Abstract
To resolve the problem of gravity mapping in the Mayo-Kani Division, we extracted a sample of data from the high-resolution Bouguer anomaly database EGM2008. The objective of this process was to map and detect subsurface anomalies in the region. Regional-residual separation was applied to the data using a third-order polynomial fit. This separation enables to obtain regional and residual maps. Other filtering actions, such as horizontal and vertical derivatives, have been applied to the data to enhance sources of anomalies in the study area. The residual map of the study area was superimposed on the geological map to delineate and interpret the correlation with the shallow geological structures. The main sources of residual gravity anomalies have been recognized. The interpretation of the derived maps revealed the N-S, E-W, NE-SW and NW-SE structural patterns. These trends have been associated with the major structural directions observed in the Far North Cameroon region. The Euler Deconvolution allowed the detection of sources of anomalies and to determine their depths. The fracture map obtained from this method has improved knowledge on the search for buried ores and the geological structures associated with oil and gas deposits. Overall, the generated gravity maps provided a better understanding of the Mayo-Kani geological setting.
Highlights
Satellite mapping has for some time been making great progress and success in the search for buried ores and structures associated with oil or gas deposits [1,2,3]
Given the importance of satellite mapping for certain states, we have decided in this study to approach the gravity mapping of the Mayo-Kani Division
Regional-residual separation by analytical polynomial fit was applied to the EGM2008-Bouguer data
Summary
Satellite mapping has for some time been making great progress and success in the search for buried ores and structures associated with oil or gas deposits [1,2,3]. Given the importance of satellite mapping for certain states, we have decided in this study to approach the gravity mapping of the Mayo-Kani Division. In this region the terrestrial and aerial data do not exist. The gravity data from this model have an important aspect [4,5,6,7,8,9,10,11]: they are less expensive and allow a quick and general coverage in less time of large areas of exploration. The resolution of these devices and their orientation may allow better detection of anomalies and fractured structures of the soil and subsoil
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