A method for refraction-based surface-consistent amplitude compensation and deconvolution includes receiving seismic traces, the seismic traces generated using at least one source and at least one receiver; calculating an amplitude residual for each seismic trace; determining surface-consistent amplitude residuals for the at least one source and the at least one receiver based on the amplitude residual for each seismic trace; and performing surface-consistent amplitude correction to each seismic trace by applying the determined surface-consistent amplitude residuals for the at least one source and the at least one receiver.

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.

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.

The present disclosure relates to Target-Enclosing Extended Image deconvolution. In a first aspect, the present disclosure provides methods to construct, from surface seismic reflection data, extended image gathers, i.e. time- and space-varying fields corresponding to virtual sources and receivers inside a subsurface volume, to retrieve both local reflection and local transmission responses corresponding to two datums at depth: an original observation datum and a second datum completely enclosing a chosen target subsurface volume away from the original observation datum (e.g., enclosing a target reservoir at depth). The methods of the present disclosure retrieve responses that are devoid of interference due to structures that may exist both above and below the target volume, i.e., the retrieved responses correspond only to the properties of the medium within or inside of the target volume.

The method processes, for each of a plurality of shots at respective source locations, seismic traces recorded at a plurality of receiver locations. Common-mid-point-modulated data are also computed by multiplying the seismic data in each seismic trace by a horizontal mid-point. A depth migration process is applied to the seismic data to obtain a first set of migrated data, and to the mid-point-modulated data to obtain a second set of migrated data. For each shot, aperture values are estimated and associated with respective subsurface positions. A migrated value for a depth and an aperture in a surface aperture common image gather at a horizontal position is a migrated value of the first set of migrated data for a shot such that the estimated aperture value associated with that subsurface position is the aperture.

Methods for correcting seismic signals by determining a signature of an outcropping geobody (e.g., a sand dune) from unprocessed seismic data, attenuating the seismic data using a variable gap deconvolution, and performing a surface consistent deconvolution and amplitude correction on the seismic data. A signature associated with the outcropping geobody and corresponding to the geometry of the geobody may be identified from the unprocessed seismic data. The signature may be used in subsequent processing, such for the determination of a variable gap length for a variable gap deconvolution applied to the seismic data. Computer-readable media and systems for correcting seismic signals are also provided.

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 optimised current velocity model is determined.

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 coventional near surface analysis.

A method for de-ghosting marine seismic trace data is described. A reference seismic trace and a candidate seismic trace are selected from acquired seismic data. The acquired seismic data is gathered using a configuration wherein either a first streamer and a second streamer are disposed at different depths relative to one another and are laterally offset relative to one another, or using a configuration wherein a first source and a second source are disposed at different depths relative to one another and are laterally offset from one another. The reference seismic trace and the candidate seismic trace are processed, e.g., to perform normal moveout correction and/or vertical datum shifting, and the processed reference seismic trace is de-ghosted using the processed, candidate seismic trace.

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.