Final results of a 3D finite difference thermal model of Newberry Volcano, Oregon. Model data are formatted as a text file with four data columns (X, Y, Z, T). X and Y coordinates are in UTM (NAD83 Zone 10N), Z is elevation from mean sea level (meters), T is temperature in deg C. Model is 40km X 40km X 12.5 km, grid node spacing is 100m in X, Y, and Z directions. A symmetric cylinder shaped magmatic heat source centered on the present day caldera is the modeled heat source. The center of the modeled body is a -1700 m (elevation) and is 600m thick with a radius of 8700m. This is the best fit results from 2D modeling of the west flank of the volcano. The model accounts for temperature dependent thermal properties and latent heat of crystallization. For additional details, assumptions made, data used, and a discussion of the validity of the model see Frone, 2015 (Link below).

Newberry Volcano, a voluminous (500 km3) basaltic/andesitic/rhyolitic shield volcano located near the intersection of the Cascade volcanic arc, the Oregon High Lava Plains and Brothers Fault Zone, and the northern Basin and Range Province, has been the site of geothermal exploration for more than 40 years. This has resulted in a unique resource: an extensive set of surficial and subsurface information appropriate to constrain the baseline structure of, and conditions within a high heat capacity magmatically hosted geothermal system. In 2012 and 2014 AltaRock Energy conducted repeated stimulation of an enhanced geothermal systems (EGS) prospect along the western flank of the Newberry Volcano. A surface based monitoring effort was conducted independent of these stimulation attempts in both 2012 and 2014 through a collaboration between NETL, Oregon State University and Zonge International. This program included utilization of 3-D and 4-D magnetotelluric, InSAR, ground-based interferometric radar, and microgravity observations within and surrounding the planned EGS stimulation zone. These observations as well as borehole and microseismic stress field and location solutions provided by AltaRock and its collaborators, in combination with well logs, petrologic and geochemical data sets, LIDAR mapping of fault traces and extrusive volcanics, surficial geologic mapping and seismic tomography, have resulted in development of a framework, subsurface geologic model for Newberry Volcano. The Newberry subsurface geologic model is a three-dimensional digital model constructed in EarthVision that enables lithology, directly and remotely measured material properties, and derived properties such as permeability, porosity and temperature, to be coregistered. This provides a powerful tool for characterizing and evaluating the sustainability of the site for EGS production and testing, particularly within the data-dense western portion of the volcano. The model has implications for understanding the previous EGS stimulations at Newberry as well as supporting future research and resource characterization opportunities. A portion of the Newberry area has been selected as a candidate site for the DOE FORGE (Frontier Observatory for Research in Geothermal Energy) Program through a collaboration between Pacific Northwest National Laboratory, Oregon State University, AltaRock Energy and additional partners. Thus, the conceptual geologic model presented here will support and benefit from future enhancements associated with that effort. --Mark-Moser et al. 2016

Newberry Volcano, a voluminous (500 km3) basaltic/andesitic/rhyolitic shield volcano located near the intersection of the Cascade volcanic arc, the Oregon High Lava Plains and Brothers Fault Zone, and the northern Basin and Range Province, has been the site of geothermal exploration for more than 40 years. This has resulted in a unique resource: an extensive set of surficial and subsurface information appropriate to constrain the baseline structure of, and conditions within a high heat capacity magmatically hosted geothermal system. In 2012 and 2014 AltaRock Energy conducted repeated stimulation of an enhanced geothermal systems (EGS) prospect along the western flank of the Newberry Volcano. A surface based monitoring effort was conducted independent of these stimulation attempts in both 2012 and 2014 through a collaboration between NETL, Oregon State University and Zonge International. This program included utilization of 3-D and 4-D magnetotelluric, InSAR, ground-based interferometric radar, and microgravity observations within and surrounding the planned EGS stimulation zone. These observations as well as borehole and microseismic stress field and location solutions provided by AltaRock and its collaborators, in combination with well logs, petrologic and geochemical data sets, LIDAR mapping of fault traces and extrusive volcanics, surficial geologic mapping and seismic tomography, have resulted in development of a framework, subsurface geologic model for Newberry Volcano. The Newberry subsurface geologic model is a three-dimensional digital model constructed in EarthVision that enables lithology, directly and remotely measured material properties, and derived properties such as permeability, porosity and temperature, to be coregistered. This provides a powerful tool for characterizing and evaluating the sustainability of the site for EGS production and testing, particularly within the data-dense western portion of the volcano. The model has implications for understanding the previous EGS stimulations at Newberry as well as supporting future research and resource characterization opportunities. A portion of the Newberry area has been selected as a candidate site for the DOE FORGE (Frontier Observatory for Research in Geothermal Energy) Program through a collaboration between Pacific Northwest National Laboratory, Oregon State University, AltaRock Energy and additional partners. Thus, the conceptual geologic model presented here will support and benefit from future enhancements associated with that effort. --Mark-Moser et al. 2016

Part of the DEEPEN (DE-risking Exploration of geothermal Plays in magmatic ENvironments) project involved developing and testing a methodology for a 3D play fairway analysis (PFA) for multiple play types (conventional hydrothermal, superhot EGS, and supercritical). This was tested using new and existing geoscientific exploration datasets at Newberry Volcano. This GDR submission includes images, data, and models related to the 3D favorability and uncertainty models and the 2D favorability and uncertainty maps. The DEEPEN PFA Methodology, detailed in the journal article below, is based on the method proposed by Poux & O'brien (2020), which uses the Leapfrog Geothermal software with the Edge extension to conduct PFA in 3D. This method uses all available data to build a 3D geodata model which can be broken down into smaller blocks and analyzed with advanced geostatistical methods. Each data set is imported into a 3D model in Leapfrog and divided into smaller blocks. Conditional queries can then be used to assign each block an index value which conditionally ranks each block's favorability, from 0-5 with 5 being most favorable, for each model (e.g., lithologic, seismic, magnetic, structural). The values between 0-5 assigned to each block are referred to as index values. The final step of the process is to combine all the index models to create a favorability index. This involves multiplying each index model by a given weight and then summing the resulting values. The DEEPEN PFA Methodology follows this approach, but split up by the specific geologic components of each play type. These components are defined as follows for each magmatic play type: 1. Conventional hydrothermal plays in magmatic environments: Heat, fluid, and permeability 2. Superhot EGS plays: Heat, thermal insulation, and producibility (the ability to create and sustain fractures suitable for and EGS reservoir) 3. Supercritical plays: Heat, supercritical fluid, pressure seal, and producibility (the proper permeability and pressure conditions to allow production of supercritical fluid) More information on these components and their development can be found in Kolker et al., (2022). For the purposes of subsurface imaging, it is easier to detect a permeable fluid-filled reservoir than it is to detect separate fluid and permeability components. Therefore, in this analysis, we combine fluid and permeability for conventional hydrothermal plays, and supercritical fluid and producibility for supercritical plays. We also project the 3D favorability volumes onto 2D surfaces for simplified joint interpretation, and we incorporate an uncertainty component. Uncertainty was modeled using the best approach for the dataset in question, for the datasets where we had enough information to do so. Identifying which subsurface parameters are the least resolved can help qualify current PFA results and focus future efforts in data collection. Where possible, the resulting uncertainty models/indices were weighted using the same weights applied to the respective datasets, and summed, following the PFA methodology above, but for uncertainty.

Part of the DEEPEN (DE-risking Exploration of geothermal Plays in magmatic ENvironments) project involved developing and testing a methodology for a 3D play fairway analysis (PFA) for multiple play types (conventional hydrothermal, superhot EGS, and supercritical). This was tested using new and existing geoscientific exploration datasets at Newberry Volcano. This GDR submission includes images, data, and models related to the 3D favorability and uncertainty models and the 2D favorability and uncertainty maps. The DEEPEN PFA Methodology, detailed in the journal article below, is based on the method proposed by Poux & O'brien (2020), which uses the Leapfrog Geothermal software with the Edge extension to conduct PFA in 3D. This method uses all available data to build a 3D geodata model which can be broken down into smaller blocks and analyzed with advanced geostatistical methods. Each data set is imported into a 3D model in Leapfrog and divided into smaller blocks. Conditional queries can then be used to assign each block an index value which conditionally ranks each block's favorability, from 0-5 with 5 being most favorable, for each model (e.g., lithologic, seismic, magnetic, structural). The values between 0-5 assigned to each block are referred to as index values. The final step of the process is to combine all the index models to create a favorability index. This involves multiplying each index model by a given weight and then summing the resulting values. The DEEPEN PFA Methodology follows this approach, but split up by the specific geologic components of each play type. These components are defined as follows for each magmatic play type: 1. Conventional hydrothermal plays in magmatic environments: Heat, fluid, and permeability 2. Superhot EGS plays: Heat, thermal insulation, and producibility (the ability to create and sustain fractures suitable for and EGS reservoir) 3. Supercritical plays: Heat, supercritical fluid, pressure seal, and producibility (the proper permeability and pressure conditions to allow production of supercritical fluid) More information on these components and their development can be found in Kolker et al., (2022). For the purposes of subsurface imaging, it is easier to detect a permeable fluid-filled reservoir than it is to detect separate fluid and permeability components. Therefore, in this analysis, we combine fluid and permeability for conventional hydrothermal plays, and supercritical fluid and producibility for supercritical plays. We also project the 3D favorability volumes onto 2D surfaces for simplified joint interpretation, and we incorporate an uncertainty component. Uncertainty was modeled using the best approach for the dataset in question, for the datasets where we had enough information to do so. Identifying which subsurface parameters are the least resolved can help qualify current PFA results and focus future efforts in data collection. Where possible, the resulting uncertainty models/indices were weighted using the same weights applied to the respective datasets, and summed, following the PFA methodology above, but for uncertainty.

As part of DEEPEN (DE-risking Exploration of geothermal Plays in magmatic ENvironments), a 3D play fairway analysis (PFA) was conducted at Newberry Volcano in Central Oregon for multiple play types (conventional hydrothermal, superhot EGS, and supercritical). For use in this PFA, combined full tensor broadband magnetotelluric (MT) and gravity data were acquired, processed, and inverted by Enthalpion Energy LLC (Enthalpion) with support from NREL staff. The data collection efforts took place from June 19th to July 24. Data were collected with the goal of gaining an improved understanding of the South Flank and the extent of the magma chamber. This GDR submission includes the raw data, single inversions, joint inversions, resolution matrices, and a report on these processes. More detailed information about the folder structure of the datasets included in this submission may be found on pages 94-97 of Magnetotelluric and Gravity Survey Report.pdf below.

As part of DEEPEN (DE-risking Exploration of geothermal Plays in magmatic ENvironments), a 3D play fairway analysis (PFA) was conducted at Newberry Volcano in Central Oregon for multiple play types (conventional hydrothermal, superhot EGS, and supercritical). For use in this PFA, combined full tensor broadband magnetotelluric (MT) and gravity data were acquired, processed, and inverted by Enthalpion Energy LLC (Enthalpion) with support from NREL staff. The data collection efforts took place from June 19th to July 24. Data were collected with the goal of gaining an improved understanding of the South Flank and the extent of the magma chamber. This GDR submission includes the raw data, single inversions, joint inversions, resolution matrices, and a report on these processes. More detailed information about the folder structure of the datasets included in this submission may be found on pages 94-97 of Magnetotelluric and Gravity Survey Report.pdf below.

Validation of Innovative Exploration Technologies for Newberry Volcano: Lithology Reports of Temperature Gradient Wells

Validation of Innovative Exploration Technologies for Newberry Volcano: Lithology Reports of Temperature Gradient Wells

Newberry Volcano, one of the largest Quaternary volcanoes in the conterminous United States, is a broad shield-shaped volcano measuring at least 60 km north-south by 30 km east-west with a maximum elevation of more than 2 km above sea level. It is the product of deposits from hundreds of eruptions, including at least 25 in (approximately) the last 12,000 years (the Holocene Epoch). Newberry Volcano has erupted as recently as 1,300 years ago, but isotopic ages indicate that the volcano began its growth as early as 0.6 million years ago. Such a long eruptive history together with recent activity suggests that Newberry Volcano is likely to erupt in the future. This DEM (digital elevation model) of Newberry Volcano contributes to natural hazard monitoring efforts, the study of regional geology, volcanic landforms, and landscape modification during and after future volcanic eruptions, both at Newberry Volcano or elsewhere globally. Acquisition of these high-precision, airborne lidar (Light Detection And Ranging) data was funded as part of the American Recovery and Reinvestment Act (ARRA) of 2009. Data were collected through the Oregon LiDAR Consortium, administered by the Oregon Department of Geology and Mineral Industries (DOGAMI). Watershed Sciences was contracted to collect 500 square miles of high-precision airborne lidar data to produce a digital map of the ground surface beneath forest cover. The lidar-derived DEM is amended to include bathymetric surveys of East Lake and Paulina Lake. The bathymetric surveys were performed in June, 2001 by Bob Reynolds of Central Oregon Community College, Bend, Oregon. The bathymetry is mosaicked into the DEM in place of the lidar derived lake surfaces. This release is comprised of a DEM dataset accompanied by a hillshade raster, each divided into eighteen tiles. Each tile’s bounding rectangle is identical to the extent of the USGS 7.5 minute topographic quadrangles covering the same area. The names of the DEM tiles are eleven characters long (e.g., dem_xxxxxx) with the prefix, "dem", indicating the file is a DEM and the last seven characters corresponding to the map reference code of the quadrangle defining the tile's spatial extent. Hillshade tile names are denoted by the prefix "hs", but are otherwise identical to the DEM they are derived from.