Abstract: Property values inside an explored underground subsurface are determined using hybrid analytic and machine learning. A training dataset representing survey data acquired over the explored underground structure is used to obtain labels via an analytic inversion. A deep neural network model generated using the training dataset and the labels is used to predict property values corresponding to the survey data using the DNN model.

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: 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: Property values inside an explored underground subsurface are determined using hybrid analytic and machine learning. A training dataset representing survey data acquired over the explored underground structure is used to obtain labels via an analytic inversion. A deep neural network model generated using the training dataset and the labels is used to predict property values corresponding to the survey data using the DNN model.

Abstract: A method for spectral analysis of seismic data obtains imaged seismic data and generates orthogonally shifted imaged seismic data gathers. The orthogonally shifted imaged seismic data gathers are processed to generate a spectrally processed imaged seismic data. Alternatively, the imaged seismic data are obtained using a spectral processing filter that is a function of a magnitude of a total wavenumber of the imaged seismic data in three dimensions and a spatially variable velocity function.

Abstract: Multi-vintage energy mapping selects a first seismic survey data and a second seismic survey dataset from a plurality of seismic survey datasets. The first seismic survey dataset includes a set of first energies associated with a first seismic survey geometry, and the second seismic survey dataset includes a set of second energies associated with a second seismic survey geometry. The first set of energies are mapped from the first seismic survey geometry to the second seismic survey geometry, and the second set of energies are mapped from the second seismic survey geometry to the first seismic survey geometry. An updated first seismic dataset and an updated second seismic dataset are generated such that only energies from the first and second seismic datasets associated with changes in a subsurface are preserved in the updated first and second seismic datasets.

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 method and apparatus for noise attenuation. The method includes receiving seismic data associated with at least two vintages (di, dj) collected for a same subsurface, wherein the first and second vintages (di, dj) are taken at different times; calculating a set of filters (fi, fj) that minimizes an energy function (E), wherein the energy function (E) includes a term representing a 4D difference between the first and second vintages (di, dj); calculating primaries (pi, pj) corresponding to the first and second vintages (di, dj) based on the set of (fi, fj); and calculating a 4D difference (?ij) based on the primaries (pi, pj). The 4D difference (?ij) is minimized.

Abstract: Computing device, computer instructions and method for calculating an image of a subsurface based on least square migration and image de-convolution using a matching operator F. The method includes receiving seismic data d; computing a first image m of the subsurface based on the seismic data d; computing a second image h of the subsurface based on the first image m; applying a transform operation to the first and second images m and h to obtain a first transform of the first image and a second transform of the second image; calculating the matching operator F by matching the first transform of the first image to the second transform of the second image; and generating an updated image mupdated of the subsurface based on the matching operator F and the first transform of the first image.

Abstract: Generating spectrally enhanced seismic data expresses seismic data as a convolution of reflectivity and a seismic source wavelet. This seismic source wavelet varies over a sampling interval and defining a total amount of energy over the sampling interval. An enhanced seismic source wavelet that is a single-valued energy spike that yields the total amount of energy over the sampling interval is generated. In addition, the reflectivity is modified to preserve amplitude variation with angle. The reflectivity is convoluted with the enhanced seismic source wavelet and residual energy is added to the convolution to generate the spectrally enhanced seismic data.

Abstract: Multi-vintage energy mapping selects a first seismic survey data and a second seismic survey dataset from a plurality of seismic survey datasets. The first seismic survey dataset includes a set of first energies associated with a first seismic survey geometry, and the second seismic survey dataset includes a set of second energies associated with a second seismic survey geometry. The first set of energies are mapped from the first seismic survey geometry to the second seismic survey geometry, and the second set of energies are mapped from the second seismic survey geometry to the first seismic survey geometry. An updated first seismic dataset and an updated second seismic dataset are generated such that only energies from the first and second seismic datasets associated with changes in a subsurface are preserved in the updated first and second seismic datasets.

Abstract: Simultaneous inversion of multi-vintage seismic data obtains seismic data for vintages and generates an initial earth model for each vintage. A cost function includes a data norm term having for at least one pair of vintages of seismic data a difference norm between a difference in obtained seismic data for the at least one pair of vintages and a difference in modeled seismic data for the at least one pair of vintages. The cost function also includes a model norm term for each pair of vintages selected from at least three vintages of seismic data. Each model norm term includes a difference norm between earth models for a given pair of vintages. A closure relationship is imposed on all earth models. The earth models are adjusted for the vintages to drive the cost function to a minimum and to produce updated earth models.

Abstract: Generating spectrally enhanced seismic data expresses seismic data as a convolution of reflectivity and a seismic source wavelet. This seismic source wavelet varies over a sampling interval and defining a total amount of energy over the sampling interval. An enhanced seismic source wavelet that is a single-valued energy spike that yields the total amount of energy over the sampling interval is generated. In addition, the reflectivity is modified to preserve amplitude variation with angle. The reflectivity is convoluted with the enhanced seismic source wavelet and residual energy is added to the convolution to generate the spectrally enhanced seismic data.

Abstract: Computing device, computer instructions and method for calculating an image of a subsurface based on least square migration and image de-convolution using a matching operator F. The method includes receiving seismic data d; computing a first image m of the subsurface based on the seismic data d; computing a second image h of the subsurface based on the first image m; applying a transform operation to the first and second images m and h to obtain a first transform of the first image and a second transform of the second image; calculating the matching operator F by matching the first transform of the first image to the second transform of the second image; and generating an updated image mupdated of the subsurface based on the matching operator F and the first transform of the first image.

Abstract: A method for spectral analysis of seismic data obtains imaged seismic data and generates orthogonally shifted imaged seismic data gathers. The orthogonally shifted imaged seismic data gathers are processed to generate a spectrally processed imaged seismic data. Alternatively, the imaged seismic data are obtained using a spectral processing filter that is a function of a magnitude of a total wavenumber of the imaged seismic data in three dimensions and a spatially variable velocity function.

Abstract: Systems and method for improved analysis of seismic data are provided. The method includes obtaining seismic data including a plurality of vintages, and generating a plurality of attribute matrices based on the seismic data. The method further includes computing a centrality measure for each vintage of the plurality of vintages using the plurality of attribute matrices, and selecting, from the plurality of vintages, a vintage with the highest centrality measure as a reference vintage. Additionally, the method includes determining an oulier from the plurality of vintages based on correlating each of the plurality of vintages with the reference vintage.

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: 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: In accordance with some embodiments of the present disclosure, systems and methods for estimating repeatability using base data are disclosed. The method includes obtaining data corresponding to a survey of an exploration area, where the data includes a plurality of traces associated with the exploration area, and an acquisition metric associated with each trace of the plurality of traces. The method also includes grouping the plurality of traces into a plurality of bins, the plurality of bins based on the acquisition metrics. The method further includes calculating an acquisition repeatability metric for each pair of traces in each bin based on the acquisition metrics, and calculating a seismic repeatability metric for each pair of traces in each bin.