Cgg Services Sas

Andrew Ratcliffe

Graham Roberts

Gordon Poole

Lian Duan

Adel Khalil

Henning Hoeber

Gilles Lambare

Adriano Gomes

Lorenzo Casasanta

Francesco Perrone

James Cooper

Tao Lin

Cris Henstock

Wenlei Gao

Alejo Sansigre

Hongbo Bi

Bruno Gratacos

Nabil Masmoudi

Luis D'Afonseca

Graham Conroy

Jeshurun Hembd

Seismic data is processed using a full-waveform inversion using a model with a pseudo-δ layer. The presence of the pseudo-δ layer in the model enables handing the difference at the water bottom between acoustically generated synthetic data and seismic data that corresponds to an elastic medium. The pseudo-δ layer may be less than 100 m thick and/or may be located directly underneath the water bottom. The pseudo-δ layer may have a negative value for S and a null value for ϵ (δ and ϵ being Thomsen's anisotropy parameters).

Full-waveform inversion with elastic mitigation using acoustic anisotropy

Computing device, computer instructions and method for identifying seismic traces prone to cycle-skipping in a full waveform inversion method. The method includes receiving recorded seismic data recorded with seismic sensors over a subsurface of interest; selecting a model that describes the subsurface; calculating, based on the model and the recorded seismic data, estimated seismic data; and choosing a probabilistic measure that characterizes a relationship between the recorded seismic data and the estimated seismic data. The probabilistic measure includes at least one statistical function.

Device and method for mitigating cycle-skipping in full waveform inversion

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.

Full waveform inversion of seismic data using partial match filtering

A method for processing seismic data from a subsurface using least squares migration or wave equation migration velocity analysis over a cost function comprising a function of a matching filter by iteratively updating the reflectivity model velocity model to yield an updated reflectivity model or updated velocity model that matches the observed seismic data.

Seismic data processing using matching filter based cost function optimization

Recorded seismic data are obtained at a plurality of receivers from a plurality of sources, and a set of sources from the plurality of sources is selected using spatial criteria based on a location of each source such that any two sources in the set of sources are separated by a predefined minimum distance of separation sufficient to reduce cross talk between sources. The set of sources is combined in a non-encoded manner into a composite source, and forward modeling for the composite source is performed to generate a synthetic seismic data set. A composite recorded seismic data set for the set of sources is determined, and the synthetic seismic data set and composite recorded seismic data set are used to determine a residual seismic data set. Backward modeling generates a gradient update used to generate an updated earth model.

Method for iterative inversion of data from non-encoded composite sources

An Earth model of a subsurface is created from acquired seismic data by migrating at least one of the incident wavefields and reflected wavefields to generate angle gathers for the seismic data and identifying for the subsurface an elastic Earth model equation for the incident wavefields and the reflected wavefields in the acquired seismic data. The elastic Earth model is a function of reflection angle between the incident wavefields and reflected wavefields and elastic parameters and is fit to the generated angle gathers through perturbation in the elastic parameters. The generated perturbations are used to create the Earth model of the subsurface.

Method for elastic model perturbation estimation from reverse time migration

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

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Henfield, United Kingdom

Andrew Ratcliffe