The deposit size frequency method for estimating undiscovered uranium deposits

The deposit size frequency (DSF) method has been developed as a generalization of the method that was used in the National Uranium Resource Evaluation (NURE) program to estimate the uranium endowment of the United States. The DSF method overcomes difficulties encountered during the NURE program when geologists were asked to provide subjective estimates of (1) the endowed fraction of an area judged favorable (factorF) for the occurrence of undiscovered uranium deposits and (2) the tons of endowed rock per unit area (factorT) within the endowed fraction of the favorable area. Because the magnitudes of factorsF andT were unfamiliar to nearly all of the geologists, most geologists responded by estimating the number of undiscovered deposits likely to occur within the favorable area and the average size of these deposits. The DSF method combines factorsF andT into a single factor (F·T) that represents the tons of endowed rock per unit area of the undiscovered deposits within the favorable area. FactorF·T, provided by the geologist, is the estimated number of undiscovered deposits per unit area in each of a number of specified deposit-size classes. The number of deposit-size classes and the size interval of each class are based on the data collected from the deposits in known (control) areas. The DSF method affords greater latitude in making subjective estimates than the NURE method and emphasizes more of the everyday experience of exploration geologists. Using the DSF method, new assessments have been made for the young, organic-rich surficial uranium deposits in Washington and idaho and for the solution-collapse breccia pipe uranium deposits in the Grand Canyon region in Arizona and adjacent Utah.     

Characterizing heterogeneous permeable media with spatial statistics and tracer data using sequential simulated annealing

Characterizing heterogeneous permeable media using flow and transport data typically requires solution of an inverse problem. Such inverse problems are intensive computationally and may involve iterative procedures requiring many forward simulations of the flow and transport problem. Previous attempts have been limited mostly to flow data such as pressure transient (interference) tests using multiple observation wells. This paper discusses an approach to generating stochastic permeability fields conditioned to geologic data in the form of a vertical variogram derived from cores and logs as well as fluid flow and transport data, such as tracer concentration history, by sequential application of simulated annealing (SA). Thus, the method incorporates elements of geostatistics within the framework of inverse modeling. For tracer-transport calculations, we have used a semianalytic transit-time algorithm which is fast, accurate, and free of numerical dispersion. For steady velocity fields, we introduce a transit-time function which demonstrates the relative importance of data from different sources. The approach is illustrated by application to a set of spatial permeability measurements and tracer data from an experiment in the Antolini Sandstone, an eolian outcrop from northern Arizona. The results clearly reveal the importance of tracer data in reproducing the correlated features (channels) of the permeability field and the scale effects of heterogeneity.     

Estimation for partially observed Markov processes

Many stochastic process models for environmental data sets assume a process of relatively simple structure which is in some sense partially observed. That is, there is an underlying process (X_n, n 0) or (X_t, t 0) for which the parameters are of interest and physically meaningful, and an observable process (Y_n, n 0) or (Y_t, t 0) which depends on the X process but not otherwise on those parameters. Examples are wide ranging: the Y process may be the X process with missing observations; the Y process may be the X process observed with a noise component; the X process might constitute a random environment for the Y process, as with hidden Markov models; the Y process might be a lower dimensional function or reduction of the X process. In principle, maximum likelihood estimation for the X process parameters can be carried out by some form of the EM algorithm applied to the Y process data. In the paper we review some current methods for exact and approximate maximum likelihood estimation. We illustrate some of the issues by considering how to estimate the parameters of a stochastic Nash cascade model for runoff. In the case of k reservoirs, the outputs of these reservoirs form a k dimensional vector Markov process, of which only the kth coordinate process is observed, usually at a discrete sample of time points.     

Using numerical modelling to evaluate tsunami hazard near the Kuril Island

A sequence of computer experiments is used to study questions concerning the tsunami problem as a quantitative estimate of tsunami danger, detailed geographical tsunami classification, determination of the parameters of critical tsunami waves, and the conditions of their development. We call a wave critical, if its impact on the coast is most hazardous.Using the Middle Kuril Island as an example, we present the results of a computer experiment which includes determining the wavefields on the shelf and estimating the effects connected with the deep-water Bussol and Diana Straits.Numerical simulation of tsunami waves of different sources permits the assessment of the extent of tsunami danger in different areas of the coastal zone of Simushir Island, depending on the location of the focus zone and their geometry.The major singularities of the wavefield arise in the zones of the deep-water straits. The distribution of the amplification factors is determined by both the global parameters of the wavefields and the local properties of individual harbours. The results obtained for a particular harbour in the northern part of Simushir Island, formed the basis for the quantitative estimate of tsunami danger for this area.     

新疆第三次荒漠化监测中的问题及其建议

回顾了新疆3次在荒漠化监测中所进行的荒漠化监测与评价指标体系的建立，也是新疆开展荒漠化监测的基础；介绍了以遥感与地理信息为主要技术的荒漠化监测评价的方法；阐述了新疆第三次荒漠化监测中存在的问题。指出目前新疆荒漠化评价存在的主要问题是评价指标的不确定性、评价指标体系的难操作性和遥感数据源选用的随机性，进而对上述问题的解决途径进行了讨论。     

Spatial analysis of elements in soils from Chengdu City

Three kinds of spatial analysis methods （geostatistics, concentration-area fractal model and the multifractal analysis called the moment method） were used for almost 50 elements, including heavy metals, disperse elements, rare elements and even others, in 6586 top soil （0-20 cm） samples and 1833 deep soil （150-200 cm） samples from Chengdu metropolitan area of 12400 km^2, southwestern China. The ranges of spatial correlation revealed by variograms are quite different for different kinds of elements in the top and deep soils. The most interest is the fact that the multifractal spectra of environmentally important elements such as Pb, Cr, Cd and Ni in top soils in the metropolitan area show systematic change from those in the deep soils, revealing a strong anthropogenic addition, while Hg, Zn, As, Cu and all common elements show no such kind of addition. In terms of multifractal properties based on the multifractal spectrum curves, those disperse and rare elements show great deviation from other major and trace elements, which is also of great interest.     

Geophysical methods applied to fault characterization and earthquake potential assessment in the Lower Tagus Valley, Portugal

The study region is located in the Lower Tagus Valley, central Portugal, and includes a large portion of the densely populated area of Lisbon. It is characterized by a moderate seismicity with a diffuse pattern, with historical earthquakes causing many casualties, serious damage and economic losses. Occurrence of earthquakes in the area indicates the presence of seismogenic structures at depth that are deficiently known due to a thick Cenozoic sedimentary cover. The hidden character of many of the faults in the Lower Tagus Valley requires the use of indirect methodologies for their study. This paper focuses on the application of high-resolution seismic reflection method for the detection of near-surface faulting on two major tectonic structures that are hidden under the recent alluvial cover of the Tagus Valley, and that have been recognized on deep oil-industry seismic reflection profiles and/or inferred from the surface geology. These are a WNW–ESE-trending fault zone located within the Lower Tagus Cenozoic basin, across the Tagus River estuary (Porto Alto fault), and a NNE–SSW-trending reverse fault zone that borders the Cenozoic Basin at the W (Vila Franca de Xira–Lisbon fault). Vertical electrical soundings were also acquired over the seismic profiles and the refraction interpretation of the reflection data was carried out. According to the interpretation of the collected data, a complex fault pattern disrupts the near surface (first 400 m) at Porto Alto, affecting the Upper Neogene and (at least for one fault) the Quaternary, with a normal offset component. The consistency with the previous oil-industry profiles interpretation supports the location and geometry of this fault zone. Concerning the second structure, two major faults were detected north of Vila Franca de Xira, supporting the extension of the Vila Franca de Xira–Lisbon fault zone northwards. One of these faults presents a reverse geometry apparently displacing Holocene alluvium. Vertical offsets of the Holocene sediments detected in the studied geophysical data of Porto Alto and Vila Franca de Xira–Lisbon faults imply minimum slip rates of 0.15–0.30 mm/year, three times larger than previously inferred for active faults in the Lower Tagus Valley and maximum estimates of average return periods of 2000–5000 years for M 6.5–7 co-seismic ruptures.