Digital transformation towards geosciences 4.0

Assist

Accelerate

Automate

Supporting subsurface industries in geoscience digitalization

through practical use cases and a cross-disciplinary approach

TELLUS DIGITAL: Digital transformation towards geosciences 4.0

The Tellus ecosystem

With TELLUS LAB explore a specific topic by a privileged partnership

a team of experienced data scientists, software architects and geoscience experts

privileged framework for bilateral or multi-partners projects with IFPEN

More information on TELLUS LAB

With TELLUS SHARE follow all topics for an affordable yearly subscription

a community of industrial companies interested in geoscience digitalization

cost-effective framework for companies to exchange on business needs, follow IFPEN projects, and get up-to-date information on this booming subject

More information on TELLUS SHARE

Demo projects

Evaluate if the pressure and the production of wells in an oil field can be estimated with graph neural networks

image for automating and replaying the maps building operations

Automated execution on large datasets and facilitates stochastic realizations, such as Monte Carlo simulations, to generate probabilistic results

Developping a robust chatbot that enhances the retrieval and use of geoscientific information

Automated segmentation of core images

An innovative workflow for semantic segmentation of sedimentological cores using deep learning techniques.

Clustering well-log data into electrofacies using machine learning with a purely unsupervised approach, cluster-number optimization, and outlier removal based on spatial autocorrelation.

When AI Meets Reservoir Engineering image

Can the pressure answer of a field be estimated with neural networks in situations of fast decision-making or when a reservoir model is not available?

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