The impact of drilling fluid and well cuttings on polychaete feeding guilds from the US northeastern continental shelf

The effect of recent drilling operations (fluid and well cuttings) on polychaete feeding guilds from the continental shelf off Atlantic City, New Jersey, was examined. Although there were some adverse effects on macrobenthos from 2160 metric tons of cuttings and mud solids discharged into the marine environment, the composition of polychaete feeding guilds remained essentially unchanged. This key trophic relationship between polychaetes and the changing environment due to the drilling operation was apparently uninterrupted. This relationship remains to be examined in other natural and perturbed habitats.     

Computer Monte Carlo simulation in quantitative resource estimation

The method of making quantitative assessments of mineral resources sufficiently detailed for economic analysis is outlined in three steps. The steps are (1) determination of types of deposits that may be present in an area, (2) estimation of the numbers of deposits of the permissible deposit types, and (3) combination by Monte Carlo simulation of the estimated numbers of deposits with the historical grades and tonnages of these deposits to produce a probability distribution of the quantities of contained metal.Two examples of the estimation of the number of deposits (step 2) are given. The first example is for mercury deposits in southwestern Alaska and the second is for lode tin deposits in the Seward Peninsula.The flow of the Monte Carlo simulation program is presented with particular attention to the dependencies between grades and tonnages of deposits and between grades of different metals in the same deposit.     

Variation in the value of mineral resources. Part I. The USA

The value of mineral resources produced in the USA during the 93 years, 1880–1972, deflated to 1967=100, totals 921 billions of dollars; this yields a value of $303,289 per mi² for the conterminous 48 states. Alaska has aggregated some 4160 millions of dollars during the same period, an average yield of some 7107 deflated dollars per mi². If we assume Alaska will achieve the average level of the “lower 48,”the potential value of its mineral resources is 178 billions of deflated 1967 dollars. Fuels account for about two-thirds of this value followed by about 20 percent for each of the aggregates, nonmetals and metals. The deflated dollar value of these four aggregate figures, fuels, nonmetals, metals, and total, during the period 1880–1972 are four time series and the economic processes which produced these series may be modelled through Box-Jenkins procedures. The value of fuels has steadily increased through the period, except for the depression years of the 1930s; this series may be represented as a multiplicative seasonal ARIMA(1,1,0)(1,0,1) model with periods at 4 and 3 yr for the autoregressive (AR) and moving average (MA) terms. Forecasts for 1973 to 1980, using the model, show the value of fuels produced to be about 20 billions of dollars per annum. The value of nonmetals also increased throughout the period except for a somewhat larger drop during the depression years of the 1930s. A multiplicative seasonal ARMA(1,0,0)(1,0,1) model with period at 7 yr for both the AR (autoregressive) and MA (moving average) terms appears to best reflect this series; the forecasts with this model fluctuate around their present annual value of some 6 billions of dollars. The value of metals behaves less consistently; it was much more strongly affected by the Great Depression and its subsequent growth is slower and less consistent than those of the fuels and nonmetals. It is appropriately represented by a multiplicative seasonal ARMA(1,0,0)(0,0,2) model with moving average (MA) periods at 6 and 11 yr respectively. Forecasts with this model show a decline in value for years beyond 1972; the large residual “error” \((\hat \sigma _e = 0.0925)\) , which is about twice as large as the equivalent errors for the value of fuels and nonmetals ( \(\hat \sigma _e = 0.0408\) and 0.0532, respectively), makes this forecast less firm. The total value of mineral resources is composed of all three series and, because fuels account for two-thirds of the total value, the two series closely resemble each other. The total value is not a simple aggregate of the three series; it is appropriately fitted by a multiplicative seasonal IMA(0,1,0)(0,0,2) model with periods at 7 and 11 yr (and error \(\hat \sigma _e = 0.0423\) ). Forecasts using this model imply that the total value of mineral resources produced will be over 30 billions of dollars per annum through 1980.     

Public attitudes and policies toward mineral resources on the brink of the 21st century

In this issue, we feature an article by W. David Menzie, a research geologist with the U.S. Geological Survey, Reston, Virginia. Dr. Menzie is a leading expert on quantitative mineral-resource assessment. He has made significant contributions to quantitative assessment methodologies through the development of spatial mineral deposit density models, grade and tonnage models, and the design of metrics for describing mineral deposit occurrences. He has also studied the geology and mineral resources of the Circle quadrangle, Alaska. Dr. Menzie earned a B.S. degree in geology from Dickinson College, an M.S. in geology, an M.A. in statistics, and a Ph.D. in Geology from the Pennsylvania State University.     

地下开采块状硫化物矿的一种简化经济滤波器

隐伏矿产资源评价和勘查早期，以及计划阶段，需要建立预可行成本模式。勘查过程中，区分经济与非经济矿床的这些成本模式有助于勘查企业集中在能获益的靶区勘查。资源评价过程中，这些模式用来排除那些即便发现但没有经济价值的矿床。美国矿业局（USBM）先前建立的简化成本模式就是为了解决这一问题的（Camm，1991）。这些成本模式采用矿床储量、品位和埋深参数评估运行成本和固定成本，也是USBM预可行分析软件的一部分（Smith，1991）。