Examining Risk in Mineral Exploration

Successful mineral exploration strategy requires identification of some of the risk sources and considering them in the decision-making process so that controllable risk can be reduced. Risk is defined as chance of failure or loss. Exploration is an economic activity involving risk and uncertainty, so risk also must be defined in an economic context. Risk reduction can be addressed in three fundamental ways: (1) increasing the number of examinations; (2) increasing success probabilities; and (3) changing success probabilities per test by learning. These provide the framework for examining exploration risk. First, the number of prospects examined is increased, such as by joint venturing, thereby reducing chance of gambler's ruin. Second, success probability is increased by exploring for deposit types more likely to be economic, such as those with a high proportion of world-class deposits. For example, in looking for 100+ ton (>3 million oz) Au deposits, porphyry Cu-Au, or epithermal quartz alunite Au types require examining fewer deposits than Comstock epithermal vein and most other deposit types. For porphyry copper exploration, a strong positive relationship between area of sulfide minerals and deposits' contained Cu can be used to reduce exploration risk by only examining large sulfide systems. In some situations, success probabilities can be increased by examining certain geologic environments. Only 8% of kuroko massive sulfide deposits are world class, but success chances can be increased to about 15% by looking in settings containing sediments and rhyolitic rocks. It is possible to reduce risk of loss during mining by sequentially developing and expanding a mine—thus reducing capital exposed at early stages and reducing present value of risked capital. Because this strategy is easier to apply in some deposit types than in others, the strategy can affect deposit types sought. Third, risk is reduced by using prior information and by changing the independence of trials assumption, that is, by learning. Bayes' formula is used to change the probability of existence of the deposit sought on the basis of successive exploration stages. Perhaps the most important way to reduce exploration risk is to employ personnel with the appropriate experience and yet who are learning.     

KAr isochron study of the Tudor Gabbro,Grenville Province,Ontario

Ten whole-rock samples from the Tudor Gabbro, Grenville Province, Ontario, Canada have been dated by the KAr method. The ages calculated by the conventional method range from 900 m.y. to 2040 m.y. On an isochron plot, three samples from a sampling site near the northern border of the gabbro lie along a 670-m.y. isochron with an initial⁴⁰Ar/³⁶Ar ratio of about 17,300 whereas all other samples lie along another 670-m.y. isochron with an initial ratio of about 5000. Although it is not certain yet as to what geological event the isochron age represents, the results clearly demonstrate that the effect of initial argon can be significant even on old samples such as these.     

Relationships between Kuroko volcanogenic massive sulfide (VMS) deposits, felsic volcanism, and island arc development in the northeast Honshu arc, Japan

The northeast (NE) Honshu arc was formed by three major volcano-tectonic events resulting from Late Cenozoic orogenic movement: continental margin volcanism (before 21?Ma), seafloor basaltic lava flows and subsequent bimodal volcanism accompanied by back-arc rifting (21 to 14?Ma), and felsic volcanism related to island arc uplift (12 to 2?Ma). Eight petrotectonic domains, parallel to the NE Honshu arc, were formed as a result of the eastward migration of volcanic activity with time. Major Kuroko volcanogenic massive sulfide (VMS) deposits are located within the eastern marginal rift zone (Kuroko rift) that formed in the final period of back-arc rifting (16 to 14?Ma). Volcanic activity in the NE Honshu arc is divided into six volcanic stages. The eruption volumes of volcanic rocks have gradually decreased from 4,600?km³ (per 1?my for a 200-km-long section along the arc) of basaltic lava flows in the back-arc spreading stage to 1,000?C2,000?km³ of bimodal hyaloclastites in the back-arc rift stage, and about 200?km³ of felsic pumice eruptions in the island arc stage. The Kuroko VMS deposits were formed at the time of abrupt decrease in the eruption volume and change in the mode of occurrence of the volcanic rocks during the final period of back-arc rifting. In the area of the Kuroko rift, felsic volcanism changed from aphyric or weakly plagioclase phyric (before 14?Ma), to quartz and plagioclase phyric with minor clinopyroxene (12 to 8?Ma), to hornblende phyric (after 8?Ma), and hornblende and biotite phyric (after 4?Ma). The Kuroko VMS deposits are closely related to the aphyric rhyolitic activity before 14?Ma. The rhyolite was generated at a relatively high temperature from a highly differentiated part of felsic magma seated at a relatively great depth and contains higher Nb, Ce, and Y contents than the post-Kuroko felsic volcanism. The Kuroko VMS deposits were formed within a specific tectonic setting, at a specific period, and associated with a particular volcanism of the arc evolution process. Therefore, detailed study of the evolutional process from rift opening to island arc tectonics is very important for the exploration of Kuroko-type VMS deposits.     

Nitrogen isotope fractionations in the Fischer-Tropsch synthesis and in the Miller-Urey reaction

Nitrogen isotope fractionations have been measured in Fischer-Tropsch and Miller-Urey reactions in order to determine whether these processes can account for the large¹⁵N/¹⁴N ratios found in organic matter in carbonaceous chondrites. Polymeric material formed in the Fischer-Tropsch reaction was enriched in¹⁵N by only 3‰ relative to the starting material (NH₃). The¹⁵N enrichment in polymers from the Miller-Urey reaction was 10–12‰. Both of these fractionations are small compared to the 80–90‰ differences observed between enstatite chondrites and carbonaceous chondrites. These large differences are apparently due to temporal or spatial variations in the isotopic composition of nitrogen in the solar nebula, rather than to fractionation during the production of organic compounds.     

Refinement of the age of the Middle Miocene Fort Ternan Beds,Western Kenya,and its implications for Old World biochronology

It has become increasingly obvious over the past two decades that the fossiliferous strata at Fort Ternan, Kenya, are probably somewhat younger than 14 Ma, an age which has long been attached to the deposits. This realisation flows from geological and biochronological observations. In order to test the hypothesis, resampling of all the lava flows in the region of Fort Ternan was undertaken in 2003, especially those underlying the Fort Ternan Beds in the Kipchorion Gorge where the sequence is the most complete. Samples obtained from lava flows underlying and overlying the fossil beds were analysed for anorthoclase K/Ar and ⁴⁰Ar/³⁹Ar and biotite ⁴⁰Ar/³⁹Ar age determinations. The results reveal that the age of the fossiliferous sediments is ca $13.7\pm 0.3\text{Ma}$. Since Fort Ternan yielded the ‘core fauna’ that defines Faunal Set IV of the East African biochronological sequence this refinement of its age will impact on age estimates of neighbouring Faunal Sets, as well as on other faunas correlated to Fort Ternan, including those in Europe belonging to MN Zones MN 5, MN 6 and MN 7/8. To cite this article: M. Pickford et al., C. R. Geoscience 338 (2006).     

Further Occurrence of Brown Ores in Kuroko-type Deposits in Japan

Abstract: The occurrence of so-called brown ore from the Kuroko-type deposits in Japan was examined. Brown ore specimens from the Kannondo, Inarizawa, Matsumine, Fukazawa, Uchinotai, Kosaka (orebody unknown) and Nurukawa deposits have been found in the ore collection stored by Dowa Mining Co. Ltd. and the subsidiary companies. In addition, occurrences from the Fukazawa, Matsumine, Ezuri, Shakanai, and Ginzan deposits were previously reported. The brown ore is characterized by its color and by its higher Ag concentration (up to around 2,400 g/t) than ordinary black ores. This type of ore occurs commonly in the Kuroko-type deposits in Japan, whereas its extent is limited. The brown ore is a type of Au-rich massive sulfide ore formed in submarine hydrothermal system.     

Measurement of a time-weighted average concentration of polycyclic aromatic hydrocarbons in seawater: An improved procedure of blue rayon hanging technique for monitoring benzo(a)pyrene

We have proposed a time-weighted measurement using blue rayon that selectively adsorbs and concentrates polycyclic aromatic hydrocarbons (PAH), e.g. benzo(a)pyrene (BaP). Though the method was demonstrated to be a convenient way to monitor PAH, the amount adsorbed to the blue rayon depends on the intensity of water stream and the level of PAH. The intensity of water stream was measured by ‘plaster ball’ method, while TWA of PAH in water was measured by a portable sampler using solid phase extraction cartridge. A level of BaP measured by the original blue rayon technique was corrected in this way by the water stream intensity, which correlated well with the TWA of BaP measured by the portable sampler. The improved blue rayon hanging method was applied to several field sites in the Seto Inland Sea of Japan. TWA of BaP ranged from 0.08 to 3.78 ngl⁻¹. These results showed the possibility that the method could be used to evaluate pollution in aquatic environment.     

Introduction to Special Issue on the Symposium on the Application of Neural Networks to the Earth Sciences

Natural Resources Research -     

Typing Mineral Deposits Using Their Grades and Tonnages in an Artificial Neural Network

A test of the ability of a probabilistic neural network to classify deposits into types on the basis of deposit tonnage and average Cu, Mo, Ag, Au, Zn, and Pb grades is conducted. The purpose is to examine whether this type of system might serve as a basis for integrating geoscience information available in large mineral databases to classify sites by deposit type. Benefits of proper classification of many sites in large regions are relatively rapid identification of terranes permissive for deposit types and recognition of specific sites perhaps worthy of exploring further.Total tonnages and average grades of 1,137 well-explored deposits identified in published grade and tonnage models representing 13 deposit types were used to train and test the network. Tonnages were transformed by logarithms and grades by square roots to reduce effects of skewness. All values were scaled by subtracting the variable's mean and dividing by its standard deviation. Half of the deposits were selected randomly to be used in training the probabilistic neural network and the other half were used for independent testing. Tests were performed with a probabilistic neural network employing a Gaussian kernel and separate sigma weights for each class (type) and each variable (grade or tonnage).Deposit types were selected to challenge the neural network. For many types, tonnages or average grades are significantly different from other types, but individual deposits may plot in the grade and tonnage space of more than one type. Porphyry Cu, porphyry Cu-Au, and porphyry Cu-Mo types have similar tonnages and relatively small differences in grades. Redbed Cu deposits typically have tonnages that could be confused with porphyry Cu deposits, also contain Cu and, in some situations, Ag. Cyprus and kuroko massive sulfide types have about the same tonnages. Cu, Zn, Ag, and Au grades. Polymetallic vein, sedimentary exhalative Zn-Pb, and Zn-Pb skarn types contain many of the same metals. Sediment-hosted Au, Comstock Au-Ag, and low-sulfide Au-quartz vein types are principally Au deposits with differing amounts of Ag.Given the intent to test the neural network under the most difficult conditions, an overall 75% agreement between the experts and the neural network is considered excellent. Among the largestclassification errors are skarn Zn-Pb and Cyprus massive sulfide deposits classed by the neuralnetwork as kuroko massive sulfides—24 and 63% error respectively. Other large errors are the classification of 92% of porphyry Cu-Mo as porphyry Cu deposits. Most of the larger classification errors involve 25 or fewer training deposits, suggesting that some errors might be the result of small sample size. About 91% of the gold deposit types were classed properly and 98% of porphyry Cu deposits were classes as some type of porphyry Cu deposit. An experienced economic geologist would not make many of the classification errors that were made by the neural network because the geologic settings of deposits would be used to reduce errors. In a separate test, the probabilistic neural network correctly classed 93% of 336 deposits in eight deposit types when trained with presence or absence of 58 minerals and six generalized rock types. The overall success rate of the probabilistic neural network when trained on tonnage and average grades would probably be more than 90% with additional information on the presence of a few rock types.