DEEPEN 3D PFA Index Models for Exploration Datasets at Newberry Volcano
DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments.
As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), index models needed to be developed to map values in geoscientific exploration datasets to favorability index values. This GDR submission includes those index models.
Index models were created by binning values in exploration datasets into chunks based on their favorability, and then applying a number between 0 and 5 to each chunk, where 0 represents very unfavorable data values and 5 represents very favorable data values. To account for differences in how exploration methods are used to detect each play component, separate index models are produced for each exploration method for each component of each play type.
Index models were created using histograms of the distributions of each exploration dataset in combination with literature and input from experts about what combinations of geophysical, geological, and geochemical signatures are considered favorable at Newberry. This is in attempt to create similar sized bins based on the current understanding of how different anomalies map to favorable areas for the different types of geothermal plays (i.e., conventional hydrothermal, superhot EGS, and supercritical). For example, an area of partial melt would likely appear as an area of low density, high conductivity, low vp, and high vp/vs. This means that these target anomalies would be given high (4 or 5) index values for the purpose of imaging the heat source. To account for differences in how exploration methods are used to detect each play component, separate index models are produced for each exploration method for each component of each play type.
Index models were produced for the following datasets:
- Geologic model
- Alteration model
- vp/vs
- vp
- vs
- Temperature model
- Seismicity (density*magnitude)
- Density
- Resistivity
- Fault distance
- Earthquake cutoff depth model
Citation Formats
TY - DATA
AB - DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments.
As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), index models needed to be developed to map values in geoscientific exploration datasets to favorability index values. This GDR submission includes those index models.
Index models were created by binning values in exploration datasets into chunks based on their favorability, and then applying a number between 0 and 5 to each chunk, where 0 represents very unfavorable data values and 5 represents very favorable data values. To account for differences in how exploration methods are used to detect each play component, separate index models are produced for each exploration method for each component of each play type.
Index models were created using histograms of the distributions of each exploration dataset in combination with literature and input from experts about what combinations of geophysical, geological, and geochemical signatures are considered favorable at Newberry. This is in attempt to create similar sized bins based on the current understanding of how different anomalies map to favorable areas for the different types of geothermal plays (i.e., conventional hydrothermal, superhot EGS, and supercritical). For example, an area of partial melt would likely appear as an area of low density, high conductivity, low vp, and high vp/vs. This means that these target anomalies would be given high (4 or 5) index values for the purpose of imaging the heat source. To account for differences in how exploration methods are used to detect each play component, separate index models are produced for each exploration method for each component of each play type.
Index models were produced for the following datasets:
- Geologic model
- Alteration model
- vp/vs
- vp
- vs
- Temperature model
- Seismicity (density*magnitude)
- Density
- Resistivity
- Fault distance
- Earthquake cutoff depth model
AU - Taverna, Nicole
A2 - Pauling, Hannah
A3 - Kolker, Amanda
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Renewable Energy Laboratory
DO - 10.15121/1995528
KW - geothermal
KW - energy
KW - DEEPEN
KW - superhot
KW - supercritical
KW - superhot EGS
KW - magmatic
KW - hydrothermal
KW - index models
KW - favorability
KW - pfa
KW - exploration
KW - characterization
KW - Newberry
LA - English
DA - 2023/06/30
PY - 2023
PB - National Renewable Energy Laboratory
T1 - DEEPEN 3D PFA Index Models for Exploration Datasets at Newberry Volcano
UR - https://doi.org/10.15121/1995528
ER -
Taverna, Nicole, et al. DEEPEN 3D PFA Index Models for Exploration Datasets at Newberry Volcano. National Renewable Energy Laboratory, 30 June, 2023, GDR. https://doi.org/10.15121/1995528.
Taverna, N., Pauling, H., & Kolker, A. (2023). DEEPEN 3D PFA Index Models for Exploration Datasets at Newberry Volcano. [Data set]. GDR. National Renewable Energy Laboratory. https://doi.org/10.15121/1995528
Taverna, Nicole, Hannah Pauling, and Amanda Kolker. DEEPEN 3D PFA Index Models for Exploration Datasets at Newberry Volcano. National Renewable Energy Laboratory, June, 30, 2023. Distributed by GDR. https://doi.org/10.15121/1995528
@misc{OEDI_Dataset_7601,
title = {DEEPEN 3D PFA Index Models for Exploration Datasets at Newberry Volcano},
author = {Taverna, Nicole and Pauling, Hannah and Kolker, Amanda},
abstractNote = {DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments.
As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), index models needed to be developed to map values in geoscientific exploration datasets to favorability index values. This GDR submission includes those index models.
Index models were created by binning values in exploration datasets into chunks based on their favorability, and then applying a number between 0 and 5 to each chunk, where 0 represents very unfavorable data values and 5 represents very favorable data values. To account for differences in how exploration methods are used to detect each play component, separate index models are produced for each exploration method for each component of each play type.
Index models were created using histograms of the distributions of each exploration dataset in combination with literature and input from experts about what combinations of geophysical, geological, and geochemical signatures are considered favorable at Newberry. This is in attempt to create similar sized bins based on the current understanding of how different anomalies map to favorable areas for the different types of geothermal plays (i.e., conventional hydrothermal, superhot EGS, and supercritical). For example, an area of partial melt would likely appear as an area of low density, high conductivity, low vp, and high vp/vs. This means that these target anomalies would be given high (4 or 5) index values for the purpose of imaging the heat source. To account for differences in how exploration methods are used to detect each play component, separate index models are produced for each exploration method for each component of each play type.
Index models were produced for the following datasets:
- Geologic model
- Alteration model
- vp/vs
- vp
- vs
- Temperature model
- Seismicity (density*magnitude)
- Density
- Resistivity
- Fault distance
- Earthquake cutoff depth model
},
url = {https://gdr.openei.org/submissions/1511},
year = {2023},
howpublished = {GDR, National Renewable Energy Laboratory, https://doi.org/10.15121/1995528},
note = {Accessed: 2025-05-28},
doi = {10.15121/1995528}
}
https://dx.doi.org/10.15121/1995528
Details
Data from Jun 30, 2023
Last updated Sep 25, 2023
Submitted Jul 5, 2023
Organization
National Renewable Energy Laboratory
Contact
Nicole Taverna
Authors
Original Source
https://gdr.openei.org/submissions/1511Research Areas
Keywords
geothermal, energy, DEEPEN, superhot, supercritical, superhot EGS, magmatic, hydrothermal, index models, favorability, pfa, exploration, characterization, NewberryDOE Project Details
Project Name DE-risking Exploration of geothermal Plays in magmatic ENvironments (DEEPEN)
Project Lead Lauren Boyd
Project Number 37178
