CGG’s new GeoSoftwares have cloud-ready machine learning capabilities

15415 Jason FullsizeCGG has announced new GeoSoftware releases including Jason 10.0, HampsonRussell 10.4 and PowerLog 10.0 with cloud-ready reservoir characterisation solutions

They also feature advanced machine learning capabilities and greater cross-product integration, improving E&P project performance and providing a better understanding of reservoir properties.

The three new releases run on Microsoft Azure’s Cloud Environment and will soon be available on other major cloud platforms, enabling geoscientists to implement compute-intensive workflows and run large projects.

The benefits of machine learning continue to drive new capabilities to address complex geological challenges. HampsonRussell Emerge now delivers deep learning in the form of Deep Feed Forward Neural Networks for better prediction of reservoir properties. An open Python ecosystem in PowerLog enables the routine use of machine and deep learning in workflows to increase automation and achieve more accurate facies predictions.

HampsonRussell 10.4 updates advanced seismic conditioning to improve seismic data quality for better inversion outcomes and AVO Modeling now offers a wider range of tools for investigating the seismic response of pre-stack data.

Jason 10.0 makes it easy to design or vet facies classifications from petrophysical logs and immediately see the effects in the elastic inversion domain. It also has improved velocity calibration for time-to-depth conversion and depth inversion.

PowerLog 10.0 advancements enable users to efficiently interpret groups of wells and apply machine learning to solve petrophysical challenges using the PowerLog Ecosystem.

Kamal al-Yahya, senior vice-president, GeoSoftware and Smart Data Solutions, said, “As always, we listen to our clients to ensure our new software releases bring innovations that really help them increase efficiency. Greater product integration is major for inter-disciplinary workflows as links between geophysics, geology and petrophysics grow ever stronger.”

“This new set of releases is also the first to deliver real benefits from our digitalization roadmap, offering a high-quality experience with the integration of machine learning and cloud-ready applications,” al-Yahya added.

Alain Charles Publishing, University House, 11-13 Lower Grosvenor Place, London, SW1W 0EX, UK
T: +44 20 7834 7676, F: +44 20 7973 0076, W: www.alaincharles.com

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