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Tellus lab team & providers
Automated multi-scenarios well correlations
Well correlations can be partially automated to efficiently consider multiple scenarios and better assess the corresponding uncertainties.
Automated extraction of images of interest in document collections
Automatic extraction of images of interest in document database can improve the efficiency of operational workflows and help professionals save time for higher-value activities
Assisted uncertainties quantification in log interpretation
Quantifying the uncertainties associated to well-log data can benefit any decision making based on machine learning workflows where these data are used
Assisted predictive mapping with machine learning
Predictive mapping is essential to evaluate underground prospectivity in various fields, such as Oil and Gas industry, Mineral prospection or Geothermal Energy
Automated prediction of rock properties ahead of the drill bit
Predicting rock properties while drilling a well, especially if at several tens of meters ahead of the drill bit, can be key to reduce the drilling risks and their associated costs
The TELLUS team is at the 2nd EAGE Digital in Vienna (23-25 march)
The TELLUS team presented 3 papers. You will find direct links to them on the full news.
TELLUS Lab trainees present geological applications of computer vision at EAGE workshop
They presented early results and good practices on the practical use of Deep Learning approaches to operational data sets of geological images
Assisted interpretation of core images
Lithological interpretation of core samples is a decisive early stage of many geoscience workflows
3 TELLUS TOOLS at EAGE Digital 2020
TELLUS Lab Team presented "Deep Learning Applications to Unstructured Geological Data: From Rock Images Characterization to Scientific Literature Mining"
Digital transformation and geoscience education: new publication in European Geologist Journal
A joint publication between the TELLUS team at IFPEN and IFP School addresses the benefits of emergent digital technologies
Assisted interpretation of wireline logs
Well logs interpretation is often rather subjective and highly time-consuming
Automated objects detection on thin section images
Accurately detecting and locating a large number of objects of interest in thin section images is an arduous task
Automated segmentation of thin section images
Quantitative analyzes of thin sections often imply tedious searches and counts of specific elements such as micro-fossils
Automated classification of rock samples
Identification of lithological types from rock samples is cornerstone in many subsurface activities
IFPEN and UNESCO share digital transformation ambitions towards sustainable resource management and energy transition
IFP Energies Nouvelles (IFPEN) and UNESCO have signed a framework partnership agreement
Applications of TELLUS technologies for the mining industry addresses at Mineral Exploration Symposium
The Mineral Exploration Symposium was co-organized by the European Association of Geoscientists and Engineers (EAGE) and the European Commission
TELLUS projects presented at the 2020 RING meeting
Research for Integrative Numerical Geology (RING) is an international research consortium dedicated to geomodelling and quantiative geosciences
towards geosciences 4.0
The TELLUS ecosystem themes of interest
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