Detecting Real Gold Anomalies from Soil Geochemical Survey using Regolith Knowledge in Areas Undercover-Example in the Sunyani Sedimentary Basin, Ghana
*Corresponding Author:Received Date: Dec 02, 2022 / Accepted Date: Dec 24, 2022 / Published Date: Dec 31, 2022
Copyright: © 2022 . This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
The complex regolith environment presents both challenges and opportunities in the determination of real gold anomalies in mineral exploration. As anomalies may be subdued by the complexities of the regolith; accounting for the regolith environment in the geochemical data interpretation could lead to the detection of real and true anomalies. The development of a regolith map using remote sensing data and field verification of the interpolated regolith map made possible the interpretation of 4254 soil samples collected in the regolith context. The gold anomalisms in the various regolith regimes were established from the respective thresholds defined from gold distribution data filtered for the four defined regolith domains. The estimated threshold values were 28 ppb for ferruginous, 38 ppb for relict, 100 ppb for erosional and 30 ppb for the depositional regime. In GIS environment and performing Krigging around the defined thresholds, gold indicator maps that showed the gold prospectivity in the different regolith environments were produced. Another unit less threshold was derived for the combined data after the gold expressions for the various regolith regimes have been normalized with the individual established threshold values. The unitless threshold value estimated was 25 and applying Probability Kriging gridding method around the 25 threshold value; the gold anomalies accounting for the regolith environments were defined, outlined and prioritized. The prospectivity of the defined anomalies was explicit when data such as regolith, geology and interpreted lineaments were draped on the Probability Krigging map.
