6 papers
Towards Fast GNN Surrogates for CO2 Migration in Complex Geological Formations
Rodrigo S. Luna, Thiago H. N. Coelho, Luiz S. L. Neto +8
This chapter discusses how a data-driven machine learning approach can reproduce key aspects of the physical behavior of multiphase flows in complex geological formations. We propo…
Accelerated Full Waveform Inversion by Deep Compressed Learning
Maayan Gelboim, Amir Adler, Mauricio Araya-Polo
We propose and test a method to reduce the dimensionality of Full Waveform Inversion (FWI) inputs as computational cost mitigation approach. Given modern seismic acquisition system…
Uncertainty Quantification in Seismic Inversion Through Integrated Importance Sampling and Ensemble Methods
Luping Qu, Mauricio Araya-Polo, Laurent Demanet
Seismic inversion is essential for geophysical exploration and geological assessment, but it is inherently subject to significant uncertainty. This uncertainty stems primarily from…
Evaluation of Programming Models and Performance for Stencil Computation on Current GPU Architectures
Baodi Shan, Mauricio Araya-Polo
Accelerated computing is widely used in high-performance computing. Therefore, it is crucial to experiment and discover how to better utilize GPUGPUs latest generations on relevant…
Matrix-Free Finite Volume Kernels on a Dataflow Architecture
Ryuichi Sai, Francois P. Hamon, John Mellor-Crummey +1
Fast and accurate numerical simulations are crucial for designing large-scale geological carbon storage projects ensuring safe long-term CO2 containment as a climate change mitigat…
A Portable Framework for Accelerating Stencil Computations on Modern Node Architectures
Ryuichi Sai, John Mellor-Crummey, Jinfan Xu +1
Finite-difference methods based on high-order stencils are widely used in seismic simulations, weather forecasting, computational fluid dynamics, and other scientific applications.…