GEOSCAN Search Results: Fastlink


TitleA log-barrier approach for airborne gamma-ray spectrometry inversion
AuthorWeihermann, J D; Oliveira, S P; Li, Y; Fonseca Ferreira, F J; Silva, A M; Fortin, RORCID logo
SourceComputers and Geosciences vol. 147, 104682, 2020 p. 1-15,
Alt SeriesNatural Resources Canada, Contribution Series 20200659
PublisherElsevier Ltd.
Mediapaper; on-line; digital
File formatpdf; html
Subjectsgeophysics; Science and Technology; mathematical and computational geology; gamma-ray spectrometers; Data processing
Illustrationsphotographs; diagrams; tables; charts
Released2020 12 29
AbstractThe standard processing of airborne gamma-ray spectrometry (AGRS) data provides useful preliminary information to interpretation in several contexts, such as environmental studies, geological mapping, and analysis of mineral deposits. For optimal results, the acquisition conditions should be nearly constant, and the flight height should be uniform. However, abrupt changes in flight height (often originated from mountainous terrain) are common and lead to spurious variations and incorrect anomaly interpretation. Moreover, the commonly used corrections applied to radiometric data do not consider the effective sampling area of a survey, especially the overlap between successive fields of view. As a consequence, the concentrations estimates of potassium (K), uranium (eU), and thorium (eTh) are not sharp. A solution to deal with this problem is to compute the concentration from the AGRS data through an inversion algorithm. Inversion of AGRS data has shown to be an effective approach to suppress the significant overlap between successive fields of view. We introduce a logarithmic barrier approach for the radiometric inversion to avoid spurious negative values in the radioelement concentration models. We choose calibration ranges from Brazil and Canada to test the proposed methodology. We produced concentration models for K, eU and eTh and compared the standard approach model with the recovered model from both ranges. The predicted data from inversion of both calibration ranges are mostly consistent with the survey data, not over smoothing the data or fitting noise. The predicted data from inversion showed more consistency with the observed data than the one predicted from the standard procedure.

Date modified: