Single-element Anomaly Mapping from Stream Sediment Geochemical Landscapes Aided by Digital Terrain Analysis

The identification of anomalies within stream sediment geochemical data is one of the fastest developing areas in mineral exploration.The various means used to achieve this objective make use of either continuous or discrete field models of stream sediment geochemical data.To map anomalies in a discrete field model of such data,two corrections are required:background correction and downstream dilution correction.Topography and geomorphology are important factors in variations of element content in stream sediments.However,few studies have considered,through the use of digital terrain analysis,the influence of geomorphic features in downstream dilution correction of stream sediment geochemical data.This study proposes and demonstrates an improvement to the traditional downstream dilution correction equation,based on the use of digital terrain analysis to map single-element anomalies in stream sediment geochemical landscapes.Moreover,this study compares the results of analyses using discrete and continuous field models of stream sediment geochemical data from the Xincang area,Tibet.The efficiency of the proposed methodology was validated against known mineral occurrences.The results indicate that catchment-based analysis outperforms interpolation-based analysis of stream sediment geochemical data for anomaly mapping.Meanwhile,the proposed modified downstream dilution correction equation proved more effective than the original equation.However,further testing of this modified downstream dilution correction is needed in other areas,in order to investigate its efficiency further.

A Fractal Measure of Spatial Association between Landslides and Conditioning Factors

Measuring the relative importance and assigning weights to conditioning factors of land- slides occurrence are significant for landslide prevention and/or mitigation. In this contribution, a fractal method is introduced for measuring the spatial relationships between landslides and condition- ing factors （such as faults, rivers, geological boundaries, and roads）, and for assigning weights to condi- tioning factors for mapping of landslide susceptibility. This method can be expressed as p=C~, where d is the fractal dimension, and C is a constant. This relationship indicates a fractal relation between land- slide density （p） and distances to conditioning factors （6）. The case of d〉0 suggests a significant spatial correlation between landslides and conditioning factors. The larger the d （〉0） value, the stronger the spatial correlation is between landslides and a specific conditioning factor. Two case studies in South China were examined to demonstrate the usefulness of this novel method.

Petrophysical Texture Heterogeneity of Vesicles in Andesite Reservoir on Micro-Scales

It is of great significance to study the spatial distribution patterns and petrophysical complexity of volcanic vesicles which determine whether the reservoir spaces of the volcanic rocks can accumulate oil and gas and enrich high yields or not.In this paper,the digital images of three different textures of vesicular andesite samples,including spherical vesicular andesite,shear deformation vesicular andesite,and secondary filling vesicular andesite,are obtained by microscopic morphology X-CT imaging technology.The spatial micro-vesicle heterogeneity of vesicular andesite samples with different textures is quantitatively analyzed by fractal and multifractal methods such as box-counting dimension and the moment method.It is found that the shear stress weakens the spatial homogeneity since vesicles rupture are accelerated,elongated directionally,and connected with one another under the strain;the secondary filling breaks the vesicles,which significantly enhances the spatial heterogeneity.In addition,shear stress and secondary filling increase the complexity of vesicle microstructures characterized by different fractal and multifractal parameters.These conclusions will provide important theoretical and practical insights into understanding the degassing of volcanic rocks and prediction of high-quality volcanic reservoirs.

Fuzzy Modeling of Surficial Uranium Prospectivity in British Columbia(Canada)with a Weighted Fuzzy Algebraic Sum Operator

This paper demonstrates knowledge-guided fuzzy logic modeling of regional-scale surficial uranium(U)prospectivity in British Columbia(Canada).The deposits/occurrences of surficial U in this region vary from those in Western Australia and Namibia;thus,requiring innovative and carefully-thought techniques of spatial evidence generation and integration.As novelty,this papers introduces a new weighted fuzzy algebraic sum operator to combine certain spatial evidence layers.The analysis trialed several layers of spatial evidence based on conceptual mineral system model of surficial U in British Columbia(Canada)as well as tested various models of evidence integration.Non-linear weighted functions of(a)spatial closeness to U-enriched felsic igneous rocks was employed as U-source spatial evidence,(b)spatial closeness to paleochannels as fluid pathways spatial evidence,and(c)surface water U content as chemical trap spatial evidence.The best models of prospectivity created by integrating the layers of spatial evidence for U-source,pathways and traps predicted at least 85%of the known surficial U deposits/occurrences in>10%of the study region with the highest prospectivity fuzzy scores.The results of analyses demonstrate that,employing the known deposits/occurrences of surficial U for scrutinizing the spatial evidence layers and the final models of prospectivity can pinpoint the most suitable critical processes and models of data integration to reduce bias in the analysis of mineral prospectivity.