The URL can be used to link to this page

Home My WebLink AboutUpdated Heat Flow Of Alaska New Insights into the Thermal Regime 2013Updated Heat Flow of Alaska New Insights into the Thermal Regime Final Report to the Alaska Energy Authority and Alaska Center for Energy and Power 6/15/2013 Joseph F. Batir , David D. Blackwell, and Maria C. Richards SMU Geothermal Laboratory Roy M. Huffington Department of Earth Sciences Southern Methodist University Dallas, TX 75275 Contents MADSUEACE.........-..-.0cncecanencnececneconeutetsss 502656555 sset ees aesestsuirsasesecsesuvevecsesiswesasecueaezactsy 2 [rit GUC COM xe cz cs see rees secsececs soaewsmserarcromenececesnecnswnsesesesenses uses Secesteccuraneee 3 ES eK oat nesses ore ns ees cee assesses Sone sneer ae Sasns gence ne eranseeseensereees 4 Generalized Geology of Alaska........... 4 Geothermal Research in Alaska.............. 5 IMGthOdOlOBY............-..---enenenonenotssnsvsstosavesas svosons sossastacensases a Heat Flow Data Collection and Calculation...............0.:ce 7 Gridding Procedure sis: 5:sercrec cecvevens sonscovocarsssessovesesesrorssscysresessisTesseeees 1 Data. Collection ...... cssscsisss senses nesnzssosesorsasessoresoxsvarenerenamsnsronenansercsrsenesessises eel? New Mitnie Data ser cceeeceressesexsacaxcensseowss cor cosnseseucsccsnsersss esses sesgaesnsursacersruseestegesteewseree 12 (Oi Fad Gast EL serene enact eer errr erer senteee seeetersetirersrenetrers 18 ub listiec 1) atc esses eeseesnemetenennsnrtnenersee nent ertisnrtc tcterevererttsnsttrsssest seseetstresrseneneeseseresnceenenees 18 RCS U1] ts Seer ecnee een ne nn ne nen neces ssen tee seeneeesnceeseseeenesesnes 20 (GCS ONS eerereeeeeereetee erent en eee an eeententnen neem ennna erect amnnearttenesrnenseaseeeestecnenmnmnseerennesenencmars 20 TESULCUIT Wy OO Keene nee ne eterna tense nnn eens tctnsesenestnnremerennenentemneemsrsereneraceer=d 2D; PACKMOWICU SEMEN IS: ssssccseesssstccessececectececerarsecncze sincenesescese sususerersecennestsntecessasseateneaseserensesateases 23 REFERENCES), .......-.-cesesececevsnsecnsesencecerecscousnseseesssueonencncencnsorensnsncnnenessst aise inst SUSisS} Ss SUsUsas SSESETE TENTS 23 INDDENGICES oreccccecececerewceesseacecsecacnesesesecaccn escent srseseesastes+srseseesecase;arearaensrnssnenesessencereesasreerered A-1 Appendix A. 2013 Heat Flow Measurements within Alaska.............ccccceceseseseseseseseeeeeeeees A-l Appendix B. Conductivity Values Collected for Heat Flow Calculation ............:.000 B-1 Appendix C. Limitation and Assumptions Related to Sparse Data ............:.:cseeeseeeeees C-1 Appendix D. Regions of Interest for Future Geothermal Energy Exploration................. D-1 Abstract The 2013 update to the Heat Flow Map of Alaska (HFMAK) is described, including the methodology for new data collection, processing and gridding of the heat flow, volcanoes, and hot springs data, and conclusions drawn from the expanded dataset. The previous version of the Heat Flow Map of Alaska was published in 2004 with the Geothermal Map of North America by the Southern Methodist University Geothermal Laboratory. This map represents heat flow, which is only one of the three necessary parts of a geothermal system. This map should be considered a reconnaissance study to guide future preliminary research. The 2004 map had sparse data primarily located on the North Slope and in selective areas known to have anomalously high heat flow. This sampling bias towards higher heat flow produced a high heat flow band over much of Alaska that led to faulty interpretations. Between 2004 and 2007, research was focused on specific locations, such as Chena Hot Springs, to assess site specific geothermal potential. For this report, 91 new sites were reviewed, of which 55 were considered of high enough confidence to be included in this version of the HEMAK. AII 55 new points were collected during the summer of 2011 and 2012. Of these 55 new points, 45 are based on hydrocarbon exploration Bottom Hole Temperature (BHT) data, two were published data, five were based on data from mineral exploration sites, and three were published temperature data that could be used to calculate heat flow values. Results from this edition of the HFMAK suggest heat flow throughout Alaska is locally variable. While a general trend of high heat flow is represented, the heat flow is not definitively assessed outside the areas of the calculated sites. A geologic region that illustrates this point using the new map is the Aleutian Volcanic Arc. A priori knowledge suggested the entire Alaska Peninsula to have high heat flow and be viable for geothermal power generation. The new data show variable heat flow ranging from high values above 120 mW/m* to values below 40 mW/m’. This variability indicates that the geothermal energy potential throughout the Alaska Peninsula is not uniform and emphasizes the natural heterogeneity of heat flow, compounded by the complex geology of Alaska. Interior Alaska is one section shown to have more variation than shown previously. New data collected between the Alaska Range and the Brooks Range vary between 61 mW/m? and 106 mW/m?. This range of heat flow is similar to the Basin and Range Provence in the conterminous United States, suggesting that geothermal systems within interior Alaska would be heterogeneously located analogous to the Basin and Range Provence. More data need to be collected in specific areas of interest for site specific geothermal energy viability to be assessed. For this to occur, wide-spread data collection through collaboration with industry and federal and state groups should be a continual process to further define the areas for most productive exploration for geothermal resources within Alaska. Introduction This report describes the 2013 update to the Heat Flow Map of Alaska (HFMAK), including the methodology for new data collection, processing and gridding of data, and conclusions drawn from the expanded dataset. The previous version of the Heat Flow Map of Alaska was published in 2004 with the Geothermal Map of North America by the Southern Methodist University Geothermal Laboratory (Figure 1). The 2004 map, however, had sparse data; the available data were primarily located on the North Slope and in selective areas known to have anomalously high heat flow. This sampling bias towards higher heat flow produced a high heat flow band over much of Alaska that supported the back-arc heat flow theory suggested for interior Alaska. Between 2004 and 2007 research was focused on specific locations, such as Chena Hot Springs, to assess site specific geothermal potential. For this report, 91 new sites were reviewed, of which 55 met the criteria to be included in this version of the HFMAK. AII 55 new points were collected during the summer of 2011 and 2012. Of these 55 new points, 45 are based on hydrocarbon exploration Bottom Hole Temperature (BHT) data, two were heat flow values, five were data from mineral exploration sites, and three were published temperature data that were used to calculate heat flow. Volcanoes, hot springs, and earthquake locations were overlaid on the map to assist in geologically constraining the heat flow contouring. Appendix A lists all map data including previously published heat flow values and new heat flow data with assigned quality that aided in contouring of the new map, as well as volcanoes and hot springs. Surface heat flow is one of the required data to determine the favorability of a site for geothermal energy production, but it is not all that is required. What is required for energy production is heat in place, fluid to move the heat, and pathways to move the fluid to the surface. Heat flow can be used to determine the amount of heat in place that can be extracted from the Earth, but does not give a good indication of presence of fluid or pathways to move the fluid for a given location. When these additional factors are taken into account, the heat flow map can be considered a favorability map for geothermal system potential: areas with a higher heat flow are suggested to have the heat in place and therefore have better potential to host a geothermal system as opposed to areas of lower heat flow. Springs « Hot % Warm 75 Heat Flow (#W/m*) Pleistocene and Holocene Volcano A Geothermal Area Wells. + yi Es | H Land Heat Flow + (data averaged .06°) 9 10-74 75-79 80-84 Ocean Heat Flow (W/m?) 20-29 90-39 40-49 + 0 . 50-59 60-69 70-79 os ne % 80-89 90-99 100-119 * . 120-149 150+ oO & = = ’ N ‘ 150 AAS 10 o S 12 0 . o SMU Geothermal Map of Alaska, 2004 ' Figure 1. 2004 Heat Flow Map of Alaska. Data on land are labeled with diamonds. Note that data within Alaska are focused on the North Slope, with low data density elsewhere to constrain the contouring of heat flow through the interior part of the state (Blackwell and Richards, 2004). Background Generalized Geology of Alaska The geology of Alaska is complex and challenging because of an intricate history of extension, subduction, deformation, sediment deposition, and volcanism. The geologic history, therefore, is typically differentiated into composite terranes that may or may not be related with respect to the depositional/deformational episode(s) during which each terrane was formed (Plafker and Berg, 1994). For new heat flow sites, the geology was simplified into volcanic and non-volcanic localities where lithology logs and/or thermal conductivity measurements were unavailable. Volcanic localities are classed as areas associated with recent volcanism. Recent volcanism implies a significant amount of volcanic glass is within the upper portion of any stratigraphic section. Volcanic glass has a lower thermal conductivity because glass is amorphous. The volcanic glass undergoes devitrification once it is buried and reaches sufficient temperatures for an extended period of time. The Alaska Peninsula is classified as a volcanic locality for the purposes of this study because it is formed by Quaternary mafic volcanism (Plafker and 4 Berg, 1994). This mafic volcanism has only a minor quartz component that is believed to still be glass, which will lower the thermal conductivity of the subsurface section. Sections composed of predominantly recent mafic volcanism need to be treated differently compared to localities without a recent volcanism fill component. Non-volcanic localities are defined as areas where there is a significant source of sediment that does not include major contributions of mafic volcanism. Data were collected within the Copper River Basin and the Gulf of Alaska Basin and sporadic exploration wells in interior basins. The Western Copper River Basin has large sections of lacustrine sediments from the last glacial maximum while the rest of the Copper River Basin has interbedded marine sediments and volcanic assemblages; likewise, the Gulf of Alaska Basin is located off shore on the Yakutat terrane and is predominantly marine sediments (Nokleberg et al., 1994; Hamilton, 1994; Williams and Galloway, 1986; Mendenhall, 1905; Magoon III, 1994). Stratigraphic sections of sediment are fundamentally different than stratigraphic sections dominated by mafic volcanism. Large sections of sediment compared to basaltic volcanic rocks will introduce more quartz and increase the thermal conductivity of the units. The Copper River Basin abuts the Wrangell Mountains, but is still considered a non-volcanic terrane because the Wrangell Mountains are predominantly felsic volcanism, meaning they have more quartz than other volcanoes such as those in the Alaska Peninsula (Plafker and Berg, 1994). Geothermal Research in Alaska The majority of geothermal research in Alaska took place during the early 1970s and 1980s supported by federal funding (Miller, 1994). Prior to 1970, geothermal resources were identified by surface manifestations; the more recent studies started to include state and regional summaries of resources based on geological, geophysical and geochemical investigations. The complicated geologic history of Alaska has kept in-depth research site specific, attempting to explain geothermal resources individually without a greater understanding of any regional correlation. The geothermal areas in Alaska, as currently characterized, can be divided into four different sections: the Central Alaskan Hot Spring Belt (CAHSB), the Aleutian Volcanic Arc, the Wrangell Mountains, and the Southeastern Panhandle (Kolker, 2008). Within these four areas, there are many known resources based on surface manifestations; however, the quality and extent of each resource has generally not been defined. Figure 2 shows the known geothermal areas and potential geothermal projects (Kolker, 2007). Land Ownership <7 oh a LEGEND ‘ : = BLM or other Federal State Native Se «U.S. Forest Service \ Geographic Symbols . Citie Space heating sites ssorts/Recreation Sites Regions of Known/Potential Geothermal Resource . Wells > 50°C e Springs > 50°C . Wells > 20 and < 50°C . Springs > 20 and < 50°C Makushin= a ay : Ne ang ee, i a os SS ——— —— ea tee ee} Figure 2. Geologic Map of Alaska with known geothermal areas shaded in red. Previously proposed geothermal projects are labeled with large red dots. Labeling for the different geothermal regional areas are as follows: CAHSB = Central Alaskan Hot Spring Belt, AVA = Aleutian Volcanic Arc, WM = Wrangell Mountains, SEP = Southeastern Panhandle (Modified after Kolker, 2007). There are site specific theories for each geothermal resource. For example, Chena Hot Springs is heated by radioactive elements in an igneous pluton, enhanced by fracture dominated fluid flow (Erkan et al., 2008; Kolker, 2008). Whereas, Pilgrim Hot Springs has deep seated faulting controlling the hot aquifer outflow at a shallow depth (Stefano, 1974; Forbes et al., 1979; Miller et al., 2013). The most extensive analysis of geothermal areas in Alaska was completed by Amanda Kolker (2008). Reservoir temperatures for selective hot springs within the CAHSB were calculated using geothermometry, but temperatures did not follow an interpretable trend; Kolker explained the reservoir temperatures using radiogenic heat of plutonic bodies (Miller et al., 1974; Kolker, 2008). Others had postulated that plutonic bodies go through cycles of heat release that create warmer cycles and cooler phases (Durrance, 1985). Kolker used this method to explain the variable reservoir temperatures across the CAHSB. While her investigation supported this theory as plausible, Kolker (2008) emphasized that the low data density yielded a poorly constrained model. Currently, the only operational geothermal power plant in Alaska is the Chena Hot Springs power plant, which began producing electricity in 2006. Exploration has been completed in other areas of known geothermal resources along the Aleutian Island Arc (Unalaska, Adak, Atka, and Akutan islands), Pilgrim Hot Springs, Manley Hot Springs, and Mount Spurr (Kolker, 2012; Erkan et al., 2008; Martini et al., 2011). Research has focused on locations with surface manifestations. It is difficult to determine the geothermal potential outside of these areas. Many Alaskan localities have geothermal resources, but not enough research has been completed to quantify the quality and quantity of these resources. The Geothermal Map of North America is considered an initial regional scale theoretical resource evaluation in many areas because no geothermal specific data are located in those regions (Blackwell et al., 1991; Blackwell and Richards, 2004). Methodology Heat Flow Data Collection and Calculation The Heat Flow Map of Alaska illustrates the amount of heat flowing from the Earth’s interior to the atmosphere. To calculate a heat flow value, the heat diffusion equation is simplified to the vertical component, equal to the geothermal gradient of a rock formation multiplied by the formation’s thermal conductivity, as shown in equation 1. aT = eek (1) Where Q= heat flow, mW/m? o geothermal gradient, °C/km k= thermal conductivity, W/m*K Geothermal Gradient, dT/dz The geothermal gradient is the rate of change in temperature with respect to depth within the Earth. Temperature measurements are collected from well bores, varying in size from the narrow (~2”) diameter mineral exploration wells to the larger diameter oil and gas industry wells. The most accurate source of a thermal gradient is from an equilibrium temperature log (ETL). An ETL is a temperature log collected within a well that is at equilibrium with the surrounding rock after the thermal effects of drilling have dissipated. The depth intervals with a conductive gradient (an example using the data collected for the 2013 HFMAK is shown in Figure 5) are the sections that represent the background geothermal gradient of the formation because conduction is the primary method of heat transfer within the crust. Gradients are calculated for these conductive sections of the ETL and used in the heat flow calculation. A well must be at equilibrium with the surrounding subsurface before the temperature measured will be representative of temperatures within the subsurface geology to give a background gradient. Even when a temperature log is at equilibrium with the surrounding rock, the background geothermal gradient may be masked because of fluid flowing within the formation(s), thermal refraction, and/or topographic effects. These are the most common disturbances seen in ETLs. Fluid flowing near or along a well will transfer the fluid’s temperatures either horizontally or vertically leading to an erroneous apparent geothermal gradient. Ideal ETL measurements are collected deeper than 100 m to remove seasonal climatic effects and include at least 100 m of conductive gradient, although a shorter gradient section can be used to calculate a heat flow measurement in some cases. Temperature logs collected between 2010 and 2012 were found to have no major fluid flow disturbances. Thermal refraction is distortion of the heat flow pattern in the Earth because of extreme lateral thermal conductivity variations. Correction requires numerical modeling of the geometry of the thermal conductivity pattern. No corrections of this type were made as the geological data in general are not detailed enough, or the probable corrections are small enough, to make the correction significant. Topographic effects cause higher geothermal gradients beneath the valleys and lower gradients beneath the ridges than typical background values. The topographic effect on temperature disturbs the gradient to a depth roughly equal to the total topographic relief from the ridge of the mountains to the lowest point in the valley for a ridge-valley topographic profile (Blackwell et al., 1980). A topographic correction has been applied for data points in this study where the correction is determined to be significant. Those wells identified for topographic effect correction had changes in geothermal gradient totaling less than 3%, so a conservative estimate of error for wells not corrected for topography would be <3%. Not all temperature log measurements are at equilibrium with the surrounding rock; therefore, understanding temperature log disturbances is necessary to collect reliable data. Several types of disturbances skew a temperature log, the two most common are: 1) any systematic climatic effect, and 2) drilling effects. Climatic effects disturb the upper most portion of a well. This fluctuation does not represent the true thermal gradient of the rock and must be discarded for heat flow calculations. The depth of the climatic effect varies; however, data would suggest this effect can be as deep as 80-100 m in Alaska (Lachenbruch and Marshall, 1969; this study). For this reason, measurements shallower than 100 m are less reliable. Drilling will also cause the temperature near a well to deviate from the true gradient by injecting fluids through the well during drilling for lubrication and cooling of the drill bit. The time required for a well to return to equilibrium is determined by the thermal conductivity and thermal diffusivity, length of time drilling took place, and the diameter of the well (Carslaw and Jaeger, 1959). Mineral exploration wells are diamond core drilled with two inch diameters or less. Studies with conditions similar to wells examined in this study show that the time required for narrow wells to reach equilibrium is less than in the case of oil and gas wells. A conservative estimate of time required to return to equilibrium is a period equal to the drilling time (Jaeger, 1961; Lee and Han, 2001). The time between drilling and temperature measurement is often not known, but when known, it was taken into account for calculating equilibrium temperature. If an Equilibrium Temperature Log (ETL) was not available, Bottom Hole Temperature (BHT) or Logging While Drilling (LWD) measurements were utilized for gradient calculations. An average gradient is calculated from the mean annual surface temperature to the BHT measurement. A mean annual surface temperature of 0 °C was used for all BHT sites because of the low resolution of available surface temperature data. The 0 °C value is within +20% of the maximum/minimum possible value, based on the mean annual surface temperature map (National Climatic Data Center, 2011). This 0 °C surface temperature assumption is not applicable on the North Slope; however, no BHT data were collected along the North Slope. BHT data are typically from oil and gas drilling, therefore are the recorded temperature at the bottom of the current well interval drilled. BHTs are disturbed by the drilling procedure and typically underestimate the equilibrium temperature, however, if the bottom of a given interval is less than the surface temperature, than the drilling fluid will heat the surrounding rock. Several different empirical temperature corrections have been developed to correct for this disturbance when using oil and gas industry BHT (Lachenbruch and Brewer, 1959; Forster et al., 1998; Harrison et al., 1983). The SMU Geothermal Laboratory determined that the Harrison correction yields the most consistent results when applied broadly to oil and gas wells deeper than 600 m where there is no basin-specific BHT correction for drilling disturbances (Blackwell et al., 2011). Data from smaller mineral exploration holes were left uncorrected. Lee and Han (2001) supported the theory that the smaller the hole, the quicker thermal equilibrium is reached, which implies applying a correction intended for large diameter oil and gas wells to the smaller diameter wells used for mineral exploration would overestimate the equilibrium temperature (Carslaw and Jaeger, 1959). Instead, mineral exploration well temperatures were conservatively estimated to be at equilibrium with an error of 10%. When applying a correction to BHT data, if there is not an ETL in the vicinity to test the accuracy of the correction applied, the quality of the data cannot be assessed in a clear way. Empirical evidence shows that BHT measurements are typically within +20% of equilibrium temperatures. This means the minimum error a BHT derived heat flow may receive by itself is +20% of the calculated heat flow (Blackwell et al., 2011). Similar to BHT measurements, LWD is a process of collecting down-hole logs during the drilling process. Some deviation measurement tools have temperature probes, which are the primary source of LWD temperature data from the mining industry. Like BHT, while these data are disturbed and generally underestimate equilibrium temperature, it was hypothesized that the thermal gradient would still be evident if the temperature disturbances were equal at the respective depths when the measurements took place. However, in this project the LWD did not provide interpretable data, and therefore LWD measurements were treated as ‘uncorrected’ BHT as described above. Thermal Conductivity, k After determining thermal gradient, the thermal conductivity of the rock layers is required to calculate the heat flow. The thermal conductivity of a rock is the rate at which heat will conduct through the rock, and varies by rock type. There are several types of devices for measuring thermal conductivity of rock samples. The devices used in the Southern Methodist University Geothermal Laboratory are a divided-bar thermal conductivity measurement apparatus and a needle probe measurement device, both shown in Figure 3. The divided bar apparatus uses a cold bath (15 °C) and a hot bath (25 °C) to create a temperature gradient within the sample. The amount of heat that travels across the sample is measured when the sample has reached steady state, and the heat flux can then be used to calculate the thermal conductivity of the rock sample relative to a standard with a known thermal conductivity value (quartz and silica glass). Samples were run for 30 minutes, which was found to be a sufficient length of time for all samples analyzed in this study to reach steady state. The needle probe is similar to the divided-bar apparatus in that it sends heat into a rock sample and measures the rate at which heat travels through the rock. It is a transient method, however. Needle probe samples were run for 4 minutes and approximately the middle 2 minutes of the temperature curve is used to represent the average rate at which heat traveled into the rock sample (Sass et al., 1984; Blackwell and Spafford, 1987). This rate is compared to standard samples to calculate an absolute thermal conductivity. To have an accurate heat flow calculation, a thermal conductivity needs to be measured for the well site where the temperature gradient was collected. This requires rock samples from the depth intervals where the temperature log shows a conductive thermal gradient that represents the regional gradient. The rock samples used in the divided-bar were prepared as cylinders as similar in size to the SMU Geothermal Laboratory standards as possible. Sample sizes varied from 1.110 to 1.120 inches in diameter and 0.531 to 1.573 inches in height. The ideal raw material is full core, but conductivity can also be measured from half core or cuttings (Goss and Combs, 1976; Blackwell and Spafford, 1987). An example of half core used with the needle probe and a thermal conductivity sample for the divided-bar apparatus is shown in Figure 4. Cuttings were not used to calculate any thermal conductivities for this report and will not be discussed further, but a detailed description of the process can be found in Beardsmore and Cull (2001). All new conductivity measurements collected for this study are listed in Appendix B. In some cases, rock samples are not available and a lithology model combined with published thermal conductivity values are used to estimate thermal conductivity. A lithology model is needed to determine what rock types are encountered in the section of a temperature log used for the thermal gradient. The ideal lithology model for a heat flow site would be a detailed lithology log from the well being examined. When unavailable, a basin or regional cross-sectional model was used; if even this information was not accessible, a basic rock type based on the general geology of the region was used to determine thermal conductivity. Thermal conductivity values to match the lithology model worked in a similar manner, using measured values of samples from the well when possible, next searching for published values in the vicinity of the well site and finally, if not in the vicinity, then use of a published value for rocks with similar characteristics including age, porosity, composition and chemistry. If an analogous rock could not be found, thermal conductivity values for sedimentary rocks from a study in the Anadarko Basin in Oklahoma (Gallardo and Blackwell, 1999) were used and modified for permafrost within the pore space where applicable. 10 Figure 3. (A) The divided-bar thermal conductivity measurement apparatus. Samples are placed in between the press where the wooden blocks are located in the picture. (B) The needle probe measuring device. Most often the needle probe would be inserted into the material, however, the tool shown here has an insulating surface glued to one side (with a piece of wood on top) so that the needle probe will send heat into the rock alone. The needle probe has a heater wire running the length of the white insulating foam at the base of the black line; the tan half cylinder under the foam is a half core rock sample. Figure 4. Different types of rock samples left is a piece of half core, right, a thermal conductivity cylinder sample. Thermal conductivity can be measured on half core samples using the needle probe; alternatively half cores can be turned into cylinder samples for the divided-bar device. Conductivity cylinders for the divided-bar apparatus are drilled out of larger rock samples from wells in close proximity to temperature data. Cuttings samples are not shown here and were not used to calculate conductivity for any samples discussed in this report. Gridding Procedure When contouring the 2013 HFMAK, the first step is for the program to generate a grid based on the available data. The next step is to adjust the contours in consideration of the regional geology in areas of no or inadequate site heat flow control. That is, the contouring is complimentary to geologic features. For example, the Denali fault is a large tectonic feature 11 running through Alaska that acts as a boundary between the Alaska Range and Coastal Alaska. A geologic feature of this magnitude might act as a thermal boundary similar to other fault systems such as the San Andres fault in California (Blackwell et al., 1991; Morgan and Gosnold, 1989). Data were contoured using the Kriging method with a search ellipse elongated in a longitudinal direction, thus mimicking the same directional trend seen in the orientation of Alaska’s geologic features. In areas without well data, locations with high concentrations of surface geothermal manifestations were assigned heat flow values for gridding purposes. Young volcanoes and hot springs were given a variable heat flow value (74-100 mW/m_”) in relation to proximity to other surface manifestations and heat flow measurements. These known geothermal manifestations and the collected data points were used to generate the initial contour map. Control points were added to force contours to follow geologic trends such as the Denali fault. The map was smoothed to reduce the effect of single data point anomalies. In order to emphasize locations with collected heat flow data versus assigned values based on geologic constraints, the 2013 HFMAK has a two layer color density scheme. Bold colored areas are locations supported by data whereas lighter colored zones are contoured to follow geologic trends. A full list of assumptions and limitations to gridding of the sparse data within Alaska is discussed in Appendix C. Data Collection New Mine Data Since 2007, a combination of rock samples and/or temperature logs were collected from 8 mineral exploration locations in Alaska for heat flow measurements, 5 of which were included in the gridding for the 2013 HFMAK. All of these sites are currently operating mines or mining exploration sites. Sites include the Red Dog Mine, Pebble Prospect, Donlin Creek, Whistler Project, Palmer Project, Usibelli Coal Mine, Ft. Knox Gold Mine, and True North Mine. Donlin Creek is the only new data point with both ETLs and thermal conductivity measurements for the highest accuracy of heat flow calculation. Each of these data points are discussed below, followed by a description of the additional data examined, including oil and gas industry BHT data and published data. Red Dog Mine The Red Dog Mine (RDM), owned by Teck Alaska, Inc., supplied temperature measurements collected between 1995 and 2006 and lithology logs from nine different water quality monitoring wells. Two of the nine wells are sufficiently deep that gradients from the bottom sections (below 80 m) can be used for heat flow calculation. Well T-96-013 has an average gradient of 16.6 °C/km after a correction for topography, and Well T-96-012 has an average gradient of 20.5 °C/km. No rock samples were available from the RDM. Instead, thermal conductivity for the major rock sections were given values from Gallardo and Blackwell (1999) and then adjusted for the presence of permafrost at this site. This process produced an average conductivity of 1.88 +.08 and 2.40 +.04 W/m*K, and an average heat flow values of 31.3 and 49.2 mW/m* for T-96-013 and T-96-012, respectively. Neither point 12 could be determined as more reliable than the other, so an average of the two points was used for the RDM site heat flow of 40.2 + 9.0 mW/m’. Figure 5 shows the temperature curves with the gradient sections used for heat flow calculation highlighted in yellow. Temperature, °C -2 -1.5 -1 -0.5 0 0.5 al 20 40 ——T-96-012 ——T-96-013 120 140 160 Figure 5. Temperature versus depth curves at the Red Dog Mine. For each well, the interval highlighted in yellow is the conductive gradient section, below the climatic effects, used for the heat flow calculation. 13 Pebble Prospect The Pebble Prospect, managed by The Pebble Limited Partnership (PLP) provided BHTs for all wells drilled on the property. This data set gives a wide spread of temperature across all depths that are examined collectively for an average gradient for the entire site. This plot is shown in Figure 6. To improve accuracy, only data from deeper than 1000 m were used. No BHT correction was applied to the data because holes drilled were small diameter core holes. This method produced an average gradient of 27.8 °C/km. An average thermal conductivity was calculated from 1000 m to the depth of the deepest data point (over 1,800 m) to match the section used for gradient calculation. Rocks encountered within this depth were a mixture of volcanic rocks, greywacke, sandstone, conglomerate, and sandstone. Thermal conductivity of 2.5+.5 W/m*K was used for the section because the site resembles a non- volcanic locality outlined earlier. The heat flow for the Pebble Prospect was calculated to be 69.5 + 13.9 mW/m”. Temperature, °C 0 10 20 30 40 50 60 200 400 600 800 m 1000 Depth 1200 1400 1600 1800 2000 Figure 6. BHT data plotted versus depth at the Pebble Prospect. No equilibrium temperature logs were available for the prospect site, but enough BHT points were available to estimate a background thermal gradient (27.8 °C/km), represented by the black line. 14 Donlin Creek The Donlin Creek site, managed by Donlin Gold, LLC., was visited in the summer of 2011 when Equilibrium Temperature Logs (ETL) were collected from 3 wells. From 3 neighboring wells, 22 rock samples were collected from which a site average thermal conductivity of 3.64 +.52 W/m*K. Each well had sections of 50 m or more where both gradient and rock thermal conductivity were collected to calculate well specific heat flow intervals. Heat flow measurements for MW05-22, MW05-23, and MW07-11 are 106.1, 99.2, and 76.6 mW/m”, respectively. Because no one site appeared better than the others, the three heat flow values were averaged for a site heat flow of 94.0 +12.4 mW/m?. Figure 7 displays the temperature curves for each well with the sections used for the gradient calculation highlighted. Gradients and average thermal conductivity for each well site is displayed in Appendix A. This new data point has higher confidence than the rest of new data added because the Donlin Creek site was the only location with ETLs and many thermal conductivity samples. Temperature, °C 0 2 4 6 8 10 20 40 60 80 ——MWw07-11 —— MWO0S5-23 £ € 100 ——Mw05-22 uv a 160 180 200 Figure 7. Temperature versus depth curves for the Donlin Creek site. Thermal gradient sections used for heat flow calculation are highlighted in yellow. 15 Whistler Project The Whistler Project, owned by Kiska Metals Corporation (KMC), was visited in 2011 to collect rock samples for thermal conductivity measurement to match Logging While Drilling (LWD) data provided by KMC. Individual LWD well temperatures within the Whistler Project area are too variable and therefore unreliable for heat flow calculation. Thus, all temperature data from the Whistler Project site were plotted to determine an average gradient to match with an average conductivity calculated for the whole depth section analyzed. These data, plotted in Figure 8A, have at least three possible gradients. There is insufficient evidence to determine which of these trends represent the correct background gradient; consequently, data were treated as BHTs and gradients calculated from individual points deeper than 500 m (Figure 8B). This depth was chosen based on diminished data scatter, and because deeper data are less affected by drilling disturbances. Two possible trends are highlighted, one by the green triangle, and one by two yellow lines. The green triangle is what is expected to occur, gradient spread decreasing with depth to an average gradient, whereas the two yellow lines, which highlight linear trends in the data, show decreasing gradient with depth. This decreasing gradient trend is not fully understood at this point, but is discussed further in the conclusions. The green triangle interpretation was taken as the average gradient of 25 °C/km. The 25 °C/km is more reasonable because geothermal gradient is not expected to drop so quickly with depth; however, the gradient was still assigned an error of 10% because it is based on disturbed temperature measurements. This was multiplied by the average measured conductivity of 2.82 +.57 W/m*k from 10 rock samples to arrive at a site heat flow of 70.6 +15.7 mW/m?. This data point has a low confidence because of the potential error associated with the temperature measurements. Temperature, °C Gradient, °C/km 0 10 20 30 10 20 30 40 0 500 ~ 100 550 200 600 300 650 £ 400 € 700 = oa 2 500 3 750 ov oe Q 600 Q 800 700 850, _-_-____—____ | Sd 800 | 900 A 900 B 950 1000) ae 1000 Figure 8. (A) Logging While Drilling (LWD) measurements at well sites on the Whistler Project site. One major geothermal gradient is visible, emphasized by the green shaded polygon, whereas two minor gradient trends are demonstrated by the brown and black lines. (B) The gradient for data points below 500 m was plotted in an attempt to constrain the background gradient, as if they were BHT values. Points below 500 m give two possibilities of gradient with depth, shown by the yellow lines and the green shaded triangle. Linear trends highlighted by the yellow lines show a drop in gradient with depth, while the green triangle shows a narrowing of gradient towards 25 °C/km with depth if several points are considered erroneous. 16 Palmer Project The Palmer Project, owned by Constantine Metal Resources, Ltd., was visited in 2011 to collect rock samples and LWD data. Wells were first plotted separately as with ETLs, however, individual well data proved too sporadic to interpret. Next, temperature data for all of the wells were plotted together as BHT data to determine if a general trend emerged for the region. This approach was also unsuccessful because there were only 36 holes, with a focus depth of less than 600 m. The combination of shallow exploration depths with few holes made it hard for any single trend to be identified. Gradient versus depth of measurement was also plotted to see if a trend would indicate a reasonable estimate of average gradient. This plot, shown in figure 9, displayed the same unexpected gradient drop with depth as the Whistler Project. End members were removed and gradients associated with each exploration hole were averaged together for a site geothermal gradient of 23.5 °C/km. This average gradient combined with the average thermal conductivity of 3.44 +.55 W/m*K from the area resulted in a calculated heat flow of 80.9 +16.2 mW/m*. One conductivity measurement was not included in the average thermal conductivity because it was suspected to have a measurement error. All thermal conductivity measurements are displayed in Appendix B. Like Whistler, the Palmer Project heat flow point also has low confidence because of the trend of decreasing gradient with depth. Gradient, C/km 0 5 10 15 20 25 30 35 40 100 200 % Depth, m > w 8 8 > a *? oe Sd * ie Sd 500 600 . a 700 Figure 9. Gradient versus depth measurements for the Palmer Project. There is a wide spread in gradients calculated from this site, so all except outliers were used to calculate the average gradient of 23.5 °C/km. Usibelli Coal Mine The Usibelli Coal Mine, Inc. provided access to several water quality monitoring wells in 2011, only one was deep enough to consider for heat flow at a total depth of 65 m. This 17 depth was not deep enough to reach temperatures unaffected by the seasonal climatic effect, and thus this location was not used in the gridding process. Ft. Knox Gold Mine The Ft. Knox Gold Mine, owned by Kinross Gold Corporation, had temperature data collected in 2007 by SMU graduate student Patrick Stepp. Five wells were logged in the area of the mine pit. Rock samples were collected but thermal conductivity measurements were not possible, therefore, only gradient values are currently available. True North Gold Mine The True North Gold Mine, owned by Kinross Gold Corporation, also had temperature data collected in 2007. Three wells were logged on the mine property. Rock samples were collected but thermal conductivity measurements were not possible, therefore, only gradient values are currently available. Oil and Gas BHT BHTs have been shown to be a valuable resource for calculating heat flow when in large quantities over small areas (Blackwell et al., 2011). Areas where hydrocarbon exploration has taken place in Alaska were examined for BHT data as an additional resource for mapping. Most of the BHT data were collected with assistance from the Alaska Oil and Gas Conservation Commission (AOGCC) in the summer of 2012. Wells are located sporadically across the interior of Alaska, with the majority of wells examined located along the Alaska Peninsula, in the Copper River Basin, and in the Gulf of Alaska Basin. Wells within the Cook Inlet Basin were not examined because of an on-going study examining temperature by the AOGCC. Wells along the North Slope were not considered because of the conventional heat flow measurements there (Lachenbruch et al., 1982; Deming et al., 1996). 78 wells outside of the Cook Inlet and North Slope were analyzed for usable BHT with 47 wells being used for contouring purposes and given a quality ranking of BHT-C following the procedure by Blackwell et al. (2011). 5 wells were given BHT-D quality rankings and not used for contouring. 26 wells were missing data and heat flow could not be estimated. The wells that were given a quality rating of BHT-D are still reported within the database and plotted on the map (if there is location information) and can be reexamined during future research. A full explanation of quality rankings can be found in Appendix A. If any wells had multiple BHT, heat flow was calculated for each BHT and then averaged for gridding purposes. Average thermal conductivity values of either 2 or 2.5 W/m*K were assigned to each well based on the well’s (non)volcanic locality. Any wells located along the Alaska Peninsula were given a thermal conductivity of 2 W/m*K, while all other wells were given 2.5 W/m*K. This procedure explained earlier was driven by the presence of recent volcanism in the Alaska Peninsula, while the other locations were lacking recent volcanism and any volcanic rocks would have likely devitrified by this time through burial. The 52 of the original 78 wells that were assigned quality rankings are reported in Appendix A. Published Data Three data points have been published since the compilation of the Heat Flow Map of Alaska in 2004 and two data points have been rediscovered in the literature. Two offshore points 18 plotted and used for gridding are the COST #1 in the Bristol Bay Basin and the Yakutat #1 in the Gulf of Alaska (Bergman et al., 2008; Bergman et al., 1993). COST #1 and Yakutat #1 have reported heat flows of 56 and 54.4 mW/m”, respectively. These points provided constraints for offshore gridding that affected the understanding of how quickly heat flow decreases away from land based on oceanic plate age. They also support the calculated heat flow from BHT points that were collected for this study. The on-shore published data included on the map are based on temperature data from the Naknek well G #1 (Vukich and Friedmann, 2011). The temperature curves published for G#1 give two different gradient estimates, one at the top of the well (49.1 °C/km) and one towards the bottom of the well (38.2 °C/km). The top section was used for heat flow calculation because it is a longer section and thus presumed to be more reliable. A value of 1.5 +0.5 W/m*K was used for the thermal conductivity because the top section of the well is a mixture of volcanic rocks, which likely have lower thermal conductivity values due to the relative lack of quartz. The calculated heat flow for G #1 is 73.6 +14.8 mW/m?. Geothermal gradients were published for the Lower Cook Inlet COST #1 (COST 1-CI) well, and the Swanson River Oil Field (SWANSON) by Leslie Magoon (1986). The gradient published for COST 1-Cl was 22.8 °C/km, and 23.7 °C/km for SWANSON. These holes were determined to be in a non- volcanic locality, therefore, a thermal conductivity of 2.5 +0.5 W/m*K was used to calculate heat flows. The COST 1-CI site had a calculated heat flow of 57 +11.4 mW/m’, and 59 +11.9 mW/m’ for the SWANSON data site. 19 Results The 2013 Heat Flow Map of Alaska (HFMAK) is show in Figure 10. A total of 55 new data points have been added to the HFMAK. Of these 55 new points, 45 were hydrocarbon exploration Bottom Hole Temperature (BHT) points, 5 were derived from published data from other authors, and 5 were new data from mineral exploration sites. The majority of the new data are BHT along the Alaska Peninsula, within the Copper River Basin, and the Gulf of Alaska Basin. The new data in the Copper River Basin support a higher heat flow in the volcanic gap between the Aleutian Volcanic Arc and the Wrangell Mountains than previously thought. The new data added along the Alaska Peninsula show more variability than the 2004 Map. The data suggest the high heat flow associated with the volcanic arc does not extend far into Bristol Bay; however, data are limited so that the contouring is relatively unconstrained. Earthquake data within Alaska were overlaid on the new map to compare the heat flow to the location of seismically active zones. Figure 11 shows the 2013 HFMAK with the locations of earthquakes from 1973-2011. Several linear earthquake trends appear that are not associated with major faults, but do coincide with hot spring groups. A location of hot springs with active seismicity would imply hot water associated with fracture permeability, both of which are necessary for electricity production. Hawk hot spring and other surrounding hot springs are one such location highlighted using this method (Waring, 1917). The general earthquake trends are in agreement with the constrained contouring based on specific geologic constraints. Conclusions Overall, heat flow throughout Alaska will be more locally variable than this statewide map or similarly scaled previous maps suggest. Bottom Hole Temperature (BHT) and Equilibrium Temperature log (ETL) data have shown variability where there are multiple data points. Even in the area of highest confidence studied, Donlin Creek, the heat flow calculations varied by up to 25% across a distance of only a few kilometers. This scale of variation is important to keep in mind when conducting reconnaissance studies using this map. While a general trend of high heat flow is represented, the heat flow is not definitely assessed outside the areas of the calculated sites. A geologic region better illustrated by the new map includes the Aleutian Volcanic Arc. A priori knowledge suggested the entire Alaska Peninsula to have high heat flow and be viable for geothermal power generation. The new data show variable heat flow ranging from high values above 120 mW/m* to values below 40 mW/m”. This variability indicates that the geothermal energy potential throughout the Alaska Peninsula is not uniform and emphasizes the natural heterogeneity of heat flow, compounded with the complex geology of Alaska. More data need to be collected in specific areas of interest for site specific geothermal energy viability to be assessed. For this to occur, wide- spread data collection through collaboration with industry and federal and state groups should be a continual process to identify the areas for most productive exploration for geothermal resources within Alaska. 20 saw 18 433°w | Map Legend | Heat Flow, mW/m? Map Symbols | Bold colors supported by data Light colors inferred by regional geology 30-39 40-49 50-59 60-69 70-79 80-89 90-99 100-110 110+ Heat Flow Data Select Cities : . i ; : MH 1 re anes Hot Springs <40 °C Volcanoes | Contour Lines Figure 10. Heat Flow Map of Alaska, 2013. Areas with collected temperature data to support contouring have bold colors; whereas areas without temperature measurements to support the contouring are displayed with light colors and are contoured based on regional geology. The color differences are shown in the legend. The legend is also for Figure 11. 21 149° W Figure 11. 2013 Heat Flow Map of Alaska with earthquakes plotted as small black dots. Contouring of the data matches the active seismicity along the Denali fault well; however, there is high seismicity between Anchorage and the Denali fault that is not explained by the thermal regime because of the limited heat flow data in the area. The map legend can be found with Figure 10. Future work This project increases our understanding of the regional thermal regime of Alaska but there is still much to be learned through more data collection. Future data collection will be done through collaboration with natural resource exploration companies to decrease cost, but this limits the spatial coverage of new data. The future of geothermal energy exploration will need to include funding for drilling projects where data have shown potential for geothermal resources. Drilling is an expensive endeavor, but new locations are necessary to fill data gaps. There are several geothermal resource development projects currently taking place such as at the Mt. Spurr volcano by Ormat Technologies, Inc. These projects collect the necessary data to calculate new heat flow; data from the Mt. Spurr project and future geothermal research should be used to calculate new heat flow points and added to the HFMAK as it becomes publically available. 22 There are also known geothermal resources along the Alaska Peninsula into the Aleutian Island Arc (e.g. Unalaska and Akutan islands) and interior Alaska that have not been developed due to financial hurdles. Economic models should be made focusing on current areas with known resources to address the financial challenges of power production along the Aleutian Islands and the remote interior Alaska. These models would inherently be different because of the differences in industry between interior Alaska and coastal Alaska, but both will open a currently untapped resource. Data that have been collected and displayed on the map will be used for numerical modeling of the Alaska Peninsula, Southeast Alaska, and the Seward Peninsula to interpret tectonic history of the respective regions. Tectonic history will give a better understanding to regional geology and supplement future hypotheses in natural resource exploration. This new edition of the Heat Flow Map of Alaska has already highlighted several locations of interest for geothermal exploration: the George Parks Highway between Denali National Park and Anchorage, Wasilla/Palmer area, Delta Junction, Glenallen/Gakona Junction, the Sitka vicinity, a survey across the Seward Peninsula, Kotzebue, and the Purcell Mountain vicinity. These locations are discussed in detail in Appendix D. Another way to assess geothermal energy potential is to make temperature at depth maps based on the surface heat flow map. This temperature at depth map will give a base temperature throughout Alaska to calculate a temperature differential compared to mean annual surface temperature. From this, estimates of heat in place can be made which can approximate potential power production. Acknowledgements The authors thank the companies and organizations that have supplied data, including: Alaska Oil and Gas Conservation Commission, Chena Hot Springs Resort, Constantine Metal Resources, Ltd., Donlin Gold, LLC., Kinross Gold Corporation, Kiska Metals Corporation, The Pebble Limited Partnership, Teck Alaska, Inc., and Usibelli Coal Mine, Inc. Groups that have provided research funding and field assistance for this map include the Alaska Energy Authority, the Alaska Center for Energy and Power, Chena Hot Springs Resort, and the American Association of Petroleum Geologists. We appreciate the editing efforts by Cathy Chickering of the SMU Geothermal Laboratory. References Alaska Volcano Observatory, “Latitudes and longitudes of Alaska volcanoes”, Alaska Volcano Observatory, 31 August 2012 web. 15 January 2013. Beardsmore, G.R. and Cull, J.P., 2001. Crustal Heat Flow: A Guide to Measurement and Modeling, Cambridge, Cambridge University Press, pp. 324. Bergman, S., Corrigan, J., Swenson, R., Talbot, J., Watts, A., and Van Kooten, G., 1993. “Fission Track, “’Ar-*’Ar, and K-Ar Geochronology and Petrology of Cenozoic and Upper Mesozoic Rocks from the Gulf of Alaska Area and Yakutat #1 Well (OCS-Y- 0211), 1992 Field Study Results”, ARCO Exploration and Production Technology Exploration Research and Technical Services, Final Report, pp. 199. 23 Bergman, S.C., Murphy, J., and Kelley, S. 2008. “Fission Track Geochronology of the North Aleutian COST #1 Well (OCS-8218), Bristol Bay Basin, Alaska”, Bristol Bay-Alaska Peninsula region, overview of 2004-2007 geologic research, RI 2008-13, 177-206. Blackwell, D.D., and Richards, M., 2004. “Geothermal Map of North America”, Am. Assoc. of Pet. Geol. | sheet, scale 1:6,500,000. Blackwell, D.D., Richards, M., Frone, Z., Batir, J.F., Ruzo, A., Dingwall, R., and Williams, M. 2011. “Temperature-at-Depth Maps for the Conterminous United States and Geothermal Resource Estimates”, Geothermal Resources Council Transactions, 35, 1545-1550. Blackwell, D.D., and Spafford, R.E, 1987. “ Experimental methods in continental heat flow”, in C.G. Sammis, and T.L. Henyey eds., Experimental Methods in Physics, Part B - Field Measurements, 24, Geophysics: Academic Press, 189-226. Blackwell, D.D., Steele, J.L., and Brott, C.A., 1980. “The Terain Effect on Terrestial Heat Flow”, Journal of Geophysical Research, 85, no. B9, 4757-4772. Blackwell, D.D., Steele, J.L., and Carter, L.C., 1991. “Heat flow patterns of the North American Continent: A discussion of the DNAG Geothermal Map of North America”, in Slemmons, D.B., Engdahl, E.R., Zoback, M.D., and Blackwell, D.D. eds., Neotectonics of North America, Boulder, Colorado, Geological Society of America, Decade Map 1. Carslaw, H.S., and Jaeger, J.C. 1959. Conduction of heat in Solids, Oxford, Oxford University Press, pp. 510. Deming, D., Sass, J.H., and Lachenbruch, A.H., 1996. “Heat Flow and Subsurface Temperature, North Slope of Alaska”, in, Johnsson, M.J. and Howell, eds., Thermal Evolution of Sedimentary Basins in Alaska, Washington, U.S. Geological Survey Bulletin 2142, 21-44. Durrance, E.M., 1985. “Hydrothermal circulation and isostasy, with particular reference to the granites of southwest England”, in Heat heat production granites, hydrothermal circulation and ore genesis, London, UK, /nstitute of Mining and Metallurgy, 71-85. Erkan, K., Holdmann, G., Benoit, W, and Blackwell, D. 2008., “Understanding the Chena Hot Springs, Alaska, Geothermal System Using Temperature and Pressure Data from Exploration Boreholes”, Geothermics, 37, 6, 565-585. Forbes, R.B., Wescott, E.M., Turner, D.L., Kienle, J., Ostercamp, T., Hawkins, D.B., Kline, J.T., Swanson, S., Reger, R.D., and Harrison, W., 1979. “A Geological and Geophysical Assessment of the Geothermal Potential of Pilgrim Springs, Alaska”, Geophysical Institute, UAF and Alaska D.G.G.S., preliminary report, pp. 39. Forster, A.; Merriam, D.F.; and Hoth, Peer., 1998. “Geohistory and Thermal Maturation in the Cherokee Basin (Mid-Continent, U.S.A.): Results from Modeling”, Am. Assoc. of Pet. Geol. Bulletin, 82, 9, 1673-1693. Gallardo, J., and Blackwell, D.D., 1999. “Thermal Structure of the Anadarko Basin”, Am. Assoc. of Pet. Geol. Bulletin, 82, 2, 333-361. Goss, R., and Combs, J., 1976. “Thermal conductivity measurement and prediction from geophysical well log parameters with borehole application”, in Second U.N. Symposium on the Development And Use of Geothermal Resources, U.S. Govt. Printing Office, 1019-1027. 24 Hamilton T.D., 1994. “Late Cenozoic glaciation of Alaska”, in Plafker, G. and Berg, H.C. eds., The Geology of Alaska, Boulder, Colorado, Geological Society of America, The Geology of North America, G-1, 813-844. Harrison, W.E., Luza, K.V., Prater, M.L, and Chueng, P.K., 1983. “Geothermal resource assessment of Oklahoma”, Oklahoma Geological Survey, Special Publication 83-1. Jaeger, J.C., 1961. “The effect of the drilling fluid on temperature measured in boreholes”, Journal of Geophysical Research, 66, 563-569. Jessop, A.M., Hobart, M.A., and Sclater, J.G., 1976. “The world heat flow data collection - 1975”, Geothermal Service of Canada, Geothermal Series # 5, Ottawa, Canada, 10 p. Kolker, A.M., 2007. “Alaska Geothermal Development: A plan”, Alaska Energy Authority, final report, pp. 22. Kolker, A.M., 2008. Geologic Setting of the Central Alaskan Hot Springs Belt: Implications for Geothermal Resource Capacity and Sustainable Energy Production. PhD Dissertation. University of Alaska Fairbanks, pp. 189. Kolker, A.M., Stelling, P., Cumming, W., and Rohrs, D. 2012. “Exploration of the Akutan Geothermal Resource Area”, Proceedings, Thirty-Seventh Workshop on Geothermal Reservoir Engineering, 37, SGP-TR-194. Lachenbruch, A.H. and Brewer, M.C., 1959. “Dissipation of the temperature effect in drilling a well in Arctic Alaska”, U.S. Geological Survey Bulletin, 1083-C, 73-109. Lachenbruch, A.H., and Marshall, B.V., 1969. “Heat flow in the Arctic”, ARCTIC, 22, 300- 311. Lachenbruch, A.H., Sass, J.H., Marshall, B.V., and Moses, T.H., Jr., 1982. “Permafrost, heat flow, and the geothermal regime of Prudhoe Bay, Alaska”, Journal of Geophysical Research, 87, 9301-9316. Lee, C., and Han, U, 2001. “Estimation of borehole temperature disturbed by drilling”, Geosciences Journal, 5, 4, 313-318. Magoon, L.B., 1986. “Geologic Studies of the Lower Cook Inlet COST No. 1 Well, Alaska Outer Continental Shelf’, U.S. Geological Survey Bulletin 1596, pp. 99. Magoon III, L.B., 1994. “Petroleum resources in Alaska”, in Plafker, G. and Berg, H.C. eds., The Geology of Alaska, Boulder, Colorado, Geological Society of America, The Geology of North America, G-1, 905-936. Martini, B.A., Lide, C., Owen, L. Walsh, P., Delwiche, B. and Payne, A., 2011. “Geothermal Resource Definition at Mt. Spurr, Alaska”, Geothermal Resources Council Transactions, 35, 897-904. Mendenhall, W.C., 1905. “Central Copper River Region, Alaska”, U.S. Geological Survey, Professional Paper 41, pp. 137. Miller, J.K., Prakash, A., Daanen, R., Haselwimmer, C., Whalen, M., Benoit, D., Cumming, W., Clark, A.C., Mager, M., and Holdmann, G., 2013. “Geologic Model of the Geothermal Anomaly at Pilgrim Hot Springs, Seward Peninsula, Alaska”, Proceedings, Thirty-Eighth Workshop on Geothermal Reservoir Engineering, 38, SGP-TR-198. Miller, T.P., Barnes, I., and Patton, W.W., Jr., 1975. “Geologic setting and Chemical characteristics of hot springs in west-central Alaska”, U.S. Geological Survey Journal of Research, 3, 149-162. 25 Miller, T.P., 1994. “Geothermal Resources of Alaska,” in Plafker, G. and Berg, H.C. eds., The Geology of Alaska, Boulder, Colorado, Geological Society of America, The Geology of North America, G-1, 979-987. Morgan, P., and Gosnold, W.D., 1989. “Heat flow and thermal regimes in the continental United States”, in Pakiser, L.C., and Mooney, W.D., Geophysical framework of the continental United States, Boulder, Colorado, Geological Society of America, Memoir 172, 493-522. Motyka, R.J., Moorman, M.A., and Liss, S.A., 1983, “Geothermal Resources of Alaska”, State of Alaska, Department of Natural Resources, Division of Geological & Geophysical Surveys, Fairbanks, Alaska — USA, Miscellaneous Publication MP 8. National Climatic Data Center, 2011. “Climatological Data Annual Summary: Alaska”, National Oceanic and Atmospheric Administration, U.S. Department of Commerce, 87, no.13, pp.36. Nokleberg W.J., Plafker, G., and Wilson, F.H., 1994. “Geology of south-central Alaska”, in Plafker, G. and Berg, H.C. eds., The Geology of Alaska, Boulder, Colorado, Geological Society of America, The Geology of North America, G-1, 311-366. Plafker, G., and Berg, H.G., 1994. “Overview of the geology and tectonic evolution of Alaska”, in Plafker, G. and Berg, H.C. eds., The Geology of Alaska, Boulder, CO., Geological Society of America, The Geology of North America, G-1, 989-1021. Sass, J.H., Kennelly Jr., J.P., Smith, E.P., and Wendt, W.E., 1984. “Laboratory line-source methods for the measurement of thermal conductivity of rocks near room temperature”, U.S. Geological Survey, Open-File Report 84-91, pp. 21. Stefano, R.R., 1974. “Low Temperature Utilization of Geothermal Water in Alaska at Pilgrim Hot Springs”, Stefano & Associates, Inc., final report, pp. 14. Turner, D.L., Swanson, S., and Wescott, E., 1981. “Continental Rifting — A New Tectonic Model for Geothermal Exploration of the Central Seward Peninsula, Alaska”, Geothermal Resources Council Transactions, 5, 213-216. Vukich, D., and Friedmann, G., 2011. “Southwest Alaska Regional Geothermal Energy Project”, Naknek Electric Association, DOE Geothermal Technologies Program 2011 Peer Review Presentation, pp. 15. Waring, G.A., 1917. “Mineral Springs of Alaska”, U.S. Geological Survey, Water-Supply Paper 418, pp. 114. Williams, J.R., and Galloway, J.P., 1986. “Map of western Copper River Basin, Alaska, showing lake sediments and shorelines, glacial moraines, and location of stratigraphic sections and radiocarbon-dated samples”, U.S. Geological Survey, Open-File Report 86-390, pp. 35 26 Appendices Appendix A. 2013 Heat Flow Measurements within Alaska Below are all points that contained temperature data used for contouring the 2013 Heat Flow Map of Alaska, including previously published points, volcanoes, hot springs, and newly collected data for this project. Points with a quality A, B, C, BHT-C, or G (Blackwell et al., 1991) were used for the gridding and contouring procedure. Any D or BHT-D points need further examination and were not used for the gridding and contouring. A “BHT-” prefix before a point denotes that the temperature is a Bottom Hole Temperature measurement from a well. “G” quality measurements are wells that are measured at a site with known geothermal potential, or surface geothermal manifestations such as a hot spring or volcano. An example of a well site with “G” quality would be wells at Chena Hot Springs drilled for geothermal energy production. Relative error associated with quality denotations are as follows: A = 45%, B=+10%, C = +20%, D = >25%, G = Geothermal (not assessed quantitatively), BHT-C = 420%, BHT-D = >25%. New points examined that did not contain temperature data are not included in this list because a heat flow could not be calculated and therefore no quality could be assigned. Data from the SMU database (available online at http://smu.edu/geothermal) already had a quality assigned to the data; all other data were given a quality ranking by the authors. A-l SMU Database Depth Gradient — Gradient Conductivity Heat Flow Longitude Latitude Name (m) (°C/km) — Interval (m) (Wim*K) — (mW/m2) Quality -132.050 54.783 MBI 208 20 121-208 23 46 A -131.780 55.163 NAI 112 21 58-112 3.2 68 A -148.863 70.336 A-B-F 660 17 - 3.4 55 B -148.663 70.281 D-G-M 650 16 . 3.4 54 B -148.527 70.378 E 605 19 - 3.6 68 B -148.412 70.212 Cc 595 16 - 3.3 51 B -148.315 70.312 N 625 16 - 3.4 53 B -134.800 57.092 WSB 168 49 137-168 3.1 150 B -133.314 56.839 ASC 211 36 91-211 19 69 B -132.133 54.912 BC 165 20 77-165 3.9 716 B - 130.478 55.407 Qol 945 31 701-945 3.8 115 B -180.925 51.483 AMCHITKA 1158 28 61-1158 1.5 41 Cc -165.267. 68.117 THOMPSON = 366 20 15-362 2.9 59 Cc -161.070 = 70.210 TLK - 37 276-523 0.8 34 & -160.700 66.100 =SEWARD - - - - 87 G -159.000 70.720 PEA 3115 40 583-3115 18 73 Cc -158.660 70.590 KAG 3822 36 541-3822 19 68 G -158.020 69.150 AWU - 23 739-748 1.7 38 Cc -156.890 70.610 SME 3031 44 188-535 19 87 c -156.880 71.100 WAL 1326 40 0-1326 he 67 Cc -156.700 66.950 N.A.N.A. - - - - 67 Cc -156.450 71.200 +P BARROW - - - . 54 : -156.060 70.930 KUY - B9) 100-857 1.6 64 Cc -155.770 70.260 NIN 3085 46 615-3085 17 77 Cc -155.730 71.190 TUL - 42 100-732 17 69 ¢ -155.690 68.480 LBN 2431 27 525-2431 17 46 E -155.630 71.160 WDS - 44 287-734 14 61 Cc -154.670 70.980 ES2 2274 42 0-2274 1) 73 Cc -154.620 70.920 ES1 2359 45 581-2359 18 79 Cc -154.610 69.750 KOL 1775 41 226-1775 1.5 62 c -154.330 70.460 IKP 4316 36 610-4316 2.0 71 ¢ -154.083 60.167, COOK INL - - - - 87 Cc -153.900 70.880 DRP 2300 38 639-2300 17 64 Cc -153.300 68.840 EKU 3157 26 0-3157 17 44 Cc -153.140 70.920 JWD 2856 43 483-2856 ed) 73 c -153.100 70.000 INI 2518 33 0-2518 17 56 c -152.940 70.570 ETK 3234 48 725-3234 19 90 Cc SMU Database Depth Gradient — Gradient Conductivity Heat Flow Longitude Latitude Name (m) (C/km) Interval (m) — (Wim*K) — (mW/m2) Quality -152.470 70.770 CHA 2384 38 0-2383 17 66 Cc -152.370 70.510 NKP 2240 51 661-2240 1.6 82 Cc -152.300 70.830 WTF 2749 39 0-2749 18 3B C -152.200 63.300 DENALI - - - - 100 Cc -152.180 69.380 SBE - 18 302-384 2.6 49 C -152.060 70.330 FCK 2749 39 0-2749 18 69 Cc -151.730 70.420 SOH - 33 146-238 2.7 83 Cc -151.720 70.560 ATI 2469 39 652-2469 1.6 64 Cc -151.500 68.083 +BROOKSR - - - - 100 C -148.863 70.336 AHTNA - - - - 100 C -148.650 63.950 ALASKAR - - - - 67 Cc -145.900 64.700 FAIRBANK - - - - 87 Cc -142.900 63.500 = TANANA - - - - 50 Cc -141.500 63.500 NORTHWAY - - - - 87 Cc -134.619 58.076 GC 189 12 44-189 4.5 55 C -132.590 55.618 SUK 212 16 128-212 a0 40 Cc -132.147 55.067 NIB 129 17 108-129 3.0 51 Cc -164.931 65.095 MI-1 85 - 0-24 - 120 G -164.930 65.096 PS-3 73 - 0-24 - 120 G -164.929 65.095 PS-4 150 - 0-30.5 - 120 G -164.929 65.096 PS-2 24 - 0-24 - 120 G -164.929 65.093 PS-5 274 - 0-21.3 - 120 G -164.929 65.097 PS-1 24 - 0-24 - 120 G -146.055 65.052 CHENA ai 60 0-185 2.7 120 G 2013 New Data 5 Gradient 1 ae Longitude Latitude Name ea an na ey iene Quality Coon) LTA eee -161.950 56.200 COST 1 5090 31.0 1378-4975 1.8 56 A -140.450 59.200 YAKUTAT | - 32.0 - - 54 A -158.197 62.079 DC_MW05-22 183 29.1 90-175 3.6 106 B -158.197 62.079 DC_MW05-23a 178 24.9 120-140 3.8 95 B -158.197 62.079 DC_MW05-23b 178 29:7 142.5-170 35 104 B -158.197 62.079 DC_MW07-11 160 21.0) 90-150 3.6 T B -162.861 68.071 RDM_T96-012 150 20.5 90-150 2.4 49 (e -162.861 68.071 RDM_T96-013 150 16.6 90-150 19 31 Cc -156.195 58.701 NAKNEK 3194 49.1 0-1097 i) 74 ¢c -152.674 59.498 COST 1-CI 3776 22.8 0-3775 2:5 57 Cc -151.069 60.679 SWANSON - 23.7 - 2.5 59 ¢ -155.279 59.901 PEBBLE PRS 1000 27.8 0-1000 25 70 BHT-C -162.959 60.648 NAPATUK CK 1 4544 30.9 0-4544 2'5 77 BHT-C -162.122 55.734 CATHEDRALRIVUNIT1 4359 33.6 0-4359 2.0 67 BHT-C -162.114 66.740 NIMIUK PT 1 1924 40.3 0-1925 25 101 BHT-C -161.569 55.863 DAVIDRIV USA I-A 4197 38.1 0-4198 2.0 76 BHT-C -161.247 55.523 CANOEBAY UNIT1 2024 40.5 0-2025 2.0 81 BHT-C -161.022 55.843 HOODOOLK UNIT USA1 2453 29.4 0-2454 2.0 59 BHT-C -160.972 55.809 HOODOOLK UNIT USA2 3427 36.5 0-3427 2.0 73 BHT-C -160.173 56.215 SANDY RIVFED1 3818 39.4 0-3818 2.0 79 BHT-C -159.782 55.936 BIG RIV A-01 3466 64.3 0-3466 2.0 129 BHT-C -158.685 56.967 PORTHEIDEN UNIT1 4578 32.9 0-4579 20 66 BHT-C -158.567 64.633 NULATO UNIT 1 3662 24.4 0-3663 DiS 61 BHT-C -157.738 57.426 UGASHIK 1 2889 46.7 0-2890 2.0 93 BHT-C -157.433 57.163 PAINTER CK 1 2412 43.3 0-2412 2.0 87 BHT-C -157.110 57.784 BECHAROF 1 2750 40.4 0-2751 2.0 81 BHT-C -157.046 56.916 KONIAG CHEVRONUSA1 3329 47.2 0-3330 2.0 94 BHT-C -155.862 57.628 BEARCK UNIT 1 3848 35.7 0-3849 2.0 71 BHT-C -152.599 61.985 WHISTLER PRJ 875 25:0 0-875 2.8 71 BHT-C -149.638 64.581 NENANA I 933 38.7 0-934 25 97 BHT-C -146.493 62.138 TAZLINA 1 1616 41.4 0-1616 25 103 BHT-C -146.265 62.282 SALMONBERRYLK UNIT! 1585 29.4 0-1585 25 73 BHT-C -146.260 59.409 MIDDLETONISST1 2522 24.1 0-2522 2.5 60 BHT-C -146.234 62.431 RAINBOW FED | 2412 47.1 0-2412 25 118 BHT-C -146.071 62.509 RAINBOW FED2 3662 29.6 0-3663 2.0 59 BHT-C -145.811 62.106 MOOSECKUNIT1 914 31.0 0-915 25 WT BHT-C -145.492 62.300 AHTNA INC 1 1574 34.4 0-1574 2.0 69 BHT-C -145.411 62.190 AHTNA INC A-O1 851 31.3 0-852 2-5 78 BHT-C 2013 New Data . Gradient = . Longitude Latitude Name oy as a ae neater Quality -144.210 60.264 BERINGRIV UNIT 1 2397 31.8 0-2397 2.5 79 BHT-C -144.165 60.210 BERING RIV UNIT 2 2420 32.3 0-2421 2.5 81 BHT-C -143.039 60.157 KALIAKH RIV UNIT2/RD 1700 41.9 0-1700 2.5 105 BHT-C -143.024 60.136 KALIAKHRIV UNIT1 1882 31.6 0-1883 2.0 63 BHT-C -142.778 60.165 DUKTOTHRIV UNIT1 1835 29.2 0-1835 2.0 58 BHT-C -142.421 60.080 WHITERIV UNIT1 3699 28.8 0-3699 2.0 57 BHT-C -142.210 60.073 WHITERIV UNIT3 4480 26.7 0-4481 2.0 53 BHT-C -142.147 60.073 WHITERIV UNIT2 3167 31.1 0-3168 2.0 62 BHT-C -142.141 65.649 DOYON LTD 1 2433 35.6 0-2433 2.0 71 BHT-C -141.717 66.805 DOYON LTD 3 2077 44.5 0-2078 2.0 89 BHT-C -141.425 59.897 RIOU BAY 1 3560 38.6 0-3561 2.0 77 BHT-C -141.152 60.037 CHAIXHILLS I/A 3365 38.2 0-3365 25 95 BHT-C -139.991 59.797 MALASPINA UNIT I-A 4125 15.1 0-4125 2.5 38 BHT-C -139.674 59.526 YAKUTAT 1 3360 21.4 0-3361 2.0 43 BHT-C -139.625 59.520 YAKUTAT 3 3053 30.2 0-3054 2.0 60 BHT-C -139.587 59.514 YAKUTAT 2 3683 29.4 0-3683 2.0 59 BHT-C -139.523 59.571 CORE HOLE | 2812 33.1 0-2812 2.0 66 BHT-C -139.373 59.371 CORE HOLE 2 3203 27.8 0-3204 2.0 56 BHT-C -139.237 59.407 DANGEROUSRIV UNIT1 3585 27.9 0-3586 2.0 56 BHT-C -138.939 59.257 CORE HOLE 3 982 34.0 0-982 2.0 68 BHT-C -135.445 59.236 PALMER PRJ 600 23.5 0-600 3.4 81 BHT-C -162.760 60.753 NAPATUKCKCORE2-A 652 17.1 0-652 2.5 17 BHT-D -147.142 61.952 EUREKA 2 1734 28.4 0-1735 2.0 57 BHT-D -146.607 62.109 TAWAWELKUNIT1 2632 31.7 0-2632 2.0 63 BHT-D -146.105 59.805 C.0.8.7. ALASKA 1 DST-01 1670 33.1 0-1670 2.0 66 BHT-D SULLIVAN 2 3674 27.5 0-3675 2.0 55 BHT-D SULLIVAN PHILLIPS | 2258 34.0 0-2259 2.0 68 BHT-D A-5 Volcanoes (Alaska Volcano Observatory, 2012) ; Gradient le Longitude Latitude Name oh id fal ae fan Quality -184.091 52.349 VOLCANO - - - - 97 G -184.053 52.357 +=VOLCANO - - - - 97 G -182.397 52.103 VOLCANO - - - - 97 G -181.866 52.014 VOLCANO - - - - 97 G -181.724 51.979 VOLCANO - - - - o7: G -181.674 51.954 VOLCANO - - - - 97 G -181.464 51.953. VOLCANO - - - - 97 G -180.402 51.929 VOLCANO - - - - 97 G -180.170 51.848 VOLCANO - - - - 97 G -178.796 51.789 VOLCANO - - - - 97 G -178.143 51.884 VOLCANO - - - - 97 G -178.027 51.867 VOLCANO - - - - 97 G -177.441 51.907 VOLCANO - - - - 97 G -177.162 51.924 VOLCANO - - - - 97 G -176.741 51.937 VOLCANO - - - - 97 G -176.632, 51.969 +~VOLCANO - - - - 97 G -176.585 51.991 VOLCANO - - - - 97 G -176.111 52.077 VOLCANO - - - - 97 G -175.511 52.169 VOLCANO - - - - 97 G -175.132 52.219 VOLCANO - - - - 97 G -174.952 52.053. VOLCANO - - - - 97 G -174.165 52.382. +WVOLCANO - - - - 97 G -174.165 52.382 VOLCANO - - - - 97 G -172.510 52.316 VOLCANO - - - - 97 G -171.925 52.801 VOLCANO - - - - 97 G -171.875 52.765 VOLCANO - - - - 97 G -171.412 52.941. VOLCANO - - - - 97 G -171.255 52.494. VOLCANO - - - - 97 G -171.140 52.571. VOLCANO - - - - 97 G -170.659 52.649 VOLCANO - - - - 97 G -170.433, 63.599 VOLCANO - - - - 90 G -170.300 57.180 VOLCANO - - - - 97 G -170.228 53.120 VOLCANO - - - - 97 G -170.113. 52.741. VOLCANO - - - - 97 G -170.058 52.891 VOLCANO - - - - 97 G -169.945 52.822. VOLCANO - - - - 97 G -169.767 53.065 VOLCANO - - - - 97 G -169.760 = 53.298 VOLCANO - - - - 97 G -169.758 52.839 VOLCANO - - - - 97 G Volcanoes (Alaska Volcano Observatory, 2012) : Gradient st Longitude Latitude Name “ aa Nah. Orvik. twin Quality -169.719 52.973. VOLCANO - - - - 97 G -169.630 56.580 VOLCANO - - - - 97 G -169.379 53.147. VOLCANO - - - a 97 G -168.694 53.126 VOLCANO - - - ~ 97 G - 168.538 53.154 VOLCANO - - - - 97 G -168.166 53.397 VOLCANO - - - - 97 G -168.034 53.927 VOLCANO - - - - 97 G -166.925 53.890 VOLCANO - : : - 97 G -166.496 60.099 VOLCANO - - - i 87 G -165.986 54.133 VOLCANO - - - - 97 G -165.661 54.252. VOLCANO - - - - 97 G -165.227. 61.525 VOLCANO - - - - 97 G -164.910 61.570 VOLCANO - - - - 97 G -164.660 60.450 VOLCANO - - - “i 97 G -164.648 54.517 VOLCANO - - - - 97 G -164.470 61.430 VOLCANO - - - - 95 G -164.414 61.638 VOLCANO - - - - 97 G -164.352 54.669 VOLCANO - - - : 97 G -164.333 66.349. +=VOLCANO - - - = 90 G -164.250 61.170 VOLCANO - - - - 97 G -163.971 54.755 VOLCANO - : < 7 97 G -163.920 65.600 VOLCANO - - - : 90 G -163.729 54.768 VOLCANO - - - = 97 G -163.591 54.799 VOLCANO - - - m 97 G -163.147. 55.417 VOLCANO - - "6 2 97 a -162.835 55.067 VOLCANO - - - : 97 G - 162.274 55.187 VOLCANO - - - - 97 G -162.123 63.449 VOLCANO - - - : 90 G -162.073 55.341 VOLCANO - - - = 97 G -161.945 55.564. VOLCANO - - - - 97 G -161.894 55.417 VOLCANO - - - = 97 G -161.854 55.457 VOLCANO - - - - 97 G -161.216 55.642 VOLCANO - - - . 97 G -160.500 65.650 VOLCANO - - - - 97 G -160.096 55.868 © VOLCANO - - - = 97 G -160.050 59.270 VOLCANO - - - - 87 G -160.041 55.913. VOLCANO - - - : 97 G -160.002 55.929 VOLCANO - - - - 97 G -159.958 55.952. VOLCANO - - - = 97 G A-7 Volcanoes (Alaska Volcano Observatory, 2012) . Gradient zs Longitude Latitude Name ai a iat mee ee Quality -159.791 56.013 VOLCANO - - - - 97 G -159.393 56.198 VOLCANO - - - - 97 G -158.787 56.551 VOLCANO - - - = 97 G -158.155 56.881 © VOLCANO - - - z 97 G -157.186 57.018 VOLCANO - - - = 97 G -156.991 57.133. VOLCANO - - - “ 97 G -156.847 57.705 VOLCANO - - - 7 97 G -156.747 57.202 VOLCANO - - - = 97 G -156.512 57.831 VOLCANO - - = a 97 G -156.370 57.750 VOLCANO - - - - 97 G -156.140 58.040 VOLCANO - - - . 97 G -155.671 58.053 +=VOLCANO - - - = 97 G -155.514 57.834 VOLCANO - - - 7 97 6 -155.400 58.157 VOLCANO - - - 2 97 G -155.357 58.169. +VOLCANO - - - = 97 G -155.254 58.195 VOLCANO - - = = 97 G -155.210 58.410 VOLCANO - - - 5 97 G -155.159 58.265 VOLCANO - - - 2 97 G -155.104 58.357 VOLCANO - - - c 97 G -155.103 58.234. +~VOLCANO - - - 5 97 G -154.953. 58.279 VOLCANO - - - c 97 G -154.686 58.334. VOLCANO - - - : 97 G -154.680 58.500 VOLCANO - - - : 97 G -154.560 58.590 VOLCANO - - - 2 97 G -154.540 58.580 VOLCANO - - - e 97 G -154.510 58.550 VOLCANO — - 2 : : 97 G -154.470 58.640 VOLCANO - - - 2 97 G -154.451 58.417. VOLCANO - - - = 97 G -154.390 58.430 VOLCANO - - - ss 97 G -154.357 58.453. +=VOLCANO - - - 5 97 G -154.300 58.475 VOLCANO - - - 97 G -154.025. 58.611 VOLCANO - - - = 97 G -153.674 58.770 VOLCANO - - - a 97 G -153.535 58.860 VOLCANO - - - . 97 G -153.435 59.363. +=VOLCANO - - - 2 97 G -153.092 60.032. VOLCANO - - - e 97 G -152.744 60.485 VOLCANO - - - a 97 G -152.672. 60.719 VOLCANO - - - 7 97 G -152.420 61.599 VOLCANO - - - - 97 G Volcanoes (Alaska Volcano Observatory, 2012) . Gradient . ss Longitude Latitude Name 7h Pat nena C ae ; eee Quality -152.254 61.299 VOLCANO - - - - 95 G -148.685 63.967 VOLCANO - - - - 97 G -148.422 64.070 VOLCANO - - - - 97 G -145.085 62.096 VOLCANO - - - - 97 G -144.640 62.116 VOLCANO - - - - 95 G -144.130 62.213 VOLCANO - - - - 95 G -144.113 62.424. VOLCANO - - - - 97 G -144.019 62.006 VOLCANO - - - - 95 G -143.620 62.023 VOLCANO - - - - 97 G -143.506 62.302 VOLCANO - - - - 97 G -143.132 62.400 VOLCANO - - - - 97 G - 143.088 62.131 VOLCANO - - - - 97 G -142.700 67.300 © VOLCANO - - - - 97 G -141.715 61.419 VOLCANO - - - - 97 G -141.622 63.720 VOLCANO - - - - 97 G -135.761 57.051 VOLCANO - - - - 97 G -133.302 55.250 VOLCANO - - - - 97 G -133.102 56.500 VOLCANO - - - - 97 G -131.051 55.320 VOLCANO - - - - 97 G Hot Springs (Motyka et al., 1983) ' Gradient Me Longitude Latitude Name laa i ug eater real) Quality fn) et -164.919 65.011 HOT SPRING - - - - 100 G -164.919 65.011 HOT SPRING - - - - 100 G -164.709 65.857 |= HOT SPRING - - - - 91 G -162.909 64.811 HOT SPRING - - - - 91 G -162.894 65.228 HOT SPRING - - - - 91 G -162.474 64.703 = HOT SPRING - - - - 91 G -162.300 64.850 HOT SPRING - - - - 91 G -161.203. 65.367 +~==HOT SPRING - - - - 91 G -159.859 61.193 © HOT SPRING - - - - 86 G -157.753 61.358 HOT SPRING - - = . 86 G -157.592 66.228 HOT SPRING - - = - 91 G -157.140 66.156 = HOT SPRING - - - - 91 G -156.773 66.344. += HOT SPRING - - - - 91 G -156.738 66.379 HOT SPRING - - - - 91 G -155.280 65.259 HOT SPRING - - - - 91 G -155.106 67.267 HOT SPRING - - - - 74 G -154.993 65.908 | HOT SPRING - - - - 91 G -154.838 64.924. HOT SPRING - - - - 91 G -154.693 65.129 HOT SPRING - - - - 91 G -154.199 65.970 | HOT SPRING - - = - 91 G -154.029 66.197 HOT SPRING - - - - 91 G -153.310 65.443. +=9HOT SPRING - - - - 86 G -151.667 65.654 += HOT SPRING - - - - 91 G -151.642. 65.869 += HOT SPRING - - - - 91 G -151.236 65.810 = HOT SPRING - - - - 91 G -150.920 65.962 HOT SPRING - - - - 91 G -150.846 66.343. +==HOT SPRING - - - - 86 G -150.636 65.007 HOT SPRING - - - - 91 G -150.633 65.006 +=HOT SPRING - - = - 91 G -150.580 65.984 HOT SPRING - - - - 91 G -149.993 65.215 = HOT SPRING - - - - 91 G -149.553 66.219 +=HOT SPRING - - = - 86 G -148.851 65.273. HOT SPRING - - - - 91 G -146.057 65.093. += HOT SPRING - - - - 100 G -144.638 65.482 HOT SPRING - - - - 86 G -144.497 65.228 = HOT SPRING - - - - 86 G A-10 Appendix B. Conductivity Values Collected for Heat Flow Calculation Below are all thermal conductivities measured for the 2013 Heat Flow Map of Alaska arranged by the site where rock samples originated. Points with ERR recorded as the conductivity are runs where there was an error and the conductivity measurement was erroneous. There are two possible sources of error: user error, or measurement error. A user error is one where the set-up of the measurement device malfunctioned because of the user improperly setting it. In this case, the needle probe would no longer be in contact with the sample, or the divided-bar would not be pressurized at the same pressure as other samples. This type of user error would be visually detected during or at the end of the measurement and that run would be labeled as an erroneous measurement. Measurement error is where the set-up of the measurement was visually correct but calculation of the thermal conductivity produced a number further from other runs of the same sample. If the range was greater than 10 % of the average conductivity, the anomalous value was labeled erroneous and not used to calculate the average conductivity for the respective sample. Run 1 Divided Bar PPO01-01 3.29 3.29 Run 1 ee 4.07 Divided Bar PPO01-02 4.13 Run 2 4.20 Run 1 : 3.02 Divided Bar PP02-01 3.04 Run 2 3.06 Run 1 Divided Bar PP02-02 3.32 3.32 Run 1 ne 1.69 Divided Bar PP02-03 1.82 Run2 1.95 Run I 3.01 Run 2 Needle Probe DCO1-01 3.09 3.04 Run3 3.36 Run 1 3.37 Run 2 Needle Probe DCO01-02 3.46 3.48 Run3 3.62 Run 1 ERR Run 2 Needle Probe DCO01-03 3.39 3.35 Run3 3.32 B-1 Run 1 S07 Run 2 Needle Probe DCO01-04 3.60 3.67 Run 3 3.83 Run | 3.60 Run 2 Needle Probe DCO01-05 3.91 3.83 Run 3 3:97, Run | 3.22 Run 2 Needle Probe DC01-06 3.24 3.22 Run 3 3.21 Run | 3.49 Run 2 Needle Probe DCO01-07 ERR 3.59 Run 3 3.70 Run | 3.72 Run 2 Needle Probe DC01-08 3.66 3.74 Run 3 3.84 Run 1 B55: Run 2 Needle Probe DCO01-09 3.60 3.67 Run 3 3.87 Run | 4.01 Run 2 Needle Probe DCO01-10 3.98 4.09 Run 3 4.28 Run | 3.80 Run 2 Needle Probe DCO02-01 3.98 3.89 Run 3 ERR Run | 3.63 Run 2 Needle Probe DC02-02 3:55 3.59 Run 3 ERR Run | 3.97 Run 2 Needle Probe DC02-03 3.91 3.93 Run 3 ERR Run | es 2.84 Ree Divided Bar DCO03-01 287 2.85 Run | Divided Bar DCO03-02 3.03 3.03 Run | Divided Bar DC03-03 2.95 2.95 Run 1 Divided Bar DC03-04 3.65 3.65 Run 1 i 3.70 Divided Bar DC03-05 3.80 Run 2 3.90 Run | Divided Bar DC03-06 3.69 3.69 Run | Divided Bar DC03-07 3.60 3.60 B-2 Run 1 Run | Run 1 Run 2 Run 3 Run | Run 2 Run 3 Run 1 Run 2 Run 3 Run | Run 2 Run 3 Run 1 Run 2 Run 3 Run | Run 2 Run 3 Run | Run 2 Run 3 Run 1 Run 2 Run 3 Run 1 Run 2 Run 3 Run | Run 2 Run 3 Divided Bar Divided Bar Needle Probe Needle Probe Needle Probe Needle Probe Needle Probe Needle Probe Needle Probe Needle Probe Needle Probe Needle Probe DC03-08 DC03-09 WHO1-01 WHO1-02 WHO01-03 WHO01-04 WHO2-01 WHO02-02 WHO2-03 WHO02-04 WHO03-01 WHO03-02 B-3 4.19 4.15 2.46 2.39 2.43 ERR 3.24 3.29 2:97 3.29 ERR 2.54 2.54 272: 2.90 2.74 2.86 2.66 2.84 ERR ath 2.98 ERR 2.04 222 2.13 2.97 ERR 3.01 ERR 3.18 3.31 4.19 4.15 2.43 3.26 3.13 2.60 2.83 2.75 2.87 2.13 2.99 3.25 Appendix C. Limitation and Assumptions Related to Sparse Data There are two major limitations associated with lack of data requiring assumptions in order to make the 2013 Heat Flow Map of Alaska (HFMAK). The first limitation is the inability to review raw data behind previously published heat flow values. Some published data are not quality ranked, and not all heat flow values published included the raw data for a secondary analysis to validate the published values; consequently, many values from previous research have been used in this map without a secondary data analysis. The second limitation is the sparseness of the data points. When there are single points separated by many kilometers, the heat flow value calculated at a specific location is only as good as the collection methods and cannot be used to map heat flow far from the point with reasonable confidence. The radial distance one data point can map with confidence is variable and primarily dependent on geology and heat transfer mechanisms. Isolated data points based on an Equilibrium Temperature log (ETL) data are trustworthy within the error of the measurements, but points based on a single BHT have high uncertainty because the temperature has nothing to be compared with, and error is known to exist in Bottom Hole Temperature (BHT) measurements. These data points, while having high uncertainty, are still plotted and contoured because a heat flow based on a temperature measurement is still more trusted than contouring based purely on geology/tectonics. These limitations in quantifying error on the map led to a semi-quantitative approach to the double color intensity scheme used in mapping. Confidence circles are made around data locations, and the area that has a bolder color is trusted to be more representative of the background heat flow than areas of the map with a lighter intensity. The circles are larger and are further from the data dependent on how reliable the data are believed to be. Confidence circles surrounding data points are only semi- quantitative because error can be qualitatively estimated based on data type (ETL, BHT, etc.) and proximity to other data, but exact error calculations were not available for all previously published data. Data points were analyzed to develop a relative size of the confidence circle radius as shown in the flow chart, Chart C-1. This qualitative approach works well for general understanding, but caution should still be used when conducting geothermal exploration even in areas where there is higher confidence in the data. All areas shown as having higher confidence are conservatively estimated at £20%. This estimated error is based on previous quality rankings of conventional heat flow data collection and experience from recent data collections. In light of the new data collected, the authors believe most data within Alaska are correctly labeled with “B” or “C” quality with an associated error up to +20% because most published data were collected using similar techniques and in comparable non-ideal scenarios. Most drill holes in Alaska were not drilled with the intention of calculating heat flow and thus are not ideal data points because they are either shallow, the well temperature is not at equilibrium, there may be large terrain effects, or other possible issues that add uncertainty to the data. Ideally, published data would have been examined for these effects prior to publishing, or would have been examined before being used within this new map; unlike the newly collected data, published data were taken at face value (Jessop et al., 1976; Sass et al., 1985; Blackwell et al., 1991). Areas lacking data were inferred based on geologic understanding of Alaska. The area with the least data was interior Alaska, between the Alaska Range and the Brooks Range. Interior Alaska is hypothesized to be the equivalent of the North American Cordillera along the West Coast of Canada and the conterminous United States; Alaska is thought to have rotated out of alignment with the opening of the Canada Basin during 130-100 Ma (Plafker and Berg, 1994). The North American Cordillera has been shown to have high regional background heat flow within Canada and average variability within the Western United States of 60-100 mW/m? (Blackwell et al., 1991; Lewis et al., 2003). The average of this variability, 80 mW/m”, was chosen as the background value for interior C-l Alaska, where there were no data or geothermal manifestations to drive heat flow contouring. Other areas without temperature data were contoured to follow large geologic trends and data nearby, such as the Alaska Peninsula following locations of volcanoes for high heat flow. In areas where there are both heat flow data and volcanoes or hot springs, volcano/hot spring heat flow estimates were edited to match the calculated heat flow data. Collected data are more reliable because it is a direct measurement of the thermal regime, whereas existence of a volcano/hot spring does not directly produce information about the current thermal regime. BHT or ETL? bounded by geology Nitros PETE ment) aU ee proximity RCL Sete Yes: Larger ira eared INCOR ete come) EURO Ley geologic bounded by oa enr tees geology CRBS uE Cs circles, CEE mn ETc bounded by individual geology CElem renin OU momo PNR Uo) similar? Yes: Larger ice earetgenni et SCS eco Emery geologic bounded by geology sir litag circle around Pile eee) erie) RUS ReCLE! bounded by that do ha’ rere cera STG mele) Chart C-1. Flow chart for establishing circle of confidence for mapping of the brighter color layer of the 2013 HFMAK. There is some quantitative measure to the circle size (larger circles around more reliable data, and smaller around less reliable data), but it is not directly related to total error within each data point. Any previously published values for the purpose of this flow chart were treated as equilibrium temperature logs (ETL). C-2 Appendix D. Regions of Interest for Future Geothermal Energy Exploration Many of the locations here are discussed by Kolker (2007) with respect to further geothermal development within Alaska. The data reviewed to make the 2013 HFMAK independently reached similar conclusions. The Alaska Peninsula and Aleutian Island Arc are not discussed here because there are many resources within those areas that can be explored. The abundance of geothermal surface manifestations within the Alaska Peninsula and Aleutians can guide future development and add data to the understanding to this volcanic setting. Figure D-1 highlights the locations of the regions of interest with blue circles overlaid on the 2013 HFMAK. ANCHORAGE AREA Talkeetna-George Parks Highway between Denali National Park and Anchorage: There are currently no data between Anchorage and Healy, Alaska. This stretch is a complex section geologically with the Aleutian volcanic arc to the west and the Denali Fault and Alaska Range to the north. More data in this area would: A. give insight to the (possible) interaction of these two major structures B. better define the boundary of the varying thermal regimes associated with the tectonic provinces C. accurately assess heat flow in this area This location warrants further study because of e the close proximity to Anchorage, providing both direct applicability to renewable energy utilization and possible reduction in the cost to drill such a well e the lack of data nearby e the number of research questions that could be answered from the results Wasilla/Palmer: This location is similar to the Talkeetna-George Parks Highway area in that it lies between the Aleutian volcanic arc and the Denali Fault to the North and is in an area hypothesized to have lower heat flow than the surrounding area. This area would provide similar results to the Talkeetna location with the added benefit of closer proximity to the Cook Inlet. Heat flow here could also be used as a calibration curve for Cook Inlet oil and gas BHT data to validate temperature correction for drilling disturbances. INTERIOR Delta Junction: Delta Junction is located approximately 100 miles southeast of Fairbanks. This location is advantageous for new well locations because it would fill a data gap in the heat flow between Fairbanks and Tok, Alaska. This area has a complex geologic and tectonic history and has known gold and geothermal resources. Understanding the thermal signature associated with this geology rich in resources could prove beneficial in future resource exploration. SOUTH CENTRAL Glenallen/Gakona Junction: Glenallen and Gakona Junction are located near the intersection of the Richardson and Glenn highways, west of the Wrangell Mountains. This is another complicated location, next to the Wrangell Mountains to the east and the Denali fault to the north. Heat flow values from oil and gas well data show an above-average heat flow for the area, but these determinations are low quality. High quality heat flow data including an ETL and rock samples for thermal conductivity at this location could be used as a calibration for the oil and gas data points associated with the Copper River Basin, adding reliability to these data. Data at this location could be compared with data to the north near Tok to test the hypothesis of the Denali fault as a thermal boundary and would establish a hard constraint for future heat flow contouring and exploration north and south of the fault. A heat flow point here would also give a better constraint on the extent of a D-1 heat flow anomaly associated with the Wrangell volcanism and provide thermal data within the proposed Aleutian arc volcanic gap. SOUTHEAST PENINSULA Sitka Vicinity: The Southeast Peninsula has a high density of hot and warm springs, and several volcanoes. Heat flow research in the area by Sass et al. (1981) attributes inconsistent heat flow measurements to erroneous readings. Brief examination of the correlation of faults to hot springs suggests there may be a tectonic explanation to the presumably erratic heat flow in the Southeast. This hypothesis can be tested with a new heat flow measurement strategically placed within the region testing critical area away from the current heat flow points. A well drilled near Sitka could serve a double purpose, also testing if there is any effect from the Mt. Edgecumbe eruption in 2220 BC that could be used for district heating, or perhaps even power generation. SEWARD PENINSULA Gradient Hole Cross Section: The Seward Peninsula has many hot springs that are spatially dispersed as well as the only section of the Central Alaskan Hot Spring Belt that has volcanoes. These and other observations have led people to propose a rifting related heat source for the Seward Peninsula (Turner et al., 1981; Kolker, 2008). This theory would imply a more prominent, disseminated heat source across the whole Peninsula versus other locations in the Central Alaskan Hot Spring Belt where geothermal potential may be only local to certain granitic plutons. This is a fundamental difference that can be tested through drilling several wells across the Seward Peninsula. The results from these wells could define the future direction of exploration for geothermal resources in this region. Kotzebue: There are two BHT-C data points with relatively lower confidence levels near the city of Kotzebue, both with above average heat flow. Little is known about the wells or the geology, but there is a perceived high heat flow near a population center. Any hot water resource would be helpful to the city of Kotzebue for either direct use applications or electricity production. Additionally, a data point near Kotzebue could provide a control on the boundary of the “theoretical” Seward Peninsula heat flow anomaly. Purcell Mountain Area: Purcell Mountain is a plutonic body associated with two hot springs, called Upper and Lower Division. A cluster of hot springs would not be enough to suggest drilling to search for a geothermal resource, however, the Purcell Mountain area is also associated with recent (1973- present) seismicity. Recent seismicity implies high permeability in the area and active faulting. Surface manifestations in the form of hot springs, and perceived permeability from the active faulting give compelling evidence for future research provided that electricity, if produced, could be transported to a nearby need. D-2 7a : : : savew 18 a33°w Map Legend Heat Flow, mW/m? Map Symbols Bold colors supported by data Light colors inferred by regional geology Heat Flow Data 30-39 40-49 50-59 60-69 70-79 80-89 90-99 100-110 110+ F Select Cities Hot Springs >40 °C Hot Springs <40 °C Volcanoes ——— Contour Lines Figure D-1. 2013 Heat Flow Map of Alaska with suggested future sites for geothermal exploration indicated by blue circles. These sites attempt to co-locate areas that will satisfy the criteria of 1) a local population with an energy need, 2) relevance to understanding broad thermal regimes of Alaska, and 3) potential for having a geothermal resource. D-3 Notes Notes