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1.
The U.S. Geological Survey (USGS) is proposing to conduct a global mineral-resource assessment using geologic maps, significant deposits, and exploration history as minimal data requirements. Using a geologic map and locations of significant pluton-related deposits, the pluton-related-deposit tract maps from the USGS national mineral-resource assessment have been reproduced with GIS-based analysis and modeling techniques. Agreement, kappa, and Jaccard's C correlation statistics between the expert USGS and calculated tract maps of 87%, 40%, and 28%, respectively, have been achieved using a combination of weights-of-evidence and weighted logistic regression methods. Between the experts' and calculated maps, the ranking of states measured by total permissive area correlates at 84%. The disagreement between the experts and calculated results can be explained primarily by tracts defined by geophysical evidence not considered in the calculations, generalization of tracts by the experts, differences in map scales, and the experts' inclusion of large tracts that are arguably not permissive. This analysis shows that tracts for regional mineral-resource assessment approximating those delineated by USGS experts can be calculated using weights of evidence and weighted logistic regression, a geologic map, and the location of significant deposits. Weights of evidence and weighted logistic regression applied to a global geologic map could provide quickly a useful reconnaissance definition of tracts for mineral assessment that is tied to the data and is reproducible. 相似文献
2.
Aggregate is a low unit-value mineral commodity. Costs to move aggregate from the mine site to the point of use is a large fraction of the resource cost to users. Production sites for aggregate occur where suitable source materials exist and where transportation and market conditions are favorable. The increasing demand for aggregate and the difficulty of developing and permitting new sites and of renewal of permits on existing sites of aggregate production indicates that aggregate will be supplied from sources yet to be developed or delineated in many areas. Site development and permitting for aggregate production is difficult because many land management plans and zoning actions fail to anticipate prospective source areas for aggregate in a way that is consistent with both the source rock quality and the transportation and socioeconomic factors that define the economic viability of the industry. Spatial analysis provides a method to integrate both geology and economic (transportation and marketplace) parameters in a regional model. Weights of evidence (WofE) analysis has been used to measure the spatial correlation of geologic map, transportation network, and population data with current production sites for crushed stone aggregate in the New England region of the northeastern United States. Weighted logistic regression (WLR) is used with the WofE results to rank areas in terms of their relative suitability for production of crushed stone. Spatial analysis indicates that 85% of the 106 crushed stone aggregate quarries in New England are sited within 1.6 km (1 mile) of either a principal highway or rail line in the region. Seventy-eight percent of crushed stone aggregate quarries are sited in census tracts with population densities exceeding 100 people/mile2. These relations illustrate the importance of proximity to both transportation corridors and developing areas where aggregate is predominately used. Only one active crushed stone quarry is located in a census tract with a population density less than 15 people/mile2, reflecting the lack of sufficient market demand in many rural areas to develop an operation there. However, since 1990, almost all new quarries have been developed in census tracts with population densities less than 200 people/mile2, indicating the difficulty of permitting new quarry sites in highly populated areas. Crushed stone aggregate is produced predominately from three hard rock types that are distributed widely in New England; 28% of sites use granitic rock, 25% use carbonate rocks, and 25% use mafic rock types that are categorized as trap rock by the aggregate industry. The other crushed stone aggregate sources include a variety of fine-grained metamorphic rock types. Carbonate rocks and Jurassic basalt (the primary trap rock source) are the most prevalent source rocks on an area-weighted basis. Spatial analysis can be used on a regional scale to rank areas by their relative suitabilityfor crushed stone aggregate production based on geology, transportation, and population parameters. The results of this regional analysis can identify areas for more detailed evaluation. As transportation or population features change, the model can be revised easily to reflect these changes. 相似文献
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4.
Assessment of Exploration Bias in Data-Driven Predictive Models and the Estimation of Undiscovered Resources 总被引：3，自引：0，他引：3
The spatial distribution of discovered resources may not fully mimic the distribution of all such resources, discovered and
undiscovered, because the process of discovery is biased by accessibility factors (e.g., outcrops, roads, and lakes) and by
exploration criteria. In data-driven predictive models, the use of training sites (resource occurrences) biased by exploration
criteria and accessibility does not necessarily translate to a biased predictive map. However, problems occur when evidence
layers correlate with these same exploration factors. These biases then can produce a data-driven model that predicts known
occurrences well, but poorly predicts undiscovered resources.
Statistical assessment of correlation between evidence layers and map-based exploration factors is difficult because it is
difficult to quantify the “degree of exploration.” However, if such a degree-of-exploration map can be produced, the benefits
can be enormous. Not only does it become possible to assess this correlation, but it becomes possible to predict undiscovered,
instead of discovered, resources.
Using geothermal systems in Nevada, USA, as an example, a degree-of-exploration model is created, which then is resolved into
purely explored and unexplored equivalents, each occurring within coextensive study areas. A weights-of-evidence (WofE) model
is built first without regard to the degree of exploration, and then a revised WofE model is calculated for the “explored
fraction” only. Differences in the weights between the two models provide a correlation measure between the evidence and the
degree of exploration.
The data used to build the geothermal evidence layers are perceived to be independent of degree of exploration. Nevertheless,
the evidence layers correlate with exploration because exploration has preferred the same favorable areas identified by the
evidence patterns. In this circumstance, however, the weights for the “explored” WofE model minimize this bias. Using these
revised weights, posterior probability is extrapolated into unexplored areas to estimate undiscovered deposits. 相似文献
5.
D.?A.?GunnEmail author L.?D.?Jones M.?G.?Raines D.?C.?Entwisle P.?R.?N.?Hobbs 《Geotechnical and Geological Engineering》2005,23(6):773-791
The requirement for quantitative thermal property data in assessing the performance of an engineered repository is identified. Experimental methods for the measurement of thermal conductivity, thermal expansivity and heat capacity are outlined and typical test results are presented for two rock-types of interest in relation to the Sellafield site. The controls on the thermal properties are discussed and a series of corrections from the rock material to the rock mass properties are presented. Finally, a correction scheme that accounts for the effect of scale is followed. 相似文献
6.
Brian J. Anderson James A. Slavin Haje Korth Scott A. Boardsen Thomas H. Zurbuchen Jim M. Raines George Gloeckler Ralph L. McNutt Jr. Sean C. Solomon 《Planetary and Space Science》2011,59(15):2037-2050
Magnetic field and plasma data from the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft on the outbound portions of the first (M1) and second (M2) flybys of Mercury reveal a region of depressed magnetic field magnitude and enhanced proton fluxes adjacent to but within the magnetopause, which we denote as a dayside boundary layer. The layer was present during both encounters despite the contrasting dayside magnetic reconnection, which was minimal during M1 and strong during M2. The overall width of the layer is estimated to be between 1000 and 1400 km, spanning most of the distance from the dayside planetary surface to the magnetopause in the mid-morning. During both flybys the magnetic pressure decrease was ∼1.6 nPa, and the width of the inner edge was comparable to proton gyro-kinetic scales. The maximum variance in the magnetic field across the inner edge was aligned with the magnetic field vector, and the magnetic field direction did not change markedly, indicating that the change in field intensity was consistent with an outward plasma-pressure gradient perpendicular to the magnetic field. Proton pressures in the layer inferred from reduced distribution observations were 0.4 nPa during M1 and 1.0 nPa during M2, indicating either that the proton pressure estimates are low or that heavy ions contribute substantially to the boundary-layer plasma pressure. If the layer is formed by protons drifting westward from the cusp, there should be a strong morning–afternoon asymmetry that is independent of the interplanetary magnetic field (IMF) direction. Conversely, if heavy ions play a major role, the layer should be strong in the morning (afternoon) for northward (southward) IMF. Future MESSENGER observations from orbit about Mercury should distinguish between these two possibilities. 相似文献
7.
A recently published study has shown that small-scale geologic map data can reproduce mineral assessments made with considerably
larger scale data. This result contradicts conventional wisdom about the importance of scale in mineral exploration, at least
for regional studies. In order to formally investigate aspects of scale, a weights-of-evidence analysis using known gold occurrences
and deposits in the Central Lapland Greenstone Belt of Finland as training sites provided a test of the predictive power of
the aeromagnetic data. These orogenic-mesothermal-type gold occurrences and deposits have strong lithologic and structural
controls associated with long (up to several kilometers), narrow (up to hundreds of meters) hydrothermal alteration zones
with associated magnetic lows. The aeromagnetic data were processed using conventional geophysical methods of successive upward
continuation simulating terrane clearance or ‘flight height’ from the original 30 m to an artificial 2000 m. The analyses
show, as expected, that the predictive power of aeromagnetic data, as measured by the weights-of-evidence contrast, decreases
with increasing flight height. Interestingly, the Moran autocorrelation of aeromagnetic data representing differing flight
height, that is spatial scales, decreases with decreasing resolution of source data. The Moran autocorrelation coefficient
scems to be another measure of the quality of the aeromagnetic data for predicting exploration targets. 相似文献
8.
D.?C.?EntwisleEmail author P.?R.?N.?Hobbs L.?D.?Jones D.?Gunn M.?G.?Raines 《Geotechnical and Geological Engineering》2005,23(6):793-809
The effective porosity, saturated sonic velocity and saturated uniaxial compressive strength were determined on a large number of Borrowdale Volcanic Group volcaniclastic core samples from three boreholes at Sellafield, Cumbria. The work formed part of the UK Nirex Limited site investigation into whether the Sellafield area could be suitable as a repository for intermediate and low level radioactive waste. Most of the intact samples were of low to very low effective porosity, had a high sonic velocity and were very strong to extremely strong. However, a proportion of values deviated significantly from this. Bivariate analysis showed a negative relationship exists between sonic velocity and effective porosity. The cross plots of these two parameters with uniaxial compressive strength showed a wide range of strength values for samples of low effective porosity and high sonic velocity. Six failure types were identified during the uniaxial compressive strength tests. The strongest samples tended to fail through the matrix and the weakest rock samples tended to fail through haematized material or along haematized veins. Effective porosity and sonic velocity measurements could not distinguish between those samples that failed through the matrix and those that failed along discrete narrow veins. The presence of narrow haematized veins has a major effect on the intact rock strength. 相似文献
9.
Raines SN Watson DM Pipher JL Forrest WJ Greenhouse MA Satyapal S Woodward CE Smith HA Fischer J Goetz JA Frank A 《The Astrophysical journal》2000,533(2):L115-L118
When some magnetic field lines connect a Kerr black hole with a disk rotating around it, energy and angular momentum are transferred between them. If the black hole rotates faster than the disk, ca&solm0;GMH>0.36 for a thin Keplerian disk, then energy and angular momentum are extracted from the black hole and transferred to the disk (MH is the mass and aMH is the angular momentum of the black hole). This way, the energy originating in the black hole may be radiated away by the disk. The total amount of energy that can be extracted from the black hole spun down from ca&solm0;GMH=0.998 to ca&solm0;GMH=0.36 by a thin Keplerian disk is approximately 0.15MHc2. This is larger than approximately 0.09MHc2, which can be extracted by the Blandford-Znajek mechanism. 相似文献
10.
Gary L. Raines 《Natural Resources Research》2008,17(2):87-97
It has been proposed that the spatial distribution of mineral deposits is bifractal. An implication of this property is that
the number of deposits in a permissive area is a function of the shape of the area. This is because the fractal density functions
of deposits are dependent on the distance from known deposits. A long thin permissive area with most of the deposits in one
end, such as the Alaskan porphyry permissive area, has a major portion of the area far from known deposits and consequently
a low density of deposits associated with most of the permissive area. On the other hand, a more equi-dimensioned permissive
area, such as the Arizona porphyry permissive area, has a more uniform density of deposits. Another implication of the fractal
distribution is that the Poisson assumption typically used for estimating deposit numbers is invalid. Based on datasets of
mineral deposits classified by type as inputs, the distributions of many different deposit types are found to have characteristically
two fractal dimensions over separate non-overlapping spatial scales in the range of 5–1000 km. In particular, one typically
observes a local dimension at spatial scales less than 30–60 km, and a regional dimension at larger spatial scales. The deposit
type, geologic setting, and sample size influence the fractal dimensions. The consequence of the geologic setting can be diminished
by using deposits classified by type. The crossover point between the two fractal domains is proportional to the median size
of the deposit type. A plot of the crossover points for porphyry copper deposits from different geologic domains against median
deposit sizes defines linear relationships and identifies regions that are significantly underexplored. Plots of the fractal
dimension can also be used to define density functions from which the number of undiscovered deposits can be estimated. This
density function is only dependent on the distribution of deposits and is independent of the definition of the permissive
area. Density functions for porphyry copper deposits appear to be significantly different for regions in the Andes, Mexico,
United States, and western Canada. Consequently, depending on which regional density function is used, quite different estimates
of numbers of undiscovered deposits can be obtained. These fractal properties suggest that geologic studies based on mapping
at scales of 1:24,000 to 1:100,000 may not recognize processes that are important in the formation of mineral deposits at
scales larger than the crossover points at 30–60 km. 相似文献