Altona, NY EGS Field Site Radon Study

Brown, Shaun

doi:10.15121/1495418

Title: Altona, NY EGS Field Site Radon Study

Dataset
Other Related Research

Abstract

Data include 222Rn activities and complimentary geochemical data for multiple field experiments as part of an EGS project

Authors:

Brown, Shaun

Lawrence Berkeley National Laboratory

Publication Date:: Fri Sep 02 04:00:00 UTC 2016

Other Number(s):: 1118

Research Org.:: DOE Geothermal Data Repository; Lawrence Berkeley National Laboratory

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Geothermal Technologies Program (EE-2C)

Collaborations:: Lawrence Berkeley National Lab

Subject:: 15 GEOTHERMAL ENERGY; 222Rn; 226Ra; 228Ra; 238U; Altona Test Site; EGS; NY; New York; Potsdam Sandstone; Th; U; altona; composition; data; element; energy; enhanced geothermal system; geochemical; geochemistry; geothermal; major element; radioactive; radioactivity; radioisotope; radium; radon; sandstone; thorium; trace element; tracer; uranium

OSTI Identifier:: 1495418

DOI:: https://doi.org/10.15121/1495418

Citation Formats


                    Brown, Shaun. Altona, NY EGS Field Site Radon Study.  United States: N. p., 2016. 
        Web.  doi:10.15121/1495418.

Copy to clipboard


                    Brown, Shaun. Altona, NY EGS Field Site Radon Study.  United States.  doi:https://doi.org/10.15121/1495418

Copy to clipboard


                    Brown, Shaun. 2016.  
"Altona, NY EGS Field Site Radon Study".  United States.  doi:https://doi.org/10.15121/1495418.  https://www.osti.gov/servlets/purl/1495418. Pub date:Fri Sep 02 04:00:00 UTC 2016

Copy to clipboard


                    
@article{osti_1495418,

  title        = {Altona, NY EGS Field Site Radon Study},

  author       = {Brown, Shaun},

  abstractNote = {Data include 222Rn activities and complimentary geochemical data for multiple field experiments as part of an EGS project},

  doi          = {10.15121/1495418},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Fri Sep 02 04:00:00 UTC 2016},

  month        = {Fri Sep 02 04:00:00 UTC 2016}

}

Copy to clipboard

Dataset:

View Dataset

DOI: https://doi.org/10.15121/1495418

Save / Share:

Export Metadata

Save to My Library

Similar records in DOE Data Explorer and OSTI.GOV collections:

AASG Wells Data for the EGS Test Site Planning and Analysis Task

Dataset Augustine, Chad

Temperature measurement data obtained from boreholes for the Association of American State Geologists (AASG) geothermal data project. Typically bottomhole temperatures are recorded from log headers, and this information is provided through a borehole temperature observation service for each state. Service includes header records, well logs, temperature measurements, and other information for each borehole. Information presented in Geothermal Prospector was derived from data aggregated from the borehole temperature observations for all states. For each observation, the given well location was recorded and the best available well identifier (name), temperature and depth were chosen. The "Well Name Source," "Temp. Type" and "Depthmore »« less
Technology Development and Field Trials of EGS Drilling Systems at Chocolate Mountain

Dataset Knudsen, Steven

Polycrystalline diamond compact (PDC) bits are routinely used in the oil and gas industry for drilling medium to hard rock but have not been adopted for geothermal drilling, largely due to past reliability issues and higher purchase costs. The Sandia Geothermal Research Department has recently completed a field demonstration of the applicability of advanced synthetic diamond drill bits for production geothermal drilling. Two commercially-available PDC bits were tested in a geothermal drilling program in the Chocolate Mountains in Southern California. These bits drilled the granitic formations with significantly better Rate of Penetration (ROP) and bit life than the roller conemore »« less
Data Arrays for Microearthquake (MEQ) Monitoring using Deep Learning for the Newberry EGS Sites

Dataset Marone, Chris

The 'Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties' project looks to apply machine learning (ML) methods to Microearthquake (MEQ) data for imaging geothermal reservoir properties and forecasting seismic events, in order to advance geothermal exploration and safe geothermal energy production. As part of the project, this submission provides data arrays for 149 microearthquakes between the year 2012 and 2013 at the Newberry EGS Site for use with the Deep Learning Algorithm that has been developed. The data provided includes raw waveform data, location data, normalized waveform data, and processed waveform data. Penn State Geothermal Teammore »« less
Newberry EGS Literature References

Dataset Rose, Kelly

Research references to literature about the Newberry geothermal area, Oregon.
NY Central System 1 Well - Ohio

Dataset Pohl, Mathias ; Crandall, Dustin ; Paronish, Thomas ; ...

CT Data that compliments the Technical Report Series document: Pohl, M.; Paronish, T.; Mitchell, N.; Jarvis, K.; Sharma, M.; Moore, J.; Crandall, D.; Danielsen, E. M.; McDonald, J. Computed Tomography Scanning and Petrophysical Measurements of Oriskany Core Across Eastern Ohio, U.S. Department of Energy, National Energy Technology Laboratory: Morgantown, WV, 2024

Similar Records