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Utah FORGE: Well 16A(78)-32 Stimulation Data (April, 2022)
This is a set of data related to the stimulation program at Utah FORGE well 16A(78)-32 during April, 2022. This includes daily reports, 1 second Pason data, tracer data, and shear stimulation data and information including a report of an evolving prognosis for the stimulation oper...
McLennan, J. Energy and Geoscience Institute at the University of Utah
May 18, 2022
11 Resources
0 Stars
Curated
11 Resources
0 Stars
Curated
Utah FORGE: Well 16A(78)-32 Logs
This dataset contains all well logs from Utah FORGE well 16A(78)-32. This includes the mud log, Sanvean Technologies logs, and Schlumberger logs. Please see the file descriptions below for information about each log.
Gilmour, B. et al Energy and Geoscience Institute at the University of Utah
Mar 08, 2021
7 Resources
0 Stars
Publicly accessible
7 Resources
0 Stars
Publicly accessible
Utah FORGE: Well 16A(78)-32 Drilling Data
This dataset includes survey data, drilling data, daily reports, summaries of daily operations, and rig photos from the drilling of Utah FORGE well 16A(78)-32, which is a highly deviated deep well. It was completed 60 days ahead of schedule.
Rig move in began 10/22/2020 and dril...
McLennan, J. et al Energy and Geoscience Institute at the University of Utah
Jan 08, 2021
15 Resources
0 Stars
Curated
15 Resources
0 Stars
Curated
Utah FORGE: Well 16A(78)-32: Summary of Drilling Activities
This is a 74 page detailed summary of the drilling activities of Utah FORGE 16A(78)-32, a highly deviated well completed on February 2nd, 2021, as part of the Utah FORGE project. This well was deviated at 65 degrees from vertical after reaching 6000 feet in depth had a total measu...
Winkler, D. et al Energy and Geoscience Institute at the University of Utah
Mar 20, 2021
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible
Utah FORGE: Report on the Thermal Properties of Wells 16A(78)-32 & 58-32 Granite
This is a report from Metarock Laboratories on the thermal properties of Utah FORGE wells 16A(78)-32 & 58-32 granite. The report includes pictures of core samples, core details for the samples (where the sample was taken and the size of the sample), sample thermal expansion test r...
Laboratories, M. et al Energy and Geoscience Institute at the University of Utah
May 04, 2021
1 Resources
0 Stars
Curated
1 Resources
0 Stars
Curated
Utah FORGE: Phase 1a Tensor Strainmeter Data for the April, 2022 Stimulation of Well 16A(78)-32
Data from two Tensor Optical Fiber Strainmeters that were operational during Stages 1, 2, and 3 of the April, 2022 stimulation of well 16A(78)-32. Each csv file contains data from each stimulation stage (stage1, stage2, stage3) for both Phase 1a strainmeter installations (FS01, f...
DeWolf, S. and Murdoch, L. Clemson University
Sep 15, 2022
8 Resources
0 Stars
Publicly accessible
8 Resources
0 Stars
Publicly accessible
Utah FORGE 2439: A Multi-Component Approach to Characterizing In-Situ Stress
Core-based in-situ stress estimation, Triaxial Ultrasonic Velocity (labTUV) data, and Deformation Rate Analysis (DRA) data for Utah FORGE well 16A(78)-32 using triaxial ultrasonic velocity and deformation rate analysis. Report documenting a multi-component approach to characterizi...
Bunger, A. et al Battelle Memorial Institute
Dec 13, 2022
4 Resources
0 Stars
Curated
4 Resources
0 Stars
Curated
Utah FORGE 2-2439v2: Report on Predicting Far-Field Stresses Using Finite Element Modeling and Near-Wellbore Machine Learning for Well 16A(78)-32
This report presents the far-field stress predictions at two locations along the vertical section of Utah FORGE Well 16A (78)-32 using a physics-based thermo-poro-mechanical model. Three principal stresses in far-field were obtained by solving an inverse problem based on the near-...
Lu, G. et al University of Pittsburgh
Aug 30, 2024
2 Resources
0 Stars
Curated
2 Resources
0 Stars
Curated
Utah FORGE: Deep Wells Water and Gas Sampling with Analyses by ThermoChem (October, 2022)
This data includes a document that describes the effort to collect and analyze water and gas samples from deep Utah FORGE wells 16A(78)-32, 58-32, 56-32 and 78B-32 along with additional pdf files showing ThermoChem's analyses attached as an appendix.
Joness, C. Energy and Geoscience Institute at the University of Utah
Oct 26, 2022
2 Resources
0 Stars
Curated
2 Resources
0 Stars
Curated
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 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
Publicly accessible
17 Resources
0 Stars
Publicly accessible
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
Publicly accessible
66 Resources
0 Stars
Publicly accessible