9 citations · 9 across the 4 of their papers we have counts for
4 papers
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…
Machine learning-based porosity estimation from spectral decomposed seismic data
Honggeun Jo, Yongchae Cho, Michael J. Pyrcz +2
Estimating porosity models via seismic data is challenging due to the signal noise and insufficient resolution of seismic data. Although impedance inversion is often used by combin…
Transverse Hydraulic Fracture Initiation: Insights from Intermediate-Scale Hydraulic Fracture Tests
Jeffrey Burghardt, Hunter Knox, Chris Strickland +8
In a uniform stress field, a tensile hydraulic fracture will favor propagation in the plane formed by the maximum (most compressive) and intermediate principal stresses. For the pr…
A Deep Learning-Accelerated Data Assimilation and Forecasting Workflow for Commercial-Scale Geologic Carbon Storage
Hewei Tang, Pengcheng Fu, Christopher S. Sherman +6
Fast assimilation of monitoring data to update forecasts of pressure buildup and carbon dioxide (CO2) plume migration under geologic uncertainties is a challenging problem in geolo…