Abstract: Computing device, computer instructions and method for processing input seismic data d. The method includes receiving the input seismic data d recorded in a first domain by seismic receivers that are towed in water, the input seismic data d including pressure data and/or and particle motion data; generating a model p in a second domain to describe the input data d; processing the model p to generate an output particle motion dataset; and generating an image of the surveyed subsurface based on the output particle motion dataset.

Abstract: A method for processing seismic data, the method including receiving seismic data acquired by at least one receiver over a water-covered subsurface formation; generating, based on the seismic data, a down-going wavefield; generating, based on the seismic data, a partial down-going wavefield with attenuated water-wave; estimating a subsurface reflectivity R using multi-dimensional deconvolution, which equates (1) a convolution of the down-going wavefield with the subsurface reflectivity R to (2) the partial down-going wavefield; and generating an image of the water-covered subsurface formation based on the subsurface reflectivity R.

Abstract: A method for generating an image of a subsurface based on blended seismic data includes receiving the blended seismic data, which is recorded so that plural traces have uncontaminated parts with different uncontaminated recording time lengths, selecting plural subgroups (SG1, SG2) of traces so that each subgroup (SG1) includes only uncontaminated parts that have a same uncontaminated recording time length, processing the traces from each subgroup to generate processed traces, mapping the processed traces to a same sampling, combining the processed traces from the plural subgroups (SG1, SG2) to generate combined processed traces, and generating an image of a structure of the subsurface based on the combined processed traces.

Abstract: 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.

Abstract: Methods and seismic data processing apparatuses use a down-going annihilation operator to generate an image from seismic data acquired over a water-covered subsurface formation. The down-going annihilation operator is derived using a down-going wavefield and an estimated water-wave extracted from the seismic data. The down-going annihilation operator may be derived in plane-wave domain.

Abstract: Computing device, computer instructions and method for processing input seismic data d. The method includes receiving the input seismic data d recorded in a first domain by seismic receivers that are towed in water, the input seismic data d including pressure data and/or and particle motion data; generating a model p in a second domain to describe the input data d; processing the model p to generate an output particle motion dataset; and generating an image of the surveyed subsurface based on the output particle motion dataset.

Abstract: Computing device, computer instructions and method process input seismic data d recorded in a first domain by seismic receivers that travel in water, the input seismic data d including pressure and particle motion measurements, including up-going and down-going wave-fields. A model p is generated in a second domain by solving an inverse problem for the input seismic data d, wherein applying an L transform to the model p describes the input data d. An L? transform, which is different from the L transform, is then applied to the model p to obtain an output seismic data in the first domain, the output seismic data having a characteristic imparted by the transform L?. The characteristic is related to pressure wave-fields and/or particle motion wave-fields interpolated at positions in-between the input seismic receivers. An image of the surveyed subsurface is generated based on the output seismic dataset.

Abstract: Computing device, computer instructions and method for processing energy at a free-surface reflection relating to an air-water interface. The method includes receiving input seismic data recorded with seismic sensors; receiving wave-height data that describes an actual shape of a top surface of a body of water; processing up-going energy at a receiver and down-going energy following a reflection at the sea-surface, using the input seismic data and a linear operator modified to take into account the wave-height data; and generating an image of the subsurface based on the up-going energy or the down-going energy or a combination of the input seismic data and one of the up-going or down-going energy.

Abstract: A method for de-blending seismic data associated with an interface located in a subsurface of the earth, includes receiving blended seismic data E generated by firing N source arrays according to a pre-determined sequence Seq; selecting N sub-datasets SDn from the blended seismic data E; interpolating each selected sub-dataset SDn to reference positions ref, where the blended seismic data E is expected to be recorded, to generate interpolated data k; de-blending, in a processor, the interpolated data k to generate de-blended data o; and generating an image of the interface of the subsurface based on the de-blended data o.

Abstract: 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.

Abstract: 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.

Abstract: Methods and apparatuses for seismic exploration of an underground structure obtain improved images by integrating partial match filtering in an FWI. Filtered (auxiliary) data replaces one of the observed data and the synthetic data in the FWI's objective function to avoid cycle skipping.

Abstract: Methods and apparatuses for seismic exploration of an underground structure obtain improved images by integrating partial match filtering in an FWI. Filtered (auxiliary) data replaces one of the observed data and the synthetic data in the FWI's objective function to avoid cycle skipping.

Abstract: Computing device, computer instructions and method process input seismic data d recorded in a first domain by seismic receivers that travel in water, the input seismic data d including pressure and particle motion measurements, including up-going and down-going wave-fields. A model p is generated in a second domain by solving an inverse problem for the input seismic data d, wherein applying an L transform to the model p describes the input data d. An L? transform, which is different from the L transform, is then applied to the model p to obtain an output seismic data in the first domain, the output seismic data having a characteristic imparted by the transform L?. The characteristic is related to pressure wave-fields and/or particle motion wave-fields interpolated at positions in-between the input seismic receivers. An image of the surveyed subsurface is generated based on the output seismic dataset.

Abstract: Method for reconstructing seismic data. The method includes receiving at a computing device an input seismic data set d related to plural shots emitted by one or more seismic sources; receiving at the computing device a positional data set dp relating to recording locations of the receivers that recorded the input seismic data set d; receiving at the computing device a receiver target location; calculating an adjusted receiver location based on (i) the positional data set dp and (ii) the receiver target location, wherein the adjusted receiver location substantially coincides with a receiver location from the positional data set dp; calculating reconstructed seismic data dr at the adjusted receiver location using the input seismic data set d and the positional data set dp; and correcting the seismic wave paths from the one or more seismic sources to the receivers based on the reconstructed seismic data dr.

Abstract: Methods (700) and devices (600) for seismic data processing estimate (720) signal-to-noise ratios of data in a spatio-temporal block of data, determine (730) data-domain weights associated to the data based on the estimated signal-to-noise ratios, and then generate (740) a model of the signal and/or a model of the noise using the data-domain weights.

Abstract: A method for de-blending seismic data associated with an interface located in a subsurface of the earth, includes receiving blended seismic data E generated by firing N source arrays according to a pre-determined sequence Seq; selecting N sub-datasets SDn from the blended seismic data E; interpolating each selected sub-dataset SDn to reference positions ref, where the blended seismic data E is expected to be recorded, to generate interpolated data k; de-blending, in a processor, the interpolated data k to generate de-blended data o; and generating an image of the interface of the subsurface based on the de-blended data o.

Abstract: A method for estimating a time variant signal representing a seismic source obtains seismic data recorded by at least one receiver and generated by the seismic source, the recorded seismic data comprising direct arrivals and derives the time variant signal using an operator that relates the time variant signal to the acquired seismic data, the operator constrained such that the time variant signal is sparse in time.

Abstract: Computing device, computer instructions and method for up-down separation of seismic data. The method includes receiving the seismic data, which includes hydrophone data and particle motion data; performing a first up-down separation, which is independent of a ghost model, using as input the hydrophone data and the particle motion data, to obtain first up-down separated data; performing a second up-down separation by using as input a combination of (i) the hydrophone data and/or the particle motion data and (ii) the first up-down separated data, wherein an output of the second up-down separation is second up-down separated data; and generating an image of the subsurface based on the second up-down separated data.

Abstract: A method for estimating a time variant signal representing a seismic source obtains seismic data recorded by at least one receiver and generated by the seismic source, the recorded seismic data comprising direct arrivals and derives the time variant signal using an operator that relates the time variant signal to the acquired seismic data, the operator constrained such that the time variant signal is sparse in time.