Technical Content

CGG has always been at the forefront of industrial High Perfor­mance Computing (HPC) architectures: we were operating vector supercomputers (Convex, Cray and NEC) in the early 1990s, and large parallel supercomputers (Convex SPP, IBM SP, Sgi Origin) by the end of that decade. At ...

The optimal transport problem was formulated more than 200 years ago to calculate the optimal way of transporting piles of sand. Due to the interesting properties of its solutions with respect to shifts between the compared distributions, optimal transport has recently been adapted to ...

Driven by the notion that blending noise may materially increase the background noise level and obscure the interpretation of weak time-lapse (4D) signals related to subtle reservoir changes, the industry has not yet seen any simultaneous-source (sim-source) surveys acquired for reservoir monitoring. Thus, whether ...

Shear wave velocity model building (S-wave VMB) is a critical and difficult processing step for converted wave imaging. Conventional S-wave VMB depends on PP-PS joint interpretation-based image registration and PP-PS joint tomography-based residual moveout flattening which have certain advantages and drawbacks. We introduce PS ...

Although the resolution of a seismic image is ultimately bound by the spatial and temporal sampling of the acquired seismic data, the seismic images obtained through conventional imaging methods normally fall far short of this limit. In addition to attenuation in the Earth, factors ...

Full-waveform inversion has been established as a standard tool for building high-resolution velocity models. To take full advantage of such models, the migration algorithm must be capable of handling fine-scale geo-bodies and sharp contrasts while affordably producing high-frequency migration stacks and gathers. Even though ...

Recently, land full-waveform inversion (FWI) has shown great potential in resolving near-surface complexity in the Delaware Basin, providing significant imaging uplift and useful information for shallow hazard identification. However, deep section updates beyond diving wave penetration remain challenging. We present an application of land ...

Machine learning (ML) has garnered great attention within the field of seismic processing due to its vast achievements for quality and efficiency in the area of computer vision. Recent academic papers have demonstrated some potential for the use of machine learning in processing seismic ...

Seismic images obtained through conventional migration methods have limitations as amplitude distortions and migration artifacts. To mitigate these limitations, we can generate FWI Images by computing the reflector-normal derivatives of the high-frequency FWI velocities. Given the resolution, accuracy, and geological consistency of the velocities ...