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DEEPEN Global Standardized Categorical Exploration Datasets for Magmatic Plays
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), weights needed to be develop...
Taverna, N. et al National Renewable Energy Laboratory
Jun 30, 2023
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
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DEEPEN 3D PFA Weights for Exploration Datasets in Magmatic Environments
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), weights needed to be develop...
Taverna, N. et al National Renewable Energy Laboratory
Jun 30, 2023
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
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 de...
Taverna, N. et al National Renewable Energy Laboratory
Jun 30, 2023
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
DEEPEN Leapfrog Geodata Model Cleaned and Reformatted Exploration Datasets from Newberry Volcano
DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments.
As part of the DEEPEN 3D play fairway analysis (PFA) conducted at Newberry Volcano for multiple play types (conventional hydrothermal, superhot EGS, and supercritical), existing geoscientific e...
Pauling, H. et al National Renewable Energy Laboratory
Jun 30, 2023
21 Resources
0 Stars
Publicly accessible
21 Resources
0 Stars
Publicly accessible
DEEPEN 3D PFA Favorability Models and 2D Favorability Maps at Newberry Volcano
DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments.
Part of the DEEPEN project involved developing and testing a methodology for a 3D play fairway analysis (PFA) for multiple play types (conventional hydrothermal, superhot EGS, and supercritical...
Taverna, N. et al National Renewable Energy Laboratory
Jun 30, 2023
26 Resources
0 Stars
Publicly accessible
26 Resources
0 Stars
Publicly accessible
GeoDAWN West Central Nevada EarthMRI Data
This submission includes both the original product resolution (OPR) and LiDAR point cloud (LPC) LiDAR data collected as part of GeoDAWN: Geoscience Data Acquisition for Western Nevada.
The USGS Earth Mapping Resources Initiative (EarthMRI) and USGS 3D Elevation Program (3DEP), De...
National Geospatial Program, U. United States Geological Survey
May 15, 2023
7 Resources
0 Stars
Publicly accessible
7 Resources
0 Stars
Publicly accessible
GeoDAWN Northwestern Elko County Nevada EarthMRI Data
This submission includes both the original product resolution (OPR) and LiDAR point cloud (LPC) LiDAR data collected as part of GeoDAWN: Geoscience Data Acquisition for Northwestern Elko County, Nevada.
The USGS Earth Mapping Resources Initiative (EarthMRI) and USGS 3D Elevation ...
National Geospatial Program, U. United States Geological Survey
May 15, 2023
7 Resources
0 Stars
Publicly accessible
7 Resources
0 Stars
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Closed Loop Geothermal Working Group: GeoCLUSTER App, Subsurface Simulation Results, and Publications
To better understand the heat production, electricity generation performance, and economic viability of closed-loop geothermal systems in hot-dry rock, the Closed-Loop Geothermal Working Group a consortium of several national labs and academic institutions has tabulated time-depe...
Beckers, K. et al Pacific Northwest National Laboratory
Feb 03, 2023
3 Resources
0 Stars
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3 Resources
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Spatially Referenced Geodatabase for Coso Geothermal Area
Mineral, Temperature, Gravity, and Fault Density maps in the Coso Geothermal Field in California.
Demir, E. et al Colorado School of Mines
Dec 01, 2022
14 Resources
0 Stars
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14 Resources
0 Stars
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Hybrid machine learning model to predict 3D in-situ permeability evolution
Enhanced geothermal systems (EGS) can provide a sustainable and renewable solution to the new energy transition. Its potential relies on the ability to create a reservoir and to accurately evaluate its evolving hydraulic properties to predict fluid flow and estimate ultimate therm...
Elsworth, D. and Marone, C. Pennsylvania State University
Nov 22, 2022
4 Resources
0 Stars
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4 Resources
0 Stars
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Dynamic Earth Energy Storage: Terawatt-year, Grid-scale Energy Storage Using Planet Earth as a Thermal Battery (GeoTES): Phase I Project Final Report
Final report for the DOE GTO funded research on geologic thermal energy storage (GeoTES), or commonly known as reservoir thermal energy storage (RTES).
The results described in this report shed light on various aspects of RTES including project siting, operational performance, m...
Atkinson, T. et al Idaho National Laboratory
Sep 02, 2022
1 Resources
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1 Resources
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Model results and data for Nontechnical Barriers to Geothermal Development
Data included in this submission support the analysis conducted for the report "Nontechnical Barriers to Geothermal Development" which is linked bellow. These data include information about the power purchase agreements (PPAs) analyzed for the report, inputs and model results for ...
Rabinowitz, H. et al Pacific Northwest National Laboratory
Jul 25, 2022
4 Resources
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4 Resources
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INGENIOUS Great Basin Regional Dataset Compilation
This is the regional dataset compilation for the INnovative Geothermal Exploration through Novel Investigations Of Undiscovered Systems (INGENIOUS) project. The primary goal of this project is to accelerate discoveries of new, commercially viable hidden geothermal systems while re...
Ayling, B. et al GBCGE, NBMG, UNR
Jun 30, 2022
16 Resources
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16 Resources
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Python Codebase and Jupyter Notebooks Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada
Git archive containing Python modules and resources used to generate machine-learning models used in the "Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada" project. This software is licensed as free to use, modify, a...
Brown, S. and Smith, C. Nevada Bureau of Mines and Geology
Jun 30, 2022
4 Resources
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4 Resources
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Kilauea Magnetotelluric Dataset
In 2002 and 2003 a collaborative effort was undertaken between Lawrence Berkeley National Laboratory, Sandia National Laboratories, the USGS Menlo Park, the USGS Hawaiian Volcano Observatory, and Electromagnetic Instruments Inc. to study the Kilauea volcano in Hawaii using the mag...
Hoversten, G. and Gasperikova, E. Lawrence Berkeley National Laboratory
Jun 16, 2022
72 Resources
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72 Resources
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GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration and Development of Hidden Geothermal Resources
Geothermal exploration and production are challenging, expensive and risky. The GeoThermalCloud uses Machine Learning to predict the location of hidden geothermal resources. This submission includes a training dataset for the GeoThermalCloud neural network. Machine Learning for Di...
Ahmmed, B. Stanford University
Apr 04, 2022
3 Resources
0 Stars
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3 Resources
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Dataset for report: Non-Technical Barriers to Geothermal Development in California and Nevada
In California and Nevada, geothermal projects are subject to non-technical barriers, which may create development delays leading to higher project costs and risks and decreased competitiveness with other electricity generation technologies. These non-technical barriers may include...
Levine, A. et al National Renewable Energy Laboratory
Mar 10, 2022
19 Resources
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19 Resources
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Economic Impact of Permitting Timelines on Produced Geothermal Power
Despite having a large geothermal power potential in the United States, only a small fraction has been developed for power generation. Various barriers, including technical, financial, and regulatory permit delays, are attributed to lower contribution of geothermal energy in the n...
Neupane, G. and Adhikari, B. Idaho National Laboratory
Feb 15, 2022
3 Resources
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3 Resources
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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results
Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells increasing or decreasing the fluid flow rates across the wells and drilling new wells at appropriate locations. Th...
Beckers, K. et al National Renewable Energy Laboratory
Oct 20, 2021
6 Resources
0 Stars
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6 Resources
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Hydrothermal mineral alterations in the Brady and Desert Peak geothermal fields
Results of the analysis of HyMap's spectra against know hydrothermally altered minerals in the Brady-Desert Peak Geothermal Areas. The analysis was performed using ENVI's Target Detection process against USGS library spectra for Chalcedony, Kaolinite, Gypsum, Hematite and Epsomite...
Moraga, J. Colorado School of Mines
Oct 01, 2021
4 Resources
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4 Resources
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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
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6 Resources
0 Stars
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DEEPEN Data Catalog for Magmatic Geothermal Systems in the United States
This data catalog contains information related to the Training Site Analysis for the Geothermica project "DE-risking Exploration of geothermal Plays in magmatic ENvironments (DEEPEN)." The DEEPEN project aims to reduce exploration risk for geothermal fluids in magmatic systems by ...
Kolker, A. et al National Renewable Energy Laboratory
Sep 30, 2021
1 Resources
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1 Resources
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Microhole drilling technology utilizing a golden section search algorithm
A fundamental issue in microhole drilling is that delivering high weight-on-bit (WOB), high torque rotational horsepower to a conventional drill bit does not scale down to the hole sizes necessary to realize the envisioned cost savings An optimization algorithm called a golden sec...
Su, J. et al Sandia National Laboratories
Jun 23, 2021
7 Resources
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7 Resources
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INGENIOUS Thermal Conductivity Measurement Source Categorization
Thermal conductivity (TC) data taken for different wells at a specified drill depth. This is an abridged version of the complete SMU heat flow database, downloaded from the SMU node of the NGDS at the beginning of INGENIOUS (approximately April 2021), and filtered to the INGENIOUS...
Batir, J. and Gentry, E. University of Nevada, Reno
Jun 01, 2021
1 Resources
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1 Resources
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USGS Geophysics, Heat Flow, and Slip and Dilation Tendency Data used in Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada
This package contains USGS data contributions to the DOE-funded Nevada Geothermal Machine Learning Project, with the objective of developing a machine learning approach to identifying new geothermal systems in the Great Basin. This package contains three major data products (geoph...
DeAngelo, J. et al Nevada Bureau of Mines and Geology
Jun 01, 2021
1 Resources
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1 Resources
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