20 citations · 65 across the 24 of their papers we have counts for
10 papers · 1 filter
OpenSeisML: Open Large-Scale Real Seismic and well-log Dataset for Generative AI
Ipsita Bhar, Huseyin Tuna Erdinc, Thales Souza +2
The advent of machine learning (ML) and computer vision has significantly accelerated seismic inversion workflows by reducing the computational cost of traditionally expensive iter…
SAGE: Subsurface AI-driven Geostatistical Extraction with proxy posterior
Huseyin Tuna Erdinc, Ipsita Bhar, Rafael Orozco +2
Recent advances in generative networks have enabled new approaches to subsurface velocity model synthesis, offering a compelling alternative to traditional methods such as Full Wav…
Power-scaled Bayesian Inference with Score-based Generative Models
Huseyin Tuna Erdinc, Yunlin Zeng, Abhinav Prakash Gahlot +1
We propose a score-based generative algorithm for sampling from power-scaled priors and likelihoods within the Bayesian inference framework. Our algorithm enables flexible control…
Well2Flow: Reconstruction of reservoir states from sparse wells using score-based generative models
Shiqin Zeng, Haoyun Li, Abhinav Prakash Gahlot +1
This study investigates the use of score-based generative models for reservoir simulation, with a focus on reconstructing spatially varying permeability and saturation fields in sa…
Probabilistic Joint Recovery Method for CO Plume Monitoring
Zijun Deng, Rafael Orozco, Abhinav Prakash Gahlot +1
Reducing CO emissions is crucial to mitigating climate change. Carbon Capture and Storage (CCS) is one of the few technologies capable of achieving net-negative CO emission…
Machine learning-enabled velocity model building with uncertainty quantification
Rafael Orozco, Huseyin Tuna Erdinc, Yunlin Zeng +2
Accurately characterizing migration velocity models is crucial for a wide range of geophysical applications, from hydrocarbon exploration to monitoring of CO2 sequestration project…