An equivalent source approach to the removal of cultural noise from HRAM survey data: examples from Midland region of central Ireland and Haynesville, Louisiana, United States

High-resolution aeromagnetic surveys are commonly flown close to the ground surface (~80m) and sample the magnetic field at about 10m spacing. Such surveys are thus susceptible to magnetic anomalies resulting from populated and/or industrial areas (rigs, pipelines etc). These anomalies are generally called “cultural noise” and need to be removed from the survey data if one wishes to carry out accurate microlevelling to identify and interpret subtle anomalies resulting from subsurface geological structures. Conventional algorithms of cultural noise removal tend to be based on Fast Fourier Transform (FFT) operations either on their own or together with identification and removal of cultural noise signals, using either manually or nonlinear filters methods. These algorithms can have difficulty interpolating across the profile edited sections (i.e., data gaps where cultural noise has been removed) and can introduce artificial anomalies. For these reasons, we have developed a semiautomated method that both identifies sections of profile data containing cultural noise and use the equivalent source approach to recover the magnetic responses of subtle geological anomalies and interpolate their field across the cultural noise gaps in the profile. Theoretical examples of combined subtle magnetic anomalies and cultural noise are used to test the effectiveness of the proposed method, which is shown to provide results that are closer to the original magnetic data without the cultural noise. We demonstrate the practical utility of the approach using highresolution aeromagnetic data from Ireland and United States.