solves the problems of insufficient precision and low efficiency of traditional seismic wave impedance inversion technology in processing complex geological data.

This application relates to a seismic wavefield extension method, apparatus, device, storage medium, and computer program. The method includes: acquiring a seismic image at any time within a reference time period; performing image denoising on the seismic image to obtain a target seismic image; calculating the dispersion relation of the wave equation corresponding to the target seismic image according to a preset spatiotemporal finite difference method; performing a Fourier transform on the wave equation according to the dispersion relation to obtain the frequency-wavenumber domain seismic wavefield corresponding to the target seismic image; selecting the negative frequency component in the wavenumber domain seismic wavefield; and performing wavefield extension on the frequency-wavenumber domain seismic wavefield according to the negative frequency component to obtain the target seismic wavefield. This application improves the efficiency of seismic wavefield extension.

Systems and methods for creating a plurality of dip-constrained pseudo-angle common image gathers (DPACIGs) to pick a residual moveout are disclosed. The method includes obtaining a plurality of plane-wave CIGs and an initial seismic velocity model, stacking the plane-wave CIGs to estimate a structural dip and applying a vector median filter (VMF) to attenuate a dip noise contained in the structural dip. The method also includes smoothing the plurality of plane-wave CIGs by applying a structural oriented smoothing (SOS) to create a plurality of dip-constrained plane-wave CIGs and applying a non-linear transform to the plurality of dip-constrained plane-wave CIGs to create a plurality of DPACIGs. The method further includes performing a migration velocity analysis (MVA) on the DPACIGs to pick a residual moveout, determining an updated seismic velocity model based on the residual moveout and creating a seismic image using the updated seismic velocity model and the seismic dataset.

This invention belongs to the field of seismic image signal processing, and provides a method and related apparatus for digitizing short-period seismograph observation maps. The method includes: removing noise from scanned short-period seismograph observation map images to obtain denoised images; using a correction formula based on the length of the recording pen, correcting for arc distortion in the denoised images to obtain arc-distortion-corrected images; since the images also have tilt distortion, based on the working principle of short-period seismographs, deriving an inherent displacement formula for the recording pen, and using this formula to correct for tilt distortion in the arc-distortion-corrected images to obtain distortion-free seismic waveform images; and digitizing the distortion-free seismic waveform images. This application solves the problem mentioned in the background art that previous solutions only completed the electronic scanning and storage of simulated seismic observation maps, without realizing the digitization of the electronic image waveforms, by performing image preprocessing and digitization processing on simulated seismic observation maps.

This invention provides a method and system for signal protection and multiple suppression in large-volume seismic data processing areas, relating to the field of seismic data processing technology. The method includes: preprocessing seismic data to form preprocessed seismic data; performing multiple prediction on the preprocessed seismic data to form a multiple prediction model; combining the multiple prediction model and the preprocessed seismic data to determine subtraction parameters; performing interpolation processing on the multiple prediction model to obtain an interpolation model; performing subtraction suppression on the interpolation model and the subtraction parameters to form subtracted post-processed data; and merging the subtracted post-processed data with the subtraction parameters to form suppressed post-processed data. This method improves the interpretation accuracy and reliability of geological analysis of seismic images by removing noise while preserving geological structural features such as faults and strata.

Methods and systems are disclosed. The method include generating a simulated seismic training dataset, where the simulated seismic training dataset includes upgoing signals and downgoing signals, each recorded on hydrophones and geophones and training a deep learning network, using the simulated seismic training dataset, to separate the upgoing signals from the downgoing signals. The method also includes obtaining field hydrophone data and field geophone data pertaining to a subsurface region of interest, recorded by a seismic acquisition system including hydrophones and geophones, and separating the field hydrophone data and field geophone data into predicted upgoing signals. The method further includes generating a seismic image of the subsurface region of interest based, at least in part, on the predicted upgoing signals.

Methods for mapping a subsurface formation can include: generating a velocity model representing the subsurface formation based on the seismic data; determining an upper bound for traveltime within the velocity model from a seismic source; and generating a seismic image of the subsurface formation by migrating the seismic data using Kirchhoff depth migration, where traveltime is calculated through ray tracing, and the maximum traveltime determines the stopping point for ray tracing. Determining an upper bound for traveltime within the velocity model from a seismic source can include: converting the velocity model into a slowness model; integrating slowness along straight paths from the seismic source to boundary points of the slowness model to generate traveltime values; and determining an upper bound of traveltime for seismic rays traveling within the velocity model by selecting a maximum traveltime value from the straight paths.

The application provides a structure-oriented bilateral filtering seismic image processing method and system, and relates to the technical field of seismic image processing. The method comprises the following steps: obtaining seismic image input information, and performing initial data processing to form to-be-processed seismic image data; performing structure tensor processing on the to-be-processed seismic image data to determine the structure direction and characteristics of the to-be-processed seismic image; determining tensor filtering coefficients according to the structure direction and characteristics of the to-be-processed seismic image; performing structure-oriented smoothing processing on the to-be-processed seismic image data according to the tensor filtering coefficients to form smoothed seismic image data; and performing bilateral filtering processing on the smoothed seismic image data to form characteristic seismic image data. The method can remove noise in the seismic image while retaining geological structure characteristics such as faults and strata in the image, thereby improving the interpretation accuracy of the seismic image and the reliability of geological analysis.