1 PROJECT SUMMARY Feasibility Test of a New ...

PROJECT SUMMARY Feasibility Test of a New Exploration Tool for the Gold-Silver-Telluride Mineral Deposits of CO, WY, and MT PD/PI: Turner, Lawrence D., President/managing geologist, DIR Exploration, Inc.

DIR established a mineral exploration method in 2009 that estimates the magnitude of concealed uranium ore resource from surface rock samples taken from northern Arizona breccia pipes. In 2016 DIR began to apply the same approach to the gold-silver-telluride ore bodies of the Cripple Creek district of Colorado.

The purpose of the proposed research is to verify that the innovation works as well for gold-silver-telluride deposits as it does for northern Arizona breccia pipes. This will be done by using the new approach to guide the research program throughout and then use conventional mineral exploration techniques to determine comparative results. Work to date has identified ten (10) multi-square mile areas within central Colorado that appear, according to the innovation, to contain economic quantities of gold-silver-telluride mineralization.

The proposed research is relevant to the goals of the FY 2017 USDA NIFA SBIR program in that, if shown to be valid, the new exploration method for the gold-silvertelluride mineralization of CO, WY, and MT will substantially reduce the amount of mineral exploration surface impact on CO, WY, and MT public lands managed by the US Forest Service and BLM by minimizing the amount of surface drilling required in goldsilver-telluride mineral exploration. If the new tool is also shown to be more efficient than conventional mineral exploration approaches, it will maintain or increase rural mining employment in the three states. These potential effects would address the major NIFA program goals of supporting the sustainable use of natural resources, and increasing rural prosperity/rural-urban interdependence.

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PROJECT NARRATIVE FEASIBILITY TEST OF A NEW EXPLORATION TOOL FOR THE GOLD-SILVER-TELLURIDE MINERAL DEPOSITS OF COLORADO, WYOMING, AND MONTANA Responsiveness to USDA SBIR Program Priorities and National Challenge Areas The chief benefit conferred to federal and state land and environmental management agencies in Colorado, Wyoming, and Montana by the success of the proposed research would be an extremely strong – as much as 99% -- reduction in Au-Ag-Te mineral exploration project oversight workload. Further, environmental disturbance related to these specific mining-related forest activities would be less than 1% of the long run status quo, as would total exploration costs to the domestic Au-Ag-Te gold mining industry. At the same time, a more consistent and higher Au-Ag-Te ore deposit discovery rate of higher quality ore from use of the innovation would reduce fossil energy use related to the mining of domestic gold deposits (Turner 2000), and make high compensation gold mining employment in rural Colorado, Wyoming, and Montana much more predictable and reliable for a considerable period of time. This being said, it is apparent that the proposed research is responsive to the “Energy Efficiency and Alternative and Renewable Energy” USDA SBIR Program Priority Area, and to the “Climate Variability and Change” NIFA National Challenge Area with their primary goal of reducing fossil energy use. Because most lands open to mineral entry in Colorado, Wyoming, and Montana potentially containing undiscovered gold-silvertelluride (“Au-Ag-Te”) mineral deposits are located on National Forests, the proposed research work also addresses the NIFA FY 2017 research priority of reducing ecological damage by forest operations under the NIFA Forests and Related Resources research topic area. The specific mining industry-related application of the general exploration innovation being tested here is expected to reduce the number of Au-Ag-Te mineral prospects that need to be examined before economic discovery, thereby improving the current level of mineral exploration industry productivity, and raising the long run Au-Ag-Te mineral deposit discovery rate in the three western US states concerned. These industrial goals therefore ultimately address the NIFA FY 2017 research priorities under the NIFA Rural and Community Development research topic areas of (1) developing technologies and services that protect or enhance the environment while promoting economic development, and (2) increasing opportunities for employment and income generation in rural communities. Identification and Significance of the Problem or Opportunity Explanatory preamble: In the following pages, the terms “linear equation” or “multivariable linear equation”, “algorithm”, and “translog production function” are used interchangeably to refer to the multi-variable linear equation that makes up the mineral exploration innovation being tested in the planned research program. Strictly speaking, the term “translog production function” is the most specific and accurate term for the 1

equation concerned as it has a specific mathematical and economic form that lends considerably to the accuracy of the estimated equation. “Algorithm” is the most general term for such an equation, while “linear equation” is of moderate specificity. See Turner and Turner, 2016, for more explanation. There are numerous metal ore deposit types, each with somewhat characteristic mineral and metal assemblages, country rock, and structural associations. Despite these useful scientific classifications, records indicate much, if not most, of the infrequent success achieved in modern mineral exploration is due to persistence of activity and expenditure, rather than effective application of observation and scientific knowledge and theory. See Figure 1.

Figure 1. The modern odds that any given exploration project will result in an economic discovery. From Kreuzer and Etheridge, 2010. Greenfields exploration is that taking place where no previous mines have been established, while brownfields exploration is carried out in districts with a history of economically successful mining.

To make things worse, during the most recent period of elevated world-wide metals exploration activity, the effectiveness of this persistence has lessened in an extremely pronounced manner. See Figure 2. The recent Figure 2 structural change in the mineral exploration industry is primarily due to progressive worldwide depletion of easily found shallow ore deposits. The more basic and more chronic problem facing the mineral exploration industry as a whole indicated in Figure 1, on the other hand, is that the opaqueness of the earth’s crust, along with its vegetative, soil, and sediment cover, creates an enormous amount of uncertainty and unpredictability for mineral exploration observers. Kahneman (2011, Chapter 21) calls such a set of conditions to making working decisions in a “low-validity environment”. Raw application of observation and scientific knowledge and theory in low-validity environments -- even by extremely educated and highly-experienced experts -- is not reliably effective and useful (ibid.).

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Figure 2. Failure of the worldwide mineral exploration industry, primarily as a result of depletion of shallow, relatively easy to discover ore deposits. From Schodde 2014, Slide 5.

Background and Rationale According to Kahneman (ibid.), however, an extremely useful antidote to the difficult problem of making valid decisions in a low-validity environment is the use of mathematical equations or algorithms that objectively and consistently capture most of the effect of the controlling variables in a given problem situation. Applying such mathematical expressions in low validity environments results in reliably better decisionmaking results than raw expert judgment (ibid.). In the mineral exploration case, any such technological advance that addresses the primary low validity problem of Figure 1 would automatically improve the problems associated with the secondary and negative structural change in the industry illustrated in Figure 2. DIR established a mineral exploration method in 2009 that estimates the magnitude of concealed uranium ore resource from surface rock samples taken from northern Arizona breccia pipes. This method is based on a multivariable linear equation derived from regression of multi-element geochemical analyses of surface samples taken from breccia pipes against the known total uranium reserves in those same pipes. See Turner and Turner (2016). This particular geochemical algorithm, applicable only to the uranium mineralization of northern Arizona breccia pipes, was ultimately validated by comparing algorithm resource predictions to published breccia pipe prospect drilling results achieved by various exploration program operators working in the region (ibid.). Although the Arizona uranium exploration and mining region is closed to new exploration and mining programs until 2031, and the DIR breccia pipe exploration algorithm therefore cannot be further applied until then, this new exploration tool will 3

allow future uranium exploration program operators in northern Arizona to avoid carrying out early drill programs on barren (non-economic) breccia pipe prospects, programs that cost over a million dollars each and take more than a year to complete. Considering it costs less than $500 to surface sample 3 to 7 breccia pipe prospects in a day, chemically analyze the collected samples, and then estimate the concealed uranium resource using the breccia pipe algorithm, the consequent scale of savings in time, money, surface disturbance, and the number of mineral prospects that need to be drillexamined to make an economically-significant ore body discovery, is obvious. In 2016 DIR began to apply the same general geochemical algorithm-deriving approach to the Au-Ag-Te ore bodies of the Cripple Creek mining district of Colorado. DIR has used the Cripple Creek mining district gold production records (Lindgren and Ransome, 1906; Louglin and Koschmann, 1935; and Thompson et al., 1985) and public domain surface rock chip geochemical data (Gott et al., 1969) to derive a multi-variable linear equation specific to Au-Ag-Te mineralization like that found at Cripple Creek. The translog production function model calculated for the Au-Ag-Te mineral deposit type is roughly similar in its controlling variables to that employed in the northern Arizona uranium-mineralized breccia pipe case (Turner and Turner, 2016), although a second geochemical barrier proxy parameter had to be added into the Cripple Creek data regression in order to account for the evident telescoping of upper sulfide-related native gold mineralization and lower sulfide-poor Au-Ag-Te mineralization. See Figure 3.1 This addition of a new mineralization control proxy was accomplished by following the McPhail study of tellurium speciation (1995) under different fluid chemistry conditions, and by using the knowledge that vanadium and manganese concentrations in country rock can serve as sensitive chemical paleo-indicators/proxies for the Eh and pH conditions conducive to the precipitation of gold and silver tellurides (Evans and Garrels, 1958; and Garrels and Christ, 1965). The high-lighted passage above contains proprietary methodological information. Although the statistical characteristics (Figure 4) and very preliminary test applications (Figures 5 and 9) of the newly-derived Au-Ag-Te mineralization algorithm are very encouraging, work still needs to be done to concretely verify that this new exploration tool can be confidently employed in field exploration for Au-Ag-Te ore deposits. The research work being proposed here will determine the technical feasibility of the new exploration approach to Au-Ag-Te ore deposits by using the algorithm to guide the entire course of the mineral exploration research program, and then, once specific exploration drilling targets are identified, by employing conventional drilling exploration methods to test the validity of the exploration innovation in the Au-Ag-Te mineral deposit case.

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Recourse to geochemical modeling of mineralizing systems and iterative hypothetical selection of controlling variables is necessary because of the limited size of readily available surface and subsurface geochemical sample sets. Given a large enough data set, much less conscious thought would have to be given to linear regression of multi-element surface sample analyses against recorded ore production cases in order to generate reasonably accurate metal deposit resource-predictive algorithms.

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Figure 3. Vertical cross-section conceptual model of Cripple Creek mineralization system after Pontius 1992, Cas and Wright, 1987 (p. 377), and Papay 2001, indicating the mineralization system activity of two separate geochemical barriers and the principal areas of operation of the four main controlling variables (purple) in the Au-Ag-Te gold resource algorithm. A lower Eh and pH barrier (AB1) evidently precipitated gold and silver as tellurides, while an upper sulfide barrier (AB2) precipitated native gold with pyrite and as auriferous pyrite. Up and down vertical migration of the AB1 geochemical barrier would have changed the active level of gold and silver telluride mineralization. See dashed vein mineralization symbol indicating the operation of this mechanism for the development of vertically-extensive telluride mineralization like that present at Cripple Creek. Unlike the northern Arizona uranium-mineralized breccia pipe algorithm precedent, the Cripple Creek algorithm estimated by DIR includes separate geochemical parameter proxies for both geochemical barriers. “Geochemical barrier” is a special geochemical term that originated in the historical USSR geological literature and refers to relatively abrupt changes in the fluid chemistry or rock chemistry that cause metals to come out of solution (Perel’man 1967). In the cases of ore deposits, the amount and concentrations of metals precipitated by the barriers are high enough to be economically useful. This approach to understanding the formation of mineral deposits in terms of geochemical barriers is extremely helpful in building geochemical models of ore body formation that can be translated into multi-element linear equations/algorithms.

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Figure 4. Graphic comparison of actual subsurface log10 gold resource values in ounces to the log10 gold resource values in ounces predicted from metal analyses of surface samples and the Au-Ag-Te algorithm (translog production function) estimated for Au-Ag-Te deposits at Cripple Creek. With an adjusted R2 value of 88.4%, the Au-Ag-Te algorithm appears accurate enough to permit surface geochemistry to function as an exploration guide to the locations of underground mineralization at the regional, mining district, or prospect scales. This statistical evidence of algorithm efficacy will require test application of the tool using conventional exploration means like surface drilling to confirm the technical feasibility of continued gold-silver exploration use of the algorithm in Colorado, Wyoming, and Montana.

Relationship with Research or Research and Development As discussed in Turner and Turner (2016), the mineral exploration innovation proposed for test here has two partial precedents in previous mineral exploration research. Miesch et al. (1959, 1960) used trace metal analyses of exposed ore material and linear regressions to estimate size of uranium deposits on the Colorado Plateau. Beus and Gregorian (1975) established multi-element means to indicate strength of geochemical barriers and degree of mineralization system exhumation by erosion. Generally speaking, the DIR mineral exploration innovation combines the independent advances made by Miesch et al. (ibid.) and Beus and Grigorian (ibid.) through the economic production function theory summarized in Heathfield and Soren (1987). Planned Phase I research will focus on delineating any structurally-controlled mineralization trends present within the ten (10) member multi-square mile Au-Ag-Te greenfields target set identified by DIR in central Colorado during 2016. These target areas were found by applying the DIR Au-Ag-Te gold resource algorithm to the public 6

domain stream sediment trace metals data of the USGS Central Colorado Assessment Project (“CCAP”; Granitto et al. 2010). This mineralization trend delineation work will be accomplished by surface sampling the ten target areas, chemically analyzing the collected samples, transforming the resulting chemical analyses into predicted gold resource values with the Au-Ag-Te mineralization algorithm, and subsequently carrying out geological mapping guided by the estimated subsurface gold resource results of the surface sampling work. If this district-scale exploration is successful, a collection of structurally-controlled mineralization trends like those already determined to be present in the Cripple Creek mining district (Figure 5) will be located and mapped within the ten Au-Ag-Te exploration target areas. This result will prepare for the Phase II work of testing a selection of the Phase I identified and mapped mineralization trends with initial surface exploration drilling. If Phase II is successful in revealing evidently continuous ore grade Au-Ag-Te and/or native gold/auriferous pyrite in drilling, the new exploration tool will have been validated for further Au-Ag-Te ore deposit exploration purposes in Colorado, Wyoming, and Montana. Figure 1 provides a reasonable basis for discussing anticipated external results if the project is successful. Mineral exploration of the sort concerned here is greenfields exploration, exploration that seeks to locate new ore deposits outside of well-established mining districts like Cripple Creek. Using conventional exploration means, according to Figure 1, the median probability of finding a new, economically-viable ore deposit outside of a recognized mining district during the execution of a single exploration drilling project is about 1 out of 360, or 0.28%. In Figure 1, it can be seen that the highest probability of making a mineral deposit discovery with a single exploration drilling project is usually in a brownfields district – a district with absolute certainty of containing economic quantities of ore – and this highest probability is about 1 out of 2, or 50%. This 50% discovery probability, then, is a good approximation of the highest probability that, industry wide, any given exploration drilling program will find economic quantities of ore under the very best of circumstances, whether the exploration is taking place in an old brownfields mining district or taking place in a newly-discovered and entirely untouched greenfields mineralization system. Assuming the exploration innovation proposed for test here is 100% accurate at the greenfields stream sediment geochemistry reconnaissance stage in identifying new Au-Ag-Te mining districts, and will thereby be getting prospect-scale mineral exploration drilling operations into the best possible neighborhood for finding ore, the above considerations suggest a maximum possible overall exploration efficiency increase multiplier of 179 (50%/0.28%=179) for the innovation being tested over conventional mineral exploration approaches. Provided the proposed research proves the exploration innovation to be reliable, and if in the long run other members of the mining exploration industry adopt the exploration innovation being tested here when carrying out Au-Ag-Te mineral exploration, then the chief benefit conferred to federal and state land and environmental management agencies in Colorado, Wyoming, and Montana would be an extremely strong reduction in mineral exploration project oversight workload. If all future Au-Ag-Te exploration work in Colorado, Wyoming, and Montana was, in fact, conducted employing the innovation concerned, then land management work load related to Au-Ag-Te exploration would be less than 1% of what it would be using conventional exploration approaches [(1 7

innovation-guided drilling project/179 conventionally-guided drilling projects) x 100% = 0.56%]. Similarly, environmental disturbance related to these specific forest activities would be less than 1% of the long run status quo, as would total exploration costs to the domestic Au-Ag-Te gold mining industry. At the same time, a more consistent and higher Au-Ag-Te ore deposit discovery rate would make high compensation gold mining employment in rural Colorado, Wyoming, and Montana much more predictable and reliable for a considerable period of time. To put these last likely consequences of the planned research into historical perspective, the still active Cripple Creek mining district has hosted gold mining since 1893, and has produced gold worth more than 32 billion current dollars over that period of time.

Figure 5. Apparent log10 subsurface gold resource ounces in the Cripple Creek mining district as estimated by the Cripple Creek Au-Ag-Te translog production function/algorithm and USGS surface rock chip sample geochemical analyses. Minimum contour level is log10 6 (antilog 1 million ounces). This map shows both the deep mineralization trend of the historical Portland-Independence-Strong underground mine cluster southeast of the Cresson Mine, and the shallow mineralization trend of Newmont’s Cresson open-pit mine. A brownfields exploration result of the Au-Ag-Te algorithm in this mining district is the clear definition of an unmined, mile long concealed mineralization trend extending northwest and southeast of the old Morning Glory mine. Small red stars mark the locations of US Geological Survey rock chip samples of Gott et al., 1969. Bold black numbers show recorded log10 oz gold production figures for mining district mines. Note the close correspondences between algorithm estimated log10 gold resource contours and bold black log10 values of historical gold production in the district.

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Technical Objectives The technical objectives of Phase I of the proposed research program are: 1. Using surface geochemical sampling and the Au-Ag-Te algorithm, detect and map Au-Ag-Te mineralization trends present in the 10 target areas identified from CCAP and private stream sediment geochemical data. Map geology, structure, and alteration ((Kelley et al., 1995), if any, coincident with any geochemicallydefined mineralization trends. 2. Using results of the above work, determine highest priority prospects, if any, for Phase II work. Soils rather than rocks will initially be sampled at the Phase I project areas. The reasons for this procedure include lower soil sample analytical costs (-30%) and the rock outcrop scarcity common in the Rocky Mountains (Gott et al., 1969). Any outcrop found within mineralization trends outlined by soil sampling will be later rock sampled during Phase I, however. It is expected that ground magnetics and apparent conductivity surveys will be required to locate Au-Ag-Te mineralization-associated structures (Kelley et al., 1995) where vegetation, talus, till, or soil prevent detailed mapping of geology, alteration, and structure. DIR possesses the geophysical equipment required for these alternative ground magnetometer and VLF means of mapping structure and gross alteration (two protonprecession magnetometers and two EM-16Rs). Note that most of the terrain that will be examined is particularly steep and thickly forestcovered, and work progress could be slower than anticipated. On the suspicion that not all 10 target areas will be completely examined in the 8-month Phase I, Phase I work will be begun on the reconnaissance target areas with the highest apparent gold resource endowment. The analytical and labor budget provided in this proposal is expected to be sufficient for Phase I examination of at least 8 of the 10 reconnaissance-identified target areas. The technical objectives of Phase II of the proposed research program would be: 1. Obtain mineral rights to the mineralized portions of the defined highest priority prospects; 2. Obtain plan of operations approval for surface drill tests of these prospects; 3. Carry out preliminary exploration drill tests; 4. Examine and chemically analyze samples obtained during drilling; and, 5. If results are positive and ore discovery is accomplished, prepare for Phase III. The general technical objective of Phase III would be to carry out sufficient exploration and ore delineation drilling to determine if the nature of the gold mineralization revealed by drilling in Phase II is sufficient to support mine development.

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Work Plan Sulfide-poor Au-Ag-Te deposits like those found within Colorado Cripple Creek mining district are among the least frequently found ore deposits sought by the gold mining industry (Table II, Robert et al., 2007), and to date no other Au-Ag-Te mining districts have been discovered in Colorado that are comparable in mineralization extent to Cripple Creek with its cumulative gold production in excess of 23 million ounces. Judging by the halting nature of the early prospecting history of the Cripple Creek mining district (Sprague 1953), however, it is possible that the difficulty in finding such ore deposits is not entirely due to the native scarcity of such mineralization, but is also caused by the fact that gold and silver tellurides are very easily weathered away in cases where such mineralization is exposed at surface (Kelley et al., 1995). The Au-Ag-Te exploration history of Colorado notwithstanding, 2015-2016 statistical analysis of public domain and private geochemical data from the Cripple Creek mining district and central Colorado by DIR has identified ten (10) separate areas on public lands that are prospective for Cripple Creek type gold mineralization. Each of these potential Au-Ag-Te target areas identified by stream sediment geochemistry transformed by the Cripple Creek gold resource translog production function (“TPF”) is, like the Cripple Creek mining district itself, within 100 miles of the NNW-trending central axis of the post-Laramide Rio Grande Rift (Tweto 1979). See Figure 6. One of the ten target areas is proximal to a historical mining district containing minor precious metal telluride mineralization in association with base metal production, while three contain mineral occurrence evidence (http://mrdata.usgs.gov/mrds/) of precious metal-rich base metal mineralization commonly associated with Au-Ag-Te ore deposition (Saunders 1986). Four are close to known precious metal vein and/or placer gold occurrences. Two of the reconnaissance target areas show no MRDS record of containing metals occurrences of any sort. Four of the ten identified Au-Ag-Te target areas are located in the Arapaho National Forest, two are in the Pike National Forest, two are in the San Isabel National Forest, one is located in the Rio Grande National Forest, and one is on ground managed by the BLM. According to Kelley et al., 1998, gold was deposited in the Cripple Creek mining district for about a two million year period beginning 31-30 million years ago. The extensional tectonics responsible for dilation in the Rio Grande Rift region along north-northweststriking (“NNW-striking”) faults like those mineralized at Cripple Creek began about 32 million years ago, just before the start of gold mineralization at Cripple Creek (ibid.). Observing the dominant, NNW-trending Rio Grande Rift-controlled mineralization trend direction in the Cripple Creek mining district (Figures 5 and 7), planned Phase I research work in each of these ten Au-Ag-Te exploration target areas is (1) sampling and chemical analysis of soil sample profiles placed perpendicular to the NNW orientation of the central axis of the Rio Grande Rift, (2) calculation of estimated subsurface gold resource values from the soil sample analyses using the Au-Ag-Te algorithm, (3) completion of follow-up spot rock chip sampling within the identified soil sample anomaly zones, and (4) detailed geological mapping, and/or ground geophysical surveying of the ground geochemically determined to be most strongly mineralized. See Figure 8. Judging from DIR study of the U.S. Geological Survey rock chip geochemical data from the Cripple 10

Creek mining district, these geochemical profiles, along with follow-up fill-in surface sampling oriented both to the northwest and northeast, are expected to define any major vein-associated Au-Ag-Te drilling targets present in each target area. Granting the success of Phase I, planned Phase II research work will primarily be exploration drilling of a select sample of the gold mineralization drilling targets identified in Phase I. Mineral drill discoveries completed in Phase II will be further explored either through mineral property lease or joint venture in preparation for eventual mining. As in the Cripple Creek mining district case, most, if not all, gold ore discovered during this research program is expected to be produced by low surface impact and low groundwater impact underground mining of low sulfide content ore (Kelley et al., 1995). Related Research or Research and Development Figures 5 and 8 show buried and near surface apparent gold resource in log10 ounces in the Cripple Creek mining district as predicted by an adaptation of the general DIR exploration innovation described and explained in detail by Turner and Turner (2016). The US Geological Survey rock chip geochemical data employed to derive these data portrayals are available online (Gott et al., 1969), as are some of the early Cripple Creek mining district gold production records also used in the regression analysis concerned (Lindgren and Ransome, 1906). A very important, but out-of-print supplement to the early Cripple Creek district gold production records provided by Lindgren and Ransome is Loughlin and Koschmann (1935). Thompson et al., 1985, provide more up to date production figures for the Ajax Mine. The linear regression estimation of the gold mineralization TPF for the Cripple Creek Au-Ag-Te mining district by DIR employed the multi-element analyses of 43 USGS surface rock samples located above 43 mine cases of recorded gold production from the district. In addition, 27 ‘blank’ cases of the USGS surface rock chip sample laboratory analyses showing no signs of being subjected to mineralization-related metal leakage (Hawkes 1957), also from the Cripple Creek mining district, were added to the regression sample set to cancel out the distorting effects of variations in background country rock trace element values on the estimated coefficients of the Au-Ag-Te mineralization TPF. See Figure 5 green diamonds for the locations of most of the surface and subsurface sample pairs used in the regression estimation of the Au-Ag-Te algorithm.2 The highlighted sentence above contains proprietary methodological information. The residuals (Figure 4) of the estimated TPF generally show errors of estimation of log10 gold resource of up to one magnitude from actual mined values, a fact partially helping to explain log10 apparent gold resource amplification and attenuation visible in Figures 5 and 8. A more important factor responsible for the local log10 gold resource sample-point estimation exaggerations shown in these two Figures, however, is the reliance that Gott et al., 1969 (pp. 2-3) unavoidably placed on prospect pit dump grab 2

Some peripheral sample cases are not shown in Figure 5 because of the necessity of trimming the much larger original map to make central map details more legible.

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Figure 6. Index map showing locations of Phase I work areas. This map contains proprietary information; namely, the locations of the mineral exploration target areas thought to contain valuable Au-Ag-Te mineralization. Strong stream sediment anomalies not marked here as target areas are either located on private ranchingfarming-mining lands, or are withdrawn from mineral entry by wilderness designation.

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Figure 7. Illustration of the dominant northwesterly, Rio Grande Rift-related, trend of mineralization in the Cripple Creek mining district using surface rock chip gold analyses values from Gott et al., 1969. Note that this conventional use of surface rock chip gold analyses does not reveal the buried gold-silver mineralization already mined in the Ajax-Portland-Independence-Strong underground mine cluster, nor does it indicate the unmined concealed gold-silver resource northwest and southeast of the old Morning Glory mine revealed by the Au-AgTe algorithm in Figure 5. Most of the Cripple Creek gold-silver production to date (~8,000,000 oz gold) has come from the concealed/buried mineralization of the Ajax-Portland-Independence-Strong cluster. Admittedly, surface rock chip gold values are very useful in locating shallow ore bodies for open pit mines like the Cresson.

samples for surface sample material. These surface rock samples are all, strictly speaking, geochemically unrepresentative, ‘high-graded’ sample material. Their necessary use also unavoidably introduces error to the regression estimation of the Cripple Creek Au-Ag-Te log10 gold resource TPF and gold resource projections made from that TPF. Nevertheless, comparing the surface rock chip gold values of Figure 7 to the apparent near surface and subsurface gold mineralization of Figures 5 and 8, it can be seen that the rock chip geochemical data transformed by the Cripple Creek Au-Ag-Te TPF successfully predict the projections of subsurface vein mineralization not indicated by the gold values of the surface rock samples taken by the USGS at the Cripple Creek mining district in Figure 7. Figure 7 surface gold values, for example, very clearly show the shallow gold mineralization exploited by the modern Cresson open pit but, unlike Figure 13

5 and 8’s apparent log10 gold resource contours, do not indicate the existence of the concealed ore bodies like the much older (and more productive) Independence, Strong, and Portland underground gold mines. As far as future exploration in this old brownfields mining district is concerned, Figure 5 and 8 log10 apparent gold resource contour data suggest, among other things, the existence of a mile long, so far undiscovered, NNW-trending, vein-hosted gold mineralization system NNW and SSE of the Morning Glory shaft. Surface and underground mining records from the district indicate the rock in this particular area has received very little, if any, concrete prospecting or exploration work since mining began in the district in 1893. The evident ability of the new exploration method, indicated here and proven in northern Arizona (Turner and Turner, 2016) to detect deeply concealed mineralization is particularly advantageous in the current era of shallow ore deposit scarcity and declining average ore grades (Schodde 2014). Figure 9 shows local results of using the Cripple Creek mining district Au-Ag-Te TPF to transform the CCAP stream sediment geochemical data (Eppinger et al, 2015; Granitto et al., 2010) into log10 apparent gold resource values. Both the Cripple Creek mining district and the much smaller-sized Carbonate King/Guffey Au-Ag-Te occurrence 20 miles west of Cripple Creek (Lovering and Goddard, 1950) show up distinctly in the transformed CCAP stream sediment data set. This Figure is an illustration of the apparent utility of the new exploration method in conducting greenfields reconnaissance exploration work, work having the goal of locating ground containing valuable metals deposits outside of already established mining districts. TPF-transformed CCAP and private geochemical data covering the part of Colorado shown in Figure 6 were used to identify the ten Au-Ag-Te target areas that are the test locations of this research program. Potential Post Application The proposed research has specific and general commercialization potential after Phase I funding. Specifically speaking, if the planned research work is successful and instances of appreciable amounts of Au-Ag-Te ore are located as a result of this feasibility test of a new mineral exploration tool, then there is a reasonable likelihood that the discovery or discoveries will be developed into operating gold-silver mines. More generally speaking, however, a successful conclusion to the research program will confer further credibility to the general exploration geochemical innovation being developed by DIR. Increased credibility should help the new gochemical/geostatistical approach to the difficult work of mineral exploration become accepted more widely by other members of the mineral exploration community. Remarks on the potential benefit of the research to the federal government have already been made on pages 1 and 7 of this narrative. It is also possible that federal organizations like the BLM and US Forest Service would find the validated Au-Ag-Te gold resource translog production function/algorithm useful in conducting future mineral inventories on public lands managed by the DOI and USDA in Colorado, Wyoming, and Montana. 14

Figure 8. In Phase I of the planned research program, anomalous stream sediment drainage cells like those outlined here in red at the Cripple Creek mining district would be soil sampled along each profile line shown. Judging by the here-contoured results of the random interval rock chip sampling carried out by the USGS (Gott et al., 1969), this profile sampling should reveal any existing gold-telluride mineralization trends like those found at Cripple Creek in the eleven gold-telluride project areas recently identified by stream sediment reconnaissance work in central Colorado (Figure 6). With additional fill-in rock chip and soil sampling, geological mapping, and possible ground geophysical surveying, any such discovered mineralized structures will be made ready for conventional exploration drilling work.

The question of the advantages of the technology being tested here has over competing methods in terms of performance, efficiency, and cost is discussed on pages 2-4, and 6-8 of this narrative. DIR Exploration, Inc., is a subchapter-S Arizona corporation formed in 1987. Depending on its level of activity, it employs from 1 to 5 geologists and geotechnicians. Its field of interest is metals mineral exploration, and the company functions as a consultant and mineral exploration program operator. The business has managed exploration research projects of the Phase I and Phase II scale for twelve years, and ore deposit delineation exploration drilling work at the Phase III scale for two years.

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Figure 9. Contoured results of applying the Cripple Creek Au-Ag-Te algorithm to geochemical analyses from USGS stream sediment samples draining two known and adjacent Au-Ag-Te mineral occurrences in central Colorado. The minimum log10 contour is 5, or 100,000 ounces gold. Round gray circles mark the locations of stream sediment samples re-analyzed as a part of the Central Colorado Assessment Project of the US Geological Survey (Eppinger et al., 2015; Granitto et al., 2010). Red lines within the Carbonate King/Guffey and Cripple Creek Au-Ag-Te stream sediment anomalies mark the outside boundaries of the stream sediment drainage cells that provided the stream sediment material creating each anomaly. Similar stream sediment anomalies were found at each of the ten Au-Ag-Te project areas that will further test the geochemical exploration innovation behind this research proposal. Note the very high contrast in stream sediment anomaly amplitude between the very strongly mineralized Cripple Creek mining district and the very weakly mineralized Guffey mining district. The “North Fork Dispersion Train” (sic) and terminal strong stream sediment anomaly either represents natural transportation of anomalous material in the North Fork sands and gravels, or is the result of possible ore train spills. Early Cripple Creek ore was shipped out of the district by a narrow gauge railroad passing down the entire North Fork drainage.

Satisfying the Public Interest As already indicated on page 1 of this narrative, the proposed research will incrementally satisfy the USDA “Strategic Goal 1: Assist Rural Communities to Create Prosperity so They are Self-Sustaining, Repopulating, and Economically Thriving” by helping to provide a more dependable and sustained level of mining industry-related employment and business. See https://headwaterseconomics.org/wphw/wp-content/uploads/eps-samplereports/mining.pdf for a topical (Montana) and current comparative tabulation of miningrelated wages, and for graphics illustrating the positive economic effect of the nonfuels mining industry on communities in the rural West.

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