PoroTomo Natural Laboratory Horizontal and Vertical Distributed Acoustic Sensing Data
This dataset includes links to the PoroTomo DAS data in both SEG-Y and hdf5 (via h5py and HSDS with h5pyd) formats with tutorial notebooks for use. Data are hosted on Amazon Web Services (AWS) Simple Storage Service (S3) through the Open Energy Data Initiative (OEDI). Also included are links to the documentation for the dataset, Jupyter Notebook tutorials for working with the data as it is stored in AWS S3, and links to data viewers in OEDI for the horizontal (DASH) and vertical (DASV) DAS datasets.
Horizontal DAS (DASH) data collection began 3/8/16, paused, and then started again on 3/11/2016 and ended 3/26/2016 using zigzag trenched fiber optic cabels. Vertical DAS (DASV) data collection began 3/17/2016 and ended 3/28/16 using a fiber optic cable through the first 363 m of a vertical well. These are raw data files from the DAS deployment at (DASH) and below (DASV) the surface during testing at the PoroTomo Natural Laboratory at Brady Hot Spring in Nevada.
SEG-Y and hdf5 files are stored in 30 second files organized into directories by day. The hdf5 files available via HSDS are stored in daily files. Metadata includes information on the timing of recording gaps and a file count is included that lists the number of files from each day of recording.
These data are available for download without login credentials through the free and publicly accessible Open Energy Data Initiative (OEDI) data viewer which allows users to browse and download individual or groups of files.
Citation Formats
University of Wisconsin. (2016). PoroTomo Natural Laboratory Horizontal and Vertical Distributed Acoustic Sensing Data [data set]. Retrieved from https://dx.doi.org/10.15121/1778858.
Feigl, Kurt, Reinisch, Elena, Patterson, Jeremy, Jreij, Samir, Parker, Lesley, Nayak, Avinash, Zeng, Xiangfang, Cardiff, Michael, Lord, Neal E., Fratta, Dante, Thurber, Clifford, Wang, Herbert, Robertson, Michelle, Coleman, Thomas, Miller, Douglas E., Spielman, Paul, Akerley, John, Kreemer, Corne, Morency, Christina, Matzel, Eric, Trainor-Guitton, Whitney, and Davatzes, Nicholas. PoroTomo Natural Laboratory Horizontal and Vertical Distributed Acoustic Sensing Data. United States: N.p., 29 Mar, 2016. Web. doi: 10.15121/1778858.
Feigl, Kurt, Reinisch, Elena, Patterson, Jeremy, Jreij, Samir, Parker, Lesley, Nayak, Avinash, Zeng, Xiangfang, Cardiff, Michael, Lord, Neal E., Fratta, Dante, Thurber, Clifford, Wang, Herbert, Robertson, Michelle, Coleman, Thomas, Miller, Douglas E., Spielman, Paul, Akerley, John, Kreemer, Corne, Morency, Christina, Matzel, Eric, Trainor-Guitton, Whitney, & Davatzes, Nicholas. PoroTomo Natural Laboratory Horizontal and Vertical Distributed Acoustic Sensing Data. United States. https://dx.doi.org/10.15121/1778858
Feigl, Kurt, Reinisch, Elena, Patterson, Jeremy, Jreij, Samir, Parker, Lesley, Nayak, Avinash, Zeng, Xiangfang, Cardiff, Michael, Lord, Neal E., Fratta, Dante, Thurber, Clifford, Wang, Herbert, Robertson, Michelle, Coleman, Thomas, Miller, Douglas E., Spielman, Paul, Akerley, John, Kreemer, Corne, Morency, Christina, Matzel, Eric, Trainor-Guitton, Whitney, and Davatzes, Nicholas. 2016. "PoroTomo Natural Laboratory Horizontal and Vertical Distributed Acoustic Sensing Data". United States. https://dx.doi.org/10.15121/1778858. https://gdr.openei.org/submissions/980.
@div{oedi_980, title = {PoroTomo Natural Laboratory Horizontal and Vertical Distributed Acoustic Sensing Data}, author = {Feigl, Kurt, Reinisch, Elena, Patterson, Jeremy, Jreij, Samir, Parker, Lesley, Nayak, Avinash, Zeng, Xiangfang, Cardiff, Michael, Lord, Neal E., Fratta, Dante, Thurber, Clifford, Wang, Herbert, Robertson, Michelle, Coleman, Thomas, Miller, Douglas E., Spielman, Paul, Akerley, John, Kreemer, Corne, Morency, Christina, Matzel, Eric, Trainor-Guitton, Whitney, and Davatzes, Nicholas.}, abstractNote = {This dataset includes links to the PoroTomo DAS data in both SEG-Y and hdf5 (via h5py and HSDS with h5pyd) formats with tutorial notebooks for use. Data are hosted on Amazon Web Services (AWS) Simple Storage Service (S3) through the Open Energy Data Initiative (OEDI). Also included are links to the documentation for the dataset, Jupyter Notebook tutorials for working with the data as it is stored in AWS S3, and links to data viewers in OEDI for the horizontal (DASH) and vertical (DASV) DAS datasets.
Horizontal DAS (DASH) data collection began 3/8/16, paused, and then started again on 3/11/2016 and ended 3/26/2016 using zigzag trenched fiber optic cabels. Vertical DAS (DASV) data collection began 3/17/2016 and ended 3/28/16 using a fiber optic cable through the first 363 m of a vertical well. These are raw data files from the DAS deployment at (DASH) and below (DASV) the surface during testing at the PoroTomo Natural Laboratory at Brady Hot Spring in Nevada.
SEG-Y and hdf5 files are stored in 30 second files organized into directories by day. The hdf5 files available via HSDS are stored in daily files. Metadata includes information on the timing of recording gaps and a file count is included that lists the number of files from each day of recording.
These data are available for download without login credentials through the free and publicly accessible Open Energy Data Initiative (OEDI) data viewer which allows users to browse and download individual or groups of files.}, doi = {10.15121/1778858}, url = {https://gdr.openei.org/submissions/980}, journal = {}, number = , volume = , place = {United States}, year = {2016}, month = {03}}
https://dx.doi.org/10.15121/1778858
Details
Data from Mar 29, 2016
Last updated Oct 24, 2024
Submitted Nov 8, 2017
Organization
University of Wisconsin
Contact
Kurt Feigl
Authors
Keywords
geothermal, PoroTomo, DAS, fiber optic, surface sensors, seismic array, distributed acoustic sensing, poroeleastic tomography, bradys geothermal field, geoscience, distributed sensing, downhole, trenched, seismicity, hydrothermal, geophysics, OEDI, raw data, Jupyter Notebook, python, hdf5, hsds, h5py, h5pydDOE Project Details
Project Name PoroTomo Project
Project Lead Elisabet Metcalfe
Project Number EE0006760