Intelligent Systems and Data Science

Oil and gas industry has been undergoing deep technological transformations since the spread of the concept of “digital oil field” during the 1980s. A number of human-only processes began to be carried by artificial intelligence, thus allowing for the rise of intelligent systems created specifically to meet the demands of the sector: optimization of production, improvement of operational safety, environmental protection and discovery of new reserves.

Intelligent systems constitute a broad area of ​​knowledge within artificial intelligence. Today, the oil industry is increasingly influenced by the power of AI at a fast-pace toward industry 4.0.

A few examples we can cite include the application of:

  • machine learning to optimize well patterns and production strategies;
  • pattern recognition in seismic imaging for delineation of rock formations and salt bodies;
  • sensors and WI-FI networks for in-field control and communication;
  • smart field and smart well designs;
  • remotely operated vehicles (ROVs) for surveillance and monitoring of underwater facilities;
  • drones for leak detection in pipelines.

At LaMEP, the research line intelligent systems and data science is mainly focused on genetic algorithms, neural networks, deep learning, and other data mining techniques for identification of hydrocarbon accumulation zones in reservoirs and pattern recognition in seismic images.