A surface-consistent refraction analysis method to automatically derive near surface corrections for seismic data processing. The method uses concepts from surface-consistent analysis applied to refracted arrivals. The method includes the use of CMP-offset-azimuth binning, evaluation of mean travel time and standard deviation for each bin, rejection of anomalous first break (FB) picks, derivation of CMP-based travel time-offset functions, conversion to velocity-depth functions, evaluation of long wavelength statics and calculation of surface-consistent residual statics through waveform cross-correlation. Residual time lags are evaluated in multiple CMP-offset-azimuth bins by similarity analysis with a pilot trace for all the other traces in the gather where the correlation window is centered at the refracted arrival. The similarity analysis may take the form of computerized cross-correlation, or other criteria such as semblance. The residuals are then used to build a system of linear equations that is simultaneously inverted for surface-consistent shot and receiver time shift corrections plus a possible subsurface residual term. All the steps are completely automated and require a fraction of the time needed for conventional near surface analysis.

A surface-consistent refraction analysis method to automatically derive near surface corrections for seismic data processing. The method uses concepts from surface-consistent analysis applied to refracted arrivals. The method includes the use of CMP-offset-azimuth binning, evaluation of mean travel time and standard deviation for each bin, rejection of anomalous first break (FB) picks, derivation of CMP-based travel time-offset functions, conversion to velocity-depth functions, evaluation of long wavelength statics and calculation of surface-consistent residual statics through waveform cross-correlation. Residual time lags are evaluated in multiple CMP-offset-azimuth bins by similarity analysis with a pilot trace for all the other traces in the gather where the correlation window is centered at the refracted arrival. The similarity analysis may take the form of computerized cross-correlation, or other criteria such as semblance. The residuals are then used to build a system of linear equations that is simultaneously inverted for surface-consistent shot and receiver time shift corrections plus a possible subsurface residual term. All the steps are completely automated and require a fraction of the time needed for conventional near surface analysis.

A surface-consistent refraction analysis method to automatically derive near surface corrections for seismic data processing. The method uses concepts from surface-consistent analysis applied to refracted arrivals. The method includes the use of CMP-offset-azimuth binning, evaluation of mean travel time and standard deviation for each bin, rejection of anomalous first break (FB) picks, derivation of CMP-based travel time-offset functions, conversion to velocity-depth functions, evaluation of long wavelength statics and calculation of surface-consistent residual statics through waveform cross-correlation. Residual time lags are evaluated in multiple CMP-offset-azimuth bins by similarity analysis with a pilot trace for all the other traces in the gather where the correlation window is centered at the refracted arrival. The similarity analysis may take the form of computerized cross-correlation, or other criteria such as semblance. The residuals are then used to build a system of linear equations that is simultaneously inverted for surface-consistent shot and receiver time shift corrections plus a possible subsurface residual term. All the steps are completely automated and require a fraction of the time needed for conventional near surface analysis.

The present disclosure describes methods and systems, including computer-implemented methods, computer program products, and computer systems, for determining first-break (FB) points. One computer-implemented method includes: selecting, by a hardware processor, potential first-break (PFB) points based on seismic data obtained by plurality of seismic receivers in a geological location; determining, by the hardware processor, a first plurality of FB lines based on the PFB points; selecting, by the hardware processor, a first FB line among the plurality of FB lines; filtering, by the hardware processor, the PFB points based on the first FB line; determining, by the hardware processor, a second plurality of FB lines based on the filtered PFB points; selecting, by the hardware processor, a second FB line among the second plurality of FB lines; and determining, by the hardware processor, FB points based on the second FB line.

The invention relates to a method for processing seismic images containing a reference trace and a control trace. During said method, a reference level and a recording level are defined. Then, the control trace is transformed on the reference level by means of a velocity model. A portion of the reference trace including the recording level is transformed by means of a current velocity model. A portion of the transformed control trace including the recording level is corrected by means of the current velocity model. Finally, an optimized current velocity model is determined.

In some implementations, airborne electromagnetic (AEM) data and seismic data for a geographic region including sand dunes are received, and the AEM data identifies apparent resistivity as a function of depth within the sand dunes. An inversion with cross-domain regularization is calculated of the AEM data and the seismic data to generate a velocity-depth model, and the velocity depth model identifies velocity variations within the sand dunes. A seismic image using the velocity-depth model is generated.

A method for processing broadband single-sensor single-source land seismic data includes receiving seismic traces, the seismic traces generated using at least one source and at least one receiver; converting the seismic traces from particle motion measured by the at least one receiver to particle motion represented by the at least one source by applying a deterministic differential filtering operation; applying a deterministic inverse-Q filtering operation on the converted seismic traces; processing the inverse-Q filtered seismic traces using a set of surface-consistent filter and attribute corrections; and generating a seismic image based on the processed seismic traces.

A method of redatuming geophysical data, wherein there is provided multi-component geophysical data, and the method includes obtaining at least one focussing function and/or at least one Green's function from the multi-component geophysical data.

Seismic data from seismic exploration surveys are mapped into a hypercube of bins or voxels in a four-dimensional space (X, Y, Offset, and Azimuth) according to Common Mid-Point (or CMP) between source and receivers. The mapped data from individual voxels or bins is then analyzed by multimodal statistics. Robust estimates of first break picks are obtained from the analysis. The first break picks are then used to as seed inputs for autopicking iteration, which proceeds to convergence. Estimates of confidence levels in the data are provided for re-picking to reduce computer processing time in successive autopicking iterations. Analysis is provided of different seismic attributes such as azimuthal velocity variations indicative of anisotropy, positioning errors of sources/receivers, geometry errors, and three dimensional distribution of inversion residuals. Analysis is also performed of standard deviation of the travel time data useful for estimating data errors in the inversion covariance matrix.

Seismic data from seismic exploration surveys are mapped into a hypercube of bins or voxels in a four-dimensional space (X, Y, Offset, and Azimuth) according to Common Mid-Point (or CMP) between source and receivers. The mapped data from individual voxels or bins is then analyzed by multimodal statistics. Robust estimates of first break picks are obtained from the analysis. The first break picks are then used to as seed inputs for autopicking iteration, which proceeds to convergence. Estimates of confidence levels in the data are provided for re-picking to reduce computer processing time in successive autopicking iterations. Analysis is provided of different seismic attributes such as azimuthal velocity variations indicative of anisotropy, positioning errors of sources/receivers, geometry errors, and three dimensional distribution of inversion residuals. Analysis is also performed of standard deviation of the travel time data useful for estimating data errors in the inversion covariance matrix.