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Title: SE Great Basin Play Fairway Analysis

Abstract

This submission includes a Na/K geothermometer probability greater than 200 deg C map, as well as two play fairway analysis (PFA) models. The probability map acts as a composite risk segment for the PFA models. The PFA models differ in their application of magnetotelluric conductors as composite risk segments. These PFA models map out the geothermal potential in the region of SE Great Basin, Utah.

Creator(s)/Author(s):
Publication Date:
Other Number(s):
643
DOE Contract Number:  
EE0006732
Product Type:
Dataset
Research Org.:
DOE Geothermal Data Repository; University of Utah
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Geothermal Technologies Program (EE-2C)
Subject:
15 Geothermal Energy
Keywords:
geothermal; geothermal potential; exploration; play fairway analysis; pfa; composite risk segment; crs; great basin; utah; geothermometer; Na/K; model; pfa modelling; geohtermal exploration model; goethermometer; geochemistry
OSTI Identifier:
1261951
DOI:
10.15121/1261951

Citation Formats

Brandt, Adam. SE Great Basin Play Fairway Analysis. United States: N. p., 2015. Web. doi:10.15121/1261951.
Brandt, Adam. SE Great Basin Play Fairway Analysis. United States. doi:10.15121/1261951.
Brandt, Adam. 2015. "SE Great Basin Play Fairway Analysis". United States. doi:10.15121/1261951. https://www.osti.gov/servlets/purl/1261951. Pub date:Sun Nov 15 00:00:00 EST 2015
@article{osti_1261951,
title = {SE Great Basin Play Fairway Analysis},
author = {Brandt, Adam},
abstractNote = {This submission includes a Na/K geothermometer probability greater than 200 deg C map, as well as two play fairway analysis (PFA) models. The probability map acts as a composite risk segment for the PFA models. The PFA models differ in their application of magnetotelluric conductors as composite risk segments. These PFA models map out the geothermal potential in the region of SE Great Basin, Utah.},
doi = {10.15121/1261951},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2015},
month = {11}
}

Dataset:

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