Get the most information out of seismic data with our leading technology and internationally recognized expertise.
Geology and Engineering
Reduce natural resource exploration and development risk with expert geological services and analysis, reservoir characterization and engineering expertise.
We harness the unique capabilities of Earth observation data to address a diverse range of challenges faced by the Energy, Mining, Engineering, Environment and Defense sectors.
Imaging expertise and industry-leading software for multi-domain data inversion with experience across natural resource and energy transition applications.
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Enhancing salt model resolution and subsalt imaging with elastic FWIMar 13, 2023
Full-waveform inversion (FWI) has become the centerpiece of velocity model building (VMB) in seismic processing in recent years. It has proven to significantly improve the velocity model, and thus the migration image, for different acquisition types and different geologic settings, including very complex environments such as salt. With the advent of FWI Imaging, which shows remarkable uplifts over conventional imaging approaches because of the inherent least-squares data-fitting process and the utilization of full-wavefield data, FWI further extends its applications from VMB into imaging. However, FWI applications in the industry as of now prevalently employ the acoustic approximation. While the acoustic approximation can sufficiently explain a majority of the recorded seismic data, thus enabling acoustic FWI to derive reasonable velocity models, its limitation manifests itself around strong impedance contrasts where the elastic effect is strong. For example, at the salt-sediment interface, acoustic FWI (A-FWI) almost always leads to apparent salt halos in the resulting velocity models. With synthetic and field data examples, we demonstrate that the salt halo is mainly caused by the large data mismatch between the elastic input data and the acoustic modeled data in acoustic FWI, particularly at middle to long offsets. Therefore, we developed an elastic FWI (E-FWI) algorithm that combines an elastic modeling engine with the time-lag cost function, which we call elastic Time-lag FWI (E-TLFWI). With a more accurate modeling engine, E-TLFWI can significantly reduce the salt halo observed in its acoustic counterpart. Nevertheless, the migration images using the acoustic and elastic FWI velocity models remain similar overall, with some slight improvements around and beneath salt boundaries, particularly near steep salt flanks, as a result of the reduced salt halo. By contrast, FWI Images derived from E-TLFWI show considerable benefits over those from acoustic Time-lag FWI (A-TLFWI), such as improved event focusing, better structural continuity, and higher signal-to-noise ratio (S/N). The sharpened salt boundaries and enhanced quality of the FWI Images justify the value of elastic FWI.
CGG Awarded OMV Contract for Multi-Year Dedicated Center
CGG has been awarded a new contract by OMV to continue operating a dedicated center at its head office in Vienna for an initial three-year period. ...
Futureproofing Rich Metadata File Ingestion with OSDU
Acting as a technology-agnostic, standards-based data platform, the OSDU has reduced energy data silos and provided the capability for applications developers to build new solutions and data ingestion services. The current OSDU schemas are primarily ...
EAGE Annual Conference and Exhibition
Come and see us at the EAGE Annual 2023 on booth #2250 to learn more about our pioneering geoscience and digital sciences developments. ...
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Are you a physicist, data scientist, engineer, mathematician or problem-solver? Good, glad we have that in common! Join us in transforming real seismic data into stunning 3D images of the Earth’s subsurface. No experience? Don’t worry, we’ll show you the way.Show Me Open Roles
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