2 citations · 2 across the 4 of their papers we have counts for
4 papers
Sequential Physics-Constrained Neural Operator Forward Modeling for the Reservoir System
Clement Etienam, Juntao Yang, Oleg Ovcharenko +4
We develop a comprehensive mathematical and computational framework for sequential surrogate modeling of three-phase black-oil reservoir dynamics using neural operators, with parti…
An intercomparison of generative machine learning methods for downscaling precipitation at fine spatial scales
Neelesh Rampal, Bryn Ward-Leikis, Yun Sing Koh +7
Machine learning (ML) offers a computationally efficient approach for generating large ensembles of high-resolution climate projections, but deterministic ML methods often smooth f…
Reservoir History Matching of the Norne field with generative exotic priors and a coupled Mixture of Experts -- Physics Informed Neural Operator Forward Model
Clement Etienam, Yang Juntao, Oleg Ovcharenko +1
We developed a novel reservoir characterization workflow that addresses reservoir history matching by coupling a physics-informed neural operator (PINO) forward model with a mixtur…
A Novel A.I Enhanced Reservoir Characterization with a Combined Mixture of Experts -- NVIDIA Modulus based Physics Informed Neural Operator Forward Model
Clement Etienam, Yang Juntao, Issam Said +4
We have developed an advanced workflow for reservoir characterization, effectively addressing the challenges of reservoir history matching through a novel approach. This method int…