Processes and systems described herein are directed to imaging a subterranean formation from seismic data recorded in a marine survey with moving marine vibrators. The marine vibrators generate random sweeps with random sweep signatures. Processes and systems generate an up-going pressure wavefield from measured pressure and vertical velocity wavefield data recorded in the marine survey and obtain a downgoing vertical acceleration wavefield that records source wavefields, directivity, source ghosts, and random signatures of the random sweeps. The downgoing vertical acceleration wavefield data is deconvolved from the up-going pressure wavefield to obtain a subsurface reflectivity wavefield that is used to generate an image of the subterranean formation with reduced contamination from source wavefields, directivity, source ghosts, and random signatures of the random sweeps.

A non-blended dataset related to a same surveyed area as a blended dataset is used to deblend the blended dataset. The non-blended dataset may be used to calculate a model dataset emulating the blended dataset, or may be transformed in a model domain and used to derive sparseness weights, model domain masking, scaling or shaping functions used to deblend the blended dataset.

A non-blended dataset related to a same surveyed area as a blended dataset is used to deblend the blended dataset. The non-blended dataset may be used to calculate a model dataset emulating the blended dataset, or may be transformed in a model domain and used to derive sparseness weights, model domain masking, scaling or shaping functions used to deblend the blended dataset.

A method is claimed for automatically transforming sonic well logs from a depth domain to a seismic two-way travel-time domain. The method includes obtaining a training well with a measured sonic well log in the depth domain and a borehole seismic dataset in the depth domain and obtaining an application well with only a measured sonic well log in the depth domain. The method further includes training a network to predict a transformed sonic well log for the training well based, at least in part, on the measured sonic well log and the borehole seismic dataset in the training well, and predicting with the network, the transformed sonic well log in the application well.

A method is claimed for automatically transforming sonic well logs from a depth domain to a seismic two-way travel-time domain. The method includes obtaining a training well with a measured sonic well log in the depth domain and a borehole seismic dataset in the depth domain and obtaining an application well with only a measured sonic well log in the depth domain. The method further includes training a network to predict a transformed sonic well log for the training well based, at least in part, on the measured sonic well log and the borehole seismic dataset in the training well, and predicting with the network, the transformed sonic well log in the application well.

A method for seismic imaging includes receiving a multi-shot seismic data set that was collected using one or more streamers having recorders configured to detect seismic waves that propagate through a subterranean domain. The method also includes partitioning the multi-shot seismic data set into windows including a source dimension. The method also includes defining one or more first basis functions that describe the windows of the multi-shot seismic data set. The method also includes generating a model that describes a decomposition of the multi-shot seismic data set using the one or more first basis functions. The method also includes defining one or more second basis functions that describe a selected output data. The method also includes combining the one or more second basis functions with the model to produce a result for a source side wavefield and a receiver side wavefield.

Techniques to reduce noise in seismic data by receiving a set of seismic data comprising a plurality of input volumes each inclusive of positional data and at least one additional attribute related to the seismic data, selecting a first input volume of the plurality of input volumes having a first additional attribute related to the seismic data, and generating a pilot volume by selecting a range of input volumes of the plurality of input volumes and stacking input volumes of the range of input volumes with the first input volume. Additionally, generating a trained dictionary based upon transformation of the pilot volume, transforming the first input volume into transformed data, imposing a sparse condition on the transformed data utilizing the trained dictionary to generate sparsified data, and inverse transforming the sparsified data to generate an output data volume as a portion of a set of modified seismic data.

An example method is for producing a seismic wave velocity model of a subsurface area. The method includes receiving, by a processor of a computing system, from a seismic receiver, seismic data input comprising a recorded seismic wave field. The method includes receiving, by the processor, an initial 1D velocity model of the subsurface area. The method includes determining, by the processor, a Laplace-Fourier transform of the recorded seismic wave field. The method includes regenerating, by the processor, the current 1D velocity model to generate inverted data representing the subsurface area. The method may include performing, by the processor, an upscaling of a plurality of 1D velocity models to produce a 3D velocity model.

An example method is for producing a seismic wave velocity model of a subsurface area. The method includes receiving, by a processor of a computing system, from a seismic receiver, seismic data input comprising a recorded seismic wave field. The method includes receiving, by the processor, an initial 1D velocity model of the subsurface area. The method includes determining, by the processor, a Laplace-Fourier transform of the recorded seismic wave field. The method includes regenerating, by the processor, the current 1D velocity model to generate inverted data representing the subsurface area. The method may include performing, by the processor, an upscaling of a plurality of 1D velocity models to produce a 3D velocity model.

This disclosure presents processes and systems for generating an image of a subterranean formation from seismic data recorded in a seismic survey of the subterranean formation. The seismic data is contaminated with low frequency noise in a low frequency band. Processes and systems reconstruct seismic data in the low frequency band of the seismic data to obtain low frequency reconstructed seismic data that is free of the low frequency noise. The low frequency reconstructed seismic data is used to construct a velocity model of the subterranean formation. The velocity model and the low frequency reconstructed seismic data are used to generate an image of the subterranean formation that reveals structures of the subterranean formation without contamination from the low frequency noise.