Utah FORGE Project 3-2417: Simulations for Distributed Acoustic Sensing Strain Signatures as an Indicator of Fracture Connectivity

Ward-Baranyay, Megan; Ajo-Franklin, Jonathan; Ghassemi, Ahmad

doi:10.15121/2369582

Title: Utah FORGE Project 3-2417: Simulations for Distributed Acoustic Sensing Strain Signatures as an Indicator of Fracture Connectivity

Dataset
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Abstract

This dataset encompasses simulations of strain signatures from both hydraulically connected and "near-miss" fractures in enhanced geothermal systems (EGS). The files and results are presented from the perspective of digital acoustic sensing's (DAS) potential to differentiate the two fracture types. This dataset was acquired by the FOGMORE R&D project (Fiber Optic Geophysical MOnitoring of Reservoir Evolution), under Utah FORGE R&D Project 3-2417. Included are simulation and results via MatLab and COMSOL files, as well as a thesis and paper summarizing the results. Some stimulated fractures may be incomplete, approaching but not intersecting the production well. These "near-miss" fractures can be addressed in future stimulation stages or re-stimulated to complete the connection. We propose the use of fiber optic distributed acoustic sensing (DAS) as a method by which near-miss stimulated fractures may be identified and distinguished from hydraulically connected fractures. The low-frequency sub-nanostrain signatures of both complete and near-miss fractures in DAS data are simulated in this study using a hydrogeomechanical discrete fracture network model. The spatial distribution of strain was found to be an accurate indicator. However, this indicator must be evaluated in the context of DAS gauge length and spatial sampling. These simulations are a precursor to tests conductedmore » at FORGE in 2023.« less

Authors:

Ward-Baranyay, Megan;

;

Rice University

Publication Date:: Sun Jan 01 04:00:00 UTC 2023

Other Number(s):: 1582

DOE Contract Number:: EE0007080

Research Org.:: DOE Geothermal Data Repository; Rice University

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Geothermal Technologies Program (EE-4G)

Collaborations:: Rice University

Subject:: 15 GEOTHERMAL ENERGY; COMSOL; DAS; DFN; EGS; FOGMORE; FORGE; MatLab; Milford; Utah; Utah FORGE; code; distributed acoustic sensing; energy; geophysics; geothermal; hydrogeomechanics; modeling; near-miss fracture; simulation; stimulation; strain; sub-nanostrain

OSTI Identifier:: 2369582

DOI:: https://doi.org/10.15121/2369582

Citation Formats


                    Ward-Baranyay, Megan, Ajo-Franklin, Jonathan, and Ghassemi, Ahmad. Utah FORGE Project 3-2417: Simulations for Distributed Acoustic Sensing Strain Signatures as an Indicator of Fracture Connectivity.  United States: N. p., 2023. 
        Web.  doi:10.15121/2369582.

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                    Ward-Baranyay, Megan, Ajo-Franklin, Jonathan, & Ghassemi, Ahmad. Utah FORGE Project 3-2417: Simulations for Distributed Acoustic Sensing Strain Signatures as an Indicator of Fracture Connectivity.  United States.  doi:https://doi.org/10.15121/2369582

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                    Ward-Baranyay, Megan, Ajo-Franklin, Jonathan, and Ghassemi, Ahmad. 2023.  
"Utah FORGE Project 3-2417: Simulations for Distributed Acoustic Sensing Strain Signatures as an Indicator of Fracture Connectivity".  United States.  doi:https://doi.org/10.15121/2369582.  https://www.osti.gov/servlets/purl/2369582. Pub date:Sun Jan 01 04:00:00 UTC 2023

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@article{osti_2369582,

  title        = {Utah FORGE Project 3-2417: Simulations for Distributed Acoustic Sensing Strain Signatures as an Indicator of Fracture Connectivity},

  author       = {Ward-Baranyay, Megan and Ajo-Franklin, Jonathan and Ghassemi, Ahmad},

  abstractNote = {This dataset encompasses simulations of strain signatures from both hydraulically connected and "near-miss" fractures in enhanced geothermal systems (EGS). The files and results are presented from the perspective of digital acoustic sensing's (DAS) potential to differentiate the two fracture types. This dataset was acquired by the FOGMORE R&D project (Fiber Optic Geophysical MOnitoring of Reservoir Evolution), under Utah FORGE R&D Project 3-2417. Included are simulation and results via MatLab and COMSOL files, as well as a thesis and paper summarizing the results. Some stimulated fractures may be incomplete, approaching but not intersecting the production well. These "near-miss" fractures can be addressed in future stimulation stages or re-stimulated to complete the connection. We propose the use of fiber optic distributed acoustic sensing (DAS) as a method by which near-miss stimulated fractures may be identified and distinguished from hydraulically connected fractures. The low-frequency sub-nanostrain signatures of both complete and near-miss fractures in DAS data are simulated in this study using a hydrogeomechanical discrete fracture network model. The spatial distribution of strain was found to be an accurate indicator. However, this indicator must be evaluated in the context of DAS gauge length and spatial sampling. These simulations are a precursor to tests conducted at FORGE in 2023.},

  doi          = {10.15121/2369582},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Sun Jan 01 04:00:00 UTC 2023},

  month        = {Sun Jan 01 04:00:00 UTC 2023}

}

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DOI: https://doi.org/10.15121/2369582

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