Cgg Services Sas

Cggveritas Services S.a.

Henning Hoeber

Adel Khalil

Gordon Poole

Ross Haacke

Andrew Ratcliffe

Can Peng

Graham Roberts

Adriano Gomes

Song Hou

Bernard Deschizeaux

James Cooper

Francesco Perrone

Lorenzo Casasanta

Ehsan Zabihi Naeini

Ivan Lim Chen Ning

Stefano Angio

Erik Hicks

Jeshurun Hembd

Arash Jafargandomi

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.

Analytics and machine learning method for estimating petrophysical property values

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.

Method and apparatus for deblending seismic data using a non-blended dataset

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.

Spectral analysis and processing of seismic data using orthogonal image gathers

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.

4D noise suppression

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.

Multi-vintage energy mapping

A method and apparatus for noise attenuation. The method includes receiving seismic data associated with at least two vintages (d, d) collected for a same subsurface, wherein the first and second vintages (d, d) are taken at different times; calculating a set of filters (f, 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 (d, d); calculating primaries (p, p) corresponding to the first and second vintages (d, d) based on the set of (f, fj); and calculating a 4D difference (&#x394;) based on the primaries (p, p). The 4D difference (&#x394;) is minimized.

Device and method for optimization of 4D and 3D seismic data

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 mof the subsurface based on the matching operator F and the first transform of the first image.

Seismic data least-square migration method and device

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.

AVA compliant pre-stack frequency spectrum enhancement of seismic data

A method, an apparatus and a computer readable medium for generating an image of a subsurface based on seismic data corresponding to at least two different times, for a same surveyed area are provided. A cost function, which is a sum over the seismic data vintages of a norm of differences between data and model predicted multiples, is minimized subject to minimizing residual multiples that are differences of corresponding multiples belonging to different vintages among the seismic data vintages.

Growing community of inventors

East Grinstead, United Kingdom

Henning Hoeber