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Processed Lab Data for Neural Network-Based Shear Stress Level Prediction

Machine learning can be used to predict fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic emissions. The files are extracted features and labels from lab data (experiment p4679). The features are extracted with a n...

Marone, C. et al Pennsylvania State University

May 14, 2021
3 Resources
0 Stars
Publicly accessible

PoroTomo: BRAD and BRDY GPS Station RINEX Files March 26, 2015

This dataset provides links to daily RINEX files for two GPS stations at Brady's Hot Springs as of March 26, 2015. The data is formatted as compressed GNSS RINEX observation files, accessible through formatted CSV files, as well as in links to the complete daily time series data. ...

Kreemer, C. University of Wisconsin

Jan 01, 2015
7 Resources
0 Stars
Curated

PoroTomo: BRAD, BRD1, and BRDY GPS Station RINEX Files April 26, 2016

This dataset provides links to daily RINEX files for two GPS stations at Brady's Hot Springs as of April 26, 2016. The data is formatted as compressed GNSS RINEX observation files, accessible through formatted CSV files, as well as in links to the complete daily time series data. ...

Kreemer, C. University of Nevada

Apr 26, 2016
8 Resources
0 Stars
Curated

EGS Collab Experiment 1: In-situ observation of pre-, co and post-seismic shear slip preceding hydraulic fracturing

Understanding the initiation and arrest of earthquakes is one of the long-standing challenges of seismology. Here we report on direct observations of borehole displacement by a meter-sized shear rupture induced by pressurization of metamorphic rock at 1.5 km depth. We observed the...

Guglielmi, Y. et al Lawrence Berkeley National Laboratory

May 22, 2018
2 Resources
0 Stars
Publicly accessible

Improvements in 2016 to Natural Reservoir Analysis in Low-Temperature Geothermal Play Fairway Analysis for the Appalachian Basin

*These files add to and replace same-named files found within Submission 559 (hover over file display names to see actual file names in bottom-left corner of screen)* The files included in this submission contain all data pertinent to the methods and results of a cohesive multi-st...

Camp, E. Cornell University

Aug 18, 2016
16 Resources
0 Stars
Publicly accessible

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 include...

Feigl, K. et al University of Wisconsin

Mar 29, 2016
20 Resources
1 Stars
Publicly accessible

Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk

In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity producti...

Siler, D. et al United States Geological Survey

Oct 01, 2021
6 Resources
0 Stars
Publicly accessible

Risk Factor Analysis in Low-Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (GPFA-AB)

This submission contains information used to compute the risk factors for the GPFA-AB project. The risk factors are natural reservoir quality, thermal resource quality, potential for induced seismicity, and utilization. The methods used to combine the risk factors included taking ...

E., T. Cornell University

Sep 30, 2015
191 Resources
0 Stars
Publicly accessible

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