Abstract

Geomagnetic measurements detect the superposition of both regional and residual anomalies. Regional anomalies are caused by deep geological structures, while the residual ones are due to shallow sources. The presence of regional anomalies complicates the interpretation of magnetic data; to this end, a variety of techniques have been proposed for regional-residual anomaly separation. Most of them are based on Fourier transforms. Although valid results can be obtained from these methods, they have some limitations, such as requiring basic knowledge on approximate cut-off frequencies. This study focuses on spatial filtering employing factorial kriging (FK) for geomagnetic anomaly separation. FK employs geostatistical filtering based on spatial dependencies of the data. In contrast to the upward continuation, which is a trial and error method and needs to be checked with different distances of continuations, the utilisation of FK on synthetic data revealed that FK could automatically perform the separation and also helps to find the optimum distance for the upward continuation method. Following experiments with a synthetic model, the method was applied to real magnetic data of Bashmaq in northwestern Iran. Applying FK on a complicated real case study showed that it could separate the regional and residual components satisfactorily. Furthermore, results from the proposed approach have been compared against the Gaussian Separation Method (GSM). The results are compared to borehole information. The lithological columns are presented as part of the geology investigation. As demonstrated in the case study, the FK method has proven to be an accurate tool to better determine the mineralisation zones compared to GSM, which, in turn, facilitates the interpretation.

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