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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
Digital transformation
towards geosciences 4.0
