Geostatistical analysis and interpretation of Ilesha aeromagnetic data south–western, Nigeria

The uses of variogam and kriging as a tool in geostatistical analysis have gained greater prominence recently in the diverse scientific field, especially for mineral exploration purpose. Ilesha, the study area, has been identified as the one the region with abundance gold deposits in Nigeria. Differ...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Environmental earth sciences 2024-12, Vol.83 (23), p.656, Article 656
Hauptverfasser: Ogunsanwo, F. O., Ozebo, V. C., Olurin, O. T., Ayanda, J. D., Olumoyegun, J. M., Adelaja, A. D., Egunjobi, K. A., Ganiyu, S. A., Oyebanjo, O. A., Olowofela, J. A.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The uses of variogam and kriging as a tool in geostatistical analysis have gained greater prominence recently in the diverse scientific field, especially for mineral exploration purpose. Ilesha, the study area, has been identified as the one the region with abundance gold deposits in Nigeria. Different methods have been used in the past for the analysis and interpretation of aeromagnetic data in the gold deposit area with less attention to the geostatistical approach. The objectives of this work are to (i) fit the aeromagnetic data into the variogram model to estimate the magnetic spatial structural dependency on the geological composition (ii) delineate the spatial magnetic anomaly associated with the lithological units using kriging interpolation techniques (iii) deduce the zone associated with strong and weak gold mineralization (iv) evaluate the kriging techniques for cross validation. The major tool used in this work is the geological map of Ilesha which was partitioned into nine (9) lithological H-units in conjunction with an aeromagnetic sheet obtained from the Nigeria Geophysical Survey Agency, Abuja. In this study, three variogram models, the spherical (S), exponential (E) and Gaussian (G) models, were used. Three kriging interpolation techniques, ordinary kriging (OK), co-kriging (CK) and radial basis function (RBF) were employed. Nugget Sill Ratio (NSR) was deduced to estimate the autocorrelation level of the variogram models while cross validation was carried out on the kriging techniques using mean square error (MSE) and root mean square error (RMSE) for predictive performance evaluation. The result obtained accounted for the variogram model in the order of S 
ISSN:1866-6280
1866-6299
DOI:10.1007/s12665-024-11956-w