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The benefits of CGG technologies and services are regularly featured in the industry press. Find out more by consulting our e-library of published industry articles. Narrow your search by entering at least one search criterion:

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The Zambezi Delta Basin: A Complex Puzzle with Missing Pieces

Geo Expro, September, 2019
Javier Martin | Madhurima Bhattacharya | Marianne Parsons
©2019 GeoPublishing Ltd

Exploration on the African continent has traditionally been concentrated in prolific basins on the Sub-Saharan Western margin, in detriment to the East. Proven prolific basins, existing infrastructure, favourable and progressively transparent regulation; along with the analysis of prospective conjugate basins of Brazil are just some of the reasons for creating a positive environment for international investors. A report submitted in 2012 by the USGS, predicts undiscovered mean gas resources of more than 370 TCFG in offshore East Africa, including Tanzania, Mozambique, Madagascar and Seychelles. World-class gas discoveries have been made between 2010 and 2013 in the offshore regions of Tanzania and Mozambique, along with onshore discoveries in Uganda and Kenya thus reinvigorating exploration interest along the Eastern African margin. The Zambezi channel, offshore Mozambique, has traditionally been the locus of intense academic research, with a number of 2D seismic and gravimetric and magnetic acquisition campaigns deployed in recent years. However, the region still remains poorly understood. With this in mind, in 2017 CGG acquired a high-resolution 3D seismic survey located in the outer Zambezi Delta Basin, west of the Beira High. This seismic survey, in conjunction with newly acquired high-resolution shipborne grav/mag survey and access to data from multiple wells in the area, aims to bring a new and fresh dimension on the geological understanding of the basin.

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Overcoming the challenges of a shallow-water sparse wide-azimuth survey to improve deep reservoir imaging in the East China Sea

The Leading Edge, August, 2019
Peipei Deng | Yongdeng Xiao | Srujan Poonamalli | Tran Thinh To | Joe Zhou | Jason Sun | Yun Wei | Hua Chen | Senqing Hu | Gang Yao | Yu Jiang
©2019 SEG

A new broadband Wide-Azimuth Towed-Streamer (WATS) survey was acquired in a shallow water region of offshore China to better resolve reservoir compartments. Two side boats were added as additional source boats to form the WATS acquisition geometry to resolve the shortcomings of narrow-azimuth acquisition along strike direction. This WATS acquisition is much sparser than common WATS surveys in deep water environments due to only one-side WATS configuration. The combination of sparse acquisition, shallow water and deep targets imposes challenges on how to optimally utilize the side-gun data as the key adding on to improve the final image. The 3D effect and severe aliasing expected in the Crossline direction pose tremendous difficulties for side gun data processing. A comprehensive flow for resolving these challenges especially in deghosting, demultiple and regularization for sparse and shallow wide-azimuth data is presented in the paper. A tilted orthorhombic (TORT) velocity model is also built with better constraints from the wide azimuth information for better fault positioning and imaging. Side gun data clearly enhances the final target reservoir imaging and better ties with the well due to better illuminations. A new channel is discovered based on the interpretation from the inverted Vp/Vs ratio, which clearly explains the previous misleading prediction that an exceptional well was drilled to a thinner and shallower channel not connected to the main reservoir.

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Revealing new hydrocarbon potential through Q-compensated prestack depth imaging at Wenchang Field, South China Sea

The Leading Edge, August, 2019
Yitao Chen | Xiaodong Wu | Yong Xia Liu | Jason Sun | Lin Li | Lie Li | Tao Xu | Min Ouyang | Yonghao Gai
©2019 SEG

The imaging of the complex fault system plays an important role in hydrocarbon exploration in Wenchang field since the fault system forms a bridge between the source rocks and reservoirs. However, it is challenging to obtain a high quality depth image of the fault system due to the complex depth velocity and Q absorption effect. In this paper, we demonstrate how a combination of Fault Constraint Tomography (FCT) model building flow and Q-compensated High Fidelity Controlled Beam Migration (QHFCBM) work together to provide a step change in the imaging quality and bring significant impact to the reservoir delineation.

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Machine learning and geophysical inversion – A numerical study

The Leading Edge, July, 2019
Brian Russell
©2019 SEG

Much recent work has been done on comparing machine learning and geophysical inversion techniques to the extraction of model parameters from seismic reflection data. In our profession we are used to analyzing the physics of geophysical problems in detail. However, in many of the recent studies the machine learning algorithms are treated almost as “black boxes”. In this study l I will use a straightforward numerical example to illustrate the difference between geophysical inversion and machine learning inversion. In doing so I will try to “demystify” machine learning algorithms and show that, like inverse problems, they have a definite mathematical structure that can be written down and understood. The example used is this tutorial is the extraction of the underlying reflection coefficients from an overlapping wavelet response that was created by convolving a reflection coefficient dipole with a symmetric wavelet. In discussing the solution to this problem I will cover the topics of deconvolution, recursive inversion, linear regression and nonlinear regression using a feedforward neural network. I will present both the full inverse approach as well as gradient descent algorithms, which can be applied to both linear and nonlinear problems. This will lead to a description of the backpropagation algorithm, which is used to train a feedforward neural network. In the final section of the tutorial I will look at the impact of local minima in the search for a global minimum in the backpropagation algorithm.

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Integration in Exploration

Oilfield Technology, May, 2019
Carl Watkins | Daniel Carruthers | Pedro Martinez Duran | Simon Otto | Mark Cowgill
©2019 Palladian Publications Ltd

Integrated exploration, new workflows for new challenges highlighting JumpStart Gabon, Marine Source Predictions and Encontrado reprocessing projects.

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