Many conceptual models have been proposed to explain the fluid-flow mechanism responsible for the origin of carbonate-hosted lead-zinc deposits such as those in the Mississippi Valley and at Pine Point. This study is devoted to the quantitative investigation of one ore-genesis mechanism: gravity-driven groundwater-flow systems. Numerical modeling techniques are used to develop a self-contained computer code for two-dimensional simulation of regional transport processes along cross sections through sedimentary basins. The finite-element method is applied to solve the steady-state, fluid-flow and heat-transport equations, and a moving-particle random-walk model is developed to predict the dispersion and advection of aqueous components. The program EQ3/EQ6 is used to compute possible reaction-path scenarios at the ore-forming site. Full integration of geochemical calculations into the transport model is currently impractical because of computer-time limitations. Results of a sensitivity analysis indicate that gravity-driven ground-water-flow systems are capable of sustaining favorable fluid-flow rates, temperatures, and metal concentrations, for ore formation near the thin edge of a basin. Dispersive processes render long-distance transport of metal and sulfide in the same fluid an unlikely process in the genesis of large ore deposits, unless metal and sulfide are being added to the fluid along the flow path. The transport of metal in sulfate-type brines is a more defensible model, in which case the presence of reducing agents control the location of ore deposition. Hydrodynamic conditions that could result.--in ore formation through mixing of two fluids are rare. The theoretical approach is a powerful tool for gaining insight into the role of fluid flow in ore genesis and in the study of specific ore districts. A preliminary model of the Pine Point deposit suggests paleoflow rates on the order of 1.0 to 5.0 m³/m² yr, paleoconcentrations of zinc on the order of 1.0 to 5.0 mg/kg • H₂O, and paleotemperatures in the range 60°C to 100°C. Under these conditions, the time required for the formation of Pine Point would be on the order of 0.5 to 5.0 million years. / Science, Faculty of / Earth, Ocean and Atmospheric Sciences, Department of / Graduate

This study aims to investigate and identify how to effectively generate blurred geospatial heatmaps for use in geo-spatial map engines. We focus on how to store the points in a way that facilitates efficient window querying, with support for zoom-level handling. We decide on primarily using a Morton-ordered variant of the point-region quadtree, which we name a HeatMap Quadtree (HMQ). The nodes of the HMQ each have access to the points they contain, through storing the number of points and the lower bound of where to look at in the input point set, which we also store in Morton order. The HMQ also has the functionality to allow for window querying at different levels of detail. We parallelize the generation of the HMQ as well as the Gaussian blurring of the raster resulting from the window query using CUDA, and compare this implementation with that of two naive solutions as well as a linear point-region quadtree. In conclusion we find that the HMQ provides a significant improvement in window querying time, at the cost of additional construction time. / Denna studie avser att undersöka och identifiera hur man effektivt kan generera Gaussiskt oskarpa geospatiala värmekartor för användning i geospatiala kartmotorer. Vi fokuserar på hur man ska lagra punkterna på ett sätt som underlättar effektiv `window querying', med stöd för zoomnivå-hantering. Vi bestämmer oss för att huvudsakligen använda oss av en Morton-ordnad variant av ett `point-region quadtree', vilket vi döper till `HeatMap Quadtree' (HMQ). Noderna i vårt HMQ har alla tillgång till punkterna dom innehåller, genom att lagra antalet punkter och den lägre gränsen för var man ska leta efter punkterna i den ursprunliga punktlistan, som vi också lagrar i Morton-ordning. Vårt HMQ har också funktionaliteten att tillåta `window querying' på olika detaljnivåer. Vi parallelliserar genererandet av vårt HMQ samt uträknandet av den Gaussiska oskärpan på rastret som resulterar från vår `window query' med hjälp av CUDA, och jämför denna implementation med två naiva lösningar samt ett linjärt `point-region quadtree'. Vår slutsats är att vårt HMQ ger en signifikant förbättring i `window query'-tid, till en kostnad av extra konstruktionstid.