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Sequential geophysical and flow inversion to characterize fracture
  networks in subsurface systems
v1v2v3 (latest)

Sequential geophysical and flow inversion to characterize fracture networks in subsurface systems

14 June 2016
M. Mudunuru
S. Karra
N. Makedonska
T. Chen
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "Sequential geophysical and flow inversion to characterize fracture networks in subsurface systems"

4 / 4 papers shown
Deep Learning to Estimate Permeability using Geophysical Data
Deep Learning to Estimate Permeability using Geophysical DataAdvances in Water Resources (Adv. Water Resour.), 2021
M. Mudunuru
E. Cromwell
H. Wang
X. Chen
261
18
0
08 Oct 2021
Using Machine Learning to Discern Eruption in Noisy Environments: A Case
  Study using CO2-driven Cold-Water Geyser in Chimayo, New Mexico
Using Machine Learning to Discern Eruption in Noisy Environments: A Case Study using CO2-driven Cold-Water Geyser in Chimayo, New Mexico
Baichuan Yuan
Yen Joe Tan
M. Mudunuru
O. Marcillo
A. Delorey
...
Jeremy D. Webster
C. Gammans
S. Karra
G. Guthrie
Paul Johnson
244
18
0
01 Oct 2018
Estimating Failure in Brittle Materials using Graph Theory
Estimating Failure in Brittle Materials using Graph Theory
M. Mudunuru
N. Panda
S. Karra
G. Srinivasan
V. Chau
E. Rougier
A. Hunter
Hari S. Viswanathan
AI4CE
69
1
0
30 Jul 2018
Regression-based reduced-order models to predict transient thermal
  output for enhanced geothermal systems
Regression-based reduced-order models to predict transient thermal output for enhanced geothermal systems
M. Mudunuru
S. Karra
D. Harp
G. Guthrie
Hari S. Viswanathan
204
15
0
14 Jun 2016
1
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