20 citations · 65 across the 24 of their papers we have counts for
26 papers
Symmetric Submodular Minimization from Comparisons
James Fox, David P. Woodruff
Given value-oracle access to a symmetric submodular function with , a nontrivial minimizer can be found using value queries. We study the weake…
Evaluating the Transfer of Co-Evolved Communication from 2D to 3D Simulation
Fernando Montes-Gonzalez
This work examines the transfer of a co-evolved communication mechanism between two robotic agents from a discrete two-dimensional (2D) simulator to a three-dimensional simulator w…
Bayesian Joint Velocity and Impedance Inversion via Diffusion Models Conditioned on Common Image Gathers
Yunlin Zeng, Huseyin Tuna Erdinc, Felix J. Herrmann
We present a multi-parameter simulation-based inference framework for joint Bayesian recovery of subsurface velocity and acoustic impedance from seismic data. A score-based diffusi…
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…
A reduced-order derivative-informed neural operator for subsurface fluid-flow
Jeongjin Park, Grant Bruer, Huseyin Tuna Erdinc +2
Neural operators have emerged as cost-effective surrogates for expensive fluid-flow simulators, particularly in computationally intensive tasks such as permeability inversion from…
Sensitivity-aware rock physics enhanced digital shadow for underground-energy storage monitoring
Abhinav Prakash Gahlot, Huseyin Tuna Erdinc, Felix J. Herrmann
Underground energy storage, which includes storage of hydrogen, compressed air, and CO2, requires careful monitoring to track potential leakage pathways, a situation where time-lap…
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…
Full-waveform variational inference with full common-image gathers and diffusion network
Yunlin Zeng, Huseyin Tuna Erdinc, Rafael Orozco +1
Accurate seismic imaging and velocity estimation are essential for subsurface characterization. Conventional inversion techniques, such as full-waveform inversion, remain computati…
Enhancing Robustness Of Digital Shadow For CO2 Storage Monitoring With Augmented Rock Physics Modeling
Abhinav Prakash Gahlot, Felix J. Herrmann
To meet climate targets, the IPCC underscores the necessity of technologies capable of removing gigatonnes of CO2 annually, with Geological Carbon Storage (GCS) playing a central r…
Advancing Geological Carbon Storage Monitoring With 3d Digital Shadow Technology
Abhinav Prakash Gahlot, Rafael Orozco, Felix J. Herrmann
Geological Carbon Storage (GCS) is a key technology for achieving global climate goals by capturing and storing CO2 in deep geological formations. Its effectiveness and safety rely…
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…
An uncertainty-aware Digital Shadow for underground multimodal CO2 storage monitoring
Abhinav Prakash Gahlot, Rafael Orozco, Ziyi Yin +1
Geological Carbon Storage GCS is arguably the only scalable net-negative CO2 emission technology available While promising subsurface complexities and heterogeneity of reservoir pr…
Seismic monitoring of CO2 plume dynamics using ensemble Kalman filtering
Grant Bruer, Abhinav Prakash Gahlot, Edmond Chow +1
Monitoring carbon dioxide (CO2) injected and stored in subsurface reservoirs is critical for avoiding failure scenarios and enables real-time optimization of CO2 injection rates. S…
WISER: multimodal variational inference for full-waveform inversion without dimensionality reduction
Ziyi Yin, Rafael Orozco, Felix J. Herrmann
We present a semi-amortized variational inference framework designed for computationally feasible uncertainty quantification in 2D full-waveform inversion to explore the multimodal…
Generative Geostatistical Modeling from Incomplete Well and Imaged Seismic Observations with Diffusion Models
Huseyin Tuna Erdinc, Rafael Orozco, Felix J. Herrmann
In this study, we introduce a novel approach to synthesizing subsurface velocity models using diffusion generative models. Conventional methods rely on extensive, high-quality data…
ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems
Rafael Orozco, Ali Siahkoohi, Mathias Louboutin +1
Due to their uncertainty quantification, Bayesian solutions to inverse problems are the framework of choice in applications that are risk averse. These benefits come at the cost of…
BEACON: Bayesian Experimental design Acceleration with Conditional Normalizing flows a case study in optimal monitor well placement for CO sequestration
Rafael Orozco, Abhinav Gahlot, Felix J. Herrmann
CO sequestration is a crucial engineering solution for mitigating climate change. However, the uncertain nature of reservoir properties, necessitates rigorous monitoring of CO$…
A Digital Twin for Geological Carbon Storage with Controlled Injectivity
Abhinav Prakash Gahlot, Haoyun Li, Ziyi Yin +2
We present an uncertainty-aware Digital Twin (DT) for geologic carbon storage (GCS), capable of handling multimodal time-lapse data and controlling CO2 injectivity to mitigate rese…
Time-lapse full-waveform permeability inversion: a feasibility study
Ziyi Yin, Mathias Louboutin, Olav Møyner +1
Time-lapse seismic monitoring necessitates integrated workflows that combine seismic and reservoir modeling to enhance reservoir property estimation. We present a feasibility study…
Probabilistic Bayesian optimal experimental design using conditional normalizing flows
Rafael Orozco, Felix J. Herrmann, Peng Chen
Bayesian optimal experimental design (OED) seeks to conduct the most informative experiment under budget constraints to update the prior knowledge of a system to its posterior from…
InvertibleNetworks.jl: A Julia package for scalable normalizing flows
Rafael Orozco, Philipp Witte, Mathias Louboutin +4
InvertibleNetworks.jl is a Julia package designed for the scalable implementation of normalizing flows, a method for density estimation and sampling in high-dimensional distributio…