A Comprehensive List of Geothermal Reservoir Properties for the Development of Geothermal Occurrence Models

GRC Transactions, Vol. 37, 2013

Greg Salwen1, Kermit Witherbee2, and Katherine Young2 1State University of New York at Binghamton 2National Renewable Energy Laboratory, Golden, CO, USA.

Keywords and permeability of the reservoir is required for geothermal en- Geothermal occurrence models, structure, OpenEI, geology, ergy production, it is important to be able to accurately capture exploration, dataset the physical characteristics of the reservoirs in developing cost- effective exploration programs. While some geothermal systems are more easily found due ABSTRACT to surface manifestations—such as hot springs, fumaroles, and geysers (Figure 2) — many systems do not develop such features Despite the fact that geothermal occurrence models (GOMs) at the surface. These “blind” geothermal systems require alter- are essential components of early stage exploration, few attempts native methods of discovery. Before drilling or applying other have been made to compile comprehensive lists of data on world- expensive exploration techniques, most exploration geologists wide geothermal resources in order to develop such models. The (e.g., King 2013) consider the development of GOMs to be “[a] properties of these geothermal resources– including the structural setting, geothermal features, tectonic setting, temperature of the reservoir, and host/cap rock characteristics–are being catalogued on OpenEI, a semantic wiki platform for crowdsourced knowledge-sharing. This additional information added to the wiki platform will provide the public with access to an enor- mous amount of geothermal information, the goal of which is to stimulate the development of GOMs and aid in exploration. This paper reviews the significance of the project, the methodologies involved in the classification of resources, and the intended future work.

Introduction Modern geothermal technologies pro- duce electricity from geothermally heated water. Hot water is either flashed to steam or is used to heat liquids with a low boil- ing point to generate gas, which is then directed through large turbines. Next, a generator converts the mechanical energy Figure 1. Geothermal surface manifestations at Yellowstone National Park. Clockwise from top left: of the turbines to electrical energy. Because mudpot, geyser (Old Faithful), hot spring (Grand Prismatic Spring), fumaroles (Roaring Mountain). Photos the combination of high heat flow, water, by: Gregory Salwen, NREL.

321 Salwen, et al. n essential component of early stage exploration” (p. 1). Thus, proceedings. Over 100 productive geothermal fields from 24 a categorization of known geothermal resource areas based on countries were identified and their properties were catalogued tectonic setting, structure, relict geothermal features, and a variety (See Figure 2 for world map of productive geothermal fields). of other parameters would be helpful in developing such GOMs. The data from this study have been stored in OpenEI1 on Prior to this study, Bjornsson and Bodvarsson (1990) and respective Geothermal Area pages under “Technical Info” and Bertani (2005) had compiled what appear to be the most com- “Geology” tabs. The public is free to sign up for an OpenEI ac- prehensive published reference lists on the permeability, porosity, count and then they may add, update, and organize data on any salinity, and temperatures of many geothermal fields. This study page using the “edit” feature. Though this particular study was seeks to expand the data collected to include all worldwide intended to promote the development of GOMs, OpenEI has been geothermal areas and many more of their characteristics. While populated and structured in such a way that the members of the the ultimate goal of this project is to benefit the development of geothermal community may add to the database in the future and GOMs, the list will also provide basic data for the geothermal analyze the data at their discretion. An example of one such pos- community and allow for the analysis and discovery of cor- sible analysis is described in the discussion section and illustrated relations between various hydrological, thermal, and structural in Figure 4. parameters. OpenEI is a semantic media-wiki platform for crowdsourcing Parameters energy information that will host this collection of data. As new research in this area is completed by those in the geothermal com- The chosen parameters collected for this study are reviewed munity, the OpenEI platform allows the latest information to be below. A full list of the parameters used in this study and their added so that the database of information continues to grow. This classifications can be found in the Appendix. paper reviews the significance of the project, the methodologies involved in the classification of resources for this study, and the Tectonic Setting intended future work. One of the most basic and important parameters involved in classifying a geothermal area is its tectonic setting because the Methodology heat source and the permeability of a geothermal system are de- The primary goal of this project is to catalogue data relevant pendent on it. The tectonic framework determines the occurrence to the process of exploration of geothermal resources. Of specific of advective or conductive heat processes as well as the strain interest are patterns in the properties of productive fields, as indus- rates that keep fault/fracture networks open. try could potentially use these patterns to predict the locations of Volcanism is conducive to geothermal systems as it induces undiscovered geothermal systems. As the basis for GOMs, these high heat flow and strain rates. Volcanism is often generated at patterns “describe a set of geophysical, geochemical, tectonic, subduction zones (encompassing about half of all productive structural, and geological features that are associated with a geo- geothermal fields according to this study), areas of rifting, and thermal resource” (King 2013, p. 1). Therefore, the geothermal hot spots. While extensional processes that thin the crust (such data on OpenEI have been organized in a way that promotes the as in the Basin and Range province and Western Turkey) are documentation of parameters relevant to geothermal resource also favorable settings for geothermal production, they typically exploration and the formation of GOMs. Secondary parameters generate geothermal systems of lower enthalpy. Recently, some of potential interest to the geothermal community are documented low-energy systems have been discovered in continental interiors as well (e.g., fluid properties). such as in Australia and Alaska. These systems, classified for this We performed an extensive literature review for this study, study as “non-tectonic,” are thought to have a higher-than-average collecting data from nearly 250 papers, reports, and conference radiogenic input from underlying granites which accounts for the high heat flow. Transtensional zones (e.g., Gulf of California Rift and Walker Lane), rift zones (e.g., the East African Rift), and leaky transform faults (e.g., Azores and Las Tres Virgenes) have been grouped for the purpose of this study into the single category of “transtensional” zones because their extensional processes often lead to the advective transfer of heat from the mantle, which powers geothermal systems. Unlike in “transtensional” zones, the extensional processes occurring in areas like the Basin and Range province and Western Turkey (deemed “extensional” for this study) have geothermal systems typically associated Figure 2. Worldwide map of productive geothermal fields that are the focus of the first stage of catalogu- with conductive heat allowed by crustal ing on OpenEI. Courtesy of ThinkGeoEnergy and Google, Map Data © 2013 MapLink. thinning.

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Structural Classification The structural settings that control the fault/fracture permeability of a reservoir—and thus the flow of hydrothermal fluids—are of particular interest in the exploration phase of geothermal development because without adequate permeability, sufficient fluids for energy production cannot be extracted. Faulds et al. (2011) and Cashman et al. (2012) demonstrated the significance of structural settings in geothermal exploration by showing that the presence of a hydrothermal system is statistically linked to structural settings in various orogenic structural zones. For example, 43% of geothermal systems in central Nevada are hosted in stepovers or relay ramps in normal fault zones, but this structural setting is host to only 8% of geothermal systems found in the Walker Lane Region of the United States (Cashman 2012). Analyses performed using data collected for this study (and posted on OpenEI) would ideally lead to similar conclusions. The structures that accommodate fault/fracture networks have been documented in detail for the U.S. Basin and Range region by Faulds et al. (2011) (see Figure 3). As a part of this study, Fauld’s structural classifications have also been applied to regions outside of the Basin and Range. Structural classifications not previously discussed by Faulds but utilized in this study include intrusion margins and associated fractures, stratigraphic boundaries, fissure swarms, caldera rim margins, and lithographic controls. These structural classifications can also aid in the understanding ofknown geothermal areas—for extrapolation to exploration of unidentified resources—by giving insight as to which underlying structures might be ideal targets. Geothermal Features Geysers, hot springs, fumaroles, and mudpots are all modern features indicative of a geothermal system. Areas that lack these Figure 3. Examples of favorable structural settings for geothermal systems from Faulds (2011). surface manifestations may be blind geothermal systems that were once host to such features, but whose surface conduits have since been obstructed. It is therefore important to search for relict geothermal features during exploration. If sediments at the surface appear opal- ized, argillized, or silicified, this may be evidence of past hydrothermal alteration. Sinter terraces, tufa mounds, sulfur depos- its, and quartz or calcium carbonate veins are indicative of past hydrothermal deposition. The types of hydrothermal alteration or deposition may indicate ancient rates of flow and groundwater chemistry, but the general presence of relict features is important in locating geothermal systems. The classifications of relict geothermal features are thus simplified for this study as either hydrothermal alteration or deposition, each indicating that further exploration techniques should be undertaken. Other Parameters Brophy (2011) has developed a set of general GOMs that have been applied to each operational geothermal area (Table 1) Table 1. Brophy’s geothermal occurrence models from Brophy (2011).

323 Salwen, et al. for this study. Similar models are expected to arise as more similar The total salinity of the fluid produced from a geothermal data are populated on OpenEI, which could benefit geothermal reservoir is important because it may indicate the origin of the exploration. waters, how they are being replenished, and the environment Topography is an important preliminary parameter for through which they pass. Likewise, the age and lithology of the geothermal resource exploration. Studies have found that, for host and cap rocks to the reservoir are documented to give further example, both calderas and horst and graben topography tend insight into reservoir conditions. to host structures favorable to the development of geothermal Finally, each documented geothermal area has its country, systems. Other notable topographic features are the types of state/area, and geothermal region (i.e., orogenic structural zone) volcanoes present and whether the area is mountainous or has indicated. Fields allowing for the input of the general geologic low topography. settings—covering structure and stratigraphy in detail—have The age of volcanism in the area is important to note because also been developed in the geothermal area template for OpenEI. volcanism contributes to the development and preservation of faults and fractures and provides a heat source. It’s assumed that Discussion the more recent the volcanism, the hotter the heat source and the greater the strain keeping the faults and fractures open. Inventories of geothermal system properties are not new The depth of each geothermal resource is documented in order (Bertani 2005) (Bjornsson and Bodvarsson 1990), but for this to see if structural settings or other parameters correlate with the study, we have catalogued many more geothermal systems and depths necessary to drill for fluid production. The temperature of parameters than ever before. While cataloging and providing ac- the water is another parameter likely to correlate with structural cessible data for the development of GOMs remains the ultimate settings or GOMs. The temperature of the water extracted at the goal of the project, the semantic wiki platform will also serve wellhead and the temperature of the reservoir as interpreted from many other purposes. geochemical analyses are documented. Unless the reservoir is Similar to Wikipedia, at the most basic level the data provided predominantly a steam field, it has been classified as non-electrical on OpenEI may serve as a reference point for researchers and grade, very low, low, moderate, high, or ultra-high temperature, industry workers alike. With this data, the geothermal community based on the classification by Sanyal (2005); this classification is free to find correlations between various reservoir properties. system appears to us to be most helpful and relevant to geothermal Where possible, the qualitative data have been reduced from development (see Table 1). lengthy descriptions to simple blocks of information so that it’s

Table 2. Sanyal’s classification of geothermal resources based on temperature from Sanyal (2005). Applicable Reservoir Mobile Fluid Well productivity Power Class of Temp Phase in Production and Controlling Factors Conversion Unusual Development or Resource erature Reservoir Mechanism Fluid State at Wellhead other than temperature Technology Operational Problems 1. Non- Artesian self- Well productivity dependent on reservoir flow electrical < 100°C Liquid water flowing wells; Liquid water Direct Use capacity and static water level Grade pumped wells Pumped wells Typical well capacity 2 to 4 MWe; Liquid water 2. Very dependent on reservoir flow 100°C to (for pumped Low Liquid water capacity and gas content in water; Binary 150°C wells); steam- Temp well productivity often limited by water mixture (for pump capacity self-flowing wells) Typical well capacity 3 to 5 MWe; dependent Pumped wells; on reservoir pressures, reservoir flow capac- Calcite scaling in production self-flowing wells Liquid water (for pumped wells); ity and gas content in water; productivity Binary; Two- 3. Low 150°C to wells and stibnite scaling in Liquid water (only at the higher- steam-water mixture (for self- of pumped wells typically limited by pump stage Flash; Temp 190°C binary plant are occasional temperature end of flowing wells) capacity and pump parasitic power need; Hybrid problems the range) productivity of self-flowing wells strongly dependent on reservoir flow capacity Single-stage Calcite scaling in production 4. Moder- Steam-water mixture (enthalpy Well productivity highly variable (3 to 12 190° to Flash; Two- wells occasional problem; ate Liquid water Self-flowing wells equal to that of saturated liquid at MWe); strongly dependent on reservoir flow 230°C stage Flash; alumino-silicate scale in in- Temp reservoir temperature) capacity Hybrid jection system a rare problem Liquid Steam-water mixture (enthalpy Silica scaling in injection Well productivity highly variable (up to 25 5. High 230°C to water; Liquid- equal to or higher than that of Single-stage system; occasionally corro- Self-flowing wells MWe); dependent on reservoir flow capacity Temp 300°C dominated saturated liquid at reservoir tem- Flash; Hybrid sion; occasionally high NCG and steam saturation two-phase perature); saturated steam content High NCG content; silica Steam- water mixture (enthalpy scaling in injection system; 6. Ultra Liquid- equal to or higher than that of Well productivity extremely variable (up to 50 Single-stage occasionally corrosion; silica High > 300°C dominated Self-flowing wells saturated liquid at reservoir condi- MWe); dependent on reservoir flow capacity Flash scaling potential in produc- Temp two-phase tion); saturated steam; superheated and steam saturation tion wells at lower wellhead steam pressures 240°C 7. Steam (33.5 bar-a Well productivity extremely variable (up to 50 Occasionally high NCG pressure; Steam Self-flowing wells Saturated or superheated steam Direct steam Field 2,800 kJ/kg MWe); dependent on reservoir flow capacity content or corrosion enthalpy)

324 Salwen, et al. easily extractable as data for statistical analyses. For example, the of data on OpenEI. Similar to the work of Faulds et al. (2011) description of structural controls at Chena Hot Springs, Alaska has and Cashman et al. (2012), GOMs applicable in various tectonic been simplified from “the hydrothermal upwelling zone may occur settings and orogenic structural zones would be ideal tools for at a fault zone junction and/or at the hypothetical contact between early geothermal resource exploration and research. Williams et Cretaceous and Tertiary plutons” (Kolker 2007, p.1) to “fault al. (2011) emphasized the importance of communication amongst intersection” and “intrusion margin and associated fractures.” the geothermal community, which could be encouraged through Figure 4 is an example of the correlations that can be drawn regular meetings held amongst experts to decide which parameters from the OpenEI data. The data points are categorized accord- to focus on, how to classify those parameters into simple terms, ing to Brophy’s occurrence models and show that, as expected, and how to define those terms. Though the interests of those in geothermal regions with magmatic input (types B and F) tend the geothermal community vary, we have created a dataset that to have higher geothermal gradients than extensional regions we hope the community finds widely accessible, understandable, (type E). Also, the red line shows the lower bound of most elec- and relevant. trically productive geothermal areas, showing that a temperature gradient of at least 70°C/km is necessary for an electric-grade geothermal resource. Aknowledgements Because OpenEI is a wiki platform, it becomes a living database that allows for future updates. As developments arise and the Funding for this project came from the DOE Office of Sci- literature on geothermal energy expands, members of the geother- ence’s Student Undergraduate Laboratory Internship program. mal community are free to actively update scientific information Thanks to the NREL-SEAC staff and Paul Brophy for the critical (geothermal area parameters, exploration techniques, technolo- reviews of this paper, and to Kendra Palmer for her technical edits. gies, modeling tools, etc.) and permitting, policy, and financing information. These data would serve as a base of knowledge that can be queried and analyzed to create GOMs as well as identify References and characterize potential hydrothermal sites. Bertani, R., 2005. “World geothermal power generation in the period 2001–2005.” Geothermics, v. 34, 6, p. 651-690.

Brophy, P., C.F. Williams, and M.J. Reed, 2011. “Energy Efficiency & Renew- able Energy.” Retrieved from http://www1.eere.energy.gov/geothermal/ pdfs/updating_classification_geothermal_resources_presentation.pdf.

Cashman, P. H., J.E. Faulds, and N.H. Hinz, 2012. “Regional Variations in Structural Controls on Geothermal Systems in the Great Basin.” GRC Transactions, v. 36, p. 1321-1326.

Faulds, J. E., N.H. Hinz, M.F. Coolbaugh, and P.H. Cashman, 2011. “Assess- ment of Favorable Structural Settings of Geothermal Systems in the Great Basin, Western USA.” GRC Transactions, v. 35, p. 777-783.

King, D., and E. Metcalfe, 2013. “Rift Zones as a Case Study for Advancing Geothermal Occurrence Models.” Thirty-Eighth Workshop on Geothermal Reservoir Engineering. Stanford, California.

Kolker, A., R. Newberry, J. Larsen, P. Layer, P., and P. Stepp, 2007. “Geo- logic Setting of the Chena Hot Springs geothermal System, Alaska.” Thirty-Second Workshop on Geothermal Reservoir Engineering. Stanford, California.

Sanyal, S. K., 2005. “Classification of Geothermal Systems - A Possible Figure 4. Example of a correlation derived from data we’ve collected. Scheme.” Thirtieth Workshop on Geothermal Reservoir Engineering. Stanford, California. This graph shows the temperature of the geothermal fluid extracted at the wellhead plotted against the depth that it is being extracted from. The Walker, J. D., A.E. Sabin, J.R. Unruh, J. Combs, and F.C. Monastero, 2005. points are classified according to Brophy’s occurrence models; the red “Development of Genetic Occurrence Models for Geothermal Prospect- line indicates a lower limit correlation of expected geothermal reservoir ing.” GRC Transactions, v. 29. properties; extensional, basaltic rifts, and andesitic volcanic regimes are circled to show general trends. Williams, C. F., M.J. Reed, and A.F. Anderson, 2011. “Updating the Classifi- cation of Geothermal Resources.” Thirty-Sixth Workshop on Geothermal Future Work Reservoir Engineering. Stanford, CA. Potential follow-on work to the current study would involve the development of GOMs based on the continual accumulation 1 http://en.openei.org/wiki/Geothermal_Resource_Areas

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APPENDIX

List of all parameters and classifications on OpenEI-Geothermal. ◦◦ Hot spot • Geothermal Field Name ◦◦ Non-tectonic (i.e., continental interiors) • Country • Age of Volcanism • State/Area • Classification of Structural Controls • Geothermal Region ◦◦ Termination of a major normal fault ◦◦ US ◦◦ Stepover or relay ramp in normal fault zone –– Alaska ◦◦ Accommodation zone –– Cascades ◦◦ Major normal fault –– Central Nevada Seismic Zone ◦◦ Apex/salient of normal fault –– Gulf of California Rift Zone ◦◦ Fault intersection –– Hawaii ◦◦ Displacement transfer zone –– Holocene Magmatic ◦◦ Pull-apart in strike slip fault zone –– Idaho Batholith ◦◦ Intrusion margins and associated fractures –– Northern Basin and Range ◦◦ Stratigraphic boundaries –– Northern Rockies ◦◦ Fissure swarms –– Northwest Basin and Range ◦◦ Caldera rim margins Rio Grande Rift –– ◦◦ Lithographically controlled – San Andreas – • Depth to Productive Reservoir(m) – San Andreas Split – ◦◦ Low value –– Sierra Nevada ◦◦ High value –– Snake River Plain –– Southern Basin and Range • Total Dissolved Solids in Fluid (ppm) –– Southern Colorado Plateau • Host Rock –– Southern Rockies ◦◦ Age –– Transition Zone ◦◦ Lithology –– Walker-Lane Transition Zone • Cap Rock –– Yellowstone Caldera ◦◦ Age • Modern Geothermal Features ◦◦ Lithology ◦◦ Hot springs • Wellhead Temperature of Fluid (°C) ◦◦ Fumaroles ◦◦ Low value ◦◦ Warm or steaming ground ◦◦ High value ◦◦ Mudpots, mudpools, or mud volcanoes ◦◦ Sanyal Classification ◦◦ Geysers • Reservoir Temperature From Geothermometry (°C) ◦◦ Blind geothermal system ◦◦ Low value • Relict Geothermal Features ◦◦ High value ◦◦ Hydrothermally altered minerals ◦◦ Sanyal Classification ◦◦ Hydrothermally deposited minerals • Brophy Occurrence Model • Topographic Expression ◦◦ A- Magma-related, dry steam resources ◦◦ Mountainous ◦◦ B- Andesitic-volcanic resources ◦◦ Horst and graben ◦◦ C- Caldera resources ◦◦ Shield volcano ◦◦ D- Sedimentary hosted, volcanic related resources ◦◦ Lava dome ◦◦ E- Extension, fault-controlled resources ◦◦ Composite volcano ◦◦ F- Oceanic ridge, basaltic resources ◦◦ Cinder cones • Conversion Technology ◦◦ Low topography ◦◦ Dry steam • Tectonic Setting ◦◦ Single flash ◦◦ Extensional ◦◦ Double flash ◦◦ Subduction zone ◦◦ Binary ◦◦ Transtensional/Rift zone ◦◦ Back pressure

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