74 citations · 131 across the 5 of their papers we have counts for
5 papers
History Matching for Geological Carbon Storage using Data-Space Inversion with Spatio-Temporal Data Parameterization
Su Jiang, Louis J. Durlofsky
History matching based on monitoring data will enable uncertainty reduction, and thus improved aquifer management, in industrial-scale carbon storage operations. In traditional mod…
Use of Multifidelity Training Data and Transfer Learning for Efficient Construction of Subsurface Flow Surrogate Models
Su Jiang, Louis J. Durlofsky
Data assimilation presents computational challenges because many high-fidelity models must be simulated. Various deep-learning-based surrogate modeling techniques have been develop…
Deep Learning-Accelerated 3D Carbon Storage Reservoir Pressure Forecasting Based on Data Assimilation Using Surface Displacement from InSAR
Hewei Tang, Pengcheng Fu, Honggeun Jo +5
Fast forecasting of reservoir pressure distribution in geologic carbon storage (GCS) by assimilating monitoring data is a challenging problem. Due to high drilling cost, GCS projec…
Data-Space Inversion Using a Recurrent Autoencoder for Time-Series Parameterization
Su Jiang, Louis J. Durlofsky
Data-space inversion (DSI) and related procedures represent a family of methods applicable for data assimilation in subsurface flow settings. These methods differ from model-based…
An adsorbed gas estimation model for shale gas reservoirs via statistical learning
Yuntian Chen, Su Jiang, Dongxiao Zhang +1
Shale gas plays an important role in reducing pollution and adjusting the structure of world energy. Gas content estimation is particularly significant in shale gas resource evalua…