Data exploration

Well correlations can be partially automated to efficiently consider multiple scenarios and better assess the corresponding uncertainties.

Web technologies for visualization of geodata & massive 3D Models

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?

Quantifying the uncertainties associated to well-log data can benefit any decision making based on machine learning workflows where these data are used

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

Document classification is one of the major parts of the manual effort, especially when the documents to classify are scattered within a huge database

Field trips are increasingly limited by budget, safety, footprint or inclusion issues

Efficiently searching for relevant information within mass of unstructured data is often a time-consuming prerequisite of scientific tasks

Companies often accumulate very large amounts of documents stored in multiple folders

It is often burdensome to handle large amounts of wells files

New geomodelling usages require solutions to share and view models independently from proprietary software

Exploiting geomodelling results is a difficult task due to the amount of generated data. Complex post-processing computations are often required

Analyzing geomodels and physical simulation results can be tedious and often involve complex post-processing