Search Documents

By K. Howard Poulsen

Shear zones are tabular tructures which tend to occur either discordantly within, or concordantly along the margins of, competent rock masse uch as plutons, sill or flows. They contain deformed equivalents of their host rock and are common sites for gold mineralization localized in tructure oriented y tematically relative to the shear zones and internal linear fabric. Apan from genetic implications, hear zone analysis proves useful in exploration for this type of deposit because the zones are generally wider and more continuous than associated mineralization and because there is an element of predictability to mineralization geometry (i.e. vein orientation. plunge).

Jan 1, 1986

By Mark A. Krall, Robert L. Geddes, James C. Frost

Introduction The Conda Partnership's Dry Valley phosphate mine is a thinly bedded, multiple seam open-pit mining operation where selective mining techniques are used to recover phosphatic shales. The mining methods used are truck/shovel and scraper/dozer operations. Ore is shipped 32 km (20 miles) by rail to a beneficiation facility. The ore is upgraded by washing and calcining. The mine and beneficiation complexes are owned by the Conda partnership. It is a joint venture between Beker Industries Corp., of Greenwich, CT, and Western Co-Operative Fertilizers (US) Inc., of Alberta, Canada. The Partnership operates as a separate entity of the two partners. The Dry Valley mine is located 48 km (30 miles) northeast of Soda Springs in Caribou County in southeastern Idaho. The mine is situated on the Caribou National Forest. Mining operations take place between 2 and 2.4 km (6400 and 7900 ft) in elevation. It is accessible partly by 32 km (20 miles) of paved roads and 16 km (10 miles) of dirt roads. The winters are long and severe, and the summers are short and mild. This article describes the history, geology, exploration, mining, and reclamation that makes this mine Idaho's largest producing mine and the western US' leading phosphate producer. History and production In the mid-1950s, Western Fertilizers of Salt Lake City, UT, drove an exploratory drift in Maybe Canyon. A large bulk sample of phosphatic shales was analyzed for phosphate content and processing characteristics. No large scale mining or processing operations were undertaken. In the late 1950s, the Dry Valley property was sold to Central Farmers of Chicago, IL. No major operations took place. In 1964, Central Farmers sold the property to El Paso Products Co. of Odessa, TX. El Paso Products supervised the mining operations of Wells Cargo Mining Co. from 1965 through 1967. During this time, El Paso Products built a beneficiation facility and a fertilizer complex in Conda. A 32-km (20-mile) railroad was also constructed from the mine to this facility. From 1968 through 1972, the mine was shut down due to a depressed fertilizer market. In 1972, El Paso products sold its ore reserves, beneficiation plant, and fertilizer complex to Beker Industries Corp. In 1979, Beker Industries sold 50% of its ore reserves and 50% of its beneficiation plant to Western Co-Operative Fertilizers (US) Inc., of Alberta Canada, forming the Conda Partnership. It has operated the mine and beneficiation plant since January 1979. From the mid-1950s to the mid-1960s, no substantial production took place. From 1965 to 1967, El Paso Products stripped 3 Mm3 (4 million cu yd) and mined 2.3 Mt (2.5 million st). From 1972 through 1983, 50 Mm3 (66 million cu yd) were stripped and 18 Mt (20 mil¬lion st) were mined. Geology The Wells Formation forms high ridges and hillsides in the Dry Valley area. It is best exposed along the west face of Dry Ridge. It forms the imposing wall on the east side of Dry Valley. The formation is divided into two members. The lower member, about 213 m (700 ft) thick, is dominantly thin to medium-bedded limestone and silty limestone. It contains nodules and stringers of chert and minor sandstone. The upper member is composed principally of thick-bedded to massive cross-bedded, light-gray to orange-yellow, fine grained sandstone. There is some interbedded brown to light-gray limestone. This member varies from 369 to 457 m (1300 to 1500 ft). Recent investigations indicate that the upper Wells is of Permian age. Under some conditions, the Wells may be water-bearing. Otherwise, it has no apparent economic significance. Grandeur Member (Park City Formation) Overlying the Wells Formation is a distinctive light-gray to white dolomitic fossiliferous limestone. This unit has been identified by the US Geological Survey (USGS) as the Grandeur Tongue Member of the Park City Formation. This member is sometimes absent due to its contact with the Meade Peak Member of the Phosphoria Formation. It is easily detectable by its color, hardness, and fetid odor. Phosphoria Formation The Phosphoria Formation of Permian age was named from Phosphoria Gulch, Bear Lake County. The formation has been studied extensively and developed for its economically valuable phosphate reserves.

Jan 11, 1985

By Peter J. Szabo

The mining executive works in a cyclical industry. His employment is subject to the vagaries of the marketplace. Boom and bust has always been the industry's story. "Big oil" failed in its mining effort. This left emotional and financial scars on many mining families. One must remember that mining executives always play a high-stakes game. Given the cyclical nature of the mining industry, mining executives need to take care of their own financial security. The mining executive that does not plan for his financial security in this cyclical business is playing Russian Roulette with his future. Take a look at those people who have reached their later years with the mining industry. One usually finds three categories of people. Those few in the first group have been fortunate enough to have worked for one company. They have survived the winnowing process of cyclicality, political problems, and takeovers. They have reached normal retirement age. For them, the retirement years are usually comfortable. People in the second group have worked for those same mining companies. But these people have been forced out by early retirement. Or they have been laid off for cyclical, takeover, or political reasons. The third group includes those who have held many positions in the mining industry. Probably not until their later years are they fully vested, if at all, in a pension program. The first small group, then, is the exception. The others, unless they have taken care of their financial security, are doomed to later years of financial problems, stress, and unhappiness. Too late in life, many realize the harsh realities of failure to plan and implement a personal financial program. Mining executives go to some of the world's leading mining schools, to learn how to make money. The curriculum is technically strong. Most mining graduates are familiar with the intricacies of discounted cash flow, present value, and the Hoskold formula. But few of these same mining schools require courses on personal financial planning. Such courses could give mining students a realistic foundation and the mechanisms with which to cope with their cyclical profession. An executive has only three sources of money. He can make money at work. He can put his money to work. Or he can get money from charities, such as government programs. Of these three sources of money, money at work has the best chance of providing financial security in later years. The mining executive must think of the day when he will be too old to work and contribute to the market place. At this point, the quantity and quality of his investments will determine whether his later years will be secure. Along with the Mining Engineering Handbook, two key books should be included in the mining executive's library. These are Venita Van Caspel's The Power of Money Dynamics and Benjamin J. Stein's Financial Passages. These books contain the basic concepts of personal financial planning so critical to an individual's financial survival. Venita points out the simple formula that is the key to financial independence: Time + Money + American Free Enterprise (Rate of Return) = Opportunity to Become Financially Independent Chart 1 shows that this is not a trite formula. The chart shows the dramatic effects of compounding over time. The chart also shows at various yields what a $2000 a year Individual Retirement Account (IRA) contribution will accumulate. Chart 1 (from Money magazine) is based on the future value of an ordinary annuity. It shows that the key to amassing a small fortune by the time a person reaches his 50s is starting to save methodically in his 20s. This, coupled with the highest yields consistent with safety of principal will ensure financial security. There are significant effects from compounding money over time. Every year the decision is put off to save for later years will cost a person dearly by the time he reaches his 50s. For example, consider the decision to put off for one year a $2000 IRA investment at a 12% return. Starting it at age 31 instead of 30 will cost the executive almost $100,000 by age 65. What if the executive waits until age 35 to get started with his $2000 a year investment? He will then lose nearly $400,000 by age 65. Stated another way, the executive costs himself this $400,000 simply because he did not invest $167 a month for five years. $167 a month - that's less than an inexpensive second car payment. This $400,000 pool of money could provide the executive a $40,000 a year income at age 65, assuming a 10% return on invest-

Jan 11, 1985

M.S. Azun I have many objections to the content of the author's paper. Before discussing it, however, I would like to repeat the property of semivariogram function. Second order stationary properties of regionalized variables (ReV's) such as semivariogram function y(h) are perfectly known in geostatistics. Also, the kriging equations in the language of mathematical statistics using second order stationary properties are well understood. However, the way to use the sample (estimated) semivariogram function in any one of the kriging procedures is vague. The sample semivariogram function is given as follows: [ ] where N is the total number of samples, Xi is the sample value at the i - th location, Xi+h is the sample value at the i + h - th location, and h is the distance among the samples. An estimation variance of sample semivariogram function of first lag is smaller than that of higher order lag. The theoretical semivariogram function reaches the variance of samples asymptotically. But this is not easily observable because of the larger variation involved in the estimate of semivariogram function. In general, an estimation procedure is done for h = 0, 1, 2, up to the greatest integer less than N/2, even though sample semivariogram function can be computable through N-1. After estimating semivariogram function, the critical question of how to model sample semivariogram function arises. As seen in the above equation, sample semivariogram function is discrete and can be smoothed by the model being selected. Therefore, modeling of sample semivariogram function is the most important step in geostatistics. It not only smoothes a discrete function but also affects the results of the kriging procedure. When the only aim is to model the semivariogram function, which is the basic point of the author's paper, one can employ any fitting techniques, such as curve fitting, or any arbitrary functions, which are called submodels in the paper. The term "arbitrary function" is used rather than "submodel" because there is no basic understanding of developing them. The author suggests that the sum of those submodels can also be used for the modeling of sample semivariogram function. The combination of any arbitrary functions brings many problems instead of giving an insight of the domain structure considered. The author used two arbitrary functions and the nugget effect in response to sample semivariogram function (Fig. 10). For the same example, he stated that the parameters involved in the mixed arbitrary function model can be accepted when the discrepancy between sample semivariogram function and the model is small visually. For verifying the fitting behavior of any selected model, one should not be contented with the visual satisfactory. Some statistical measure such as goodness of fit has to be used. The author's practice is no more than an exercise in curve fitting without any fundamental understanding or conceptualization of the underlying physical mechanism. Furthermore, the selection of any model is not an easy task if the purpose is the search for the "best" response to the observed second order properties of ReV's. I suggest that the Markovian model (Azun, 1983), on the basis of a theoretical understanding of underlying mechanism, which gives more information about the occurrence of regionalized variables, is used to respond all properties of ReV's. There are a lot of problems for modeling of one-dimensional sample semivariogram function. Thus, it is not appropriate to go to higher order dimensional sample semivariogram function modeling. In the meantime, I would recommend that one can connect the values of standardized sample semivariogram function rather than simple values of semivariogram function in the two-dimensional estimation. The standardized values can be computed in dividing the semivariogram function value by the number of sample pairs involved in each lag regardless of the directions. In conclusion, geostatistics is an interdisciplinary area in mining that uses the principles of mathematical statistics. Thus, it should not violate any probabilistic and statistical rules. When Matheron was developing the theory of geostatistical study in the early years of geostatistics, many mining people had a reservation accepting the geostatistical tools. However, this does not mean that we, the geostatisticians, might try to convince those people using some "strange" tools or rules as some authors implied (Baafi and Kim, 1984). Instead, we have to develop and explain the geostatistical tools staying only in the framework of statistical concepts and properties. References Azun, M.S., 1983, "Stochastic Process Modeling of Spatially Distributed Geostatistical Data," Columbia University, Ph.D. Thesis. Baafi, E.Y., and Kim, Y.C., 1984, "Discussion - Comparison of Different Ore Reserve Estimation Methods Using Conditional Simulation," Mining Engineering, Vol. 36, No. 3, p. 280. Reply by J.M. Rendu The interactive method proposed by Rendu allows practitioners to develop semivariogram models that take into account not only the numerical information obtained by sampling, but also highly significant additional information that often cannot be quantified. The geology of the deposit - including hypotheses concerning its genesis, sampling methods, assaying methods, and mathematical methods used to calculate the semivariograms - all have an influence on the numerical results obtained and on how these results should be interpreted. If all the information concerning the spatial distribution of values in a mineral deposit was contained in the sample values, it could be argued that statistical techniques alone would produce optimum models. However, this is rarely, if ever, the case. Methods that allow the user to take into account his experience and his geologic understanding of the deposit should not be rejected for the sake of theoretical statistical purity.

Jan 11, 1985

By David L. Rife

Introduction Our society is currently experiencing a change in civil philosophy toward US industrialization. We have become increasingly bent on the pursuit of a nirvanic state of zero risk. The money supply has become inversely proportional to its sources. And most mining companies, traditionally conservative, have become increasingly risk conscious. Rising taxes, high inflation, and decades of a steadily decreasing gross national product (GNP) - coincident with moral decay and disarmament - have eroded America's economic health. Psychology of US metal markets has shifted across the economic spectrum to disillusionment and discouragement. The sagging national economy, expanding governmental debt, and a backward mineral policy in concert with worldwide unrest and turmoil have caused great volatility in the metal markets. Congressional inaccessibility of US resources has contributed to its loss in strategic leadership and dependency on foreign suppliers and the common market. Large scale mining activities are now on the decline. And there is an overall slump in mineral exploration in this country. America now faces the sobering reality of almost total importation of 13 key mineral commodities and total dependence on foreign sources for five of them. There is a growing dependency on 21 of the 34 minerals vital to the US economy. And virtually everything needed can be imported directly from third world countries. Almost 85% of the free world's supply or production of vanadium, chromium, platinoids, manganese, and titanium - an essential to the aerospace industry - comes from South Africa. That country now plays a forefront position in supplying the West with minerals. The Soviets have become increasingly aware of this situation. They have made key moves in procuring for their own purposes major raw materials markets, particularly in South Africa. This is obviously threatening to the US' direction and brings about vulnerability to shortages and cutoffs. In spite of these developments and the overall change in the mining industry, there is good opportunity for growth ahead. The way has been paved for the smaller mining companies, particularly the more bullish of these. Smaller mining organizations possess a tight management and strong sense of direction. They can easily adapt to and cope with change. "Windows" that exist in the industry directly depend on a number of factors. These include the busi¬ness climate, market research and planning, management and human resources, applied appropriate technology, favorable hunting ground, and entrepreneurship. Mining as business Mining (and exploration) as a business is by its very nature highly speculative. It involves greater risk for a longer period of time than most other businesses. The entire mineral estate in the US continues to shrink. This is primarily because of various legislated wilderness measures. Consequently, the probability of finding an economic ore deposit in the US has decayed to less than 1%. Although the risk is high, the stakes far outweigh the gamble and are larger than most other businesses can offer. Mining properties, as investments or business opportunities, can provide effective hedges against long-term inflation because the real price for selected commodities, such as gold, may sometimes rise faster than inflation. Recessionary periods seem to provide the best climate for entering the mineral business or for a particular mining organization to expand its activities. Looking ahead and seizing opportunities during a depressed market will pay off. Property payments and royalties are likely to be lower. And the potential for an upward shift in prices for a given commodity is very positive. The decision to invest in a prom-

Jan 9, 1985

By Victor F. Hollister

Introduction Trends of successful discovery technology and psychology emerge from a thoughtful study of various companies' exploration programs. These subjective patterns can be generalized into groups of factors for discussion. Here, for convenience, factors that influence exploration success are separated into management and geologic concerns. Most successful discoveries have a demonstrably favorable management combined with a technically competent geologic input. Both are required. But the management input is decisive. Management factors include the correct definition of management's role; cost of exploration; time needed for exploration; commodity selection; and the fostering of autonomy, creativity, and confidence in the geology department. Geologic factors include imaginative technical competence (field as well as academic), correct development and use of empirical exploration or prospecting models, and dedication. Success comes to those entities that are properly managed and have technological competence. A management team that directs a company's business has been compared to a dynasty. The dynasty lays out policy and follows up with appropriate action. In that management's power is pervasive, the term is appropriate. Management's role is, however, more important. Many examples can be cited where the geologic input was impeccable. But management somehow snatched defeat from the jaws of victory, and the exploration success was turned to a third party's profit. Management Factors Management's role can be broadly generalized to four parts. These are to identify the commodities it seeks, define its part in the exploration process, develop a functioning exploration department, and have the desire to succeed. It must have confidence in its geologists and delegate to them the authority and responsibility they need to operate successfully. Head office management cannot do the thinking for a field staff thousands of kilometers away. There is no substitute for confidence and delegation of authority. Successes came to those who had the freedom to act. Motivation is a management requisite. Management's role is to prevent destructive, internecine political battles within the corporate structure. Most large US mining corporations have well known histories of political strife that have damaged their exploration efforts. Management's role must, above all, include the desire to succeed. There are cases where management has been confronted with a commercial exploration success, but their reaction is to request additional study or exploration. Perhaps the problem of bringing a commercial find into production is beyond their capabilities. But a bona fide discovery sent back for additional work commonly is lost due to that management. The cost of exploration is a factor that management must accept. A variety of studies made during the past 40 years shows the cost per discovery to be $25 million, $38 million, $200 million, or even $290 million. These figures are derived by dividing the total exploration expenditure by the number of discoveries. However, successful management dynasties have a much lower cost per discovery during their management regime. Asarco, from 1948 through 1963, had one of the lowest cost discovery rates in the world. Duval Corp., from 1948 through 1968, had comparably low discovery costs. Placer Development, from 1955, was equally successful. Western Mining in Australia has had one of the longest lived dynasties associated with exploration success. Time is vital in exploration success. Most successful exploration case histories stress sufficient time in project exploration so that the target is well tested. A large target cannot always be adequately evaluated by a few holes (strat or concept testing). Serendipity helps in exploring large targets, but it best operates in a lengthy program. Numerous case histories include pleasant surprises. But these came mostly after the 10th hole. Commodity markets are important factors governing exploration success. Management's decision to explore for a specific commodity can doom its effort if that product suffers from severe oversupply. Unquestionably, progressive copper price increases from 1948 through 1968 helped convert marginal porphyry copper discoveries

Jan 8, 1985

By Paul D. Tomlingson

Part one of this two-part series covers conceptualizing and developing a maintenance information system. It explains what information is necessary to manage such a system. Next month, part two will discuss using this type of system with administrative information, including error and absentee reports as well as open work files. Introduction There is no doubt that quality, timely, and accurate information can make a solid contribution to maintenance cost reduction objectives. Yet, despite obvious benefits, methods being used to acquire information systems are proving costly, frustrating, and often unsuccessful. Those needing the information are disappointed. Mine managers, hoping to reduce costs with quality information, are instead seeing no system, no savings, and massive spending on information endeavors of questionable benefit. Options Any software vendor will happily sell you his program. Numerous mining organizations, having "gone to the cleaners" themselves, will gladly make their programs available to help cover huge trial and error development costs. Any package can only be a generalization. Any program bought from some other organization must undergo numerous modifications to make it work properly. In the process the initial cost is doubled. Many mining maintenance organizations do not know how to go about the task of conceptualizing, developing, installing, and effectively using a maintenance management information system. Consequently, many have hedged their primary responsibility of specifying what information they want, how they will get it, and how they will use it effectively. Into this void have jumped many who claim they can help. But some may not understand the special information needs of maintenance in the mining industry. By default, the whole scene of maintenance information systems has become confused and in need of clarification. A Starting Point Four broad phases are used to organize the steps by which maintenance acquires an effective maintenance management information system and initiates its use. Conceptualization is an identification of needs, factors that influence development, and an assessment of support for the system. Development is a plan of action for bringing the conceptualized information system to life. Consideration is given to the practical aspects of collecting field data, processing it, and converting it into useful information. Implementation consists of those actions by which the newly developed system is integrated into the organization and put in the hands of its personnel so that its value can be derived. Use addresses the means by which personnel use the information to accomplish maintenance improvement objectives. These phases are preceded by establishing the need for the information system. They are followed by a requirement to measure its success (Fig. 1). Conceptualizing the Information System Responsibilities - The information system user must acquire the system best suited for its use. A step-by-step process is essential to avoid many serious problems than can easily occur. The most important step is to clearly identify its objectives and lay out a course of action to achieve those objectives. The major reason for the failure to achieve information objectives is not carrying out this responsibility. Maintenance cannot delegate the task to data processing. It can obtain technical assistance but it must retain responsibility. Nor can maintenance purchase

Jan 7, 1985

By Frank W. Luerssen

Introduction "Austerity" is perhaps an overly generous description of the past three years in the American steel industry. Steel plants operated at an average of only 57% of their capability in 1982-84. The dismal losses for last year are still being totaled. But during the two years before this period, American steelmakers recorded an aggregate net loss of a staggering $6.8 billion. Steelmakers responded by closing numerous marginal facilities. And production capability was cut by 13.6 Mt (15 million st). Capital expenditures still averaged $2 billion annually. But this was inadequate to maintain the existing base of steelmaking facilities. The general economy experienced a satisfactory recovery during this period. American steel, however, continued to suffer from a lagging recovery in the capital goods sector. This was due to record penetration of its domestic market by imports and from very weak realizing prices on the volume that was available. In addition to the direct influx of offshore steel products - which itself depressed prices - the industry also became painfully aware of the growing importance of "indirect" imports. These came in the form of steel-containing producer and consumer durables. Industrial equipment and autos fabricated from foreign steel accounted for the equivalent of 6 Mt (6.5 million st) of lost market opportunity for domestic steel-makers last year. That is over and above the 23.5 Mt (26 million st) of direct steel imports. Given these factors, Inland Steel was not spared from the threeyear downpour of red ink. Despite its record of continuing modernization in steel, our single-plant location in the world's best steel-consuming market, and the high proportion of consumer durables related products, such as cold rolled and coated sheet in our mix, Inland suffered aggregate losses of $277 million during the 1982-84 period. Strategic Planning The foregoing establishes a perspective - a base from which we have restructured our view of the steel industry, and of our own role within that picture. Until possibly two years ago, this present weakness in steel demand was viewed around the world as an aberration, eventually to pass. By contrast, it is now recognized that austere times are the normal steel environment. The topic here is management of resources. This implies an emphasis on strategic planning. It is worthwhile to examine some of the more critical assumptions that were driving strategies among a number of steel companies just before the 1980s. Those projected characteristics of the future steel environment were arrived at through painstaking analysis. They were carefully and heavily quantified and were generally shared by outside observers and our peers within the steel industry. • First, the assumption was made that domestic steel demand would continue to grow at an average rate of 2% per year. • Second, it was assumed that this growth in the American market would continue to be filled predominantly by US mills. It was believed that increases in steel and steel-related demand overseas would absorb much of the ominously growing capacity of third

Jan 6, 1985

By Sandy Clamage

"Seeing the elephant" was a term often heard from 1849 to 1859, the period of the great California Gold Rush. The phrase was used by those who dreamed of instant wealth that was believed could be found in California's virgin earth and mighty rivers. When news of fabulous gold strikes throughout the Mother Lode reached far away places, thousands of gold seekers left home and family to join in this incredible adventure. The barren, placid state of California soon became one of the most bustling, populous areas in the West. Before the Rush Before 1848, Mexico ruled California. It was then a remote region, isolated from the urbane world of the East by 2900 km (1800 miles) of scorching desert and impassible mountains. By sea, it was 29 000 km (18,000 miles) via Cape Horn. Spaniards and Mexicans settled the coastal lands on tracts donated to them by the Mexican government. The inland area was the domain of Indians and a few settlers who also had been granted estates by the government. Among those settlers was Captain John Sutter. He had been fortunate enough to obtain about 11 leagues of land (spanning 100 km or 60 miles in length) from Governor Alvarado of Mexico. Sutter was somewhat of a visionary and possessed a gifted tongue. He managed to receive most of what he desired with minimal trouble. Enchanted with Sutter's personality, Alvarado promised him Mexican citizenship. Alvarado also commissioned him to become "representative of the government and officer of justice on the Northern frontier." With uncanny foresight, Sutter began building a fortress on his land in the Sacramento Valley. It later became known as Sutter's Fort. It was more than just a fort, however. It also became a stopping place and home for many foreigners and Americans who traveled to California, and it eventually became the mecca for overland pilgrims. Sutter engaged in many projects. These included a cattle ranch, fur trade and trapping, and the construction of an irrigation system. With the influx of immigrants over the years, the community around the fort grew rapidly. Lumber was much in demand and Captain Sutter agreed to supply the necessary capital for a community sawmill. The site chosen was some 72 km (45 miles) northeast of the fort on the south fork of the American River in the town of Coloma. During the course of its construction, Sutter's carpenter, James Marshall, discovered a problem with the tailrace on the mill. First Strike Early in the morning on Jan. 24, 1848, Marshall was checking the tailrace. He noticed an object shining in a foot of water at the bottom of a ditch. He reached down and picked it up. His heart began to thump wildly as he realized he was holding a gold nugget. Sutter planned to keep the find a secret for as long as possible. He knew very well that he could become an extremely wealthy man. The ever loyal Marshall remained faithful to his employer and the pair did their best to obtain more

Jan 3, 1985

By E. Tulcanaza

M.S. Azun I do not at all agree with the basic points of the author's conclusion. The use of lognormal or normal model to respond to the attribute distribution function should be carefully questioned. If fitting a distribution function of regionalized variables is the main purpose, one may employ one of certain well-known families of distributions, such as Tukey's lambda functions. For instance, the distribution function of gold assay values studied by Krige (Krige, 1978) may fit the lognormal model well, but one should not exclude that the basic idea of using the distribution function of observed data is to have insight of the physical mechanism that gives rise to the regionalized variables. In Applied Geostatistics, there are many examples considering only lognormal or normal model for the distribution function of geostatistical data even if the observed distribution function has more than one mode. Of course, using lognormal or normal model always brings easy computation for the statistical properties of attribute under investigation. Still, I object to adopting any of those models without having any "statistical inference." As seen from the author's paper, lognormal and normal model produce the same average grade (0.746% copper) and almost the same sample variance. Therefore, which model explains the probabilistic behavior of ore deposit is always an important question that should be replied by the geostatistician using not the common sense but the statistical and probabilistic methods. For kriging procedures, such as linear kriging, one should describe either second order stationary properties or bivariate properties of regionalized variables. Second order properties, such as correlogram function or semivariogram function, are the inputs of the so-called kriging equations. Selecting one of any useable models for the observed second order properties, such as spherical model, is not easy since the models are not based on the correlations structure of the regionalized variables. How those models being used in Applied Geostatistics can be distinguished is another important problem. One may develop many fitting models to respond to the observed second order properties of regionalized variables. However, I suggest that the model should be based on the probabilistic behavior of geologic process. The author used spherical model for copper, wolfram, and silver grades from isotropic sector (Fig. 2, 4, 3b) and exponential model for silver grades obtained along raises in isotropic sector (Fig. 3a). It seems that those semivariograms given in Fig. 3b for isotropic sector and Fig. 4 may be described by the random model implying that regionalized variables do belong to renewal process (Azun, 1983). If I knew the total number of data points used in estimation, I may prove that my conclusion is correct. Recalling the test for the first order sample correlogram value, the test procedure is introduced such that the independence is rejected if [ ] where Za/2 is the a/2 percentile of standard normal random variable and N is the total number of samples used in estimation (Azun, 1983). For the other observed semivariogram functions I suggest the author might try to use the so-called "Markovian model" describing not only the correlation structure of regionalized variables, but also the physical mechanism that produces the regionalized variables. The Markovian model for correlogram function is, [ ] The Markovian model for the other second order properties of ReV are also derived. T ve B, in the above equation, show, for example, structural change and mineralizational variation in a considered deposit, respectively (Azun, 1983). In selecting any model, it is not easy to search for the "best" response to the observed second order properties of ReV's. The Markovian model, based on a theoretical understanding of underlying mechanism, gives more information about the occurrence of regionalized variables and respond to all properties. Random model and the so-called hole effect structure can be easily defined as a special form of the Markovian model (Azun, 1983). An estimation of any second order properties of regionalized variables may be computed through (N-1) lag. However, the dependency between the regionalized variables may be deemed to have "died out" after the so-called stationarity width (range). In practice, the estimation is carried out through 25% of the total number samples available. Therefore, the large fluctuations around the zero level and variance for correlogram or covariogram function and semi-variogram function, respectively, cannot be observed. Since the number of pairs involved in the estimation of higher second order properties is small, the estimation variance at those lags is large. There is no need to show higher order estimated second order properties. After using one of any kriging procedure for block estimation, the distribution function of average grades has the same mean as the drilling sample grades but

Jan 3, 1985

By R. Kent Comann

Introduction This article describes ways to maximize employment potential for those looking for a job in the minerals industry. Advice on the right way to prepare a resume is followed by tips on where and how to look for a job and ways to make the best of an interview. Information on current salaries is also included. RESUME NAME: Give home and college addresses and telephone numbers, ADDRESS: if still in school. Otherwise, give home address and TELEPHONE: telephone plus business telephone number. JOB OBJECTIVE: What do you want to do? EDUCATION: List degree(s), name of college(s), location(s), and date(s) degree(s) received or to be awarded. Do not list your high school but do include postgraduate education, training, or seminars. WORK EXPERIENCE: List your most recent experience first, and the rest in reverse chronological order. Include dates (month and year) and company names. First show the entire time spent with each employer, then list the various jobs (with dates and duties) you may have had with this employer. MILITARY SERVICE: List dates, branch of service, and duties. If you did not serve, delete this section. COLLEGE ACTIVITIES: Show organizations, sports, and offices held. Only list these if you are a graduating senior, otherwise delete this section. PERSONAL DATA: List age, marital status, height, weight (optional), foreign languages spoken, professional memberships, and health (if good or excellent, otherwise do not mention it in the resume). If you prefer a certain location and would not accept a job anywhere else, list the location desired. Otherwise, do not restrict yourself. Also list special skills, hobbies, or interests that will help sell you to the company. Be brief in this section and use good judgement as to what you say. REFERENCES: Furnished on request. Resume Guidelines There are some things to remember when preparing a resume. These include: • Limit your resume to one page, unless you have a lot of experience. Then it should be a maximum of two pages. • Use 8.5 x 11 plain bond paper, white or off-white. Stay away from colored paper, odd size paper, and cute resumes. They are counter-productive. • Make certain your resume is typed professionally. Be sure to check for spelling, grammar, and typographical errors. • Have your resume reproduced by copier or printing shop. Do not use carbon copies. • Keep your sentences and remarks short and punchy. Use action verbs. • Have a good layout that is easy to read, brief, and uncluttered. Allow some white space in your resume. There are also some things you should not do when preparing a resume. These include the following: • Do not include a photograph or mention your religion, race, or sex. • Do not leave gaps of time unaccounted for in your resume. • Do not include your college transcripts with your resume or list all the courses you took in college. • Do not list all the articles you have written. Only list one or two, if appropriate for, say, a research and development job. • Do not include reference letters with your resume. Any good, prospective employer will make telephone reference checks. • Do not use "Curriculum Vitae," use "Resume." • Do not include unnecessary data such as your social security number, passport number, or PE registration number. If you are a PE or EIT, be sure to mention that in your resume. Do not mention US citizenship or US work permit unless you have a foreign education or are not a native US citizen. • Do not include present salary or salary requirements. This will come out in the interview. • Do not use the word "I" in your resume or refer to yourself in the third person. • Do not lie, distort, exaggerate, or editorialize in your resume. • Do not have your resume prepared by an outside resume service. This is unnecessary, costly, and generally not effective.

Jan 2, 1985

By D. W. Gentry

Introduction Until recently, there were many jobs for mineral engineering graduates. Traditionally, minerals-related career paths available to university graduates stem from rather standard offerings in the disciplines of mining, metallurgy, petroleum, geology, geophysical engineering, and mineral economics. Within each discipline, there exists many career opportunities. In fact, until fairly recently, the most difficult decision for most graduates was choosing among all the available alternatives. Unfortunately, this relative state of euphoria changed quickly and dramatically within the minerals sector. Within two or three years, graduates from minerals-related engineering disciplines found it exceedingly difficult - and then almost impossible - to secure employment in the minerals sector upon graduation. At the same time, there were dramatic reductions in production requirements and, ultimately, mine closings. This resulted in massive layoffs and often termination of professional personnel possessing significant and valuable industrial experience. Obviously, this worsened an already bad employment picture for those hoping to begin a career in minerals. Certainly, there is no universal agreement on what the future offers for the US minerals industry or the career opportunities associated with it. However, there are a number of considerations that deserve study by students, faculty, administrators, and industrial personnel before minerals-related career paths are chosen. Where Will the Jobs Be and How Many? Everyone is aware that the minerals industry is very cyclic. It is not surprising then that job opportunities for new graduates also fluctuate. Typically, there is a two-to-four year lag between industry's engineering manpower needs and the academic community's ability to produce this talent. Due to the response lag, there will necessarily be years when supply and demand do not match. Employment Projections It is extremely difficult to anticipate what the key career paths might be within the next few years. Considerable speculation remains with respect to whether activity in the US minerals sector over the short-, intermediate-, and long-term will improve, remain status quo, or further deteriorate. However, some information pertaining to the prospects for career opportunities in mining engineering was offered by Tingley and Ghose (ME, Sept. 1983, p. 1274) from a study performed by Fenvessy and Schwab. Results from this industry-sponsored survey suggest that the US will experience 700 more mining engineers than needed in 1985, 1300 in 1990, and 1800 in the year 2000. These conclusions were based on the assumptions that future graduate levels remain flat and demand increases 3.6% annually. Educators quickly argued that depressed job markets, coupled with university student mobility, would negate the assumption of flat mining graduate levels in the immediate future. Student Mobility Student mobility from one engineering discipline to another is high. This is perhaps best demonstrated by the tremendous growth in programs such as computer engineering and computer science at the expense of enrollments in the more traditional engineering programs. The ability and willingness of students to quickly change engineering disciplines in response to existing and perceived job market demands have created significant student, faculty, and resource dislocations within universities nationwide. This has resulted in problems for university faculty and administrators responsible for effective use of

Jan 2, 1985

By Richard L. Stotlar

Introduction During the last decade, the metallic minerals segment of the industry could be categorized as a "feast-or-famine" business. It is no secret that metallic minerals are cyclical. Employment opportunities greatly depend on the supply and demand for its mineral products. It is also not unusual for there to be a lag between the industry's manpower requirements and academia's ability to produce new graduates. Due to this lag, there will be years with manpower shortages, as in the mid-1970s. At other times, supply will exceed demand. The question is where will the jobs be in the years to come? This presentation will review reasons why employment opportunities have declined within the metallic minerals industry. It will also predict future demand for mineral engineering graduates. And it will outline strategies for obtaining an employment offer. Historical Review - Employment From 1977 through 1983, about 75% of all metal mining employees were directly engaged in production activities, down from 83% in 1965. This decline reflects increased use of labor saving equipment, and more government regulation and foreign competition. Metal mining's employment decreased from 74,000 jobs in 1982 to fewer than 68,000 in 1983 - an 8% decline. The overall industry is having these problems because of the general downturn in the economy. For example, at the beginning of this decade, US automobile and steel industries were in trouble. Interest rates were too high and volatile. This adversely affected construction, housing starts, and manufacturing. All these industries, being large users of base metals, drastically affected the metals industry. US copper companies are still having problems. Reports indicate that many copper employers have cut production, laid-off workers, and permanently closed mines, refineries, and smelters. A decline in the demand for US produced metal products, such as copper, obviously affects some mineral engineering employment opportunities. Other factors to consider when looking at employment opportunities and why it has become difficult for US metal producers to compete in the world market include: • The grades of ore bodies of many US minerals are considerably lower than the grades of ores being mined elsewhere in the world. • The grades of ore bodies currently being mined in the US are steadily declining. • Foreign producers are largely government controlled and are not necessarily subject to the realities of supply and demand. • US environmental regulations have considerably added to production costs. Foreign producers in most countries do not have to worry about these additional costs. • US mines are getting deeper. This adds to the cost of production because of the increasing distance the ore has to be transported. • Plants and equipment are outdated. Many companies find themselves operating with equipment and plants that need modernizing or replacing. This obviously hinders competitive productivity. • Labor and management have had problems. Work stoppages in certain mining businesses and high wage and benefit costs in relation to foreign producers place US producers at a disadvantage. • Much land is unavailable. The US government owns most of the land considered to have the best potential for minerals development. Most of this land is unavailable for mining or exploration. Therefore, it appears that finding employment with a company whose primary business is mining and processing most metals, such as copper, in the US will be quite restricted and competitive. Future Demand It is difficult to anticipate what key employment opportunities within the next few years will be available to mineral engineering graduates. The Engineering Manpower Commission estimated that US engineering schools awarded 72,471 undergraduate degrees in 1983 vs. 66,990 in 1982. This was the eighth consecutive year in which the number of baccalaureates awarded has increased. On a brighter note, the US government's Occupational Outlook Quarterly stated that the growth rate through 1995 for all engineers is an encouraging 49% over present levels. The estimated number of engineers employed in 1982 is 1.2 million. The numerical in-

Jan 2, 1985

By John R. Marks

Introduction An engineer is a builder and a problem solver. He uses knowledge of the properties of matter and energy to furnish the needs of society. Engineers form the bridge between scientific researchers and the general public, most of whom are technologically illiterate. Mining, metallurgical, and petroleum engineers extract minerals from the ground and process them into usable forms. Then, other engineers further process them into society's needs. Minerals engineers deal with more uncertainty than other engineers. Each ore deposit has its own personality and each ore is metallurgically unique. Minerals engineers, therefore, must be flexible, often applying larger safety factors and contingencies than other engineers, and frequently functioning as a jack of all trades. A minerals engineer can work in coal, oil, oil shale, base metals, ferrous metals, precious metals, industrial minerals, strategic minerals, or in exploration. Other mining jobs include banking and financing, education and research, marketing and sales, and government. As a minerals engineer, you may be among the first to work on the ocean floor or the moon. College Preparation A difference between college and industry is the type of problems to be solved. A typical college problem has an exact answer derived from given information. An industry problem is more apt to have a solution chosen from a number of alternatives. Information required for the solution is not given. It must be measured, calculated, looked-up, estimated, or otherwise derived. Solutions involve trade-offs, economics, and human factors, as well as application of physical laws and theory. When a college problem is answered, you move on to the next one. In industry, however, the headaches may just be starting with the implementation of the solution. Students often complain that they see little use for the theory they are learning. This is valid. A good professor will link theory and practice. Another difference between college and industry is the price of failure. In college, you can make a half-hearted effort in an assignment and take your C or D. On the job, however, poor engineering results in potentially effective projects being rejected and unsound projects being undertaken. Poor performance results in cost overruns, schedule holdups, oversights, disgruntled employees, irate bosses, unsafe structures, and unreliable systems. The costs are time, money, and possibly lives. The student pays the university for his work - not the other way around. So the rewards for good schoolwork often seem nebulous. But education must be viewed as an investment. Working for good grades will help you think better, learn more, receive better job offers, and perform more effectively on the job. There is no substitute for hard work. Avoid taking the easiest electives. If you desire a more liberal education or dislike rigorous physical sciences, mathematics, or engineering courses, change majors. Remember, you are training to be an engineer, not a computer programmer or market analyst. At least one summer of industry employment is necessary for minerals engineering students. The sooner you gain actual experience, the sooner you will know whether to change majors. Most large companies hire students during summer. It is best to send out applications around Christmas break. First and second year students usually work as laborers. Upper-classmen may work as engineering technicians. Students must sometimes choose between returning to a company at a higher position or trying a different company at a lower position, for more varied experience. Both alternatives have advantages. Do your best on these summer jobs. The company is watching. If you do well, the chances are good you will get a job offer when you graduate. Good references are important when you begin job hunting. Interviewing occurs near the end of your school career. The standard procedure is to send your resume with a cover letter to each company you are interested in. The resume for a graduating engineer with little experience need not exceed one page. The cover letter must be written for the individual company.

Jan 2, 1985

By Richard D. Mills

Throughout the mining industry, many companies perform sophisticated business and financial analyses of proposed capital investments. However, once the project is approved, it is never reevaluated. At best, there is an attempt to control capital costs and minimize overruns. The post-installation appraisal, a formalized review of investment performance, may prove helpful. Typical Project Review A typical capital investment is approved after business and financial benefits have been reviewed with management.* The financial data shown to management often include a net income statement, cash flow analysis and summary economic data similar to those shown in Table 1 overleaf. These financials report the expected impact of the project on the corporation financial statements. This project is a rudimentary example of a capital investment decision. An actual project would undergo a more sophisticated analysis incorporating depletion benefits, deferred taxes and a detailed cost breakdown. The example project has several financial benefits that could result in management approval. For example, it provides an immediate net income benefit to the company, generates positive cash flows every year of the project life and has a discounted cash flow rate of return of 25 percent. However, it also has the disadvantage of a long payback period. A sensitivity analysis would show which areas of the analysis have the greatest impacts on profitability. Post-Installation Program Objectives The post-installation appraisal goes beyond the analysis shown in Table 1 by comparing actual results to those projected in the original economic analysis. The post-installation program has three primary objectives: 1. To provide a periodic performance review of major spending programs. 2. To review decision-making and evaluation procedures. 3. To provide a means of controlling individual project investments. The first major function of the post-installation program is the periodic review of actual performance of projects and investment programs, identifying those factors which proved critical to the health of investments. This review will serve to keep management abreast of progress, provide a comparison of actual performance against expectations, and provide valuable information that can be used for improving future economics. The second major function of the program is to perform a continuous review of the decision-making process. This includes testing of evaluation procedures, forecasting techniques, and logic used in making decisions. An information system should be set up whereby original evaluations and historical performance data gathered under the appraisal program are documented for use by evaluators and management when assessing past and future investment proposals. Such data should be particularly useful in evaluating new and developing types of operations and in activities where companies repeatedly reinvest. The primary purpose of this feedback system is to sharpen estimates to assure that they are realistic and attainable. The appraisal program also provides assurance that consistent evaluation procedures are being used throughout a company, leading to improved procedures

Jan 1, 1985

By Arnold R. Pasieka, George V. Sotirow

"The object of this paper is to outline a computerized net cash flow approach for practical cutoff grade determinations. A cutoff grade carries not only geological but also economic value, in which costs are balanced against revenues. For different situations, cutoff grades are a 'standard of value' that are determined for the purpose of classifying economic or uneconomic mineral reserves in a specified time frame. In a constantly changing technical and economic environment, the decision to develop or maintain a mining operation at its best economic potential, requires an appropriate cutoff grade strategy, a strategy consistent with short- and long-term operational and corporate objectives and one based on realistic marketing and metal prices forecasts. The use of a project evaluation computer program, in combination with specific corporate net cash flow requirements, shows the most promising and flexible team approach for cutoff grade optimization.IntroductionThe recent recession has had a devastating effect on the Canadian mining industry. Exploration and mining R&D expenditures have been critically reduced and now are believed to be below healthy levels. Ore reserves, mine life and cutoff grades are careening in several directions because of low base metal prices, relatively high costs and sensitive precious metal prices.These conditions demand an improved understanding of the terms ""ore"" and ""cutoff grades"" as they are applied to the planning process and day-to-day operations. ""Ore"" or 'ore reserves"" is a dynamic concept, reflecting a cumulative effect of changes in geological, technical and economic conditions in terms of material which can be mined at a potential profit. By contrast, if economics are not the primary consideration, the term ""mineral reserve"" or ""mineral inventory"" should be used to describe the mineral deposit. For different situations, cutoff grade is ""a standard of value"" determined for the purpose of classifying mineral reserves as economic or uneconomic in a specified time frame. The question of mining at average reserve grade or low-grade material during high metal prices is of paramount importance for cutoff grade strategy."

Jan 1, 1985

By R. Blickensderfer

The laboratory wear testing capabilities of the Bureau of Mines are described, Wear tests are used to support the Bureau?s research efforts toward reducing the wear of equipment used for mining and minerals processing and any wear involving a loss of strategic or critical materials. The emphasis is on abrasive wear because it accounts for most of the wear losses that occur in mining and minerals processing equipment, Spalling wear, caused by repetitive impact in grinding equipment, also is included, Ten abrasive wear tests, including high- stress and low-stress and two-body and three-body conditions, are described: dry-sand, rubber-wheel abrasive wear; Taber Abraser; abrasion resistance of refractory materials; dry-particle erosive wear; elevated-temperature, dry-particle erosive wear; low-angle slurry pot; jaw crusher gouging wear; ball mill wear; pin-on-drum abrasive wear; and high-speed impact gouging. Two repetitive impact tests are described: ball-on-block impact-spalling and ball-on-ball impact-spalling. Test equipment, procedures, and specimens are described, and typical test results are presented and discussed.

Jan 1, 1985

By D. T. Couillard

Video technology is becoming an important tool for many designers of industrial training programs. This report describes how trainers at the Minntac Mine, Mt. Iron, MN, have developed videocassettes of safe job procedures (SJP's) for training miners assigned to perform unfamiliar work tasks. All steps necessary for videocassette production, from idea to finished product, as well as the required equipment and prices, are listed and/or briefly explained. Minntac officials believe that the SJP videocassettes have contributed significantly to a reduction in mine accidents.

Jan 1, 1985

By R. B. Prater

The Bureau of Mines conducted research to separate the F from byproduct Zn concentrates obtained from fluorspar (CaF2) production, as part of the Bureau's effort to devise efficient, environmentally acceptable technology for recovering Zn from resources considered undesirable by Zn producers. Sulfuric acid (H2SO4) was found to be effective in F removal, while ammonium carbonate [(NH4)2C031 was not. The most important variables for reducing the necessary residence time were found to be temperature and agitation. Optimum leaching conditions were 75° C and 500 r/min for 2 h at 40 pct solids with 0.2 g acid per gram of concentrate, which resulted in a 98.3-pct F extraction. Zinc losses during F removal were in the range of 2 to 3.3 pct. Other elements such as Fe, Cd, Ca, and Cu were also partially dissolved. About 93 pct of the F was removed from the leach solution by neutralization and precipitation with calcium hydroxide [Ca(OH)2]. Additional treatment might be necessary to limit the buildup of soluble elements in the recycled leach solution.

Jan 1, 1985

By Tom Tallone

In the majority of metal and nonmetal mining operations, narrow vein deposits are being mined with slusher hoists. Thin; method of mucking is costly, due in part to its inherent labor intense operation and to its inability to muck 100 pct of the deposits. Mechanized equipment would greatly improve the material handling in narrow vein mining and would dramatically reduce the operational cost. The Compact Loader/Trammer, known as the "mini-mucker" has been developed to increase productivity of the load/haul/dump portion of the typical narrow vein mining cycle. This is Volume II of the final report and concerns the operation and maintenance of the mini-mucker. Volume I covers a general and design review of the activities on the subject contract and are available under separate cover.

Jan 1, 1985