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G. L. Raines

Publications and source records attributed to G. L. Raines.

At least 19 recordsLinked to original sources
USGS2008

Are fractal dimensions of the spatial distribution of mineral deposits meaningful?

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. ?? 2008 International Association for Mathematical Geology.

Natural Resources Research↗
USGS2007

Development and implementation of a Bayesian-based aquifer vulnerability assessment in Florida

The Florida Aquifer Vulnerability Assessment (FAVA) was designed to provide a tool for environmental, regulatory, resource management, and planning professionals to facilitate protection of groundwater resources from surface sources of contamination. The FAVA project implements weights-of-evidence (WofE), a data-driven, Bayesian-probabilistic model to generate a series of maps reflecting relative aquifer vulnerability of Florida's principal aquifer systems. The vulnerability assessment process, from project design to map implementation is described herein in reference to the Floridan aquifer system (FAS). The WofE model calculates weighted relationships between hydrogeologic data layers that influence aquifer vulnerability and ambient groundwater parameters in wells that reflect relative degrees of vulnerability. Statewide model input data layers (evidential themes) include soil hydraulic conductivity, density of karst features, thickness of aquifer confinement, and hydraulic head difference between the FAS and the watertable. Wells with median dissolved nitrogen concentrations exceeding statistically established thresholds serve as training points in the WofE model. The resulting vulnerability map (response theme) reflects classified posterior probabilities based on spatial relationships between the evidential themes and training points. The response theme is subjected to extensive sensitivity and validation testing. Among the model validation techniques is calculation of a response theme based on a different water-quality indicator of relative recharge or vulnerability: dissolved oxygen. Successful implementation of the FAVA maps was facilitated by the overall project design, which included a needs assessment and iterative technical advisory committee input and review. Ongoing programs to protect Florida's springsheds have led to development of larger-scale WofE-based vulnerability assessments. Additional applications of the maps include land-use planning amendments and prioritization of land purchases to protect groundwater resources. ?? International Association for Mathematical Geology 2007.

Natural Resources Research↗
USGS2007

Assessment of exploration bias in data-driven predictive models and the estimation of undiscovered resources

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. ?? International Association for Mathematical Geology 2007.

Natural Resources Research↗
USGS2007

Porphyry copper deposit tract definition - A global analysis comparing geologic map scales

Geologic maps are a fundamental data source used to define mineral-resource potential tracts for the first step of a mineral resource assessment. Further, it is generally believed that the scale of the geologic map is a critical consideration. Previously published research has demonstrated that the U.S. Geological Survey porphyry tracts identified for the United States, which are based on 1:500,000-scale geology and larger scale data and published at 1:1,000,000 scale, can be approximated using a more generalized 1:2,500,000-scale geologic map. Comparison of the USGS porphyry tracts for the United States with weights-of-evidence models made using a 1:10,000,000-scale geologic map, which was made for petroleum applications, and a 1:35,000,000-scale geologic map, which was created as context for the distribution of porphyry deposits, demonstrates that, again, the USGS US porphyry tracts identified are similar to tracts defined on features from these small scale maps. In fact, the results using the 1:35,000,000-scale map show a slightly higher correlation with the USGS US tract definition, probably because the conceptual context for this small-scale map is more appropriate for porphyry tract definition than either of the other maps. This finding demonstrates that geologic maps are conceptual maps. The map information shown in each map is selected and generalized for the map to display the concepts deemed important for the map maker's purpose. Some geologic maps of small scale prove to be useful for regional mineral-resource tract definition, despite the decrease in spatial accuracy with decreasing scale. The utility of a particular geologic map for a particular application is critically dependent on the alignment of the intention of the map maker with the application. ?? International Association for Mathematical Geology 2007.

Natural Resources Research↗
USGS2007

Quantitative analysis of scale of aeromagnetic data raises questions about geologic-map scale

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. ?? Springer Science+Business Media, LLC 2007.

Natural Resources Research↗
USGS2006

Prediction and discovery of new geothermal resources in the Great Basin: Multiple evidence of a large undiscovered resource base

Geothermal potential maps by themselves cannot directly be used to estimate undiscovered resources. To address the undiscovered resource base in the Great Basin, a new and relatively quantitative methodology is presented. The methodology involves three steps, the first being the construction of a data-driven probabilistic model of the location of known geothermal systems using weights of evidence. The second step is the construction of a degree-of-exploration model. This degree-of-exploration model uses expert judgment in a fuzzy logic context to estimate how well each spot in the state has been explored, using as constraints digital maps of the depth to the water table, presence of the carbonate aquifer, and the location, depth, and type of drill-holes. Finally, the exploration model and the data-driven occurrence model are combined together quantitatively using area-weighted modifications to the weights-of-evidence equations. Using this methodology in the state of Nevada, the number of undiscovered geothermal systems with reservoir temperatures ???100??C is estimated at 157, which is 3.2 times greater than the 69 known systems. Currently, nine of the 69 known systems are producing electricity. If it is conservatively assumed that an additional nine for a total of 18 of the known systems will eventually produce electricity, then the model predicts 59 known and undiscovered geothermal systems are capable of producing electricity under current economic conditions in the state, a figure that is more than six times higher than the current number. Many additional geothermal systems could potentially become economic under improved economic conditions or with improved methods of reservoir stimulation (Enhanced Geothermal Systems).This large predicted geothermal resource base appears corroborated by recent grass-roots geothermal discoveries in the state of Nevada. At least two and possibly three newly recognized geothermal systems with estimated reservoir temperatures ???150??C have been identified on the Pyramid Lake Paiute Reservation in west-central Nevada. Evidence of three blind geothermal systems has recently been uncovered near the borate-bearing playas at Rhodes, Teels, and Columbus Marshes in southwestern Nevada. Recent gold exploration drilling has resulted in at least four new geothermal discoveries, including the McGinness Hills geothermal system with an estimated reservoir temperature of roughly 200??C. All of this evidence suggests that the potential for expansion of geothermal power production in Nevada is significant.

Conference Paper↗
USGS2005

Predicting mining activity with parallel genetic algorithms

We explore several different techniques in our quest to improve the overall model performance of a genetic algorithm calibrated probabilistic cellular automata. We use the Kappa statistic to measure correlation between ground truth data and data predicted by the model. Within the genetic algorithm, we introduce a new evaluation function sensitive to spatial correctness and we explore the idea of evolving different rule parameters for different subregions of the land. We reduce the time required to run a simulation from 6 hours to 10 minutes by parallelizing the code and employing a 10-node cluster. Our empirical results suggest that using the spatially sensitive evaluation function does indeed improve the performance of the model and our preliminary results also show that evolving different rule parameters for different regions tends to improve overall model performance. Copyright 2005 ACM.

Conference Paper↗
USGS2003

Genetic Algorithm Calibration of Probabilistic Cellular Automata for Modeling Mining Permit Activity

We use a genetic algorithm to calibrate a spatially and temporally resolved cellular automata to model mining activity on public land in Idaho and western Montana. The genetic algorithm searches through a space of transition rule parameters of a two dimensional cellular automata model to find rule parameters that fit observed mining activity data. Previous work by one of the authors in calibrating the cellular automaton took weeks - the genetic algorithm takes a day and produces rules leading to about the same (or better) fit to observed data. These preliminary results indicate that genetic algorithms are a viable tool in calibrating cellular automata for this application. Experience gained during the calibration of this cellular automata suggests that mineral resource information is a critical factor in the quality of the results. With automated calibration, further refinements of how the mineral-resource information is provided to the cellular automaton will probably improve our model.

Conference Paper↗
USGS2003

Geothermal GIS coverage of the Great Basin, USA: Defining regional controls and favorable exploration terrains

A geographic information system (GIS) of geothermal resources, built last year for the state of Nevada, is being expanded to cover the Great Basin, USA. Data from that GIS is being made available to industry, other researchers, and the public via a web site at the Great Basin Center for Geothermal Energy, Reno, Nevada. That web site features a search engine, supports ArcExplorer?? for on-line map construction, and provides downloadable data layers in several formats. Though data collection continues, preliminary analysis has begun. Contour maps of geothermal temperatures, constructed using geothermometer temperatures calculated from a Great Basin geochemical database compiled by the Geo-Heat Center, reveal distinctive trends and patterns. As expected, magmatic-type and extensional-type geothermal systems have profoundly different associations, with magmatic-type systems following major tectonic boundaries, and extensional-type systems associating with regionally high heat flow, thin crust, active faulting, and high extensional strain rates. As described by earlier researchers, including Rowen and Wetlaufer (1981) and Koenig and McNitt (1983), high-temperature (> 100??C) geothermal systems appear to follow regional northeast trends, most conspicuously including the Humboldt structural zone in Nevada, the "Black Rock-Alvord Desert" trend in Oregon and Nevada, and the "Newcastle-Roosevelt" trend in Utah and Nevada. Weights-of-evidence analyses confirm a preference of high-temperature geothermal systems for young northeast-trending faults, but the distribution of geothermal systems correlates even better with high rates of crustal extension, as measured from global positioning system (GPS) stations in Nevada. A predictive map of geothermal potential based only on areas of high extensional strain rates and high heat flux does an excellent job of regionally predicting the location of most known geothermal systems in Nevada, and may prove useful in identifying blind systems.

Conference Paper↗
USGS2002

Description and comparison of geologic maps with FRAGSTATS - A spatial statistics program

FRAGSTATS is a public-domain GIS implementation of a set of spatial statistics that address a fundamental problem in GIS applications, description and comparison of maps. The spatial statistics from the 1:2,500,000-scale United States geologic map of Nevada, the central United States, and the northeastern United States quantify the differences in complexity and variability between these three geologic terranes. Nevada is defined by a large number of patches of small size and low size variability, whereas the Central area has a small number of patches with smaller relative size variability. All three areas have similar map-unit shape complexity with Nevada having the lowest. Based on the density of edges, the areas can be ranked from highest to lowest, as Nevada, Central, and Northeast. The Shannon diversity index ranks the areas from highest to lowest, as Northeast, Nevada, and Central, but the Shannon evenness index ranks them from highest to lowest, as Northeast, Central, and Nevada. These rankings may reflect the influence of folding in the Northeast and Central areas as opposed to basin and range extension in Nevada. The core areas statistic ranks the areas for spatial accuracy from highest to lowest, as Central, Northeast, and Nevada, with Northeast and Nevada being similar. For a scale comparison, the FRAGSTATS statistics quantify the increased complexity and spatial accuracy that is inherent in going from small- to larger-scale maps. For example for 1:2,500,000-1:500,000-scale maps of Nevada, respectively, the area weighted fractal dimension increase from 1.1 to 1.18, and the total core areas index almost doubles from 39.09 to 63.38. In addition, the fractal dimensions discriminate gross lithology and tectonic terranes. ?? 2002 Elsevier Science Ltd. All rights reserved.

Computers & Geosciences↗
USGS2002

Preliminary cellular-automata forecast of permit activity from 1998 to 2010, Idaho and Western Montana

For public land management in Idaho and western Montana, the U.S. Forest Service (USFS) has requested that the U.S. Geological Survey (USGS) predict where mineral-related activity will occur in the next decade. Cellular automata provide an approach to simulation of this human activity. Cellular automata (CA) are defined by an array of cells , which evolve by a simple transition rule, the automaton . Based on exploration trends, we assume that future exploration will focus in areas of past exploration. Spatial-temporal information about mineral-related activity, that is permits issued by USFS and Bureau of Land Management (BLM) in the last decade, and spatial information about undiscovered resources, provide a basis to calibrate a CA. The CA implemented is a modified annealed voting rule that simulates mineral-related activity with spatial and temporal resolution of 1 mi 2 and 1 year based on activity from 1989 to 1998. For this CA, the state of the economy and exploration technology is assumed constant for the next decade. The calibrated CA reproduces the 1989–1998-permit activity with an agreement of 94%, which increases to 98% within one year. Analysis of the confusion matrix and kappa correlation statistics indicates that the CA underestimates high activity and overestimates low activity. Spatially, the major differences between the actual and calculated activity are that the calculated activity occurs in a slightly larger number of small patches and is slightly more uneven than the actual activity. Using the calibrated CA in a Monte Carlo simulation projecting from 1998 to 2010, an estimate of the probability of mineral activity shows high levels of activity in Boise, Caribou, Elmore, Lincoln, and western Valley counties in Idaho and Beaverhead, Madison, and Stillwater counties in Montana, and generally low activity elsewhere.

Idaho, Montana↗
USGS2002

A Geothermal GIS for Nevada: Defining Regional Controls and Favorable Exploration Terrains for Extensional Geothermal Systems

Spatial analysis with a GIS was used to evaluate geothermal systems in Nevada using digital maps of geology, heat flow, young faults, young volcanism, depth to groundwater, groundwater geochemistry, earthquakes, and gravity. High-temperature (>160??C) extensional geothermal systems are preferentially associated with northeast-striking late Pleistocene and younger faults, caused by crustal extension, which in most of Nevada is currently oriented northwesterly (as measured by GPS). The distribution of sparse young (<1.5Ma) basaltic vents also correlate with geothermal systems, possibly because the vents help identify which young structures penetrate deeply into the crust. As expected, elevated concentrations of boron and lithium in groundwater were found to be favorable indicators of geothermal activity. Known high-temperature (>160??C) geothermal systems in Nevada are more likely to occur in areas where the groundwater table is shallow (<30m). Undiscovered geothermal systems may occur where groundwater levels are deeper and hot springs do not issue at the surface. A logistic regression exploration model was developed for geothermal systems, using young faults, young volcanics, positive gravity anomalies, and earthquakes to predict areas where deeper groundwater tables are most likely to conceal geothermal systems.

Conference Paper↗
USGS2001

Assessment method for epithermal gold deposits in northeast Washington State using weights-of-evidence GIS modeling

The weights-of-evidence analysis, a quantitative mineral resource mapping tool, is used to delineate favorable areas for epithermal gold deposits and to predict future exploration activity of the mineral industry for similar deposits in a four-county area (222 x 277 km), including the Okanogan and Colville National Forests of northeastern Washington. Modeling is applied in six steps: (1) building a spatial digital database, (2) extracting predictive evidence for a particular deposit, based on an exploration model, (3) calculating relative weights for each predictive map, (4) combining the geologic evidence maps to predict the location of undiscovered mineral resources and (5) measuring the intensity of recent exploration activity by use of mining claims on federal lands, and (6) combining mineral resource and exploration activity into an assessment model of future mining activity. The analysis is accomplished on a personal computer using ArcView GIS platform with Spatial Analyst and Weights-of-Evidence software. In accord with the descriptive model for epithermal gold deposits, digital geologic evidential themes assembled include lithologic map units, thrust faults, normal faults, and igneous dikes. Similarly, geochemical evidential themes include placer gold deposits and gold and silver analyses from stream sediment (silt) samples from National Forest lands. Fifty mines, prospects, or occurrences of epithermal gold deposits, the training set, define the appropriate a really-associated terrane. The areal (or spatial) correlation of each evidential theme with the training set yield predictor theme maps for lithology, placer sites and normal faults. The weights-of-evidence analysis disqualified the thrust fault, dike, and gold and silver silt analyses evidential themes because they lacked spatial correlation with the training set. The decision to accept or reject evidential themes as predictors is assisted by considering probabilistic data consisting of weights and contrast values calculated for themes according to areal correlation with the training sites. Predictor themes having acceptable weights and contrast values are combined into a preliminary model to predict the locations of undiscovered epithermal gold deposits. This model facilitates ranking of tracts as non-permissive, permissive or favorable categories based on exclusionary, passive, and active criteria through evaluation of probabilistic data provided by interaction of predictor themes. The method is very similar to the visual inspection method of drawing conclusions from anomalies on a manually overlain system of maps. This method serves as a model for future mineral assessment procedures because of its objective nature. To develop a model to predict future exploration activity, the locations of lode mining claims were summarized for 1980, 1985, 1990, and 1996. Land parcels containing historic claims were identified either as those with mining claims present in 1980 or valid claims present in 1985. Current claim parcels were identified as those containing valid lode claims in either 1990 or 1996. A consistent parcel contains both historic and current claims. The epithermal gold and mining claim activity models were combined into an assessment (or mineral resource-activity) model to assist in land use decisions by providing a prediction of mineral exploration activity on federal land in the next decade. Ranks in the assessment model are: (1) no activity, (2) low activity, (3) low to moderate activity, (4) moderate activity and (5) high activity.

Washington↗
USGS1992

The Conterminous United States Mineral Assessment Program: Background information to accompany folio of geologic, geochemical, geophysical, and mineral resource maps of the Ajo and Lukeville 1° by 2° quadrangles, Arizona

Encompassing about 21,000 km 2 in southwestern Arizona, the Ajo and Lukeville 1° by 2° quadrangles have been the subject of mineral resource investigations utilizing field and laboratory studies in the disciplines of geology, geochemistry, geophysics, and Landsat imagery. The results of these studies are published as a folio of maps, figures, and tables, with accompanying discussions. Past mineral production has been limited to copper from the Ajo Mining District. In addition to copper, the quadrangles contain potentially significant resources of gold and silver; a few other commodities, including molybdenum and evaporites, may also exist in the area as appreciable resources. This circular provides background information on the mineral deposits and on the investigations and integrates the information presented in the folio. The bibliography cites references to the geology, geochemistry, geophysics, and mineral deposits of the two quadrangles.

Arizona↗