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Journal Article

Detecting fractures and monitoring hydraulic fracturing processes at the first EGS Collab testbed using borehole DAS ambient noise

Authors

Li,  David
External Organizations;

Huang,  Lianjie
External Organizations;

Zheng,  Yingcai
External Organizations;

Li,  Yingping
External Organizations;

Schoenball,  Martin
External Organizations;

/persons/resource/verort

Rodriguez Tribaldos,  Veronica
2.2 Geophysical Imaging of the Subsurface, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Ajo-Franklin,  Jonathan
External Organizations;

Hopp,  Chet
External Organizations;

Johnson,  Tim
External Organizations;

Knox,  Hunter
External Organizations;

Blankenship,  Doug
External Organizations;

Dobson,  Patrick
External Organizations;

Kneafsey,  Tim
External Organizations;

Robertson,  Michelle
External Organizations;

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Fulltext (public)

5025649.pdf
(Publisher version), 8MB

Supplementary Material (public)
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Citation

Li, D., Huang, L., Zheng, Y., Li, Y., Schoenball, M., Rodriguez Tribaldos, V., Ajo-Franklin, J., Hopp, C., Johnson, T., Knox, H., Blankenship, D., Dobson, P., Kneafsey, T., Robertson, M. (2024): Detecting fractures and monitoring hydraulic fracturing processes at the first EGS Collab testbed using borehole DAS ambient noise. - Geophysics, 89, 2, D131-D138.
https://doi.org/10.1190/geo2023-0078.1


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5025649
Abstract
Enhanced geothermal systems (EGS) require cost-effective monitoring of fracture networks. We validate the capability of using borehole distributed acoustic sensing (DAS) ambient noise for fracture monitoring using core photos and core logs. The EGS Collab project has conducted 10 m scale field experiments of hydraulic fracture stimulation using 50–60 m deep experimental wells at the Sanford Underground Research Facility (SURF) in Lead, South Dakota. The first EGS Collab testbed is located at 1616.67 m (4850 ft) depth at SURF and consists of one injection well, one production well, and six monitoring wells. All wells are drilled subhorizontally from an access tunnel called a drift. The project uses a single continuous fiber-optic cable installed sequentially in the six monitoring wells to record DAS data for monitoring hydraulic fracturing during stimulation. We analyze 60 s time records of the borehole DAS ambient noise data and compute the noise root-mean-square (rms) amplitude on each channel (points along the fiber cable) to obtain DAS ambient noise rms amplitude depth profiles along the monitoring wellbore. Our noise rms amplitude profiles indicate amplitude peaks at distinct depths. We compare the DAS noise rms amplitude profiles with borehole core photos and core logs and find that the DAS noise rms amplitude peaks correspond to the locations of fractures or lithologic changes indicated in the core photos or core logs. We then compute the hourly DAS noise rms amplitude profiles in two monitoring wells during three stimulation cycles in 72 h and find that the DAS noise rms amplitude profiles vary with time, indicating the fracture opening/growth or closing during the hydraulic stimulation. Our results demonstrate that borehole DAS passive ambient noise can be used to detect fractures and monitor fracturing processes in EGS reservoirs.