Abstract:
A device, medium and method for deblending seismic data associated with a subsurface of the earth. The method includes receiving an input dataset generated by first and second sources S1 and S2 that are operating as simultaneous sources; arranging the input dataset based on the firing times of source S1; applying with a computing system an annihilation filter to the arranged input dataset to estimate cross-talk noise; convolving the cross-talk noise estimate with an operator to form a signal estimate using the firing times of S1 and S2; and generating an image of the subsurface based on the signal estimate.
Abstract:
The present disclosure includes a method for suppressing 4D noise. The method includes calculating a first similarity map based on the similarity of one of one or more first 3D images and a second 3D image. The first and second 3D images are derived from first and second surveys, respectively. The method also includes calculating a second similarity map based on the similarity of one of the one or more first 3D images and a third 3D image, which is derived from the second survey. The method also includes calculating a third similarity map based on the similarity of first and second 4D images, which are based on differences between the 3D images. The method also includes generating a composite 4D image based at least on the first, second, and third similarity maps. The present disclosure may also include associated systems and apparatus.
Abstract:
A device, medium and method for deblending seismic data associated with a subsurface of the earth. The method includes receiving an input dataset generated by first and second sources S1 and S2 that are operating as simultaneous sources; arranging the input dataset based on the firing times of source S1; applying with a computing system an annihilation filter to the arranged input dataset to estimate cross-talk noise; convolving the cross-talk noise estimate with an operator to form a signal estimate using the firing times of S1 and S2; and generating an image of the subsurface based on the signal estimate.
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 maximizing a repeatability between a base seismic survey and a monitor seismic survey of a same surveyed subsurface during a 4-dimensional (4D) project. The method includes receiving first seismic data associated with the base seismic survey; receiving second seismic data associated with the monitor seismic survey, wherein the monitor seismic survey is performed later in time than the base seismic survey; estimating subsurface reflection-points and incidence angles; determining 4D-binning based on the estimated subsurface reflection-points and incidence angles; and maximizing the repeatability between the first seismic data and the second seismic data by using the 4D-binning.
Abstract:
A method for increasing similarity between a first seismic dataset and a second seismic dataset from at least one seismic survey of a subsurface. The first and second seismic datasets are migrated to a dip angle image domain. The migrated first and second seismic datasets are used in the dip angle image domain to calculate a set of decimating weights to be applied to the first seismic dataset and the second seismic dataset to maximize a similarity between the first seismic dataset and the second seismic dataset. The decimated weights are applied to the first and second seismic datasets, and an image of the subsurface is generated using the first seismic dataset and the second seismic dataset following application of the decimated weights.
Abstract:
The present disclosure includes a method for suppressing 4D noise. The method includes calculating a first similarity map based on the similarity of one of one or more first 3D images and a second 3D image. The first and second 3D images are derived from first and second surveys, respectively. The method also includes calculating a second similarity map based on the similarity of one of the one or more first 3D images and a third 3D image, which is derived from the second survey. The method also includes calculating a third similarity map based on the similarity of first and second 4D images, which are based on differences between the 3D images. The method also includes generating a composite 4D image based at least on the first, second, and third similarity maps. The present disclosure may also include associated systems and apparatus.