Search

The version three of Earth Magnetic Anomaly Grid (EMAG2-v3) used in this work is aimed at establishing the spatial relationships between tectonic structures and gold and associated mineralization in the Pangar-Djérem area, central and southern Cameroon. Various processing and transformation of image data such as the reduction to the equator, horizontal gradient, generalized derivative, and pseudogravity allowed the identification and delineation of numerous faults related to Syn-D1, Syn-D2, and Syn-D3 deformations. The main orientations, W-E, SW-NE, and SE-NW, obtained from these faults define the intensity of the Pan-African and Eburnian tectonics in the Cameroonian basement. Correlations between mapped faults and mineral occurrences define a structural control of gold mineralization in the study area. Furthermore, the spatial relationships between these faults and the igneous/metasedimentary rocks demonstrate that the Eburnian and Pan-African orogenies favoured the circulation of gold-enriched fluids along faults and shear zones. Gold mineralization in the Pangar-Djérem zone is of the vein type (primary gold), resulting from the intrusion of type I granites and the circulation of enriched fluids in a brittle to ductile shear context. The pseudogravity anomalies associated with the sedimentary deposits/rocks and the SW-NE structures of the Sanaga and Bétaré-Oya Faults define an environment of detrital sedimentary deposits, consisting of metavolcanic and metasedimentary rocks, and justify the existence of gold-bearing quartz veins.

The aim of this study is to determine the depth of deep tectonic structures observed in the Adamawa-Yadé zone (central part of Cameroon) and propose a new structural map of this area. The horizontal gradient associated with upward continuation and the 3D Euler deconvolution methods have been applied to the Earth Magnetic Anomaly Grid 2 (EMAG2) data from the study area. The determination of the maximum magnitude of the horizontal gradient of the total magnetic intensity field reduced to the equator, in addition to the main contacts deducted by Euler solution, allowed the production of a structural map to show the fault systems for the survey area. This result reveals the existence of two structural domains which is thus confirmed by the contrast of magnetic susceptibility in the Central Cameroon Zone. The suggested depths are in the range of 3.34 km to 4.63 km. The structural map shows two types of faults (minors and majors) with W-E, N-S, NW-SE, NE-SW, ENE-WSW, WNW-ESE, NNE-SSW, and NNW-SSE trending. The major faults which are deepest (3.81 km to 4.63 km) with NE-SW, W-E, and N-S direction are very represented in the second domain which includes the Pangar-Djerem zone. This domain which recovers many localities (Ngaoundéré, Tibati, Ngaoundal, Yoko Bétaré-Oya, and Yaoundé) is associated with the Pan-African orogeny and the Cameroon Volcanic Line.

Accurate interpretation of geological structures inverted from gravity data is highly dependent on the coverage of the recorded gravity data. In this work, Artificial Neural Networks (ANNs) are implemented using Levenberg-Marquardt algorithm (LMA) to construct a background density model for predicting gravity data across Northern Cameroon and its surroundings. This approach yields statistical predictions of gravity values (low values of errors) with 97.48%, 0.10, and 0.89, respectively, for correlation, Mean Bias Error, and Root Mean Square Error for two inputs (latitude, longitude) and 97.08%, 0.13, and 1.14 for three inputs (latitude, longitude, and elevation) for a set of anomalies as output. The model validation is obtained by comparing the results to other classical approaches and to the computed Bouguer, lineaments, and Euler maps obtained from measured gravity data. The depth of most of the deep faults and their orientation are in agreement with those obtained from other studies. The results achieved in this study establish the possibility of enhancing the quality of the analysis, interpretation, and modeling of gravity data collected on sparse grid of recording stations.