117 citations · 146 across the 5 of their papers we have counts for
5 papers
Optimization and uncertainty quantification model for time-continuous geothermal energy extraction undergoing re-injection
Hussein Hoteit, Xupeng He, Bicheng Yan +1
Geothermal field modeling is often associated with uncertainties related to the subsurface static properties and the dynamics of fluid flow and heat transfer. Uncertainty quantific…
A Robust Deep Learning Workflow to Predict Multiphase Flow Behavior during Geological CO2 Sequestration Injection and Post-Injection Periods
Bicheng Yan, Bailian Chen, Dylan Robert Harp +1
This paper contributes to the development and evaluation of a deep learning workflow that accurately and efficiently predicts the temporal-spatial evolution of pressure and CO2 plu…
Improving Deep Learning Performance for Predicting Large-Scale Porous-Media Flow through Feature Coarsening
Bicheng Yan, Dylan Robert Harp, Bailian Chen +1
Physics-based simulation for fluid flow in porous media is a computational technology to predict the temporal-spatial evolution of state variables (e.g. pressure) in porous media,…
A Physics-Constrained Deep Learning Model for Simulating Multiphase Flow in 3D Heterogeneous Porous Media
Bicheng Yan, Dylan Robert Harp, Bailian Chen +1
In this work, an efficient physics-constrained deep learning model is developed for solving multiphase flow in 3D heterogeneous porous media. The model fully leverages the spatial…
A Gradient-based Deep Neural Network Model for Simulating Multiphase Flow in Porous Media
Bicheng Yan, Dylan Robert Harp, Rajesh J. Pawar
Simulation of multiphase flow in porous media is crucial for the effective management of subsurface energy and environment related activities. The numerical simulators used for mod…