A method and apparatus for imaging seismic data includes obtaining an initial model of a subsurface formation, wherein the model includes a plurality of nodes that form at least part of a grid; an initial dip value for the nodes; and a set of origin coordinates for each of the nodes; performing bottom-up ray tracing for each node in the model, resulting in a set of arrival coordinates for each node; identifying a plurality of gathers from the seismic data; for each gather: calculating a set of midpoint coordinates; defining a midpoint vicinity surrounding the set of midpoint coordinates; identifying the nodes having arrival coordinates within the midpoint vicinity; and estimating a unique aperture for each of the gathers based on the respective origin coordinates; storing the estimated apertures in a table; and generating a subsurface volume or image with subsurface reflectors determined with apertures of the respective gathers.

Raw 3D seismic streamer wavefield data is received as a receiver-ghosted shot gather. The received receiver-ghosted shot gather shot gather is processed into a normalized form as normalized data. The normalized data is partitioned into a plurality of user-defined sub-gathers and processed to generate a complete receiver-deghosted shot gather. Output of the complete receiver-deghosted shot gather is initiated.

Seismic survey data is received, indexed into index sets, and each index set partitioned into data blocks. For each particular data block of a particular index set, the particular data block is sliced into frequency slices. For each particular frequency slice of the particular data block, the particular frequency slice is processed to remove random and erratic noise by: forming a Hankel matrix from the particular frequency slice: determining an optimal rank for the Hankel matrix, determining a clean signal and erratic noise from the ranked Hankel matrix, and returning the clean signal and erratic noise for the particular frequency slice. A clean signal is assembled from the index sets.

Systems, methods, and computer-readable media for estimating a component of a seismic wavefield. The method may include accessing marine seismic data comprising a plurality of discrete measurements of a seismic wavefield; processing the marine seismic data to determine a relationship between a plurality of components of the seismic wavefield and each of the discrete measurements; and estimating from the marine seismic data processed via the one or more processors, each component of the seismic wavefield separated from each of the other plurality of components of the seismic wavefield and evaluated at a predetermined position.

Method for acquiring, at reduced acquisition cost, seismic data using simultaneous, field-encoded sources in the field (702), and then constructing pseudo source-records (703) that better meet the requirements for using additional simultaneous computer-encoded sourcing for computer simulations or forward modeling (706) as part of (707) iterative FWI (Full Wavefield Inversion) or RTM (Reverse Time Migration), with additional reduction in computational costs. By better meeting the requirements of simultaneous sourcing for FWI or RTM (701), artifacts and crosstalk are reduced in the output. The method can be used for marine streamer acquisition and other non-fixed spread geometries to acquire both positive and negative offsets and to mitigate the “missing data” problem for simultaneous-source FWI. It can also be used for land data to overcome issues with moving spreads and long continuous records.

There is provided herein a new system and method of local attribute match filtering which operates in the local attribute domain via the use of complex wavelet transform technology. This approach is adaptable to address various noise types in seismic data and, more particularly, is well suited to reduce the noise in geophone data as long as an associated hydrophone signal is relatively noise-free.

Leveraging migration and demigration, here we propose a learning-based approach for fast denoising with applications to fast-track processing. The method is designed to directly work on raw data without separating each noise type and character. The automatic attenuation of noise is attained by performing migration/demigration guided sparse inversion. By discussing examples from a Permian Basin dataset with very challenging noise issues, we attest the feasibility of this learning-based approach as a fast turnaround alternative to conventional denoising methodology.

A method or system is configured for determining a seismic attenuation quality factor Q for intervals of subsurface formations by performing actions including receiving vertical seismic profile traces. The actions include filtering the vertical seismic profile traces with an inverse impulse response of a downhole receiver. The actions include transforming the vertical seismic profile data from the particle motion measured by the downhole receiver to the far-field particle motions represented by the source wavelet. The actions include determining a ratio of the spectral amplitudes of the direct arrival event of the transformed vertical seismic profile data and the source Klauder wavelet. A quality factor Q is generated representing an attenuation of the seismic signal between the source at ground level surface and the downhole receiver.

A distributed acoustic sensing (DAS) system is coupled to an optical fiber along a plurality of channels. The system generates a DAS seismic profile of the subsurface formation based on detected seismic data, identifies at least one region having coherent noise, and identifies which of the plurality of channels are within the identified at least one region. For each trace of data associated with the plurality of noisy channels, the system converts, from a time to a wavelet domain, the trace of data and a reference trace having less coherent noise, and suppresses the wavelet coefficients of the trace of data based on the wavelet coefficients of the reference trace. After the system mitigates the noise in the wavelet domain, an inverse wavelet transform is applied to the trace of data to convert back to the time domain and create a reduced noise DAS seismic profile.

A method is described for seismic inversion including receiving a processed seismic image and an enhanced seismic image representative of a subsurface volume of interest; forward modeling the processed seismic image and the enhanced seismic image to generate a first modeled dataset and a second modeled dataset; differencing the first modeled dataset and the second modeled dataset to create a residual dataset; filtering the first modeled dataset to generate an approximation of illumination; preconditioning the residual dataset with the approximation of illumination to generate an adjoint source; back projecting the adjoint source to determine a model update; and applying the model update to an earth model of the subsurface volume of interest.