Preliminary Ranking of Geothermal Potential in the Cascade and Aleutian Volcanic Arcs, Part I: Data Collection

GRC Transactions, Vol. 39, 2015

Lisa Shevenell1, Mark Coolbaugh1,2, Nicholas H. Hinz2, Pete Stelling3, Glenn Melosh4, William Cumming5, and Corné Kreemer2 1ATLAS Geoscience, Inc., Reno NV, USA 2Nevada Bureau of Mines and Geology, UNR, Reno NV, USA 3Western Washington University, Bellingham WA, USA 4GEODE, Santa Rosa CA, USA • 5Cumming Geoscience, Santa Rosa CA, USA [email protected] • [email protected] • [email protected] • [email protected] [email protected] • [email protected] • [email protected]

Keywords Cascade, Aleutian, volcanic, geothermal, potential, structure, database

ABSTRACT

As part of a DOE funded project on Geothermal Play Fairway Analysis, a geothermal assessment of volcanic centers in the Cascade and Aleutian volcanic arcs is being conducted that includes a large data gathering effort discussed in this paper, and a statistical modeling effort to qualitatively rank the geothermal potential of individual VCs in these two US arcs, discussed in a second companion paper. The data compiled from the Cascades and Aleutians are compared to geologic, geochemical and geophysical information from productive volcanic arc centers in the other parts of the world. Seven other volcanic arc segments from around the globe are used in this comparative study. Preliminary findings from data evaluation indicate that there are systematic changes in structural setting, from an extensional influence south of Mt. Hood (in part due to encroachment of the back arc in the southern half) to more compressional north of Mt. Hood. Comparison with productive geothermal fields around the world shows that large fumarolic areas are associated with most >240°C power-producing geothermal systems outside the US arcs (e.g., Kamojang, Indonesia, among others), whereas there is a general absence of large fumarolic areas in the Cascades and Aleutian arcs, aside from of the Lassen volcano area. As a result, fewer deep, successful wells have been drilled in the US in the Cascades and Aleutians, whereas there are many producing wells associated with fumarolic volcanic centers outside the US. Few high temperature (>200°C) systems are known in the US arcs (e.g., Newberry), and there is no direct evidence to date for very high temperature (>300°C) geothermal systems, whereas there are 21 such known systems in other volcanic arcs of the world (e.g., Silangkitang and Lahendong, Indonesia; Hachijojima and Matsukawa, Japan; Amiata, Italy; Los Azufres, Mexico, to name a few).

Introduction Much of the worlds’ geothermal production comes from young eruptive centers in active volcanic arcs. In spite of the fact that the United States is the largest producer of geothermal energy in the world, and is well endowed with young volcanic centers (VCs) in both the Cascades and Aleutian volcanic arcs, no production from either of those arcs is currently realized. Possible explanations for this lack of production include 1) the environmentally protected status or permitting challenges at some areas (e.g. Mt. Lassen, CA; Mt. Newberry, OR; Medicine Lake, CA), and 2) the remoteness of some VCs (e.g. many of the island volcanos of the Aleutian Arc). Nevertheless, geothermal exploration wells have been drilled at some VCs in these arcs (e.g., Mt. Meager, BC; Newberry caldera, OR; Glass Mountain, CA) without commercial development proceeding. It is understood that not all arc VCs in the world are created equal in terms of geothermal potential, because of local differences in structural setting, host rocks, eruption frequency and composition, and other factors. It therefore remains quantitatively unclear to what extent the lack of development of the Cascades and Aleutian Arcs is influenced by such underlying physical and chemical favorability.

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The current work attempts to quantitatively evaluate geothermal potential in the Cascade and Aleutian Arcs based on a comparison of key physiochemical parameters present at producing young arc VCs around the world. The data collection, evaluation and modeling are used to evaluate if the Cascades and Aleutians are inherently different than other arcs in terms of geothermal potential, and determine which portions of the Cascades and Aleutians offer the best potential for geothermal development in the context of play fairway analysis. The work to date on this project is documented in two parts: Part I (this paper) discusses data collection and availability, and local data variability; Part II (Coolbaugh et al., 2015) discusses regional trends and preliminary modeling to rank VCs in the Cascade and Aleutian VCs for their potential to host a power-productive hydrothermal system. Data evaluated in Part 1 include all major VCs in the Aleutians and Cascades, and those VCs in other volcanic arcs throughout the world with producing systems or known high temperature systems based on deep drilling and successful well tests.

Objective The primary objective of this research is to quantifiably rank the geothermal potential of each of the young VCs of the Cascade and Aleutian Arcs. This ranking would help focus future exploration efforts into the most prospective areas. If initial success can be gained in one or more areas, it would encourage expanded exploration in the remaining portions of the volcanic arcs.

Regional Data Compilation Data compiled were assembled into a master VC spreadsheet. These data included the following: 1. Relationship of VCs to producing geothermal systems (distance to geothermal system, installed power capacity, power density, temperature, depths); 2. Fluid geochemistry (spring and well geothermometry, measured temperature and fluid compositions and pH); 3. Tectonic setting (plate types, strike and dip); 4. Local structural setting (primary, secondary and tertiary, and styles and azimuth); 5. Spatial relationships of arc and trench relative to VCs; 6. Volcanic attributes(vent types, dominant and secondary rock types, eruption style, youthfulness and frequency alteration areas, snow cover areas); 7. Strain rate parameters (dilation, shear, type, motion vectors, and relative plate motion parameters); , 8. Crustal thickness. This section presents the regional data sets used in the study. Volcanic Arcs Data from volca- Table 1. List of arc segments from which VCs were selected for evaluation in this play fairway project. nic arcs across the globe Arc Arc-Trench System Lower Plate Upper Plate Upper Plate Type are included in this work Segment to provide comparisons 1 Aleutians Pacific North American Oceanic to Continental to systems located with- 2 Cascades (US and Canada) Juan de Fuca North American Continental 3 Mexico Cocos North American Continental in the US volcanic arcs. 3 Central America Cocos Caribbean Continental A summary of these 3 Caribbean South American Caribbean Oceanic subduction zones ap- 4 South America Nazca-Antarctic South American Continental pears in Table 1, which 5 Kamchatka-Kuril Islands Pacific East Siberia (N. American) Oceanic to Evolved Oceanic lists the different upper 5 Japan, central Pacific Japan (N. American) Evolved Oceanic 5 Marianas Pacific Filipino Oceanic plate types associated 5 Japan, south-Taiwan Filipino Eurasian Oceanic to Continental? with each arc segment. 6 Philippines-Taiwan Filipino Eurasian Oceanic to Evolved Oceanic 6 Sumatra-Java-Timor Australian Eurasian Oceanic to Evolved Oceanic? Geothermal 7 Papua-Solomon Microplates (3+) various various Oceanic to Evolved Oceanic? Power Plants 7 Vanuatu-Fiji-Samoa Australian Eurasian Oceanic to Evolved Oceanic 7 Tonga Pacific Australian Oceanic Initial data 7 New Zealand Pacific Australian Continental collection includes 8 Greece African Aegean microplate Oceanic to Evolved Oceanic? compilation of power 9 Italy Adriatic European Continental

772 Shevenell, et al. plants located within volcanic arc segments world-wide. A preliminary list of power plants was obtained from the ThinkGeoEnergy web site, and additional information on power plant locations, capacities, dates of commission- ing, and corrected locations were compiled for this study from a search of published literature. All power plants were located in Google Earth and accurate coordinates were included in the compilation. A summary of these power plants appears in Appendix A. Several sites without power plants but with successful flow tests on wells with commercial temperatures are included in the study (e.g. Medicine Lake) and hence, such sites do not include information on start dates. The power plant sites noted in Appendix A were compiled to help focus data compilation efforts to those areas known to have producing systems and likely to have sufficient data from which to make meaningful comparisons. Arc Volcanic Centers The initial list of VCs was obtained from a November 2014 download of Holocene vent data at the Global Volcanism Program (GVP) web site hosted by the Smithsonian (http://volcano.si.edu/). Locations of these major vents or volcanoes were verified in Google Earth (WGS 1984); many coordinates listed in the Smithsonian database were of insufficient accuracy and were updated. Additional VCs were added in the process of checking these locations and consulting the published literature. Individual VC from within each of the arc segments noted in Table 1 were then evaluated for inclusion into the study based on a series of selection criteria. A shield volcano was defined as a VC to be included in the study if its height exceeds of 500 m. Isolated cinder cones are not included in the compilation as the residual heat associated with them is expected to be minimal. In the case of the Aleutians, many of the volcanoes are located on relatively small islands, and all VC that are less than 5 km in diameter were eliminated. All submarine vents were also eliminated from the data set. All VC with existing power plants were included in local data collection. Local data (e.g., geochemistry) was not collected outside of the Cascades and Aleutians from VC that do not currently host a power plant or do not have deep wells to confirm or deny the presence of a thermal system. The restriction of data collection outside the Cascades and Aleutians to VCs with producing geothermal systems was in part a practical consideration. The scope of the project did not allow sufficient time and resources to document detailed characteristics of >700 VCs, but more importantly, many of these VCs in other parts of the world had little published data with which to compare with the producing centers. For consistency in data comparisons, it was considered better not to include them. Some volcanoes were combined into a grouped VC based on proximity. When nearby vents were within approximately 8 km of one another, the volcanoes were grouped into one VC. A summary of these groupings appears in Appendix B. The final list of world VC associated with arc volcanism includes a total of 733 centers, 67% of which have had one or more Holocene eruption based on the Smithsonian database. Unique identifiers were assigned to each of these 733 VC such that future data sets can be linked via this number. Crustal Thickness A world crustal thickness model created by the USGS (Laske et al., 2013) was downloaded and intersected with the power plant and arc VC databases such that one crustal thickness value was assigned to each VC, including those without power plants, resulting in 733 data points extracted from the world crustal thickness model. Because of coarse grid spacing and locations of some VC near boundaries of grids, some values for crustal thickness were individually assigned based on professional judgement in consultation with this database. This data set and analysis are discussed in greater detail in Coolbaugh et al. (2015). Strain and Plate Motion Data from a new global geodetic strain rate and plate motion model (released in Oct. 2014; Kreemer, et al., 2014) were downloaded and transformed into respective components of dilatational and shear strain as well as strain style. Rela- tive plate motion vectors were calculated for each arc VC in the database. These data and analysis of various components of strain are discussed in greater detail in Coolbaugh et al. (2015). Regional Tectonics and Arc Orientations The general regional tectonic setting of the volcanic arcs were compiled for each VC from Smithsonian database and summarized in Table 1. Heat Flow New regional Cascade heat flow data were acquired from Dave Blackwell and Maria Richards (Blackwell et al., 2015a, b; Frone, et al., 2015) to be used in the final modeling of the geothermal favorability of the Cascades VC play fairways during the second half of the project.

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Local Data Compilation

Local data on specific VCs were compiled for all Aleutian and Cascade VC and the world VC associated with producing geothermal fields, or those known to be power-capable based on successful flow tests. Structure & Tectonic Settings Data pertaining to the local structural and regional tectonic settings were collected from published geologic maps, databases, papers, reports, and through cross-checking against structures visible in available imagery with GoogleEarth, ArcGIS, and Bing Maps (Hinz et al., 2015). Primary parameters include characterization of the regional tectonic setting (e.g., broadly extensional, compressional, or dominated by a single major strike-slip fault zone) and local structural setting (e.g., pull-apart or fault intersection). Additional parameters collected within a 10 km radius of each VC include relative level of kinematic linkage of vents, relative density of Quaternary fault scarps; fault slip rate(s); recency of faulting; and primary, secondary, tertiary orientations of major structures. The orientation of SHmin was also compiled from published data local to each volcano or estimated from regional data available in World Stress Map (Heidbach et al., 2008). These additional parameters pertaining to the structural framework and fault kinematics qualitatively and quantitatively help define interpretation of the regional tectonic setting and the local structural setting. The classifications also facilitate a comparison between geologically observed tectonic conditions versus rankings produced by world stress and strain models, and also facilitate grouping of volcanic systems by potential play fairway types including strike-slip pull-apart systems and extensional rift-like systems. Additional details of the structural setting of VC for this work are described in Hinz et al. (2015). Volcanic Attributes The initial compilation of volcanism characteristics was completed for VCs of the Cascade and Aleutian Arcs, and other world arc VCs with established power production or potential. Several world volcanic databases, including the Smith- sonian, Alaska Volcano Observatory (AVO; http://www.avo.alaska.edu/) and GeoRoc (http://georoc.mpch-mainz.gwdg.de/ georoc/) databases were used in combination with Google Earth. The AVO volcanic vent database was downloaded and checked with the Smithsonian GVP database, and missing data in the GVP database was supplemented by AVO data to create a single database. Data were summarized for types of volcanic vents by VC, eruption timing and frequency, major rock types, plate boundary type, etc. During this compilation, the added AVO volcano locations were checked on Google Earth and the coordinates were updated in approximately ½ the cases. Additional databases used in the compilation are the state geological survey volcanic and geologic data for Washington (https://fortress.wa.gov/dnr/geology/?Theme=wigm) and all National Geothermal Data System (NGDS) vent data for AK, CA, OR and WA. This information was compiled in conjunction with the two previously noted data sets into a master data sheet on volcanic attributes. Within this new volcano database, quantitative and qualitative evaluations of the surface expressions of each VC grouping were made using the Smithsonian paragraph, Google Earth paragraph, geomorphology of the surface expressions and Google Earth historical imagery and measurement tools. Columns were added to the database as needed to collect a comprehensive suite of information for each VC. Types of data compiled for each VC include information related to the composition, eruptive style, eruption frequency, youthfulness, size/volume, clustering of VCs and characteristics of minor volcanic features occurring between major VCs. Footprint area, rather than volumes, of several types of volcanic features were measured in Google Earth as volume mea- surements would require large assumptions. In addition, the position of VCs in their respective arcs was measured (backarc vs forearc) by measuring the distance perpendicular from the trench to each VC (the arc-trench gap). Using these data and assuming a melt generation depth of 110 km, the subduction angle was estimated for each VC. The amount of permanent ice/glacier cover and the amount of visible alteration were also compiled for each of the above mentioned VCs. In several regions the Google Earth imagery was either too coarse or the ground surface was too obscured (trees, snow, etc.) to accurately distinguish altered ground. In these cases the measured extent of alteration represents a minimum estimate. Compositional data of igneous rocks collected for each VC were obtained from the GeoRoc database, a global clearinghouse for geochemical data related to volcanic studies. Submission of chemical data to GeoRoc is common but not mandatory, and thus the database is not comprehensive. Data obtained from GeoRoc may therefore be biased by which studies were chosen for submission, a problem that would be true of any geochemical clearinghouse. These data were used to comple- ment generalized compositional data in the Smithsonian and Google Earth paragraphs to establish chemical trends among producing geothermal fields worldwide. Future compositional data from the AVO database will be added to Aleutian VCs. Geochemistry/Geothermometry Sources of Geochemical Data Data were compiled for the Aleutian and Cascade arc VCs from files prepared for the National Geothermal Data System (NGDS). Charge balances were calculated for all analyses and samples with an incomplete analysis (e.g., one or

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only a few chemical constituents) or a charge balance >20% were omitted from the database. However, any the record that contained a SiO2 analysis was retained regardless of charge balance so that silica geothermometers could be calculated for the location. The data were then clipped to the study area in ArcMap, reducing the records to only those located within the study area for the play fairway project (NW California, W Washington and Oregon, and Aleutian Islands). Sample sites were selected from a 20 km buffer zone around each VC. Additional data for the VCs in the study area were obtained from review of 115 published sources, adding an additional 32 analyses to the geochemical database. Once the data were reduced to the study areas (VC), the analyses were evaluated through various sorts and additional analyses were removed from the data set. Ones that were removed at this stage typically had a good charge balance, but the balance was fortuitous and based on a limited, incomplete analysis, such as an analysis that only reported Na and Cl. Because the charge balances on these samples was misleading, the records were removed from the database. Data for the VCs (VC) in other arcs of the world were obtained almost exclusively through data entry from published sources. Name searches for geochemical data by VC and geothermal field were conducted in the following source databases: GRC, IGA, OSTI, Geothermics, GeoRef, and AVO. Searches were conducted on both primary and secondary VC and geothermal field names. A total of 183 publications were reviewed from which data were entered and compiled from 117 papers, some of which contained information on multiple geothermal fields or VCs. Additional geochemical data were obtained for arc VC in South America from a digital database maintained by co-author Glenn Melosh. Processing of Geochemical Data One analysis, one geothermometer, and one measured temperature were compiled for both a spring and a deep well (where available) for each VC. When multiple spring or well data were available for a particular VC, one representative sample was included in the master geochemical data set such that one entry per VC would be included in modeling. The highest temperature spring or well sample with the most complete analysis and best charge balance was selected when a choice of samples was available. Low pH samples were avoided when possible as their chemistry would lead to unreliable calculated geothermometer temperatures due to a variety of factors including leaching of soluble SiO2 near discharge. In many cases for all locations (e.g., World as well as Cascades and Aleutians), only minimal information could be gleaned from individual published literature sources such as a single temperature or geothermometer value without an accompanying full chemical analysis to evaluate. Although the quality of these data could not be directly ascertained via methods such as charge balances, the data were retained in the master data set to maximize the amount of information available for the model. For these cases without full chemical analyses, and only a notation of a geothermometer value, the value was listed in a Best Estimate column regardless of whether the geothermometer was obtained from a water or gas sample or if it was unstated by what method the estimate was made. Geothermometer Calculations Estimated subsurface temperatures were calculated using all compiled water analyses using the following geothermometers: Geothermometer Reference K-Mg Giggenbach, 1988 Na-K Giggenbach, 1988 Na-K-Ca Fournier and Truesdell, 1973 Na-K-Ca, Mg corrected Fournier and Potter, 1979 Quartz Fournier, 1981 Chalcedony Fournier, 1981 Quartz-Adiabatic cooling Fournier, 1981 SiO2-Gigg Giggenbach, 1992 SiO2-Mariner Mariner et al., 1983 Each geothermometer was calculated in a spreadsheet along with a column for the average of the Na-K-Ca, Mg- corrected and SiO2-Mariner geothermometer values. The SiO2-Mariner temperature is based on a threshold in which the quartz geothermometer is used if the Mg-corrected Na-K-Ca temperature is ≥100°C, and the chalcedony temperature is used if this temperature is <100°C. One representative geothermometer value was selected for each record based on the following criteria. If the record had both a SiO2 and Na-K-Ca, Mg-corr geothermometer, the average was taken as the geothermometer for that sample. If the record only reported SiO2 and no cation data, the SiO2-Gigg geothermometer was selected as the value for that record. When either or both the Na-K-Ca, Mg-corr and SiO2 geothermometers were lacking or unrealistically low, the K-Mg geothermometer was selected since the sample was most likely from a lower temperature source for which this geothermometer is preferred. When SiO2 was either lacking or unrealistically low (e.g., negative numbers), the Na-K-Ca geothermometer was recorded for the record. However, when the maturity index (MI) for a samples was >2.5, the Na-K-Ca

775 Shevenell, et al. geothermometer was selected in preference to the quartz or the average of the two. If the quartz and Na-K-Ca estimates were within ±20°C, the average was used as the best estimate. When the MI was <2, the best estimate of the sample was based on the quartz geothermometer. As noted, low pH waters were avoided but were used in some cases when those were the only analyses available. The “best” analysis was picked in this case based on what appeared most reasonable from the various SiO2 and Na-K-Ca geothermometer availability and MI. Thermal Manifestations The same 298 published sources used to collect geochemical data were also searched for notations of the presence or absence of fumaroles, sinters and travertines, and summaries compiled. Notations of surface manifestations in the Smithsonian database were also included in this compilation. Most data sources did not specify fumarole temperatures or manifestation sizes. A visual search for fumaroles was then initiated in Google Earth to locate fumarole fields associated with all world VCs to estimate size of the fields. Preliminary searches indicate data from these evaluations could be quite subjective, as well as incomplete due to the variation of image quality among areas. However, the information on the largest fields will be available during subsequent modeling efforts. Summary of Geochemical and Manifestation Data Table 2 summarizes the num- Table 2. Summary of available data from spring and well chemistry and geothermal manifestations ber of the different data types as of spring 2015. The number of VCs containing data for the individual columns is listed, with ad- available in the geochemical/sur- ditional data being compiled after spring 2015. face manifestation data set along Total Meas Spring Measured Well Surface Number Spring Geother- Well Geother- Fumaroles Manifesta- with the percent of coverage of each of VC Temp mometer Temp mometer tions data type over all VC included in US Volcanic Arcs this study. Note the total number Aleutians 63 22 21 2 2 58 8 of VC with fumarole notations in the literature includes those where Cascades 41 18 16 7 5 12 5 it was noted that no fumaroles are World Volcanic Arcs present. Central America 14 8 8 12 9 10 6 Surface manifestations in Europe 2 1 1 3 2 2 1 Table 2 include VC at which either Indonesia 20 14 15 9 7 16 6 or both sinter and travertine were Japan 14 8 8 10 10 6 1 noted in the literature search. The New Zealand 9 2 9 6 9 7 4 large number of data for fumaroles Papua New Guinea 1 0 0 1 1 1 0 in the Aleutians is a result of a Philippines 9 3 4 8 7 8 1 specific notation of the presence or Russia 6 4 5 3 3 2 0 absence of fumaroles at Alaska VC South America 7 7 7 4 5 4 2 by Schaefer et al. (2014). No other West Indies 2 1 2 2 2 1 0 arc segment includes comprehen- Totals: 188 88 96 67 62 127 34 sive information on the absence % Aleutian with data 35% 33% 3% 3% 92% 13% of fumaroles at particular VCs. % Cascades with data 44% 39% 17% 12% 29% 12% Many of the data gaps apparent % World with data 57% 70% 69% 65% 68% 25% in geothermometer and measured temperatures are due to the inability to locate data for a particular VC in the literature. Although it is known that geochemical and temperature data exist for many of these geothermal fields, the information is currently held proprietary. The exception to this trend is seen in the Alaska data in which the low number of well temperatures and geothermometers occurs because there are very few VCs drilled in the Aleutians, and hence, limited data. Hence, much of the “missing” data for VCs can be attributed to lack of drilling in Alaska and paucity of publications on drilled geothermal fields outside the US. In Alaska, geochemistry for wells is only available at two of the 63 VCs. Even in Alaska where disclosure has been relatively complete, spring data are available at only 21 of the centers because many of the islands have not been explored to any great extent. Hence, rankings among the Aleutian VC will likely be more dependent on regional data sets that include all of the VC such as crustal strain, thickness, plate velocities and dips and less on measured and calculated temperatures. Clay Caps An association of clay caps with economic geothermal systems has been widely documented (e.g., Muñoz, 2014). Increasingly, they are also recognizing that clay caps that have been breached, eroded, or otherwise compromised by surface erosional and mass wasting processes (e.g., glaciation, canyon dissection, volcanic sector collapse) can acceler-

776 Shevenell, et al. ate the natural “production rate” of an exposed geothermal reservoir, by way of hot springs and fumaroles or catastrophic breaching events, ultimately leading to draw-down and reduced power availability as fluids “leak” from the system. Ac- cordingly, efforts are being made to develop indices that estimate the degree of clay cap development, and its potential to be breached at the surface, for each VC. The development of these indices is still in the experimental/exploratory stage, and will be more thoroughly investigated in the final data collection stage of this project. Lithology Reservoir lithology is a recognized parameter influencing geothermal potential. In particular, based on relationships observed in a number of volcanic arcs, co-authors Glenn Melosh and Bill Cumming have emphasized the importance of thick, lithologically diverse recent volcanic rocks as positive factors for permeability development where such rocks occur at reservoir depths and for development of an effective smectite clay cap. The accurate prediction of lithologies at reservoir depths is challenging and has not yet been completed in this project. Efforts to characterize reservoir lithology will be continued in the last half of the project. There is optimism that it will be possible to place reservoir lithologic environments into broad categories, such as submarine vs non-marine volcanic rocks, volcanic rocks vs non-volcanic rocks, and broad age classes of sedimentary, metamorphic/igneous rocks. Tectonic uplift may alone may be a sufficient discriminant for a likely reservoir in older rocks less likely to form distributed permeability.

Data Analysis Structural Setting Regional tectonic settings were assigned to one of six primary categories. Four of these categories include extensional, transtensional, transpressional, and compressional settings; all of which are generally characterized by broad aerial strain distribution across numerous faults. The two other categories include transtensional or transpressional strike-slip dominated arc-segments. These latter two designations are dominated by single large magnitude strike-slip faults (e.g. grand Great Sumatra fault or Philippine fault). Strain is largely focused along these faults, greatly impacting locally intersected VCs and leaving other VCs unaffected. These strike-slip dominated arc segments contrast with the other settings (extensional, transtensional, transpressional, compressional) by the degree in which strain is broadly distributed across numerous faults or localized along single major fault zones. Preliminary results indicate that the regional tectonic setting, local structural setting, and strain rates associated with intra-arc faults are highly variable from arc to arc and even from arc segment to arc segment (e.g., Washington Cascades versus Oregon Cascades). This initial data evaluation also included documentation of the systematic changes in structural setting, from an extensional influence south of Mt. Hood (in part due to encroachment of the back arc in the southern half) to more compressional north of Mt. Hood. The increased normal faulting due to back-arc spreading south of Jefferson allows smaller-scale fractures to act as temporary magmatic conduits. This would also promote fissure eruptions rather than larger individual strato-cones. Evaluation of the local structural settings associated with individual VCs include a wide range of structures: normal fault accommodation zones, fault intersections, major caldera ring faults, displacement transfer zones, fault terminations, gravitational collapse faults on volcanic ocean island edifices, areas of regionally high-density of normal faults, pull-aparts, centers of strike-slip faults, centers of normal faults, restraining bends in strike-slip faults, and step-overs between normal faults. The types of regional tectonic settings are related to suites of local structural settings. For example, pure extensional tectonic settings typically include a number of normal fault terminations, step-overs in normal faults, fault intersections, and accommodation zones. Alternatively, arc segments where strain is focused along major strike-slip fault zones are associated with a suite of pull-aparts, restraining bends, fault intersections, and displacement transfer zones. The most common structural settings associated with Aleutian VCs include fault intersections (37%) with other categories (5%) and unknown (58%). The Cascade VCs are associated with fault intersections (49%), step-overs (24%), accommodation zones (17%), other categories (10%), and unknown (5%). Of the 74 total productive arc systems in the world the structural settings include fault intersections (29%), step-overs (11%), pull-aparts (11%), displacement transfer zones (8%), other categories (21%), and unknown (20%). Fault intersections between normal faults and other normal faults or strike-slip faults is the most common structural setting in the Cascades, Aleutians, and with productive arc systems around the world (not necessarily by MWe total, just by sheer number of volcanoes). Initial findings indicate a positive correlation between extensional strain (extensional strain can be associated with multiple tectonic settings and not only pure regional extension) and relative structural complexity as favorable indicators (density of faults, fractures, and fault/fracture intersections oriented favorably for extension enhance permeability). The degree of certainty for each primary structural/tectonic category is being added/refined for each VC. This degree of certainty relates to one or more reasons, including (1) VCs that are largely covered with permanent snow fields/glaciers, (2) are heavily vegetated with locally poor image quality, or (3) are not covered by existing published studies that provide any local detailed structural data.

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Characteristics of Volcanism Initial evaluation of the inventoried volcanic characteristics indicates that productive geothermal systems can occur in a broad range of volcanic settings in terms of lithologic composition, eruptive style (calderas, stratovolcanoes, dome fields, etc.), and location. While this diversity is encouraging in terms of the ability of economic systems to form in a broad range of volcanic environments, it complicates efforts to predict geothermal potential based solely on characteristics of volcanism. Nevertheless, some potential correlations have been identified. The vast majority of producing fields in arc settings occur less than ten kilometers of the main arc trend, although notable exceptions exist. Productive geothermal systems in forearc settings tend to be 10-15 km of the main volcanic arc, whereas productive backarc fields are more likely to be a greater distance from the main arc (between 20-50 km behind the arc). Additionally, a possible relationship exists between volcanic centers whose last eruptive products consisted of andesite and large (>100 MW installed power) producing geothermal systems. Also, and perhaps more significantly, volcanic centers with relatively low compositional diversity (e.g. only basaltic eruptions) appear to correlate with lower amounts of installed power. Some notable relationships also exist between the presence of minor volcanic features between adjacent major VCs and installed power. These inter-VC features include cinder cones, domes, stratocones (small VCs that have had multiple eruptions but diameters <8 km), shield volcanoes (large diameter but relief <500 m), calderas, tuyas (sub-glacial lava domes). Inter-VC Holocene stratocones, shield volcanoes, and tuyas are not associated with any productive geothermal field. A similar but less pronounced relationship exists between power production and the presence of inter-VC cinder cones, whether in a field, lineament or in isolation. The presence of lava domes or surface alteration appear to be poor indicators of geothermal potential as there does not appear to be any correlation, either positive or negative, with 50 installed power. 45 The type of volcanic features present shows some correlation with installed power. In general, 56% of 40 power-producing geothermal systems are associated with a 35 Holocene

s 24 systems; caldera (Figure 1). Of these power producing systems asso- r 30 1455 MWe total nt e ciated with calderas, approximately 45% of the geothermal e 61 MWe avg c

c systems are associated with an older (Pleistocene) caldera i 25 n and 55% are associated with Holocene centers. Although c a Non-caldera o l 20 v systems

fewer systems are associated with Pleistocene calderas, # 15 32 systems; these geothermal systems tend to produce more power Pleistocene 3722 MWe total 20 systems; than either non-caldera systems or Holocene caldera sys- 10 116 MWe avg. 3588 MWe total tems. A general inverse correlation exists between power 179 MWe avg production and the presence of cinder cones on or between 5 adjacent volcanic centers, whether in a field, lineament or 0 in isolation. The presence of lava domes or surface altera- Power with caldera Power without caldera tion appear to be poor indicators of geothermal potential as Figure 1. Summary of power producing systems in arc settings in relation there does not appear to be any correlation, either positive to caldera occurrence. or negative, with installed power. Geochemical and Temperature Data Several relationships among geothermometers, measured temperatures and other factors such as eruption frequency, dilatation and distances from and dip of the subducting slab were evaluated. No single factor appears to dominate measured and calculated temperatures, but rather a complex interplay among geologic conditions. Future work will include multivariate analyses, to include correspondence analysis, to better assess the relative weightings of the different geologic factors in hosting a productive geothermal system (e.g., high temperature, high permeability). Some general observations can be made from the compiled geothermometer and temperature data. As expected, spring geothermometers from the same field as geothermometers calculated from well chemistry are typically lower as waters discharging at the surface are likely to have experienced some re-equilibration and mixing during flow to the surface. For instance, Hochstein and Sudarman (2015) observed that geothermometer temperatures from surface emanations are typically not equilibrated and unreliable as reservoir estimates in volcanic geothermal systems throughout Indonesia. Thus, a spring geothermometer temperature can be expected to provide a minimum reservoir temperature estimates in these volcanic arc environments. Similarly, spring geothermometer temperatures are nearly always lower than deep well temperatures from the same field (Fig. 2), again indicating that spring geothermometers tend to give minimum expected reservoir temperatures. Exceptions to this rule include Lassen for which deep drilling information is lacking. The other points plotted with lower

778 Shevenell, et al. well than spring geothermom- Spring Geothermometer Temperature vs Reservoir Temperature eter temperatures in Figure 2 Aleutian 400 are Nevados de Chillán (Chile), North Cascades Southern Cascades Lahendong 350 Rotorua (New Zealand), and Central America )

C South America Kirishimayama (Japan). Well ° ( 300

e Japan geothermometers taken from r u

t Philip/Indo Medicine

a Telaga Bodas r 250 Lake deep wells are much closer to e New Zealand p their reservoir temperatures m Italy e

T Meager 200 Gas 2 l l

(Figure 3; R = 0.41) due to less e 1:1 Slope W mixing, dissolution, precipita- 150 Slope 1:1.5 Makushin m Akutan u m tion, and re-equilibration of i Crater Lassen x 100 sampled fluids than in the case a Lake Olallie Butte M of spring samples. 50 The Aleutians generally exhibit the lowest (maximum) 0 10 60 110 160 210 260 310 360 measured and geothermometer Spring Geothermometer Temperature (°C) temperatures of all the arcs, with the northern Cascades next, fol- Figure 2. Spring geothermomter temperatures at fields with measured temperatures from deep boreholes. lowed by the southern Cascades (Figure 4). Maximum known temperatures in the Aleutians Well Geothermometer Temperature vs Reservoir Temperature 400 and Cascades are all lower Aleutian than other world VC settings 350 North Cascades Newberry

) Southern Cascades C

currently under production, al- ° ( 300 Central America e though exploration of these US r South America u t a r 250 Japan systems is incomplete and there e

p Philip/Indo are no production wells at this m e New Zealand Meager T

200 l l Italy time with which to make direct e W comparisons. Meager shows 150 1:1 Slope Makushin m Akutan

u 1:1.5 Slope m the highest temperatures in the i Lassen x 100 Hood a

northern Cascades, although is M known to be of low permeability 50 at economically viable tem- 0 peratures (e.g., Ghomshei, et al., 10 60 110 160 210 260 310 360 2004). Similarly, Newberry has Well Geothermometer Temperature (°C) the highest measured temperature in the southern Cascades, Figure 3. Well geothermomter temperatures at fields with measured temperatures from deep boreholes. yet it is also known to be low permeability and is currently 450 the focus of an EGS study (e.g., Ladouhos et al., 2013). The sec- 400 ond highest temperatures in the 350 southern Cascades occur at Las-

) 300 Newberry C

° Meager sen, an area off-limits to future ( e

r 250

u Makushin

geothermal development due t a to its national park status. Only e r 200 em p

two systems in the Aleutians T are drilled, with both showing 150 promising maximum measured 100 temperatures: Akutan (182°C) 50 and Makushin (195°C). 0 Surface Manifestations Aleutian N Cascades S Cascades Central Am S. America Japan Indo/Phil New Zealand Italy Many world VC have an Measure Well T Well Geothermom T Spring Geothermom T abundance of boiling and near Figure 4. Summary of maximum measured well temperatures and geothermometer temperatures in boiling springs and fumaroles, world volcanic arc.

779 Shevenell, et al. whereas those in the Cascades and Aleutians are typically of lower temperature and of smaller surface area coverage. Large fumarole fields are uncommon in the US arcs, with the primary exception being the Lassen volcanic field that discharges through fumaroles and springs over a wide area. Aside from Lassen, there are no known large fumarole fields in the US to rival large surface expressions such as those at Kamojang Indonesia that has a 600,000 m2 fumarole/spring field (Healy and Mahon, 1982) that is clearly visible in Google Earth imagery, measuring approximately 475,000 m2 based on the currently visible steam cloud. Many other geothermal systems in Central and South America, New Zealand, Indonesia and the Philippines also express large fumarolic areas and these will be documented in part 2 of this project.

Probability Assignments In order to rank the various VC in a statistical model, a preliminary model was constructed (Coolbaugh et al, 2015) that uses probability factors assigned for each of the data types discussed here in order to weight the relative importance of data within particular data categories such as structure or temperature. Details of the incorporation of these factors into the preliminary model appear in an accompanying paper in this volume by Coolbaugh et al. (2015), whereas the rationale for selection of these factors is discussed below.

Structure Table 3. Relative rating of tectonic and structural settings used in preliminary Based on the structural analysis in the vari- model discussed in Coolbaugh et al. (2015). ous arcs, a qualitative scale of structural settings Tectonic Setting Local Structural Setting was established to assist in the ranking of VCs for Probability Probability geothermal potential in Part 2 of this work (Cool- Factor Factor baugh et al., 2015). These factors are summarized Regional Accommodation Zone 1.0 in Table 3 where larger numbers are assigned to Transtension 1 Displacement Transfer 1.0 settings more likely to result in increased perme- Extension 0.8 Pull Apart 1.0 ability, a primary and dominant factor in establishing Transpression 2 Numerous Normal Faults 0.6 a power-productive natural hydrothermal system. Compression 0.1 Step-over 0.6 Unknown 0 Fault Termination 0.5 Geothermometry and Temperature Fault Intersection 0.5 The rationale for selection of probability fac- Caldera Ring Faults 0.2 tors for geothermometers and temperatures at VCs Normal Faults 0.2 is summarized in Table 4, with the maximum prob- Local Gravity-driven Normal Faults 0.1 ability factor assignment in the preliminary model Strike-slip transtension 0.8 Restraining Bend 0.0 set to 0.5. Typically lower spring and well measured Strike-slip transpression 0.5 Unknown 0.0 temperatures are less likely to be associated with a higher temperature system, and hence they received lower factors (e.g., 0.1 for springs and wells <50°C). Because springs typically can only have a maximum temperature at the boiling temperature of the elevation of discharge, any spring >90°C is assumed to suggest a higher probability of a high temperature resource at depth. These springs are assigned the maximum factor in the preliminary modeling exercise. However, for such a high ranking in measured well temperatures, it was assumed that a measured well temperature in excess of 130°C is required to be suitable for power production. Thus, different temperature ranges are used for springs versus wells. Temperature ranges assigned to the probability factors for geothermometer values also differ between springs and wells, and differ from measured temperatures as geothermometer values are typically higher than measured temperatures and a higher temperature is required for assignment of similar probability factors. Not all data types in Table 4 are available at all VC, and some may have measured temperatures and no water analyses from which to calculate geothermometers Table 4. Probability factors assigned to measured and geothermometer temperatures of springs and wells used as initial input into the preliminary geothermal favorability ranking model of Coolbaugh et al. (2015). whereas others have calculated geothermometers of either Springs Wells Measured Geothermom Measured Geothermom or both wells and spring, but Probability Probability Probability Probability recording of measured tem- Temp (°C) Temp (°C) Temp (°C) Temp (°C) peratures was neglected in the <50 0.1 <50 0.1 <50 0.05 <100 0.05 publications consulted. When 50-75 0.3 50-75 0.2 50-100 0.3 100-130 0.2 no data are available for a par- >75-90 0.4 >75-100 0.3 >100-130 0.4 >130-200 0.3 ticular data type, a factor was >90 0.5 >100-150 0.4 >130 0.5 >200-250 0.4 assigned based on the criteria >150 0.5 >250 0.5 discussed in Coolbaugh et al. (2015). unknown -0.18 unknown -0.18 unknown -0.18 unknown -0.18

780 Shevenell, et al.

Surface Manifestations The presence of surface manifestations at geothermal systems has long been a primary and initial exploration tool to locate power-productive geothermal fields. In this work, initially assigned probability factors of a productive geothermal system ranged from 0 to 0.5 for fumaroles and common surface deposits (sinters and travertines). In most publications, simply the presence or absence of fumaroles at a field is noted, with temperatures noted sporadically, so that the weighting of fumaroles is based on a simple four tier system noted in Table 5. Fumaroles are typically associated with high temperature systems and receive a relatively high weighting factor relative to the absence of such features, but large fumarole fields (e.g., Kamojang) receive the highest probability factor of 0.5. Efforts Table 5. Probability factors assigned to surface manifesta- are underway to distinguish magmatic from hydrothermally sourced tions in the preliminary geothermal favorability ranking fumaroles in the databases, as the occurrence of the latter carries more model of Coolbaugh et al. (2015). significance for geothermal potential. Probability Probability Sinter and travertine are distinguished based on the likely Fumaroles Deposits Factor Factor temperature of deposition. Sinters are known to precipitate from high temperature fluids, high in SiO2, with likely source temperatures N 0 none 0 >180°C. Travertines, on the other hand, are not necessarily associated with thermal waters, and when they are, are typically associated with Y 0.4 Travertine 0.2 lower temperature, carbonate dominated waters. Thus, travertines in Cluster/field/many 0.5 Sinter 0.5 the absence of sinters at a VC receive a lower factor as they are likely to be associated with a thermal outflow, but are not necessarily associ- unknown -0.18 unknown -0.18 ated with a power-productive field.

Conclusions and Future Work Regional data relevant to geothermal assessments were collected from 733 VCs associated with subducting slabs worlds-wide, whereas local data from individual VCs has been compiled for a subset of these arc volcanoes. The subset of local data includes all Aleutian and Cascade VCs (defined herein) and volcanic systems either hosting existing power plants or systems that have successful well tests to provide indications of the presence of a viable high temperature systems. Deep drilling results from low temperature systems are typically not available due to the tendency to not publish negative results. From these compiled data, the volcanic systems in the Cascades and Aleutians were compared to productive geothermal systems in arc settings elsewhere in the world to help assess the geothermal potential in the US volcanic arcs. This paper provides a preliminary discussion and evaluation of these data, primarily the local data, whereas a companion paper (Coolbaugh et al., 2015) presents preliminary results of regional data and trends and a preliminary model of geothermal play fairways assigned based on these data. A final predictive model and play fairway analysis is forthcoming and will be reported at the end of the current project. Some preliminary findings from this first half of the DOE sponsored project include the following. Based on available exploration data, lower temperature systems are generally associated with the Cascades and Aleutian arc volcanoes than in other arc systems around the world where production temperatures can exceed 300°C. The maximum known temperatures in the Aleutians, northern Cascades and southern Cascades are 195°C, 240°C and 265°C at Makushin, Meager and New- berry, respectively. However, not many arc systems in the US have deep drilling results, and additional high temperature systems could be found. Nevertheless, existing data from deep wells and spring and well geothermometers indicate that the systems in the US arc settings will typically be somewhat lower temperature than those in other arcs around the world. Similarly, the US arc systems typically display a smaller aerial extent of fumarole manifestations, with the exception of the Lassen volcanic field that has hot springs and fumaroles issuing over a relatively large area. Significant snow cover and irregular imagery in Aleutians make surface feature identification difficult (e.g., fumaroles and volcanic vents), although large fumarole fields would likely be visible if present in patches of melted snow. Variations in volcanism were evaluated in a number of ways with the compiled data including evaluation of features between primary VCs. These data show that inter-vent calderas (6 of them) are always associated with productive geothermal fields, whereas none of the inter-vent Holocene stratocones, small shield volcanoes, or tuyas are associated with productive fields. The presence of inter-vent cinder cones is generally not associated with productive fields and inter-vent domes and surface alteration do not correlate, either positively or negatively, with geothermal productivity. Significant structural and volcanic style and compositional variability was observed among and within the arc segments investigated, complicating future ranking schemes. However, general trends have been observed that suggest some individual arc segments may be more prospective for geothermal systems than others. For instance, variations in structure and strain along the length of the Cascades are observed. There are systematic changes in structural setting, from an extensional influence south of Mt. Hood to more compressional north of Mt. Hood suggesting geothermal potential in the northern Cascades will be less than in the southern part of the arc.

781 Shevenell, et al.

Future work during the second half of the project will include: 1. refining structural and tectonic settings 2. incorporation of land use and power consumption data to highlight areas off limits to development and areas more likely for development due to power needs 3. continue calculation of the sizes of visible fumarole fields and assignment of fumarole type by magmatic or hydrothermal, in part based on location on summits versus flanks, or distal to, volcanic edifices 4. compile any additional spring and well geochemical data that can be acquired 5. review gas geochemistry and geothermometry, commonly reported in non-US arc VC 6. include evaluation of clay cap integrity on productivity of systems

Acknowledgements The information, data, or work presented herein was funded in part by the Office of Energy Efficiency and Renew- able Energy (EERE), U.S. Department of Energy, under Award Number DE- EE0006725 to ATLAS Geosciences. The authors wish to thank Janet Schaefer (Alaska Division of Natural Resources), John Power (Alaska Volcano Observatory), Dave Blackwell and Maria Richards (SMU), and Dick Benoit who have provided timely data and discussions on VCs, heat flow and geothermal features in the Cascade and Aleutian Arcs. The authors thank Frank Monastero for his review comments on of a draft of this paper. Disclaimer: The information, data, or work presented herein was funded in part by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

References Blackwell, D.D. Richards, M.C., and Gosnold, W.D., 2015a. SMU Geothermal Laboratory Equilibrium Heat Flow Database, SMU Node of the National Geothermal Data System at http://geothermal.smu.edu. Blackwell, D.D., Richards. M.C., Frone, Z., 2015b. Final Report on Shallow EGS Regional Resource Potential Map Development of the Cascades, submitted to National Renewable Energy Laboratory for contract XXL-4-42123001. Coolbaugh, M., L. Shevenell, N.H. Hinz, P. Stelling, G. Melosh, W. Cumming, and C. Kreemer, 2015. Preliminary Ranking of Geothermal Potential in the Cascade and Aleutian Volcanic Arcs, Part II: Preliminary Model. Geothermal Resources Council Transactions 39: Fournier, R.O., 1981. Application of Water Geochemistry to Geothermal Exploration and Reservoir Engineering. In: Rybach, L. and Muffler, L.J.P., Geothermal Systems: Principals and Case Histories. Wiley, Chichester, pp. 109-143. Fournier, R.O., and Potter, II, R.W., 1979. Magnesium correction to the Na-K-Ca chemical geothermometer. Geochim. Cosmochim. Acta 43: 1543-1550. Fournier, R.O., Truesdell, A.H., 1973. An Empirical Na-K-Ca Geothermometer for Natural Waters. Geochimica et Cosmochimica Acta 37: 1255-1275. Frone Z., M. Richards, D. Blackwell, and C. Augustine, 2015. Shallow EGS Resource Potential Maps of the Cascades, 40th Workshop on Geothermal Reservoir Engineering, Stanford University, California. 15 p., SGP-TR-204. Giggenbach, W.F., 1992, “Chemical Techniques in Geothermal Exploration: Chapter 5”, in, Franco D’Amore, coordinator, Application of Geochem- istry in Geothermal Reservoir Development, Series of Technical Guides on the use of Geothermal Energy, UNITAR/UNDP Centre on Small Energy Resources, Rome-Italy, 1991, p. 119-144. Giggenbach, W.F., 1988. Geothermal Solute Equilibria. Derivation of Na-K-Mg-Ca Geoindicators. Geochimica et Cosmochimica Acta 52: 2749-2765. Ghomshei, M., S. Sanyal, K. MacLeod, R. Henneberger, A. Ryder, J. Meech, and B. Fainbank, 2004. Status of the South Meager Geothermal Project British Columbia, Canada: Resource Evaluation and Plans for Development. Geothermal Resources Council Transactions 28: 339-344. Hinz, N.H., M. Coolbaugh, L. Shevenell, G. Melosh, W. Cumming, P. Stelling, 2015. Preliminary Ranking of Geothermal Potential in the Cascade and Aleutian Volcanic Arcs, Part II: Structural and Tectonic Settings of Volcanic Centers. Geothermal Resources Council Transactions 39: Healy, and A.J. Mahon, 1982. Kawah Kamojang Geothermal Field, West Java. New Zealand Geothermal Workshop, Vol 4 Part 2, 313-319. Heidbach, O., Tingay, M., Barth, A., Reinecker, J., Kurfe, D. and Müller, B., 2008, The World Stress Map database release 2008 doi:10.1594/GFZ WSM Rel2008. Hochstein, M.P., and S. Sudarman, 2015. Indonesian Volcanic Geothermal Systems. World Geothermal Congress 2015, Melbourne, Australia, 19-25 April 2015, 11 p. Kreemer, C., Blewitt, G., and Klein, E.C., 2014, A geodetic plate motion and global strain rate model: Geochemistry, Geophysics, Geosystems, v. 15, p. 3849-3889. doi: 10.1002/2014GC005407. Ladouhos, T.T., S. Petty, Y. Nordin, M. Moore, K. Grasso, M. Uddenberg, and M.W. Swyer, 2013. Stimulation results from the Newberry Volcano EGS Demonstration. Geothermal Resources Council Transactions 37: 133-140 Laske, G., Masters., G., Ma, Z. and Pasyanos, M., 2013, Update on CRUST1.0 - A 1-degree Global Model of Earth’s Crust, Geophysical Research Abstracts, 15, Abstract EGU2013-2658, 2013, (made available Aug. 2014). Mariner, R.H., Presser, T.S., and Evans, W.C., 1983, Geochemistry of active geothermal systems in the northern Basin and Range Province; Geothermal Resources Council Special Report No. 13.

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Muñoz, G., 2014. Exploring for Geothermal Resources with Electromagnetic Methods. Surveys in Geophysics: 35(1): 101-122. Schaefer, J.R., C.E. Cameron, and C.J. Nye, 2014. Historically active volcanoes of Alaska, in Schaefer, J.R., Cameron, C.E., and Nye, C.J., Histori- cally active volcanoes of Alaska: Alaska Division of Geological & Geophysical Surveys Miscellaneous Publication 133 v. 1.2, 1 sheet, scale 1:3,000,000. http://www.dggs.alaska.gov/pubs/id/20181 Appendix A Summary of Productive Geothermal Systems in Volcanic Arc Settings Geothermal systems that are not currently producing power but have deep drilling information and successful well tests are included with the estimated MW capacity noted in the Installed Capacity column.

Installed Reservoir Primary Volcano Start Reservoir Plant_Name Country Class Capacity Depth Type Date Temp (°C) (MW) (m) Meager Canada Complex Flow x 4.8 Medicine Lake United States Shield Flow x 25.0 Domo de San Pedro Mexico Stratovolcano Flow x 25.0 Cerritos Colorados (La Primavera) Mexico Caldera Flow x 10.0 Los Azufres Mexico Caldera Plant 1982 195.0 275 1600 Los Humeros Mexico Caldera(s) Plant 1990 40.0 341 1500 Las Pailas Costa Rica Complex Plant 2011 42.0 Miravalles Costa Rica Stratovolcano Plant 1994 165.5 235 1500 Ahuachapan El Salvador Stratovolcano(es) Plant 1975 95.0 250 1050 Berlin El Salvador Stratovolcano Plant 1999 109.4 290 2250 Orzunil Guatemala Stratovolcano Plant 1999 28.0 290 1900 Cerro Blanco Guatemala Lava dome(s) Plant x 5.0 Amatitlan Guatemala Complex Plant 2007 24.0 285 1500 San Jacinto-Tizate Nicaragua Stratovolcano(es) Plant 2005 72.0 275 Momotombo Nicaragua Stratovolcano Plant 1983 77.5 220 1650 Roseau Valley Dominica Stratovolcano(es) Flow x 11.0 La Bouillante France Stratovolcano Plant 1986 15.0 250 700 Puchildiza Chile Stratovolcano Flow x 10.0 190 Pabellon (Apacheta) Chile Lava dome(s) Flow x 20.0 240 El Tatio Chile Lava dome(s) Flow x 25.0 Laguna Colorada (Sol de la Manana) Chile Lava dome(s) Flow x 30.0 250 Chillan Chile Stratovolcano Flow x 5.0 190 Tolhuaca Chile Stratovolcano Flow x 12.0 Copehue Chile-Argentina Stratovolcano Plant 1988 0.7 Okeanskaya Japan - admin by Russia Stratovolcano Plant 2007 3.6 Mendeleevskaya Japan - admin by Russia Stratovolcano Plant 2007 1.8 Paratunskaya Russia Lava dome(s) Plant 1967 0.7 Mutnovskaya-Verkhne Russia Complex Plant 1998 62.0 255 1600 Pauzhetskaya Russia Lava dome(s) Plant 1966 14.5 195 550 Mori Japan Caldera Plant 1982 25.0 235 1250 Sumikawa-Ohnuma Japan Stratovolcano Plant 1974 59.5 250 2000 Matsukawa Japan Complex Plant 1966 23.5 255 1250 Kakkonda Japan Stratovolcano(es) Plant 1978 80.0 275 750 Uenotai Japan Stratovolcano Plant 1994 28.8 310 1500 Onikobe Japan Caldera Plant 1975 12.5 250 750 Yanaizu-Nishiyama Japan Shield Plant 1995 65.0 290 1800 Hachijojima Japan Stratovolcano(es) Plant 1999 3.3 275 1080 Suginoi Hotel Japan Lava dome(s) Plant 1980 3.0 Hatchobaru-Otake Japan Stratovolcano(es) Plant 1967 124.5 270 1750 Takigami Japan Stratovolcano(es) Plant 1996 25.0 245 2000 Ogiri Japan Shield Plant 1996 30.0 230 1500 Yamakawa (Fushime) Japan Caldera(s) Plant 1995 30.0 320 Chingshui Taiwan Stratovolcano Plant 1981 3.0 Mak-Ban (Bulalo) Philippines Stratovolcano Plant 1979 442.8 285 900 Maribarara Philippines Stratovolcano Plant 2014 20.0 Tiwi Philippines Stratovolcano Plant 1979 330.0 280 900 Bacman (Bacon-Manito) Philippines Compound Plant 1993 150.0 270 1500 Leyte Philippines Stratovolcano Plant 1983 700.0 278 2000 NNGP (Mambucal) Philippines Stratovolcano Plant 2007 49.0 Palinpinon Philippines Complex Plant 1993 232.5 300 2500 Mindanao Philippines Stratovolcano Plant 1995 106.0 280 500 Lahendong Indonesia Caldera Plant 2002 62.5 300 1500 Sibayak Indonesia Stratovolcano(es) Plant 1996 13.2 Namora-i-Langgit Indonesia Stratovolcano Flow x 105.0 Sibualbuali Indonesia Stratovolcano Flow x 9.0 Silangkitang Indonesia Stratovolcano Flow x 65.0 Muara Laboh Indonesia Stratovolcano Flow x 110.0 Lempur Kerinci Indonesia Stratovolcano Flow x 10.0 Lumut Balai Indonesia Stratovolcano? Flow x 55.0 230 Rentau Dedap Indonesia Stratovolcano? Flow x 110.0 Ulubelu Indonesia Caldera Plant 2012 110.0 Salak (Awibengkok) Indonesia Stratovolcano Plant 1994 377.0 260 1500 Kamojang Indonesia Complex Plant 1983 200.0 245 1500 Patuha-Cibuni Indonesia Stratovolcano Plant x 60.0 Wayang Windu Indonesia Lava dome Plant 2000 227.0 260 1500 Dieng Indonesia Complex Plant 1998 60.0 270 1500 Karaja-Telaga Bodas Indonesia Stratovolcano Flow x 13.0 Darajat Indonesia Stratovolcano(es) Plant 1994 260.0 245 2000 Ulumbu Indonesia Stratovolcano Plant 2014 5.0 Mataloko Indonesia Stratovolcano Plant 2013 2.5 Lihir Papua New Guinea Compound Plant 2001 56.0 275 650 Rotorua New Zealand Caldera Thermals x 50.0 Kawerau New Zealand Lava dome(s) Plant 1966 122.2 280 1500 Reporoa-Waiotapu New Zealand Caldera Plant x 50.0 Ohaaki-Broadlands New Zealand Caldera Plant 1989 103.0 275 2000 Wairakei-Tauhara New Zealand Caldera(s) Plant 1958 364.0 250 1500 Rotokawa New Zealand Caldera(s) Plant 1997 175.0 300 2250 Ngatamariki New Zealand Caldera(s) Plant 2013 82.0 273 Mokai New Zealand Caldera(s) Plant 1999 111.0 295 2000 Orakeikorako New Zealand Caldera(s) Thermals x 25.0 Larderello Italy Explosion crater(s) Plant 1913 795.0 235 2500 Amiata Piancastagnaio Italy Lava dome(s) Plant 1969 60.0 328 2000 Bagnore Italy Lava dome(s) Plant 1998 60.0 317 2000

783 Shevenell, et al.

Appendix B Major volcanos grouped into single volcanic centers for the purpose of this study.

Grouped Volcanic Centers (VC) Arc Segment Primary Center Grouped Volcano 1 Grouped Volcano 2 Grouped Volcano 3 Location Aleutians 1 Adagdak Alaska 1 Amukta Chagulak Alaska 1 Carlisle Alaska 1 Cleveland Alaska 1 Gas Rocks Alaska 1 Kagamil Uliaga Alaska 1 Kaguyak Devils Desk Alaska 1 Katmai Trident Novarupta Alaska 1 Kliuchef Alaska 1 Korovin Atka Alaska 1 Kukak Steller Denison Alaska 1 Mageik Martin Alaska 1 Moffett Alaska 1 Pavlof Pavlof Sister Alaska 1 Stepovak Bay 4 Stepovak Bay 3 Stepovak Bay 2 Stepovak Bay 1 Alaska 1 Tana Alaska 1 Tanaga Takawangha Alaska 1 Ugashik-Peulik Alaska 1 Ukinrek Maars/Gas Rocks Alaska Cascades 2 Garibaldi Garibaldi Lake Canada 2 West Crater Bare Mtn Trout Ck Hill Washington 2 Belknap Mt Washington Oregon 2 South Sister North Sister Middle Sister Broken Top Oregon 2 Bachelor Tumalo Oregon 2 Mt. Theilson Howlock Mtn Oregon 2 Harvey Mtn Ashhurst Mtn California 2 Crater Mtn Bogard Buttes California 2 Antelope Mtn Logan Mtn California 2 Prospect Peak West Prospect Pk California 3 Ruiz, Nevado del Santa Isabel Colombia 3 Irazu-Turrialba Turrialba Costa Rica 3 Watt, Morne Morne Trois Pitons Morne Plat Pays Dominica 3 Santa Ana Izalco El Salvador 3 Tecapa-El Tigre El Tigre Taburete Usulutan El Salvador 3 San Miguel Chinameca El Salvador 3 Conchagua Conchaguita El Salvador 3 Soufriere Guadeloupe Bouillante Chain France 3 Santa Maria Almolonga Guatemala 3 Atitlan Toliman Guatemala 3 Fuego Acatenango Guatemala 3 Tigre, Isla el Isla Zacate Grande Honduras 3 Iztaccihuatl-Popocatepetl Popocatepetl Papayo) Mexico 3 Orizaba, Pico de Las Cumbres Mexico 3 Pilas, Las Cerro Negro Nicaragua 4 Acamarachi Colachi Chile 4 Descabezado Grande Cerro Azul Chile 4 Las Tres Cruces El Solo Chile-Argentina 5 Yakedake Akandanayama Japan 5 Myokosan Niigata-Yakeyama Japan 5 Kusatsu-Shiranesan Shiga Japan 5 Nantai Omanago Group Japan 5 Hachimantai Akita-Yakeyama Japan 5 Kussharo Mashu Japan 5 Shiretoko-Iozan Rausudake Tenchozan Japan 5 Odamoisan [Tebenkov] Etorofu-Yakeyama Japan - admin by Russia 5 Goriaschaia Sopka Milne Russia 5 Ebeko-Vernadskii Ridge Vernadskii Ridge Russia 5 Barkhatnaya Sopka Unnamed Russia 5 Zhupanovsky Dzenzursky Russia 5 Akademia Nauk Karymksy Russia 5 Komarov Gamchen Vysoky Russia 5 Kamen Klyuchevskoy Bezymianny Russia 6 Geureudong-Telong, Bur ni Bur ni Telong Indonesia 6 Salak Perbakti-Gagak Indonesia 6 Papandayan-Kendang Kendang Indonesia 6 Galunggung-Talagabodas Talagabodas Indonesia 6 Tengger Caldera Semeru Indonesia 6 Guntur Kawah Kamojang Indonesia 6 Poco Leok Ranakah Indonesia 6 Kelimutu Sukaria Caldera Indonesia 6 Soputan-Sempu Sempu Indonesia 6 Lokon-Empung-Mahawu Mahawu Indonesia 6 Ragang Latukan Makaturing Philippines 7 Balbi Tore Papua New Guinea 7 Bagana-Billy Mitchell Billy Mitchell Papua New Guinea 7 Takuan Group Loloru Papua New Guinea 7 Tofua Kao Tonga 8 Nisyros Yli Greece 9 Vulcano Lipari Italy

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