Using geostatistical Bayesian Updating to integrate airborne radiometrics and soil geochemistry to improve mapping for mineral exploration

Mineral exploration programmes around the world use data from remote sensing, geophysics and direct sampling. On a regional scale, the combination of airborne geophysics and ground-based geochemical sampling can aid geological mapping and economic minerals exploration. The fact that airborne geophysical and traditional soil-sampling data are generated at different spatial resolutions means that they are not immediately comparable due to their different sampling density. Several geostatistical techniques, including indicator cokriging and collocated cokriging, can be used to integrate different types of data into a geostatistical model. With increasing numbers of variables the inference of the cross-covariance model required for cokriging can be demanding in terms of effort and computational time. In this paper a Gaussian-based Bayesian updating approach is applied to integrate airborne radiometric data and ground-sampled geochemical soil data to maximise information generated from the soil survey, to enable more accurate geological interpretation for the exploration and development of natural resources. The Bayesian updating technique decomposes the collocated estimate into a production of two models: prior and likelihood models. The prior model is built from primary information and the likelihood model is built from secondary information. The prior model is then updated with the likelihood model to build the final model. The approach allows multiple secondary variables to be simultaneously integrated into the mapping of the primary variable. The Bayesian updating approach is demonstrated using a case study from Northern Ireland where the history of mineral prospecting for precious and base metals dates from the 18th century. Vein-hosted, strata-bound and volcanogenic occurrences of mineralisation are found. The geostatistical technique was used to improve the resolution of soil geochemistry, collected one sample per 2 km2, by integrating more closely measured airborne geophysical data from the GSNI Tellus Survey, measured over a footprint of 65 x 200 m. The directly measured geochemistry data were considered as primary data in the Bayesian approach and the airborne radiometric data were used as secondary data. The approach produced more detailed updated maps and in particular maximized information on mapped estimates of zinc, copper and lead. Greater delineation of an elongated northwest/southeast trending zone in the updated maps strengthened the potential to investigate stratabound base metal deposits.

Accessory minerals and potentially toxic elements in Tanzanian vermiculites with respect to agricultural applications

The study assessed accessory minerals and metals in Tanzanian vermiculites with respect to their potential suitability for agricultural applications. Mineral and chemical analyses were involved. Pot experiments were also conducted to assess plant uptake of metals from soil with vermiculites. Fibrous sepiolite and amphiboles were minerals of health concern found in some samples. The sepiolite fibers had aspect ratios similar to those of asbestos minerals, which cause respiratory disorders and lung cancer when inhaled and thus pose a potential health risk to animals and humans. The amphibole fibers were thicker than 10 μm and are unlikely to be inhaled. Chromium (Cr) and nickel (Ni) concentrations in some samples were greater than the limits permitted in agricultural soils, but the elements are not highly plant available and do not inhibit the uptake of essential macronutrients. Heating vermiculites at 400-600° C enhanced extractability of Cr and Ni and should preferably be avoided. © Taylor & Francis Group, LLC.