84 citations · 156 across the 7 of their papers we have counts for
7 papers
Spatial-Temporal Densely Connected Convolutional Networks: An Application to CO2 Leakage Detection
Zheng Zhou, Youzuo Lin, Yue Wu +3
In carbon capture and sequestration, building an effective monitoring method is a crucial step to detect and respond to CO2 leakage. CO2 leakage detection methods rely on geophysic…
A Data-Driven CO2 Leakage Detection Using Seismic Data and Spatial-Temporal Densely Connected Convolutional Neural Networks
Zheng Zhou, Youzuo Lin, Zhongping Zhang +4
In carbon capture and sequestration, developing effective monitoring methods is needed to detect and respond to CO2 leakage. CO2 leakage detection methods rely on geophysical obser…
Using Machine Learning to Discern Eruption in Noisy Environments: A Case Study using CO2-driven Cold-Water Geyser in Chimayo, New Mexico
B. Yuan, Y. J. Tan, M. K. Mudunuru +8
We present an approach based on machine learning (ML) to distinguish eruption and precursory signals of Chimayó geyser (New Mexico, USA) under noisy environments. This geyser can b…
Molecular Dynamics Simulations of Turbostratic Dry and Hydrated Montmorillonite with Intercalated Carbon Dioxide
Evgeniy M. Myshakin, Meysam Makaremi, Vyacheslav N. Romanov +2
Molecular dynamics simulations using classical force fields were carried out to study energetic and structural properties of rotationally disordered clay mineral-water-CO2 systems…
Multiphase Monte Carlo and Molecular Dynamics Simulations of Water and CO2 Intercalation in Montmorillonite and Beidellite
Meysam Makaremi, Kenneth Jordan, George Guthrie +1
Multiphase Gibbs ensemble Monte Carlo simulations were carried out to compute the free energy of swelling for Na-montmorillonite and Na-beidellite interacting with CO2 and H2O at p…
Efficient Data-Driven Geologic Feature Detection from Pre-stack Seismic Measurements using Randomized Machine-Learning Algorithm
Youzuo Lin, Shusen Wang, Jayaraman Thiagarajan +2
Conventional seismic techniques for detecting the subsurface geologic features are challenged by limited data coverage, computational inefficiency, and subjective human factors. We…
Regression-based reduced-order models to predict transient thermal output for enhanced geothermal systems
M. K. Mudunuru, S. Karra, D. R. Harp +2
The goal of this paper is to assess the utility of Reduced-Order Models (ROMs) developed from 3D physics-based models for predicting transient thermal power output for an enhanced…