5 papers
Modeling the geospatial evolution of COVID-19 using spatio-temporal convolutional sequence-to-sequence neural networks
Mário Cardoso, André Cavalheiro, Alexandre Borges +6
Europe was hit hard by the COVID-19 pandemic and Portugal was one of the most affected countries, having suffered three waves in the first twelve months. Approximately between Jan…
Strategies for integrating uncertainty in iterative geostatistical seismic inversion
Pedro Pereira, Fernando Bordignon, Leonardo Azevedo +2
Iterative geostatistical seismic inversion integrates seismic and well data to infer the spatial distribution of subsurface elastic properties. These methods provide limited assess…
Geostatistical Rock Physics AVA Inversion
Leonardo Azevedo, Dario Grana, Catarina Amaro
Reservoir models are numerical representations of the subsurface petrophysical properties such as porosity, volume of minerals and fluid saturations. These are often derived from e…
Coupling geologically consistent geostatistical history matching with parameter uncertainty quantification
Eduardo Barrela, Vasily Demyanov, Leonardo Azevedo
Iterative geostatistical history matching uses stochastic sequential simulation to generate and perturb subsurface Earth models to match historical production data. The areas of in…
Multi-scale uncertainty quantification in geostatistical seismic inversion
Leonardo Azevedo, Vasily Demyanov
Geostatistical seismic inversion is commonly used to infer the spatial distribution of the subsurface petro-elastic properties by perturbing the model parameter space through itera…