A method and a system for implementing the method are disclosed wherein the seismic input data and land acquisition input data may be obtained from a non-flat surface, sometimes mild or foothill topography as well as the shot and receiver lines might not necessarily be straight, and often curve to avoid obstacles on the land surface. In particular, the method and system disclosed, decomposes the cross-spread data into sparse common spread beams, then maps those sparse beams into common-spread depth domain, in order to finally stack them to construct the subsurface depth images. The common spread beam migration and processing have higher signal to noise ratio, as well as faster turn-around processing time, for the cross-spread land acquisition over the common-shot or common offset beam migration/processing. The common spread beam migration method and system disclosed, will eventually help illuminate and interpret the hydro-carbonate targets for the seismic processing.

Methods and systems for determining a spectral ratio log using a time domain seismic image and a seismic velocity model are disclosed. The method includes determining a first mono-spectral seismic image and a second mono-spectral seismic image from the time domain seismic image. The method further includes determining a time domain spectral ratio image from the first mono-spectral seismic image and the second mono-spectral seismic image and transforming the time domain spectral ratio image into a depth domain spectral ratio image using the seismic velocity model. The method still further includes defining a wellbore path through the depth domain spectral ratio image and determining a spectral ratio log along the wellbore path from the depth domain spectral ratio.

Methods for processing seismic data acquired with non-impulsive moving sources are provided. Some methods remove cross-talk noise from the seismic data using emitted signal data and an underground formation's response estimate, which may be iteratively enhanced. Some methods perform resampling before a spatial or a spatio-temporal inversion. Some methods compensate for source's motion during the inversion, and/or are usable for multiple independently moving sources.

Estimating an earth response can include deconvolving a multi-dimensional source wavefield from near-continuously recorded seismic data recorded at a receiver position. The deconvolving can include spreading the near-continuously recorded seismic data across a plurality of possible source emission angles. The result of the deconvolution can be the earth response estimate.

Hydrocarbon exploration and extraction can be facilitated using machine-learning models. For example, a system described herein can receive seismic data indicating locations of geological bodies in a target area of a subterranean formation. The system can provide the seismic data as input to a trained machine-learning model for determining whether the target area of the subterranean formation includes one or more types of geological bodies. The system can receive an output from the trained machine-learning model indicating whether or not the target area of the subterranean formation includes the one or more types of geological bodies. The system can then execute one or more processing operations for facilitating hydrocarbon exploration or extraction based on the seismic data and the output from the trained machine-learning model.

A method for obtaining zero-offset and near zero offset seismic data from a marine survey, with separation of direct arrival information and reflectivity information, the method including: modeling a direct arrival estimate at a passive near-field hydrophone array by using a notional source separation on active near-field hydrophone data; generating reflection data for the passive near-field hydrophone array by subtraction of the modeled direct wave from data recorded by the passive near-field hydrophone array; generating near zero-offset reflectivity traces by stacking the reflection data for the passive near-field hydrophone array on a string-by-string basis or on a combination of strings basis; generating reflectivity information at the active near-field hydrophone array by subtracting the direct arrival estimate modeled using the notional source separation from the active near-field hydrophone data; and generating an estimate of zero-offset reflectivity traces by calculating a cross-correlation between the between the reflectivity information at the active near-field hydrophone array and the near zero-offset traces and performing an optimized stacking with summation weights based on coefficients of the cross-correlation.

A method and a system for implementing the method are disclosed wherein the seismic input data and land acquisition input data may be obtained from a non-flat surface, sometimes mild or foothill topography as well as the shot and receiver lines might not necessarily be straight, and often curve to avoid obstacles on the land surface. In particular, the method and system disclosed, decomposes the cross-spread data into sparse common spread beams, then maps those sparse beams into common-spread depth domain, in order to finally stack them to construct the subsurface depth images. The common spread beam migration and processing have higher signal to noise ratio, as well as faster turn-around processing time, for the cross-spread land acquisition over the common-shot or common offset beam migration/processing. The common spread beam migration method and system disclosed, will eventually help illuminate and interpret the hydro-carbonate targets for the seismic processing.

Apparatus, methods, and systems for determining body wave slowness values for a target formation zone. A method includes selecting a target axial resolution based on the size of a receiver array, obtaining a plurality of waveform data sets corresponding to a target formation zone and each acquired at a different shot position, reconstructing the plurality of waveform data sets to generate a plurality of subarray data sets corresponding to the target formation zone, determining a slowness value for each subarray data set and determining a slowness versus offset value for each subarray data set. The method may also include generating a borehole model having at least one alteration formation zone and a virgin formation zone and generating a slowness versus offset model based at least in part on the borehole model. The method may also include determining a radial depth of the alteration formation zone.

Various implementations directed to quality control and preconditioning of seismic data are provided. In one implementation, a method may include receiving particle motion data from particle motion sensors disposed on seismic streamers. The method may also include performing quality control (QC) processing on the particle motion data. The method may further include performing preconditioning processing on the QC-processed particle motion data. The method may additionally include attenuating noise in the preconditioning-processed particle motion data.

Methods, systems, and computer-readable medium to perform operations including: generating a first time-frequency spectrum of a first seismic trace from an original seismic dataset; generating a second time-frequency spectrum of a second seismic trace from an enhanced seismic dataset, where the second seismic trace corresponds to the first seismic trace; and re-combining an amplitude spectrum of the first time-frequency spectrum and a phase spectrum of the second time-frequency spectrum to generate a third time-frequency spectrum of an output trace that corresponds to the first and second seismic traces.