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Imperial Valley Dark Fiber Project Continuous DAS Data
The Imperial Valley Dark Fiber Project acquired Distributed Acoustic Sensing (DAS) seismic data on a ~28 km segment of dark fiber between the cities of Calipatria and Imperial in the Imperial Valley, Southern California. Dark fiber refers to unused optical fiber cables in telecommunications networks and is repurposed in this project for DAS applications. The objective, which is further detailed in the attached journal article from Ajo-Franklin et al., is to demonstrate dark fiber DAS as a tool for basin-scale geothermal exploration and monitoring. The included DAS data were recorded during two days at the beginning the project. Data is stored in the .h5 (HDF5) file format, readable using various software tools, including the 'h5read' and 'h5info' functions in Matlab. Provided here are examples of methods to read and use the data with the 'h5py' package in Python.
Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[
"019:20"
]
|
| contactPoint |
{
"fn": "Avinash Nayak",
"@type": "vcard:Contact",
"hasEmail": "mailto:anayak7@lbl.gov"
}
|
| dataQuality |
true
|
| description | The Imperial Valley Dark Fiber Project acquired Distributed Acoustic Sensing (DAS) seismic data on a ~28 km segment of dark fiber between the cities of Calipatria and Imperial in the Imperial Valley, Southern California. Dark fiber refers to unused optical fiber cables in telecommunications networks and is repurposed in this project for DAS applications. The objective, which is further detailed in the attached journal article from Ajo-Franklin et al., is to demonstrate dark fiber DAS as a tool for basin-scale geothermal exploration and monitoring. The included DAS data were recorded during two days at the beginning the project. Data is stored in the .h5 (HDF5) file format, readable using various software tools, including the 'h5read' and 'h5info' functions in Matlab. Provided here are examples of methods to read and use the data with the 'h5py' package in Python. |
| distribution |
[
{
"@type": "dcat:Distribution",
"title": "Imperial Valley Dark Fiber DAS Data on AWS",
"format": "HTML",
"accessURL": "https://data.openei.org/s3_viewer?bucket=gdr-data-lake&prefix=imperialvalleydas%2F",
"mediaType": "text/html",
"description": "This dataset contains continuous raw DAS data acquired over a period of two days (November 12-13, 2020) at the beginning of the Imperial Valley Dark Fiber Project. It consists 2,880 files, with each file containing a one minute segment of strain rate data in .h5 (HDF5) format. Technical specifications of the DAS data acquisition are - 6,912 channels, 4 m channel spacing, 10 m gauge length, and a 500 Hz sample rate. The accompanying Jupyter notebooks provide methods for extracting the data and viewing all metadata within these files."
},
{
"@type": "dcat:Distribution",
"title": "Dark Fiber Data Juyter Notebook Tutorial",
"format": "ipynb",
"accessURL": "https://github.com/openEDI/documentation/blob/main/ImperialValleyDarkFiber/DarkFiber_Tutorial_Notebook.ipynb",
"mediaType": "application/octet-stream",
"description": "A jupyter notebook that details reading, checking, and plotting the Dark Fiber project data. The notebook includes examples of how to load the data directly from the s3 bucket, as well as how to locally download a file to use."
},
{
"@type": "dcat:Distribution",
"title": "GDR Data Lake Registry on AWS",
"format": "HTML",
"accessURL": "https://registry.opendata.aws/gdr-data-lake/",
"mediaType": "text/html",
"description": "AWS public dataset program registry page for data released under the Department of Energy's (DOE) Geothermal Data Repository (GDR) Data Lake. The registry page contains information about dataset documentation, access, and contact, for each of the GDR Data Lake datasets."
},
{
"@type": "dcat:Distribution",
"title": "Journal Article - Imperial Valley Dark Fiber Project",
"format": "HTML",
"accessURL": "https://www.osti.gov/pages/biblio/1903439",
"mediaType": "text/html",
"description": "This journal article from Ajo-Franklin et al. offers a review of the Imperial Valley Dark Fiber Project. It discusses the geothermal setting targeted by the project and explains the role of Distributed Acoustic Sensing (DAS) and dark fiber sensing in this context. The article details the project's experimental design, system deployment, and data extraction methods. It concludes with initial observations, findings, and outlines future directions for the project."
}
]
|
| DOI | 10.15121/2281889 |
| identifier | https://data.openei.org/submissions/7590 |
| issued | 2020-11-10T07:00:00Z |
| keyword |
[
"DAS",
"Jupyter notebook",
"Python",
"brawley",
"dark fiber",
"dark fiber DAS",
"distributed acoustic sensing",
"earthquakes",
"energy",
"fiber optic",
"geophysics",
"geothermal",
"geothermal exploration",
"h5py",
"hdf5",
"hidden geothermal resources",
"imperial valley",
"raw data",
"salton sea",
"seismic data",
"seismic noise",
"seismicity",
"southern california",
"strain rate",
"tectonics",
"telecommunications fiber"
]
|
| landingPage | https://gdr.openei.org/submissions/1499 |
| license | https://creativecommons.org/licenses/by/4.0/ |
| modified | 2024-01-19T18:12:52Z |
| programCode |
[
"019:006"
]
|
| projectLead | Alexandra Prisjatschew |
| projectNumber |
"35524"
|
| projectTitle | Using Dark Fiber and Distributed Acoustic Sensing (DAS) to Map and Monitor Geothermal Resources at the Basin Scale |
| publisher |
{
"name": "Lawrence Berkeley National Laboratory",
"@type": "org:Organization"
}
|
| spatial |
"{"type":"Polygon","coordinates":[[[-180,-83],[180,-83],[180,83],[-180,83],[-180,-83]]]}"
|
| title | Imperial Valley Dark Fiber Project Continuous DAS Data |
