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 16A(78)-32. These fracture sets are fully stochastic and do not contain the deterministic set that matches the pilot well 58-32 FMI data. Well 58-32 has been completed and 16A(78)-32 is to be drilled as part of Phase 3. The original .fab files are not included due to redundancy. The *.fabgz data for the 800m and 1200m depth areas are in the native FracMan format and have been compressed using Gzip. Filtered data for the 800m depth area includes .csv spreadsheets, native FracMan (.fab), and GOCAD (.ts) files that are in a compressed zip format. The file titled "SGW 2020 Finnila and Podgorney DFN fracture files on GDR.pdf" is a description of the data and should be reviewed prior to data use.
Exploring Hydraulic Fracture Stimulation Patterns in the FORGE Reservoir Using Multiple Stochastic DFN Realizations and Variable Stress Conditions
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SGW 2020 Finnila and Podgorney DFN fracture files on GDR.pdf
Utah FORGE Well 16A78-32 Simplified Discrete Fracture Network Data
Citation Formats
Golder Associates Inc.. (2020). Utah FORGE: Discrete Fracture Network (DFN) Data [data set]. Retrieved from https://dx.doi.org/10.15121/1776595.
Finnila, Aleta, Podgorney, Robert. Utah FORGE: Discrete Fracture Network (DFN) Data. United States: N.p., 24 Jun, 2020. Web. doi: 10.15121/1776595.
Finnila, Aleta, Podgorney, Robert. Utah FORGE: Discrete Fracture Network (DFN) Data. United States. https://dx.doi.org/10.15121/1776595
Finnila, Aleta, Podgorney, Robert. 2020. "Utah FORGE: Discrete Fracture Network (DFN) Data". United States. https://dx.doi.org/10.15121/1776595. https://gdr.openei.org/submissions/1222.
@div{oedi_1222, title = {Utah FORGE: Discrete Fracture Network (DFN) Data}, author = {Finnila, Aleta, Podgorney, Robert.}, abstractNote = {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 16A(78)-32. These fracture sets are fully stochastic and do not contain the deterministic set that matches the pilot well 58-32 FMI data. Well 58-32 has been completed and 16A(78)-32 is to be drilled as part of Phase 3. The original .fab files are not included due to redundancy. The *.fabgz data for the 800m and 1200m depth areas are in the native FracMan format and have been compressed using Gzip. Filtered data for the 800m depth area includes .csv spreadsheets, native FracMan (.fab), and GOCAD (.ts) files that are in a compressed zip format. The file titled "SGW 2020 Finnila and Podgorney DFN fracture files on GDR.pdf" is a description of the data and should be reviewed prior to data use.}, doi = {10.15121/1776595}, url = {https://gdr.openei.org/submissions/1222}, journal = {}, number = , volume = , place = {United States}, year = {2020}, month = {06}}
https://dx.doi.org/10.15121/1776595
Details
Data from Jun 24, 2020
Last updated Jan 12, 2022
Submitted Jun 24, 2020
Organization
Golder Associates Inc.
Contact
Aleta Finnila
425.883.0777
Authors
Aleta Finnila
Golder Associates Inc.Robert Podgorney
Idaho National LaboratoryKeywords
geothermal, energy, Utah FORGE, FORGE, Utah geothermal, reservoir, engineering, hydraulic, fracturing, EGS, Discrete Fracture Network, DFN, fracture modelling, Milford, modeling, fracture, hydroshear, inflated, pore pressure, stress, FracMan, stimulation, drilling, pressure, Golder, simulation, reservoir planning, hydraulic fracturingDOE Project Details
Project Name Utah FORGE
Project Lead Lauren Boyd
Project Number EE0007080