56 citations · 196 across the 19 of their papers we have counts for
19 papers
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…
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…
Superstep wavefield propagation
Tamas Nemeth, Kurt Nihei, Alex Loddoch +10
This paper describes how to propagate wavefields for arbitrary numbers of traditional time steps in a single step, called a superstep. We show how to construct operators that accom…
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…
WISE: full-Waveform variational Inference via Subsurface Extensions
Ziyi Yin, Rafael Orozco, Mathias Louboutin +1
We introduce a probabilistic technique for full-waveform inversion, employing variational inference and conditional normalizing flows to quantify uncertainty in migration-velocity…
Inference of CO2 flow patterns -- a feasibility study
Abhinav Prakash Gahlot, Huseyin Tuna Erdinc, Rafael Orozco +2
As the global deployment of carbon capture and sequestration (CCS) technology intensifies in the fight against climate change, it becomes increasingly imperative to establish robus…
3D seismic survey design by maximizing the spectral gap
Yijun Zhang, Ziyi Yin, Oscar López +3
The massive cost of 3D acquisition calls for methods to reduce the number of receivers by designing optimal receiver sampling masks. Recent studies on 2D seismic showed that maximi…
Solving multiphysics-based inverse problems with learned surrogates and constraints
Ziyi Yin, Rafael Orozco, Mathias Louboutin +1
Solving multiphysics-based inverse problems for geological carbon storage monitoring can be challenging when multimodal time-lapse data are expensive to collect and costly to simul…
Learned multiphysics inversion with differentiable programming and machine learning
Mathias Louboutin, Ziyi Yin, Rafael Orozco +7
We present the Seismic Laboratory for Imaging and Modeling/Monitoring (SLIM) open-source software framework for computational geophysics and, more generally, inverse problems invol…
Optimized time-lapse acquisition design via spectral gap ratio minimization
Yijun Zhang, Ziyi Yin, Oscar Lopez +4
Modern-day reservoir management and monitoring of geological carbon storage increasingly call for costly time-lapse seismic data collection. In this letter, we show how techniques…
De-risking Carbon Capture and Sequestration with Explainable CO2 Leakage Detection in Time-lapse Seismic Monitoring Images
Huseyin Tuna Erdinc, Abhinav Prakash Gahlot, Ziyi Yin +2
With the growing global deployment of carbon capture and sequestration technology to combat climate change, monitoring and detection of potential CO2 leakage through existing or st…
De-risking geological carbon storage from high resolution time-lapse seismic to explainable leakage detection
Ziyi Yin, Huseyin Tuna Erdinc, Abhinav Prakash Gahlot +2
Geological carbon storage represents one of the few truly scalable technologies capable of reducing the CO2 concentration in the atmosphere. While this technology has the potential…
A simulation-free seismic survey design by maximizing the spectral gap
Yijun Zhang, Mathias Louboutin, Ali Siahkoohi +3
Due to the tremendous cost of seismic data acquisition, methods have been developed to reduce the amount of data acquired by designing optimal missing trace reconstruction algorith…
Model-Parallel Fourier Neural Operators as Learned Surrogates for Large-Scale Parametric PDEs
Thomas J. Grady, Rishi Khan, Mathias Louboutin +5
Fourier neural operators (FNOs) are a recently introduced neural network architecture for learning solution operators of partial differential equations (PDEs), which have been show…
Accelerating innovation with software abstractions for scalable computational geophysics
Mathias Louboutin, Philipp A. Witte, Ali Siahkoohi +4
We present the SLIM (https://github.com/slimgroup) open-source software framework for computational geophysics, and more generally, inverse problems based on the wave-equation (e.g…
Learned coupled inversion for carbon sequestration monitoring and forecasting with Fourier neural operators
Ziyi Yin, Ali Siahkoohi, Mathias Louboutin +1
Seismic monitoring of carbon storage sequestration is a challenging problem involving both fluid-flow physics and wave physics. Additionally, monitoring usually requires the solver…
Compressive time-lapse seismic monitoring of carbon storage and sequestration with the joint recovery model
Ziyi Yin, Mathias Louboutin, Felix J. Herrmann
Time-lapse seismic monitoring of carbon storage and sequestration is often challenging because the time-lapse signature of the growth of CO2 plumes is weak in amplitude and therefo…
Extended source imaging, a unifying framework for seismic & medical imaging
Ziyi Yin, Rafael Orozco, Philipp Witte +3
We present three imaging modalities that live on the crossroads of seismic and medical imaging. Through the lens of extended source imaging, we can draw deep connections among the…