Geoscience Digitalization Continues Apace

Paris, France | Jun 4, 2019

Rapid Expansion in Machine Learning Applications Alongside Migration to the Cloud Advances Workflows

At industry events over the last couple of years, digitalization has become a major point of interest with dedicated technical sessions and exhibition feature areas to explore this growing topic. CGG has likewise embraced this technology to transform many areas of its business. Perhaps the biggest area of interest in the industry right now is around machine learning and the opportunities it offers to potentially revolutionize geoscience workflows.

To help geoscientists take advantage of machine learning and deep learning technology, CGG GeoSoftware has developed a machine learning ecosystem. It provides open access to data within its geophysical and petrophysical applications. Python-scripted machine learning lets users get their hands dirty if they like to tinker under the hood, or take advantage of carefully selected pre-built recipes. Many tasks can now be completed more quickly and with more detailed results, for example, well log editing and petrophysical analysis, facies classification and reservoir property prediction. Meanwhile, deep neural networks provide benefits for tasks as varied as reservoir quality assessment and near-surface characterization. Learn more about these applications at the daily CGG booth theater presentations.

Even if geoscientists are not using machine learning personally, they’ll find it increasingly involved across various aspects of geoscience projects and workflows around them. CGG’s Subsurface Imaging experts now benefit from the addition of machine learning to improve tasks such as surface wave inversion, processing QC, job logistics and resource utilization. Their papers on these topics include:

• Learn to Invert: Surface Wave Inversion with Deep Neural Network
  (Workshop 10, Monday 9:40am)
• Near-surface characterization in Southern Oman: multi-wave inversion guided by machine learning
  (Near Surface Technologies I, Tuesday 8.30am)
• Leveraging a supervised machine learning toolkit for better seismic processing quality
  (Deep Learning and Data Analytics - Seismic Applications I & Methods and Applications II, Thursday 3:30pm)

Before the industry gets to the point where it can truly benefit from big data analytics and take full advantage of machine learning there is a need to reach a minimum common denominator in terms of the data itself. Recent efforts have seen the liberation of huge volumes of data from legacy formats, migrating to new data management platforms which include an increasing mix of cloud storage. CGG Smart Data Solutions help to ease this digital transition with end-to-end services from expert upcycling of legacy data into the cloud to the deployment of their modern and flexible GeoTrove data management platform.

Integration and interoperability of geoscience data becomes important to really take advantage of data analytics and machine learning applications. CGG has spent the last few years gaining valuable experience while taking its geological library into the digital realm, using a proprietary taxonomy and ontology to create a unique framework for its GeoVerse data set. Meanwhile, its multi-client seismic library is now assessable through its new GeoStore portal, with controlled access to historical client entitlement data. Upload to the cloud is underway for the entire multi-client seismic library.

The cloud offers more than just data storage – cloud computing provides scalable and flexible solutions to compute-intensive reservoir characterization workflows and very large projects. Through its technical collaboration with Microsoft, CGG’s latest GeoSoftware releases run seamlessly in the Microsoft Azure Cloud Environment. Other major cloud platforms soon will follow.

To find out more about machine learning, visit CGG booth #720 at 3:30 on Tuesday for its Happy Hour event! Or listen to CGG delivering the keynote presentation on Wednesday at 9:30 on the Digital Transformation Area theatre. For information about all of CGG’s activity at EAGE 2019, which includes digitalization and a whole lot more, visit cgg.com/eage2019.