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CGG publishes a wealth of geoscientific research. Search our large e-library of technical abstracts by entering at least one search criterion:

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Proactive satellite-based monitoring for enhanced offshore situational awareness

Workshop/forum/seminar (other), March, 2018
David Hamersley

The scope for using EO satellites for routine monitoring of offshore operations is continually expanding in ways that make factors of cost and time more feasible than ever before. Near-real-time processing and delivery remain the most appropriate solution for emergency scenarios; however, proactive monitoring programs can be undertaken to routinely acquire imagery over offshore infrastructure and environmentally sensitive areas, thus enhancing situational awareness for all interested parties. Increased awareness of activities and incidents occurring around offshore infrastructure can be compiled into a continually growing database to demonstrate good practise, provide an historical account of incidents, and feed into response scenarios.

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Anisotropic Pre-Stack Depth Migration processing in the Permian Basin, Texas

SEG - Society of Exploration Geophysicists, September, 2017
Ananya Roy | Lin Zheng | Xin Hu | CGG ; Robin Pearson | Ernesto V. Oropeza | Sarah Mueller | Mark Chang | Anadarko Petroleum Corporation
©2017 SEG

The Wolfcamp reservoir of the Permian Basin has recently generated interest for its potentially vast oil and gas reserves. Imaging this reservoir using seismic data is challenging despite the uncomplicated geology at reservoir depth, because the near-surface in this region is complex. In this work, we apply a modern depth processing flow to data from the Permian Basin and analyze its impact on the resolution of near-surface anomalies and on imaging at the reservoir.

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Velocity model building challenges and solutions for seabed- and paleo-canyons: a case study in Campos Basin, Brazil

SEG - Society of Exploration Geophysicists, September, 2017
Kai Zhang | Javier Subia | Chevron; Chanjuan Sun | Hao Shen | Nuree Han
©2017 SEG

The Campos Basin, offshore Brazil, features complex shallow geology in the forms of pronounced seabed canyons and paleo-canyons. The rapid variations in the velocity field due to these complex shallow geologic features can be difficult for ray-based tomography techniques to resolve, resulting in distorted images in deeper section. Full waveform inversion (FWI) is able to utilize the recorded diving–wave energy to resolve the high-resolution velocity model in these geologically complex areas. Additionally, dip-constrained non-linear slope tomography introduces dip constraints to ray-based residual move-out tomography and is able to capture small-scale velocity anomalies associated with these shallow heterogeneities. A combined workflow of FWI and dip-constrained tomography enabled Chevron to build accurate and detailed velocity models in the Campos Basin, resulting in fewer seismic image distortions. We demonstrate the method using a Campos Basin, Brazil narrow-azimuth streamer dataset.

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Improved iterative least-squares migration using curvelet-domain Hessian filters

SEG - Society of Exploration Geophysicists, September, 2017
Ming Wang | Shouting Huang | Ping Wang
©2017 SEG

Least-squares migration (LSM) can potentially provide better amplitude fidelity, higher image resolution, and fewer migration artifacts than standard migration. Conventional LSM is often solved iteratively through linearized inversion, and therefore is often referred to as iterative LSM. In recent years, various single-iteration LSM approaches have been proposed as a cost-effective approximation of iterative LSM and have produced promising results. To exploit the full potential of LSM, we propose to employ the curvelet-domain Hessian filter (CHF), useful in single-iteration LSM, as a preconditioner for conventional iterative LSM. We call this approach CHF-preconditioned LSM (CPLSM). We first validate our CPLSM approach using SEAM I synthetic data and show that it produces better amplitude fidelity over the single-iteration CHF approach and converges faster than conventional iterative LSM. Furthermore, we demonstrate with an application to field data that CPLSM produces fewer migration artifacts and less noise than conventional iterative LSM. This addresses a known problem of iterative LSM that is caused by the use of inaccurate modeling algorithms followed by overfitting the modeled synthetic data to the recorded data.

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Applications of single-iteration Kirchhoff least-squares migration

SEG - Society of Exploration Geophysicists, September, 2017
Lorenzo Casasanta | Francesco Perrone | Graham Roberts | Andrew Ratcliffe | Karen Purcell | Arash JafarGandomi | Gordon Poole
©2017 SEG

Least-squares depth migration approximates the inverse of the forward modeling. We show two real data applications of a single iteration (non-iterative) Kirchhoff least-squares depth migration process, generically referred to as migration deconvolution, to highlight the benefits of this process. Our first example demonstrates improved amplitude behavior of least-squares migration deconvolution images in an offshore Gabon data set. In the second example we propose an efficient way to include attenuation in the least-squares migration process and, using a Central North Sea data set, highlight a stable uplift in both resolution and illumination of the final image.

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