34 citations · 34 across the 2 of their papers we have counts for
3 papers
Integrating Score-Based Diffusion Models with Machine Learning-Enhanced Localization for Advanced Data Assimilation in Geological Carbon Storage
Gabriel Serrão Seabra, Nikolaj T. Mücke, Vinicius Luiz Santos Silva +3
Accurate characterization of subsurface heterogeneity is important for the safe and effective implementation of geological carbon storage (GCS) projects. This paper explores how ma…
Mitigating loss of variance in ensemble data assimilation: machine learning-based and distance-free localization
Vinicius L. S. Silva, Gabriel S. Seabra, Alexandre A. Emerick
We propose two new methods based/inspired by machine learning for tabular data and distance-free localization to enhance the covariance estimations in an ensemble data assimilation…
AI enhanced data assimilation and uncertainty quantification applied to Geological Carbon Storage
G. S. Seabra, N. T. Mücke, V. L. S. Silva +2
This study investigates the integration of machine learning (ML) and data assimilation (DA) techniques, focusing on implementing surrogate models for Geological Carbon Storage (GCS…