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Donald A. Singer

Publications and source records attributed to Donald A. Singer.

At least 55 records · Page 3Linked to original sources
USGS1996

Application of a feedforward neural network in the search for kuroko deposits in the Hokuroku District, Japan

A feedforward neural network with one hidden layer and five neurons was trained to recognize the distance to kuroko mineral deposits. Average amounts per hole of pyrite, sericite, and gypsum plus anhydrite as measured by X-rays in 69 drillholes were used to train the net. Drillholes near and between the Fukazawa, Furutobe, and Shakanai mines were used. The training data were selected carefully to represent well-explored areas where some confidence of the distance to ore was assured. A logarithmic transform was applied to remove the skewness of distance and each variable was scaled and centered by subtracting the median and dividing by the interquartile range. The learning algorithm of annealing plus conjugate gradients was used to minimize the mean squared error of the scaled distance to ore. The trained network then was applied to all of the 152 drillholes that had measured gypsum, sericite, and pyrite. A contour plot of the neural net predicted distance to ore shows fairly wide areas of 1 km or less to ore; each of the known deposit groups is within the 1 km contour. The high and low distances on the margins of the contoured distance plot are in part the result of boundary effects of the contouring algorithm. For example, the short distances to ore predicted west of the Shakanai (Hanaoka) deposits are in basement. However, the short distances to ore predicted northeast of Furotobe, just off the figure, coincide with the location of the Nurukawa kuroko deposit and the Omaki deposit, south of the Shakanai-Hanaoka deposits, seems to be on an extension of short distance to ore contour, but is beyond the 3 km limit from drillholes. Also of interest are some areas only a few kilometers from the Fukazawa and Shakanai groups of deposits that are estimated to be many kilometers from ore, apparently reflecting the network's recognition of the extreme local variability of the geology near some deposits.

Mathematical Geology↗
USGS1995

World class base and precious metal deposits; a quantitative analysis

Over 62 percent of the 193,000 metric tons of gold discovered to date is located in four countries and more than 68 percent occurs in four types of mineral deposits. About 55 percent of the 1,740,000 metric tons of silver found is in four countries and 45 percent is in four types of deposits. Fifty-six percent of the 1.52 billion metric tons of discovered copper is from four countries and four types of deposits contain 88 percent of the total. Over 50 percent of both the 713,000,000 metric tons of zinc and 349,000,000 metric tons of lead discovered to date come from four countries and 70 percent of both metals occur in four types of deposits. All discovered gold would fit in a cube with a height oF 22 m, silver in a 55-m cube, copper in a 550-m cube, zinc in a 460-m cube, and lead in a 310-m cube. At least 74 percent of gold, silver, zinc, and lead is in deposits having average grades above the respective median grades and 44 percent of copper is in deposits with average grades above the median grade of all deposits. Lower grade deposits contain less total metal than higher grade deposits. Tonnage of mineralized rock is an even better predictor of contained metal with over 96 percent of each metal's total residing in deposits having greater than median size and between 47 and 79 percent of metal contained in the largest 10 percent of deposits. World class deposits, defined as the upper 10 percent of deposits in terms of contained metal, account for over 86 percent of all gold, 79 percent of silver, 84 percent of copper, 71 percent of zinc, and 73 percent of lead. These giant deposits contain at least 100 metric tons (3.2 Moz) gold, 2,400 metric tons (77 Moz) silver, 2 million metric tons copper, 1.7 million metric tons zinc, or 1 million metric tons lead. Mineral deposits occur rarely in the earth's crust and large ones are especially uncommon. This analysis shows that only the unusually large deposits can significantly affect supply.

Economic Geology↗
USGS1992

Predicting sizes of undiscovered mineral deposits; an example using mercury deposits in California

A critical part of the exploration for mineral deposits or of quantitative mineral resource assessments is the estimation of how large undiscoveredeposits might be. Typically, this problem is addressed using grade and tonnage models in which a major source of variation in possible sizes is accounted for by the differences in types of deposits (Cox and Singer, 1986; Mosier and Page, 1988; Bliss, 1992). It is clear from studies of petroleum exploration that larger oil fields tend to be found early in the process (Arps and Roberts, 1958). If the same behavior exists in mineral exploration, then tonnage models constructed from local data may be biased estimators of the tonnages of any remaining undiscoveredeposits in the area. Although Singer and Mosier (1981) showed that larger porphyry copper deposits should be found earlier than smaller deposits in a given geologic and exploration environment, there are no definitive studies that we could find which actually test the hypothesis that larger mineral deposits are discovered early in the exploration of a region. In this paper the hypothesis that larger mineral deposits are discovered early in the exploration of a region is tested by examining the relationship between discovery order and size of known mercury deposits in the California Coast Ranges. We then present a new maximum likelihood approach to modeling the size distribution of undiscovered mineral deposits by examining the sizes of the mercury deposits discovered early in the exploration process.

Economic Geology↗
USGS1991

Application of the FINDER system to the search for epithermal vein gold-silver deposits : Kushikino, Japan, a case study

The FINDER system employs geometric probability, Bayesian statistics, and the normal probability density function to integrate spatial and frequency information to produce a map of probabilities of target centers. Target centers can be mineral deposits, alteration associated with mineral deposits, or any other target that can be represented by a regular shape on a two dimensional map. The size, shape, mean, and standard deviation for each variable are characterized in a control area and the results applied by means of FINDER to the study area. The Kushikino deposit consists of groups of quartz-calcite-adularia veins that produced 55 tonnes of gold and 456 tonnes of silver since 1660. Part of a 6 by 10 km area near Kushikino served as a control area. Within the control area, data plotting, contouring, and cluster analysis were used to identify the barren and mineralized populations. Sodium was found to be depleted in an elliptically shaped area 3.1 by 1.6 km, potassium was both depleted and enriched locally in an elliptically shaped area 3.0 by 1.3 km, and sulfur was enriched in an elliptically shaped area 5.8 by 1.6 km. The potassium, sodium, and sulfur content from 233 surface rock samples were each used in FINDER to produce probability maps for the 12 by 30 km study area which includes Kushikino. High probability areas for each of the individual variables are over and offset up to 4 km eastward from the main Kushikino veins. In general, high probability areas identified by FINDER are displaced from the main veins and cover not only the host andesite and the dacite-andesite that is about the same age as the Kushikino mineralization, but also younger sedimentary rocks, andesite, and tuff units east and northeast of Kushikino. The maps also display the same patterns observed near Kushikino, but with somewhat lower probabilities, about 1.5 km east of the old gold prospect, Hajima, and in a broad zone 2.5 km east-west and 1 km north-south, centered 2 km west of the old gold prospect, Yaeyama.

Geoinformatics↗
USGS1990

Program to prepare standard figures for grade-tonnage models on a Macintosh

Grade-tonnage models are frequency distributions of deposit tonnage and grades of mineral deposits of a specific type. The program described here allows users to prepare standard figures of grade and tonnage distributions and display the deposit name associated with any of the data points. Titles and scales appropriate for most deposit types are plotted automatically for tonnage, Cu, Ni, Sn, Nb, W, Au, Hg, Mo, Zn, Pb, Ag, Co, Pt, Pd, Sb, Fe, Cr, Mn, and Ba.

Book chapter↗
USGS1988

Integrating spatial and frequency information in the search for kuroko deposits of the Hokuroku District, Japan

A new method (FINDER) that uses the area of influence and Bayesian statistics to aid in selection of target areas on the basis of one or more variables and multiple observations was tested with drill hole data. A previously defined bimodal distribution of Na 2 O with the low sodium group confined to a 1.5 X 3.0-km zone beneath the cluster of deposits at Fukazawa was used as a control area for one test of FINDER. Using the Na 2 O means and standard deviations for the control area and minimum Na 2 O values from 174 drill holes, a probability map of centers of sodium depletion is produced for the Hokuroku district. High probability areas correspond to the known deposits that should have been rediscovered and to several areas without known deposits.Use of X-ray data from 165 drill holes, some of which also have chemical analyses, led to the identification of two additional variables, sericite and gypsum plus anhydrite, that allow more drill holes to be used and that expand the areas of influence around drill holes. Sericite is enriched up to 2.15 km and gypsum plus anhydrite up to 3.5 km from the centroid of the control area Fukazawa deposits. For the deposit groups with X-ray data nearby, Fukazawa, Shakanai, and Furutobe, a pattern of sericite enrichment, kuroko deposits, and gypsum plus anhydrite enrichment over 4 or 5 km is shown.With sodium, sericite, and gypsum plus anhydrite, FINDER's high probability areas include each of the four groups of kuroko deposits that should have been rediscovered and only one known deposit that is much smaller than Fukazawa is missed. Several large areas that are favorable centers of undiscovered deposits and other areas that are unlikely centers of deposits are also identified.

Hokuroku District↗
USGS1988

Models of grades and tonnages of some lode tin deposits

Descriptive and grade/tonnage models have recently been built for many types of deposits. Such models consist of descriptions of mineralogy, host rocks, ore textures, controls, alteration, geochemical signatures, age, and tectonic settings, together with statistical models of grades, tonnages, and contained metal of deposits of each type. The models are used to identify areas that may contain undiscovered deposits of given types, to convey to non-geologists an idea of the importance of such deposits, and to test and refine classifications of mineral deposits. Descriptive and grade/tonnage models have recently been built for five types of primary tin deposits: rhyolite-hosted such as in Mexico; hydrothermal lodes such as in Cornwall, England, and the Herberton district, Queensland; replacement (or exhalative?) such as Renison Bell, Tasmania; skarn such as at Lost River, Alaska; and greisen such as in the Erzgebirge. Analyses of frequency distributions of tonnage, contained metal, tin grades and the relationships between these variables show that the deposits fall into four well-defined domains that have definite geological characteristics. Rhyolite-hosted, or Mexican, deposits contain a median of 4 t of tin and have a median grade of 0.4% Sn. Hydrothermal lode deposits have the highest grades. Half of such deposits have grades over 1.0% Sn, and the majority contain more than 1,000 t Sn. Large hydrothermal vein deposits contain more than 50,000 t Sn. Replacement (or exhalative?) deposits contain the largest amount of tin (median = 40,000 t). They are only of slightly lower grade (median = 0.80% Sn) than the hydrothermal lodes. Greisen or stockwork deposits have larger tonnages than replacement deposits, but contain less tin (median = 25,000 t).They are also of much lower grade (median = 0.3% Sn). Though grades and tonnages are available for only four skarn deposits, they appear to be more like greisen deposits than replacement deposits when compared using grades, tonnage and contained tin. Although these individual models of primary tin deposits must be regarded as preliminary because of the relatively small number of deposits upon which they are built, they clearly demonstrate differences among types and provide basic information that can be useful in making decisions about exploration strategy, land classification, and tin supply.

Book chapter↗
USGS1986

Quantitative estimation of undiscovered mineral resources: A case study of US Forest Service Wilderness tracts in the Pacific Mountain system

The need by land managers and planners for more quantitative measures of mineral values has prompted scientists at the U.S. Geological Survey to test a probabilistic method of mineral resource assessment on a portion of the wilderness lands that have been studied by the Survey during the past 20 years. A quantitative estimate of undiscovered mineral resources is made by linking the techniques of subjective estimation, geologic mineral deposit models, and Monte Carlo simulation. The study, which uses grade-tonnage and occurrence models for 21 geologic deposit types, considers 91 U.S. Forest Service wilderness tracts in California, Nevada, Oregon, and Washington. Estimates of the amounts of the 11 metals contained in undiscovered mineral deposits of the types studied range from negligible to several years of U.S. consumption. Although these estimates are limited to metals contained in undiscovered deposits of a small number of metallic mineral deposit types, the assessment procedure can be expanded by the use of additional deposit models and by using information about identified mineral resources. This will allow models of economic processes such as exploration, development, and production to be applied.

Economic Geology↗
USGS1986

Relationship of grade, tonnage, and basement lithology in volcanic-hosted epithermal precious-and base-metal quartz-adularia-type districts

Examination of grades, tonnages, and basement rocks for 88 epithermal precious- and base-metal quartz-adularia-type districts in North, Central, and South America, and Japan reveals that the type of basement rock below the mineralized veins is useful for predicting grade and size of deposits. Epithermal districts overlying basement with salt and evaporites, or rocks with trapped sea water, have a median tonnage (production and reserves) of 1.4 million metric tons and median grades of 1.5g/t Au, 130g/t Ag, 2.5%Pb, 1.7%Zn, and 0.16%Cu. Districts overlying sedimentary basements have a median tonnage of 0.77 million metric tons and median grades of 7.5g/t Au, 110g/t Ag, <0.025%Zn, <0.005%Cu, and <0.001%Pb. Districts overlying igneous basements have a median tonnage of 0.3 million metric tons and median grades of 5.9g/t Au, 38g/t Ag, <0.25%Zn, <0.002%Cu, and <0.003%Pb. This investigation suggests that basement rocks affect vein components in epithermal precious- and base-metal quartz-adularia-type deposits.

Mining Geology↗