117 citations · 193 across the 10 of their papers we have counts for
11 papers
Physics-informed machine learning with differentiable programming for heterogeneous underground reservoir pressure management
Aleksandra Pachalieva, Daniel O'Malley, Dylan Robert Harp +1
Avoiding over-pressurization in subsurface reservoirs is critical for applications like CO2 sequestration and wastewater injection. Managing the pressures by controlling injection/…
Dynamic Risk Assessment for Geologic CO2 Sequestration
Bailian Chen, Dylan R. Harp, Yingqi Zhang +2
At a geologic CO2 sequestration (GCS) site, geologic uncertainty usually leads to large uncertainty in the predictions of properties that influence metrics for leakage risk assessm…
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…
Great SCO2T! Rapid tool for carbon sequestration science, engineering, and economics
Richard S. Middleton, Jeffrey M. Bielicki, Bailian Chen +12
CO2 capture and storage (CCS) technology is likely to be widely deployed in coming decades in response to major climate and economics drivers: CCS is part of every clean energy pat…
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…
Adaptive hybrid optimization strategy for calibration and parameter estimation of physical models
Velimir V. Vesselinov, Dylan R. Harp
A new adaptive hybrid optimization strategy, entitled squads, is proposed for complex inverse analysis of computationally intensive physical models. The new strategy is designed to…
Contaminant remediation decision analysis using information gap theory
Dylan R. Harp, Velimir V. Vesselinov
Decision making under severe lack of information is a ubiquitous situation in nearly every applied field of engineering, policy, and science. A severe lack of information precludes…
Accounting for the influence of aquifer heterogeneity on spatial propagation of pumping drawdown
Dylan R. Harp, Velimir V. Vesselinov
It has been previously observed that during a pumping test in heterogeneous media, drawdown data from different time periods collected at a single location produce different estima…