Removal of cultural noise from high-resolution aeromagnetic data using a two stage equivalent source approach

High-resolution aeromagnetic surveys are commonly used to locate subtle anomalies that are important in mineral and oil exploration. However, such anomalies, especially in highly populated areas, are often masked by undesirable magnetic signals from near surface man-made objects – known as ‘cultural noise’ – making post processing and interpretation of the aeromagnetic data difficult. Magnetic data need to be cleaned of this cultural noise before applying advanced processing and interpretation methods. Conventional algorithms for cultural noise removal tend to identify and remove noise signals, either manually or using non-linear filters. These methods are often combined with Fast Fourier Transform filters to smooth the result. These algorithms usually introduce artificial anomalies, have difficulty interpolating across edited sections and rarely yield clean data. For these reasons, we have developed a semi-automated two stage equivalent source approach to remove cultural noise and image subtle geological anomalies. A theoretical example that combines a magnetic anomaly due to a dyke with three cultural noise sources is used to test the effectiveness of the proposed method. Comparison of the equivalent source and conventional results shows that the equivalent source method more closely recovers the original magnetic data. We then demonstrate the practical utility of the two stage equivalent source approach using a high-resolution aeromagnetic dataset from Harberton Bridge, Ireland.