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Utah FORGE Well 16A(78)-32 Simplified Discrete Fracture Network Data
The FORGE team is making these fracture models available to researchers wanting a set of natural fractures in the FORGE reservoir for use in their own modeling work. They have been used to predict stimulation distances during hydraulic stimulation at the open toe section of well 1...
Finnila, A. Golder Associates Inc.
Jun 01, 2021
3 Resources
0 Stars
Curated
3 Resources
0 Stars
Curated
Utah FORGE Project 2439: Machine Learning for Well 16A(78)-32 Stress Predictions September 2023 Report
This task completion report documents the development and implementation of machine learning (ML) models for the prediction of in-situ vertical (Sv), minimum horizontal (SHmin) and maximum horizontal (SHmax) stresses in well 16A(78)-32. The detailed description of the experimental...
Mustafa, A. et al Battelle Memorial Institute
Sep 28, 2023
3 Resources
0 Stars
Curated
3 Resources
0 Stars
Curated
Utah FORGE: 2023 Large Upscaled Discrete Fracture Network Models
This dataset includes the data and a report on the large upscaled discrete fracture network modeling done for the Utah FORGE project in 2023. The FORGE modeling team is making five discrete fracture network (DFN) realizations of a large reservoir model available to researchers. Th...
Finnila, A. Energy and Geoscience Institute at the University of Utah
Oct 02, 2023
17 Resources
0 Stars
Curated
17 Resources
0 Stars
Curated
Utah FORGE: Discrete Fracture Network (DFN) Data
The FORGE team is making these fracture models available to researchers wanting a set of natural fractures in the FORGE reservoir for use in their own modeling work. They have been used to predict stimulation distances during hydraulic stimulation at the open toe section of well 1...
Finnila, A. and Podgorney, R. Golder Associates Inc.
Jun 24, 2020
66 Resources
0 Stars
Curated
66 Resources
0 Stars
Curated