Data Science
and Artificial Intelligence

LAMCE carries out research in the area of Data Science and Artificial Intelligence applied to the oil industry and health in the following areas:

Artificial Intelligence (computational vision) for tomographic image analysis of carbonate rocks: applications in lithological classification, texture segmentation and petrophysical properties prevision;

Artificial Intelligence for direct hydrocarbons indicators (DHI): rock and reservoir facies identification using elastic seismic inversion attributes;

Artificial Intelligence (computational vision) for medical applications: identification and estimating the severity of COVID-19 based on X-ray and tomographic images;

Space-time forecast using artificial intelligence (computational vision): application to rain forecast using radar images;

Specialized natural language processing in the oil industry;

Mobility estimation based on cell phones call detail record (cdr): application for epidemiological modeling.

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Computational
Mechanics

Historically, LAMCE has been operating for more than 30 years in the development and implementation of simulators via discrete methods, such as finite elements methods, finite differences, discrete elements for the numerical solution of engineering problems in general and, more specifically, for the oil and gas sector.

Computational Modeling of rock mechanics problems and rock-fluid interaction. Acloped models for rock-fluid interaction in perforation and production phase.

Computer modeling for the analysis and mechanical project of subsea equipment and land installations;

New algorithms development in the light of new architecture and computational technologies, providing the best performance, efficiency and fidelity to the problem physics (solid mechanics, fluid mechanics, nonlinear stress analysis, thermal problems and its multiple couplings);

Multiphase flow simulation in heterogeneous porous mediums, big dimension problems approach and high loyalty;

Porous rocks geomechanical modeling saturated for the analysis of well stability problems in perforation and production phase;

Modeling the behavior and analysis of stress in risers, umbilicals and subsea pipelines, soil-structure interactions, fluid-structure interactions, analysis of stresses in TDP, TDZ, etc..;

Modeling and simulation of water alternating gas (WAG) injection, polymer injection, reactive processes;

Simulation of the action of waves and currents on electromechanical converter devices for power generation;

Simulation of wind action on wind turbines and its components, simulation of acloped fluid-structure dynamic response for fixed or floated installations.

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Environmental
Modeling

The Environmental Modeling Core (NUMA) operates in the Environmental Modeling area researching atmospheric and oceanic processes and developing computational model for:

Forecasting and environmental monitoring atmospheric and oceanic processes through environmental data analysis and use of computational modeling in different space scales;

Modeling of the pollutants dispersion in the atmosphere, oceans and rivers;

Climate modeling associated with processes of climate variability and change. Optical Remote Sensing of the Atmosphere and Ocean (polar and geostationary sensors);

Renewable energy:
- Analysis of Energy Potential
- Shortcast e nowcast of solar and wind energy availability
- Analysis of Renewable energy Potential

Meteorological and oceanographic instrumentation and observation.

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Geophysical Modeling

The Multidisciplinary Modeling Core uses advanced techniques of High-performance computing (HPC) and Artificial Intelligence focused on the improvement of the seismic imaging on complex geological structures and develops innovations on the following areas:

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Earth
Observation

LAMCE’s Earth Observation Core (NOTE) uses its experience in in-situ data collection, instrumentation and remote sensing for the monitoring of physical, chemical and biological Earth systems, as well as to promote the complete and open sharing of all its data to research communities, industry, academia, governments and civil society.

The Earth Observation Core operates to monitor and evaluate the status and changes in natural and artificial environments as a contribution to establishing international standards for measurements of the Earth's surface, atmosphere and ocean through its in-house research and cooperation with partners, as well as enabling and disseminating data acquisition, access and storage.

Main Activities:
Orbital Data Dissemination Center: structure for the acquisition, processing, storage and operational dissemination of meteo-oceanographic data obtained via satellites for application in the energy area, especially the oil sector, as well as monitoring severe meteorological events;

Development of methodologies for validating data from spaceborne sensors and in-situ data using adjustment algorithms associated with radiometric, geometric and atmospheric corrections in local and regional conditions.

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Remote Sensing

by Radar applied to the Petroleum Industry

The studies carried out at the Remote Sensing Core have the goal of detecting oil exudations in oceanic regions, indicative of the presence of active oil systems, as well as establishing their tectonic and environmental context and their repetitiveness over time. This information is fundamental as a boundary condition for the computational modeling of oil generation and migration processes, adding value to oil industry projects carried out in exploratory frontiers.

The research comprises the following technological areas:

Use and development of remote sensing techniques to detect oil slicks in the marine environment related to exudations or spills;

Research the sensitivity of terrestrial and aquatic biomes to possible environmental impacts resulting from oil industry activities;

Spatial data analysis and mining using geostatistical and fuzzy logic techniques, thus facilitating the generation of information;

processing of radar images (filter adjustments, contrats, highlights, resolutions, etc.) with the aim of highlighting parts that may indicate oil leaks or exudation;

Detection of flooded areas.

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Scientific
Visualization

Created in 1997, the Scientific Visualization Core is dedicated to the development and deployment of cutting-edge technologies in the research areas of Virtual and Augmented Reality, Scientific Visualization, Image Processing, Computational Vision, Mobile Computing and Tracking Systems.

The Core is responsible for the entire operation of the Visualization Center, the main cooperative and presentation space in LAMCE’s building.

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